From cae5d4d4ea43493670d038ec01c466bec81edf38 Mon Sep 17 00:00:00 2001
From: Daniel Hiltgen <dhiltgen@users.noreply.github.com>
Date: Wed, 5 Mar 2025 14:11:21 -0800
Subject: [PATCH 001/157] Win: doc new rocm zip file (#9367)

To stay under the 2G github artifact limit, we're splitting ROCm
out like we do on linux.
---
 docs/windows.md | 8 +++++---
 1 file changed, 5 insertions(+), 3 deletions(-)

diff --git a/docs/windows.md b/docs/windows.md
index 018cc41d..78b99a5d 100644
--- a/docs/windows.md
+++ b/docs/windows.md
@@ -81,9 +81,11 @@ help you keep up to date.
 
 If you'd like to install or integrate Ollama as a service, a standalone
 `ollama-windows-amd64.zip` zip file is available containing only the Ollama CLI
-and GPU library dependencies for Nvidia and AMD. This allows for embedding
-Ollama in existing applications, or running it as a system service via `ollama
-serve` with tools such as [NSSM](https://nssm.cc/).
+and GPU library dependencies for Nvidia.  If you have an AMD GPU, also download
+and extract the additional ROCm package `ollama-windows-amd64-rocm.zip` into the
+same directory.  This allows for embedding Ollama in existing applications, or
+running it as a system service via `ollama serve` with tools such as
+[NSSM](https://nssm.cc/). 
 
 > [!NOTE]  
 > If you are upgrading from a prior version, you should remove the old directories first.

From e2252d0fc6ea5c410b1ac4fa0a722beda78b3431 Mon Sep 17 00:00:00 2001
From: Blake Mizerany <blake.mizerany@gmail.com>
Date: Wed, 5 Mar 2025 14:48:18 -0800
Subject: [PATCH 002/157] server/internal/registry: take over pulls from server
 package (#9485)

This commit replaces the old pull implementation in the server package
with the new, faster, more robust pull implementation in the registry
package.

The new endpoint, and now the remove endpoint too, are behind the
feature gate "client2" enabled only by setting the OLLAMA_EXPERIMENT
environment variable include "client2".

Currently, the progress indication is wired to perform the same as the
previous implementation to avoid making changes to the CLI, and because
the status reports happen at the start of the download, and the end of
the write to disk, the progress indication is not as smooth as it could
be. This is a known issue and will be addressed in a future change.

This implementation may be ~0.5-1.0% slower in rare cases, depending on
network and disk speed, but is generally MUCH faster and more robust
than the its predecessor in all other cases.
---
 api/types.go                                  |   6 +-
 go.mod                                        |   1 +
 go.sum                                        |   2 +
 server/internal/client/ollama/registry.go     | 117 +++++++++++-----
 .../internal/client/ollama/registry_test.go   |   2 +-
 server/internal/client/ollama/trace.go        |  10 +-
 server/internal/registry/server.go            |  97 +++++++++++++
 server/internal/registry/server_test.go       | 130 +++++++++++++++++-
 .../library/smol/latest                       |   0
 .../internal/registry/testdata/registry.txt   |  22 +++
 server/routes.go                              |  35 +++--
 11 files changed, 370 insertions(+), 52 deletions(-)
 rename server/internal/registry/testdata/models/manifests/{registry.ollama.ai => example.com}/library/smol/latest (100%)
 create mode 100644 server/internal/registry/testdata/registry.txt

diff --git a/api/types.go b/api/types.go
index 637ca204..fef836bd 100644
--- a/api/types.go
+++ b/api/types.go
@@ -361,9 +361,9 @@ type CopyRequest struct {
 // PullRequest is the request passed to [Client.Pull].
 type PullRequest struct {
 	Model    string `json:"model"`
-	Insecure bool   `json:"insecure,omitempty"`
-	Username string `json:"username"`
-	Password string `json:"password"`
+	Insecure bool   `json:"insecure,omitempty"` // Deprecated: ignored
+	Username string `json:"username"`           // Deprecated: ignored
+	Password string `json:"password"`           // Deprecated: ignored
 	Stream   *bool  `json:"stream,omitempty"`
 
 	// Deprecated: set the model name with Model instead
diff --git a/go.mod b/go.mod
index af0cedc8..c45c9892 100644
--- a/go.mod
+++ b/go.mod
@@ -24,6 +24,7 @@ require (
 	github.com/nlpodyssey/gopickle v0.3.0
 	github.com/pdevine/tensor v0.0.0-20240510204454-f88f4562727c
 	golang.org/x/image v0.22.0
+	golang.org/x/tools v0.30.0
 	gonum.org/v1/gonum v0.15.0
 )
 
diff --git a/go.sum b/go.sum
index 013a7db7..0ab97b90 100644
--- a/go.sum
+++ b/go.sum
@@ -309,6 +309,8 @@ golang.org/x/tools v0.0.0-20200130002326-2f3ba24bd6e7/go.mod h1:TB2adYChydJhpapK
 golang.org/x/tools v0.0.0-20200619180055-7c47624df98f/go.mod h1:EkVYQZoAsY45+roYkvgYkIh4xh/qjgUK9TdY2XT94GE=
 golang.org/x/tools v0.0.0-20210106214847-113979e3529a/go.mod h1:emZCQorbCU4vsT4fOWvOPXz4eW1wZW4PmDk9uLelYpA=
 golang.org/x/tools v0.1.4/go.mod h1:o0xws9oXOQQZyjljx8fwUC0k7L1pTE6eaCbjGeHmOkk=
+golang.org/x/tools v0.30.0 h1:BgcpHewrV5AUp2G9MebG4XPFI1E2W41zU1SaqVA9vJY=
+golang.org/x/tools v0.30.0/go.mod h1:c347cR/OJfw5TI+GfX7RUPNMdDRRbjvYTS0jPyvsVtY=
 golang.org/x/xerrors v0.0.0-20190717185122-a985d3407aa7/go.mod h1:I/5z698sn9Ka8TeJc9MKroUUfqBBauWjQqLJ2OPfmY0=
 golang.org/x/xerrors v0.0.0-20191011141410-1b5146add898/go.mod h1:I/5z698sn9Ka8TeJc9MKroUUfqBBauWjQqLJ2OPfmY0=
 golang.org/x/xerrors v0.0.0-20191204190536-9bdfabe68543/go.mod h1:I/5z698sn9Ka8TeJc9MKroUUfqBBauWjQqLJ2OPfmY0=
diff --git a/server/internal/client/ollama/registry.go b/server/internal/client/ollama/registry.go
index 007de5e8..423a6ad2 100644
--- a/server/internal/client/ollama/registry.go
+++ b/server/internal/client/ollama/registry.go
@@ -45,9 +45,9 @@ import (
 
 // Errors
 var (
-	// ErrManifestNotFound is returned when a manifest is not found in the
+	// ErrModelNotFound is returned when a manifest is not found in the
 	// cache or registry.
-	ErrManifestNotFound = errors.New("manifest not found")
+	ErrModelNotFound = errors.New("model not found")
 
 	// ErrManifestInvalid is returned when a manifest found in a local or
 	// remote cache is invalid.
@@ -114,7 +114,18 @@ type Error struct {
 }
 
 func (e *Error) Error() string {
-	return fmt.Sprintf("registry responded with status %d: %s %s", e.Status, e.Code, e.Message)
+	var b strings.Builder
+	b.WriteString("registry responded with status ")
+	b.WriteString(strconv.Itoa(e.Status))
+	if e.Code != "" {
+		b.WriteString(": code ")
+		b.WriteString(e.Code)
+	}
+	if e.Message != "" {
+		b.WriteString(": ")
+		b.WriteString(e.Message)
+	}
+	return b.String()
 }
 
 func (e *Error) LogValue() slog.Value {
@@ -355,7 +366,7 @@ func (r *Registry) Push(ctx context.Context, name string, p *PushParams) error {
 				n.Model(),
 				l.Digest,
 			)
-			res, err := r.doOK(ctx, "POST", startURL, nil)
+			res, err := r.send(ctx, "POST", startURL, nil)
 			if err != nil {
 				return err
 			}
@@ -379,7 +390,7 @@ func (r *Registry) Push(ctx context.Context, name string, p *PushParams) error {
 			}
 			req.ContentLength = l.Size
 
-			res, err = doOK(r.client(), req)
+			res, err = sendRequest(r.client(), req)
 			if err == nil {
 				res.Body.Close()
 			}
@@ -399,7 +410,7 @@ func (r *Registry) Push(ctx context.Context, name string, p *PushParams) error {
 		n.Model(),
 		n.Tag(),
 	)
-	res, err := r.doOK(ctx, "PUT", path, bytes.NewReader(m.Data))
+	res, err := r.send(ctx, "PUT", path, bytes.NewReader(m.Data))
 	if err == nil {
 		res.Body.Close()
 	}
@@ -448,10 +459,15 @@ func (r *Registry) Pull(ctx context.Context, name string) error {
 
 	t := traceFromContext(ctx)
 
-	var g errgroup.Group
+	g, ctx := errgroup.WithContext(ctx)
 	g.SetLimit(r.maxStreams())
 
-	for _, l := range m.Layers {
+	layers := m.Layers
+	if m.Config != nil && m.Config.Digest.IsValid() {
+		layers = append(layers, m.Config)
+	}
+
+	for _, l := range layers {
 		if exists(l) {
 			t.update(l, l.Size, ErrCached)
 			continue
@@ -468,7 +484,9 @@ func (r *Registry) Pull(ctx context.Context, name string) error {
 
 		if l.Size <= r.maxChunkingThreshold() {
 			g.Go(func() error {
-				res, err := doOK(r.client(), req)
+				// TODO(bmizerany): retry/backoff like below in
+				// the chunking case
+				res, err := sendRequest(r.client(), req)
 				if err != nil {
 					return err
 				}
@@ -494,19 +512,21 @@ func (r *Registry) Pull(ctx context.Context, name string) error {
 			// fire an initial request to get the final URL and
 			// then use that URL for the chunk requests.
 			req.Header.Set("Range", "bytes=0-0")
-			res, err := doOK(r.client(), req)
+			res, err := sendRequest(r.client(), req)
 			if err != nil {
 				return err
 			}
 			res.Body.Close()
 			req = res.Request.WithContext(req.Context())
 
-			streamNo := 0
-			tws := make([]*bufio.Writer, r.maxStreams()-1)
+			wp := writerPool{size: r.maxChunkSize()}
+
 			for chunk := range chunks.Of(l.Size, r.maxChunkSize()) {
+				if ctx.Err() != nil {
+					break
+				}
+
 				ticket := q.Take()
-				bufIdx := streamNo % len(tws)
-				streamNo++
 				g.Go(func() (err error) {
 					defer func() {
 						if err != nil {
@@ -520,23 +540,18 @@ func (r *Registry) Pull(ctx context.Context, name string) error {
 						if err != nil {
 							return err
 						}
-
 						err := func() error {
 							req := req.Clone(req.Context())
 							req.Header.Set("Range", fmt.Sprintf("bytes=%s", chunk))
-							res, err := doOK(r.client(), req)
+							res, err := sendRequest(r.client(), req)
 							if err != nil {
 								return err
 							}
 							defer res.Body.Close()
 
-							tw := tws[bufIdx]
-							if tw == nil {
-								tw = bufio.NewWriterSize(nil, int(r.maxChunkSize()))
-								tws[bufIdx] = tw
-							}
+							tw := wp.get()
 							tw.Reset(ticket)
-							defer tw.Reset(nil) // release ticket
+							defer wp.put(tw)
 
 							_, err = io.CopyN(tw, res.Body, chunk.Size())
 							if err != nil {
@@ -595,6 +610,9 @@ type Manifest struct {
 	Name   string   `json:"-"` // the canonical name of the model
 	Data   []byte   `json:"-"` // the raw data of the manifest
 	Layers []*Layer `json:"layers"`
+
+	// For legacy reasons, we still have to download the config layer.
+	Config *Layer `json:"config"`
 }
 
 var emptyDigest, _ = blob.ParseDigest("sha256:0000000000000000000000000000000000000000000000000000000000000000")
@@ -678,7 +696,7 @@ func (r *Registry) ResolveLocal(name string) (*Manifest, error) {
 	data, err := os.ReadFile(c.GetFile(d))
 	if err != nil {
 		if errors.Is(err, fs.ErrNotExist) {
-			return nil, fmt.Errorf("%w: %s", ErrManifestNotFound, name)
+			return nil, fmt.Errorf("%w: %s", ErrModelNotFound, name)
 		}
 		return nil, err
 	}
@@ -701,7 +719,7 @@ func (r *Registry) Resolve(ctx context.Context, name string) (*Manifest, error)
 		manifestURL = fmt.Sprintf("%s://%s/v2/%s/%s/blobs/%s", scheme, n.Host(), n.Namespace(), n.Model(), d)
 	}
 
-	res, err := r.doOK(ctx, "GET", manifestURL, nil)
+	res, err := r.send(ctx, "GET", manifestURL, nil)
 	if err != nil {
 		return nil, err
 	}
@@ -726,7 +744,7 @@ func (r *Registry) client() *http.Client {
 }
 
 // newRequest constructs a new request, ready to use, with the given method,
-// url, and body, presigned with client Key and UserAgent.
+// url, and body, pre-signed with client [Key] and [UserAgent].
 func (r *Registry) newRequest(ctx context.Context, method, url string, body io.Reader) (*http.Request, error) {
 	req, err := http.NewRequestWithContext(ctx, method, url, body)
 	if err != nil {
@@ -745,11 +763,17 @@ func (r *Registry) newRequest(ctx context.Context, method, url string, body io.R
 	return req, nil
 }
 
-// doOK makes a request with the given client and request, and returns the
+// sendRequest makes a request with the given client and request, and returns the
 // response if the status code is 200. If the status code is not 200, an Error
 // is parsed from the response body and returned. If any other error occurs, it
 // is returned.
-func doOK(c *http.Client, r *http.Request) (*http.Response, error) {
+func sendRequest(c *http.Client, r *http.Request) (_ *http.Response, err error) {
+	defer func() {
+		if err != nil {
+			err = fmt.Errorf("request error %s: %w", r.URL, err)
+		}
+	}()
+
 	if r.URL.Scheme == "https+insecure" {
 		// TODO(bmizerany): clone client.Transport, set
 		// InsecureSkipVerify, etc.
@@ -792,20 +816,26 @@ func doOK(c *http.Client, r *http.Request) (*http.Response, error) {
 			// Use the raw body if we can't parse it as an error object.
 			re.Message = string(out)
 		}
+
+		// coerce MANIFEST_UNKNOWN to ErrManifestNotFound
+		if strings.EqualFold(re.Code, "MANIFEST_UNKNOWN") {
+			return nil, ErrModelNotFound
+		}
+
 		re.Status = res.StatusCode
 		return nil, &re
 	}
 	return res, nil
 }
 
-// doOK is a convenience method for making a request with newRequest and
-// passing it to doOK with r.client().
-func (r *Registry) doOK(ctx context.Context, method, path string, body io.Reader) (*http.Response, error) {
+// send is a convenience method for making a request with newRequest and
+// passing it to send with r.client().
+func (r *Registry) send(ctx context.Context, method, path string, body io.Reader) (*http.Response, error) {
 	req, err := r.newRequest(ctx, method, path, body)
 	if err != nil {
 		return nil, err
 	}
-	return doOK(r.client(), req)
+	return sendRequest(r.client(), req)
 }
 
 // makeAuthToken creates an Ollama auth token for the given private key.
@@ -960,3 +990,28 @@ func splitExtended(s string) (scheme, name, digest string) {
 	}
 	return scheme, s, digest
 }
+
+type writerPool struct {
+	size int64 // set by the caller
+
+	mu sync.Mutex
+	ws []*bufio.Writer
+}
+
+func (p *writerPool) get() *bufio.Writer {
+	p.mu.Lock()
+	defer p.mu.Unlock()
+	if len(p.ws) == 0 {
+		return bufio.NewWriterSize(nil, int(p.size))
+	}
+	w := p.ws[len(p.ws)-1]
+	p.ws = p.ws[:len(p.ws)-1]
+	return w
+}
+
+func (p *writerPool) put(w *bufio.Writer) {
+	p.mu.Lock()
+	defer p.mu.Unlock()
+	w.Reset(nil)
+	p.ws = append(p.ws, w)
+}
diff --git a/server/internal/client/ollama/registry_test.go b/server/internal/client/ollama/registry_test.go
index b9b4271b..8f4e1604 100644
--- a/server/internal/client/ollama/registry_test.go
+++ b/server/internal/client/ollama/registry_test.go
@@ -608,7 +608,7 @@ func TestInsecureSkipVerify(t *testing.T) {
 	url := fmt.Sprintf("https://%s/%s", s.Listener.Addr(), name)
 	_, err := rc.Resolve(t.Context(), url)
 	if err == nil || !strings.Contains(err.Error(), "failed to verify") {
-		t.Errorf("err = %v; want cert verifiction failure", err)
+		t.Errorf("err = %v; want cert verification failure", err)
 	}
 
 	url = fmt.Sprintf("https+insecure://%s/%s", s.Listener.Addr(), name)
diff --git a/server/internal/client/ollama/trace.go b/server/internal/client/ollama/trace.go
index e300870b..69435c40 100644
--- a/server/internal/client/ollama/trace.go
+++ b/server/internal/client/ollama/trace.go
@@ -13,9 +13,13 @@ type Trace struct {
 	// Update is called during [Registry.Push] and [Registry.Pull] to
 	// report the progress of blob uploads and downloads.
 	//
-	// It is called once at the beginning of the download with a zero n and
-	// then once per read operation with the number of bytes read so far,
-	// and an error if any.
+	// The n argument is the number of bytes transferred so far, and err is
+	// any error that has occurred. If n == 0, and err is nil, the download
+	// or upload has just started. If err is [ErrCached], the download or
+	// upload has been skipped because the blob is already present in the
+	// local cache or remote registry, respectively. Otherwise, if err is
+	// non-nil, the download or upload has failed. When l.Size == n, and
+	// err is nil, the download or upload has completed.
 	//
 	// A function assigned must be safe for concurrent use. The function is
 	// called synchronously and so should not block or take long to run.
diff --git a/server/internal/registry/server.go b/server/internal/registry/server.go
index 4d44aa8d..62fefb4c 100644
--- a/server/internal/registry/server.go
+++ b/server/internal/registry/server.go
@@ -7,10 +7,14 @@ import (
 	"cmp"
 	"encoding/json"
 	"errors"
+	"fmt"
 	"io"
 	"log/slog"
 	"net/http"
+	"sync"
+	"time"
 
+	"github.com/ollama/ollama/server/internal/cache/blob"
 	"github.com/ollama/ollama/server/internal/client/ollama"
 )
 
@@ -109,6 +113,8 @@ func (s *Local) serveHTTP(rec *statusCodeRecorder, r *http.Request) {
 		switch r.URL.Path {
 		case "/api/delete":
 			return false, s.handleDelete(rec, r)
+		case "/api/pull":
+			return false, s.handlePull(rec, r)
 		default:
 			if s.Fallback != nil {
 				s.Fallback.ServeHTTP(rec, r)
@@ -214,6 +220,97 @@ func (s *Local) handleDelete(_ http.ResponseWriter, r *http.Request) error {
 	return s.Prune()
 }
 
+type progressUpdateJSON struct {
+	Status    string      `json:"status"`
+	Digest    blob.Digest `json:"digest,omitempty,omitzero"`
+	Total     int64       `json:"total,omitempty,omitzero"`
+	Completed int64       `json:"completed,omitempty,omitzero"`
+}
+
+func (s *Local) handlePull(w http.ResponseWriter, r *http.Request) error {
+	if r.Method != "POST" {
+		return errMethodNotAllowed
+	}
+
+	p, err := decodeUserJSON[*params](r.Body)
+	if err != nil {
+		return err
+	}
+
+	maybeFlush := func() {
+		fl, _ := w.(http.Flusher)
+		if fl != nil {
+			fl.Flush()
+		}
+	}
+	defer maybeFlush()
+
+	var mu sync.Mutex
+	enc := json.NewEncoder(w)
+	enc.Encode(progressUpdateJSON{Status: "pulling manifest"})
+
+	ctx := ollama.WithTrace(r.Context(), &ollama.Trace{
+		Update: func(l *ollama.Layer, n int64, err error) {
+			mu.Lock()
+			defer mu.Unlock()
+
+			// TODO(bmizerany): coalesce these updates; writing per
+			// update is expensive
+			enc.Encode(progressUpdateJSON{
+				Digest:    l.Digest,
+				Status:    "pulling",
+				Total:     l.Size,
+				Completed: n,
+			})
+		},
+	})
+
+	done := make(chan error, 1)
+	go func() {
+		// TODO(bmizerany): continue to support non-streaming responses
+		done <- s.Client.Pull(ctx, p.model())
+	}()
+
+	func() {
+		t := time.NewTicker(100 * time.Millisecond)
+		defer t.Stop()
+		for {
+			select {
+			case <-t.C:
+				mu.Lock()
+				maybeFlush()
+				mu.Unlock()
+			case err := <-done:
+				if err != nil {
+					var status string
+					if errors.Is(err, ollama.ErrModelNotFound) {
+						status = fmt.Sprintf("error: model %q not found", p.model())
+						enc.Encode(progressUpdateJSON{Status: status})
+					} else {
+						status = fmt.Sprintf("error: %v", err)
+						enc.Encode(progressUpdateJSON{Status: status})
+					}
+					return
+				}
+
+				// These final updates are not strictly necessary, because they have
+				// already happened at this point. Our pull handler code used to do
+				// these steps after, not during, the pull, and they were slow, so we
+				// wanted to provide feedback to users what was happening. For now, we
+				// keep them to not jar users who are used to seeing them. We can phase
+				// them out with a new and nicer UX later. One without progress bars
+				// and digests that no one cares about.
+				enc.Encode(progressUpdateJSON{Status: "verifying layers"})
+				enc.Encode(progressUpdateJSON{Status: "writing manifest"})
+				enc.Encode(progressUpdateJSON{Status: "success"})
+				return
+			}
+		}
+	}()
+
+	return nil
+}
+
 func decodeUserJSON[T any](r io.Reader) (T, error) {
 	var v T
 	err := json.NewDecoder(r).Decode(&v)
diff --git a/server/internal/registry/server_test.go b/server/internal/registry/server_test.go
index e44d88c0..597e9bd6 100644
--- a/server/internal/registry/server_test.go
+++ b/server/internal/registry/server_test.go
@@ -1,17 +1,27 @@
 package registry
 
 import (
+	"bytes"
+	"context"
 	"encoding/json"
+	"fmt"
+	"io"
+	"io/fs"
+	"net"
 	"net/http"
 	"net/http/httptest"
 	"os"
 	"regexp"
 	"strings"
+	"sync"
 	"testing"
 
 	"github.com/ollama/ollama/server/internal/cache/blob"
 	"github.com/ollama/ollama/server/internal/client/ollama"
 	"github.com/ollama/ollama/server/internal/testutil"
+	"golang.org/x/tools/txtar"
+
+	_ "embed"
 )
 
 type panicTransport struct{}
@@ -30,7 +40,7 @@ type bytesResetter interface {
 	Reset()
 }
 
-func newTestServer(t *testing.T) *Local {
+func newTestServer(t *testing.T, upstreamRegistry http.HandlerFunc) *Local {
 	t.Helper()
 	dir := t.TempDir()
 	err := os.CopyFS(dir, os.DirFS("testdata/models"))
@@ -41,10 +51,25 @@ func newTestServer(t *testing.T) *Local {
 	if err != nil {
 		t.Fatal(err)
 	}
+
+	client := panicOnRoundTrip
+	if upstreamRegistry != nil {
+		s := httptest.NewTLSServer(upstreamRegistry)
+		t.Cleanup(s.Close)
+		tr := s.Client().Transport.(*http.Transport).Clone()
+		tr.DialContext = func(ctx context.Context, _, _ string) (net.Conn, error) {
+			var d net.Dialer
+			return d.DialContext(ctx, "tcp", s.Listener.Addr().String())
+		}
+		client = &http.Client{Transport: tr}
+	}
+
 	rc := &ollama.Registry{
 		Cache:      c,
-		HTTPClient: panicOnRoundTrip,
+		HTTPClient: client,
+		Mask:       "example.com/library/_:latest",
 	}
+
 	l := &Local{
 		Client: rc,
 		Logger: testutil.Slogger(t),
@@ -85,7 +110,7 @@ func captureLogs(t *testing.T, s *Local) (*Local, bytesResetter) {
 func TestServerDelete(t *testing.T) {
 	check := testutil.Checker(t)
 
-	s := newTestServer(t)
+	s := newTestServer(t, nil)
 
 	_, err := s.Client.ResolveLocal("smol")
 	check(err)
@@ -127,8 +152,105 @@ func TestServerDelete(t *testing.T) {
 	}
 }
 
+//go:embed testdata/registry.txt
+var registryTXT []byte
+
+var registryFS = sync.OnceValue(func() fs.FS {
+	// Txtar gets hung up on \r\n line endings, so we need to convert them
+	// to \n when parsing the txtar on Windows.
+	data := bytes.ReplaceAll(registryTXT, []byte("\r\n"), []byte("\n"))
+	a := txtar.Parse(data)
+	fmt.Printf("%q\n", a.Comment)
+	fsys, err := txtar.FS(a)
+	if err != nil {
+		panic(err)
+	}
+	return fsys
+})
+
+func TestServerPull(t *testing.T) {
+	modelsHandler := http.FileServerFS(registryFS())
+	s := newTestServer(t, func(w http.ResponseWriter, r *http.Request) {
+		switch r.URL.Path {
+		case "/v2/library/BOOM/manifests/latest":
+			w.WriteHeader(999)
+			io.WriteString(w, `{"error": "boom"}`)
+		case "/v2/library/unknown/manifests/latest":
+			w.WriteHeader(404)
+			io.WriteString(w, `{"errors": [{"code": "MANIFEST_UNKNOWN", "message": "manifest unknown"}]}`)
+		default:
+			t.Logf("serving file: %s", r.URL.Path)
+			modelsHandler.ServeHTTP(w, r)
+		}
+	})
+
+	checkResponse := func(got *httptest.ResponseRecorder, wantlines string) {
+		t.Helper()
+
+		if got.Code != 200 {
+			t.Fatalf("Code = %d; want 200", got.Code)
+		}
+		gotlines := got.Body.String()
+		t.Logf("got:\n%s", gotlines)
+		for want := range strings.Lines(wantlines) {
+			want = strings.TrimSpace(want)
+			want, unwanted := strings.CutPrefix(want, "!")
+			want = strings.TrimSpace(want)
+			if !unwanted && !strings.Contains(gotlines, want) {
+				t.Fatalf("! missing %q in body", want)
+			}
+			if unwanted && strings.Contains(gotlines, want) {
+				t.Fatalf("! unexpected %q in body", want)
+			}
+		}
+	}
+
+	got := s.send(t, "POST", "/api/pull", `{"model": "BOOM"}`)
+	checkResponse(got, `
+		{"status":"pulling manifest"}
+		{"status":"error: request error https://example.com/v2/library/BOOM/manifests/latest: registry responded with status 999: boom"}
+	`)
+
+	got = s.send(t, "POST", "/api/pull", `{"model": "smol"}`)
+	checkResponse(got, `
+		{"status":"pulling manifest"}
+		{"status":"pulling","digest":"sha256:68e0ec597aee59d35f8dc44942d7b17d471ade10d3aca07a5bb7177713950312","total":5}
+		{"status":"pulling","digest":"sha256:ca3d163bab055381827226140568f3bef7eaac187cebd76878e0b63e9e442356","total":3}
+		{"status":"pulling","digest":"sha256:68e0ec597aee59d35f8dc44942d7b17d471ade10d3aca07a5bb7177713950312","total":5,"completed":5}
+		{"status":"pulling","digest":"sha256:ca3d163bab055381827226140568f3bef7eaac187cebd76878e0b63e9e442356","total":3,"completed":3}
+		{"status":"verifying layers"}
+		{"status":"writing manifest"}
+		{"status":"success"}
+	`)
+
+	got = s.send(t, "POST", "/api/pull", `{"model": "unknown"}`)
+	checkResponse(got, `
+		{"status":"pulling manifest"}
+		{"status":"error: model \"unknown\" not found"}
+	`)
+
+	got = s.send(t, "DELETE", "/api/pull", `{"model": "smol"}`)
+	checkErrorResponse(t, got, 405, "method_not_allowed", "method not allowed")
+
+	got = s.send(t, "POST", "/api/pull", `!`)
+	checkErrorResponse(t, got, 400, "bad_request", "invalid character '!' looking for beginning of value")
+
+	got = s.send(t, "POST", "/api/pull", ``)
+	checkErrorResponse(t, got, 400, "bad_request", "empty request body")
+
+	got = s.send(t, "POST", "/api/pull", `{"model": "://"}`)
+	checkResponse(got, `
+		{"status":"pulling manifest"}
+		{"status":"error: invalid or missing name: \"\""}
+
+		!verifying
+		!writing
+		!success
+	`)
+}
+
 func TestServerUnknownPath(t *testing.T) {
-	s := newTestServer(t)
+	s := newTestServer(t, nil)
 	got := s.send(t, "DELETE", "/api/unknown", `{}`)
 	checkErrorResponse(t, got, 404, "not_found", "not found")
 }
diff --git a/server/internal/registry/testdata/models/manifests/registry.ollama.ai/library/smol/latest b/server/internal/registry/testdata/models/manifests/example.com/library/smol/latest
similarity index 100%
rename from server/internal/registry/testdata/models/manifests/registry.ollama.ai/library/smol/latest
rename to server/internal/registry/testdata/models/manifests/example.com/library/smol/latest
diff --git a/server/internal/registry/testdata/registry.txt b/server/internal/registry/testdata/registry.txt
new file mode 100644
index 00000000..2fc363fc
--- /dev/null
+++ b/server/internal/registry/testdata/registry.txt
@@ -0,0 +1,22 @@
+-- v2/library/smol/manifests/latest --
+{
+  "schemaVersion": 2,
+  "mediaType": "application/vnd.docker.distribution.manifest.v2+json",
+  "config": {
+    "mediaType": "application/vnd.docker.container.image.v1+json",
+    "digest": "sha256:ca3d163bab055381827226140568f3bef7eaac187cebd76878e0b63e9e442356",
+    "size": 3
+  },
+  "layers": [
+    {
+      "mediaType": "application/vnd.ollama.image.model",
+      "digest": "sha256:68e0ec597aee59d35f8dc44942d7b17d471ade10d3aca07a5bb7177713950312",
+      "size": 5
+    }
+  ]
+}
+
+-- v2/library/smol/blobs/sha256:68e0ec597aee59d35f8dc44942d7b17d471ade10d3aca07a5bb7177713950312 --
+GGUF
+-- v2/library/smol/blobs/sha256:ca3d163bab055381827226140568f3bef7eaac187cebd76878e0b63e9e442356 --
+{}
diff --git a/server/routes.go b/server/routes.go
index 73e94dc6..3efa12e4 100644
--- a/server/routes.go
+++ b/server/routes.go
@@ -42,6 +42,12 @@ import (
 	"github.com/ollama/ollama/version"
 )
 
+func experimentEnabled(name string) bool {
+	return slices.Contains(strings.Split(os.Getenv("OLLAMA_EXPERIMENT"), ","), name)
+}
+
+var useClient2 = experimentEnabled("client2")
+
 var mode string = gin.DebugMode
 
 type Server struct {
@@ -1173,6 +1179,7 @@ func (s *Server) GenerateRoutes(rc *ollama.Registry) (http.Handler, error) {
 	r.HEAD("/api/tags", s.ListHandler)
 	r.GET("/api/tags", s.ListHandler)
 	r.POST("/api/show", s.ShowHandler)
+	r.DELETE("/api/delete", s.DeleteHandler)
 
 	// Create
 	r.POST("/api/create", s.CreateHandler)
@@ -1194,16 +1201,19 @@ func (s *Server) GenerateRoutes(rc *ollama.Registry) (http.Handler, error) {
 	r.GET("/v1/models", openai.ListMiddleware(), s.ListHandler)
 	r.GET("/v1/models/:model", openai.RetrieveMiddleware(), s.ShowHandler)
 
-	// wrap old with new
-	rs := &registry.Local{
-		Client:   rc,
-		Logger:   slog.Default(), // TODO(bmizerany): Take a logger, do not use slog.Default()
-		Fallback: r,
+	if rc != nil {
+		// wrap old with new
+		rs := &registry.Local{
+			Client:   rc,
+			Logger:   slog.Default(), // TODO(bmizerany): Take a logger, do not use slog.Default()
+			Fallback: r,
 
-		Prune: PruneLayers,
+			Prune: PruneLayers,
+		}
+		return rs, nil
 	}
 
-	return rs, nil
+	return r, nil
 }
 
 func Serve(ln net.Listener) error {
@@ -1258,15 +1268,20 @@ func Serve(ln net.Listener) error {
 
 	s := &Server{addr: ln.Addr()}
 
-	rc, err := ollama.DefaultRegistry()
-	if err != nil {
-		return err
+	var rc *ollama.Registry
+	if useClient2 {
+		var err error
+		rc, err = ollama.DefaultRegistry()
+		if err != nil {
+			return err
+		}
 	}
 
 	h, err := s.GenerateRoutes(rc)
 	if err != nil {
 		return err
 	}
+
 	http.Handle("/", h)
 
 	ctx, done := context.WithCancel(context.Background())

From b70fc4d51e76fc023afcd005c467d415c0c62750 Mon Sep 17 00:00:00 2001
From: Jesse Gross <jesse@ollama.com>
Date: Wed, 5 Mar 2025 13:27:53 -0800
Subject: [PATCH 003/157] model: Don't unconditionally add special tokens

We sometimes tokenize partial strings. For example, with
multimodal inputs, we split the input string around the images
and then tokenize each piece. In these cases, we should only add
the special tokens on the first piece.
---
 llm/server.go                 |  2 +-
 model/process_text.go         |  6 +++---
 model/process_text_test.go    | 14 +++++++-------
 runner/ollamarunner/runner.go |  2 +-
 4 files changed, 12 insertions(+), 12 deletions(-)

diff --git a/llm/server.go b/llm/server.go
index 09690a5f..9553ba8f 100644
--- a/llm/server.go
+++ b/llm/server.go
@@ -973,7 +973,7 @@ func (s *llmServer) Tokenize(ctx context.Context, content string) ([]int, error)
 		return s.llamaModel.Tokenize(content, false, true)
 	}
 	if s.textProcessor != nil {
-		tokens, err := s.textProcessor.Encode(content)
+		tokens, err := s.textProcessor.Encode(content, false)
 		if err != nil {
 			return nil, err
 		}
diff --git a/model/process_text.go b/model/process_text.go
index 7083f36f..bfb0a5f2 100644
--- a/model/process_text.go
+++ b/model/process_text.go
@@ -19,7 +19,7 @@ const (
 )
 
 type TextProcessor interface {
-	Encode(string) ([]int32, error)
+	Encode(s string, addSpecial bool) ([]int32, error)
 	Decode([]int32) (string, error)
 	Is(int32, Special) bool
 }
@@ -144,7 +144,7 @@ type merge struct {
 	runes []rune
 }
 
-func (bpe BytePairEncoding) Encode(s string) ([]int32, error) {
+func (bpe BytePairEncoding) Encode(s string, addSpecial bool) ([]int32, error) {
 	fragments := []fragment{{value: s}}
 	for _, special := range bpe.vocab.SpecialVocabulary() {
 		// TODO: process special tokens concurrently
@@ -282,7 +282,7 @@ func (bpe BytePairEncoding) Encode(s string) ([]int32, error) {
 		}
 	}
 
-	if len(ids) > 0 {
+	if addSpecial && len(ids) > 0 {
 		if bpe.vocab.AddBOS {
 			if ids[0] == bpe.vocab.BOS {
 				slog.Warn("adding bos token to prompt which already has it", "id", bpe.vocab.BOS)
diff --git a/model/process_text_test.go b/model/process_text_test.go
index cad1f94f..f4830321 100644
--- a/model/process_text_test.go
+++ b/model/process_text_test.go
@@ -74,7 +74,7 @@ func TestLlama(t *testing.T) {
 	t.Run("simple", func(t *testing.T) {
 		t.Parallel()
 
-		ids, err := tokenizer.Encode("hello world")
+		ids, err := tokenizer.Encode("hello world", true)
 		if err != nil {
 			t.Error(err)
 		}
@@ -92,7 +92,7 @@ func TestLlama(t *testing.T) {
 			t.Errorf("got %q, want hello world", s)
 		}
 
-		ids, err = tokenizer.Encode("hello <|end_of_text|>")
+		ids, err = tokenizer.Encode("hello <|end_of_text|>", true)
 		if err != nil {
 			t.Error(err)
 		}
@@ -126,7 +126,7 @@ func TestLlama(t *testing.T) {
 		}
 
 		for s, want := range cases {
-			ids, err := tokenizer.Encode(s)
+			ids, err := tokenizer.Encode(s, true)
 			if err != nil {
 				t.Error(err)
 			}
@@ -152,7 +152,7 @@ func TestLlama(t *testing.T) {
 		}
 
 		for _, want := range cases {
-			ids, err := tokenizer.Encode(want)
+			ids, err := tokenizer.Encode(want, true)
 			if err != nil {
 				t.Error(err)
 			}
@@ -176,7 +176,7 @@ func TestLlama(t *testing.T) {
 		}
 
 		for s, want := range cases {
-			ids, err := tokenizer.Encode(s)
+			ids, err := tokenizer.Encode(s, true)
 			if err != nil {
 				t.Fatal(err)
 			}
@@ -222,7 +222,7 @@ func BenchmarkBytePairEncoding(b *testing.B) {
 		b.Run("encode"+strconv.Itoa(n), func(b *testing.B) {
 			b.ResetTimer()
 			for range b.N {
-				_, err := tokenizer.Encode(string(bts))
+				_, err := tokenizer.Encode(string(bts), true)
 				if err != nil {
 					b.Fatal(err)
 				}
@@ -230,7 +230,7 @@ func BenchmarkBytePairEncoding(b *testing.B) {
 		})
 
 		b.Run("decode"+strconv.Itoa(n), func(b *testing.B) {
-			ids, err := tokenizer.Encode(string(bts))
+			ids, err := tokenizer.Encode(string(bts), true)
 			if err != nil {
 				b.Fatal(err)
 			}
diff --git a/runner/ollamarunner/runner.go b/runner/ollamarunner/runner.go
index 1a4bbf19..9ba6563f 100644
--- a/runner/ollamarunner/runner.go
+++ b/runner/ollamarunner/runner.go
@@ -161,7 +161,7 @@ func (s *Server) inputs(prompt string, images []ImageData) ([]input, error) {
 
 	for i, part := range parts {
 		// text - tokenize
-		tokens, err := s.model.(model.TextProcessor).Encode(part)
+		tokens, err := s.model.(model.TextProcessor).Encode(part, i == 0)
 		if err != nil {
 			return nil, err
 		}

From a7e63b82be6dfcd8011e0b45f19658be71c0e2b9 Mon Sep 17 00:00:00 2001
From: Jesse Gross <jesse@ollama.com>
Date: Wed, 5 Mar 2025 12:08:06 -0800
Subject: [PATCH 004/157] ollamarunner: Improve multimodal input handling

Various vision models have different requirements for how they
receive their inputs. For example:
 - Mllama wants images together with text and the image embeddings
   don't themselves have positions or get stored in the main KV cache
 - Llava-style models feed in embeddings similar to tokens and
   images correspond to a varying number of tokens in the cache.

In addition, the strategy for providing inputs must support batching
and multiple sequences, which are managed by the runner. At the same
time, we want to keep data handling fully in the model so that new
architectures are not bottlenecked by runner code which does not
understand their particular requirements.

This provides a method for models to edit the input stream so that
it meets their needs while still being in a format that the runner
understands. This allows the runner to avoid special processing
for different models.

In addition, this fixes a regression where non-vision models may
try to incorrectly interpret images.
---
 model/model.go                    |  70 +++++++++++++++++--
 model/models/mllama/model.go      | 109 +++++++++++++++++++++---------
 runner/ollamarunner/cache.go      |  20 +++---
 runner/ollamarunner/cache_test.go |  74 +++++++++++---------
 runner/ollamarunner/runner.go     | 104 ++++++++++++++++------------
 5 files changed, 247 insertions(+), 130 deletions(-)

diff --git a/model/model.go b/model/model.go
index f8ed8741..75b7f639 100644
--- a/model/model.go
+++ b/model/model.go
@@ -3,7 +3,6 @@ package model
 import (
 	"errors"
 	"fmt"
-	"image"
 	_ "image/jpeg"
 	_ "image/png"
 	"log/slog"
@@ -22,14 +21,40 @@ import (
 	_ "github.com/ollama/ollama/ml/backend"
 )
 
+// Input represents one token in the input stream
+type Input struct {
+	// Token is a single element of text.
+	Token int32
+
+	// Multimodal is opaque data representing a non-text
+	// element such as an image (or part of one if the image
+	// can be processed in pieces). It may be either together
+	// with Token or on its own.
+	Multimodal any
+
+	// MultimodalHash is a unique representation of the data
+	// stored in Multimodal, used for caching and comparing
+	// equality.
+	MultimodalHash uint64
+}
+
+// MultimodalIndex is a multimodal element (such as an image)
+// together with an index into the slice of Inputs with the
+// corresponding token. Note that the index is not the same
+// as the position - to find that use the index with the
+// Positions slice.
+type MultimodalIndex struct {
+	Index      int
+	Multimodal any
+}
+
 // Options contains the inputs for a model forward pass
 type Options struct {
-	Inputs    []int32
-	Positions []int32
-	Sequences []int
-	Outputs   []int32
-
-	Images []image.Image
+	Inputs     []int32
+	Multimodal []MultimodalIndex
+	Positions  []int32
+	Sequences  []int
+	Outputs    []int32
 }
 
 type config struct {
@@ -59,6 +84,37 @@ type Model interface {
 	Config() config
 }
 
+// MultimodalProcessor must be implemented by multimodal models.
+type MultimodalProcessor interface {
+	// EncodeMultimodal processes a single input (such as an image) and
+	// generates an output (typically an embedding) that can be used by the model.
+	//
+	// The return value is most typically an ml.Tensor, however, different
+	// type are possible, such as an object containing a tensor plus
+	// additional metadata, a slice of tensors or even just the original input.
+	//
+	// The result may be cached by the runner.
+	EncodeMultimodal(ml.Context, []byte) (any, error)
+
+	// PostTokenize is called after tokenization to allow the model to edit the
+	// input stream to correctly arrange multimodal elements.
+	//
+	// The input is a slice of tokens with the results of EncodeMultimodal interleaved
+	// in the order that the user provided them. Each element of the slice will be
+	// either a single token or single multimodal object.
+	//
+	// The model must ensure that inputs are stored according to how they will be
+	// processed and stored in the cache. For example, Llava-style models should insert
+	// placeholder tokens equal to the feature size of the corresponding image with
+	// the image itself attached to and split across these tokens. When Forward is called
+	// a partial subset of these tokens may be submitted according to the batch size.
+	//
+	// This function is also responsible for updating MultimodalHash for any Multimodal
+	// that is modified to ensure that there is a unique hash value that accurately
+	// represents the contents.
+	PostTokenize(ml.Context, []Input) ([]Input, error)
+}
+
 var models = make(map[string]func(ml.Config) (Model, error))
 
 // Register registers a model constructor for the given architecture
diff --git a/model/models/mllama/model.go b/model/models/mllama/model.go
index 8fee0cdb..945c7295 100644
--- a/model/models/mllama/model.go
+++ b/model/models/mllama/model.go
@@ -1,7 +1,12 @@
 package mllama
 
 import (
+	"bytes"
+	"encoding/binary"
 	"fmt"
+	"hash/fnv"
+	"image"
+	"slices"
 
 	"github.com/ollama/ollama/kvcache"
 	"github.com/ollama/ollama/ml"
@@ -56,41 +61,79 @@ func New(c ml.Config) (model.Model, error) {
 	return &m, nil
 }
 
+func (m *Model) EncodeMultimodal(ctx ml.Context, multimodalData []byte) (any, error) {
+	image, _, err := image.Decode(bytes.NewReader(multimodalData))
+	if err != nil {
+		return nil, err
+	}
+
+	f32s, aspectRatioID, err := m.ImageProcessor.ProcessImage(image)
+	if err != nil {
+		return nil, err
+	}
+
+	pixelValues, err := ctx.FromFloatSlice(f32s,
+		m.ImageProcessor.imageSize,
+		m.ImageProcessor.imageSize,
+		m.ImageProcessor.numChannels,
+		m.ImageProcessor.maxNumTiles,
+	)
+	if err != nil {
+		return nil, err
+	}
+
+	aspectRatio, err := ctx.FromIntSlice([]int32{int32(aspectRatioID)}, 1)
+	if err != nil {
+		return nil, err
+	}
+
+	positions := make([]int32, 1601)
+	for i := range positions {
+		positions[i] = int32(i)
+	}
+
+	positionIDs, err := ctx.FromIntSlice(positions, len(positions))
+	if err != nil {
+		return nil, err
+	}
+
+	crossAttentionStates := m.VisionModel.Forward(ctx, pixelValues, positionIDs, aspectRatio)
+	return m.Projector.Forward(ctx, crossAttentionStates), nil
+}
+
+func (m *Model) PostTokenize(ctx ml.Context, inputs []model.Input) ([]model.Input, error) {
+	var images []model.Input
+	fnvHash := fnv.New64a()
+
+	for i := range inputs {
+		if inputs[i].Multimodal == nil {
+			if len(images) > 0 {
+				inputs[i].Multimodal = images[0].Multimodal
+				inputs[i].MultimodalHash = images[0].MultimodalHash
+				for j := 1; j < len(images); j++ {
+					inputs[i].Multimodal = inputs[i].Multimodal.(ml.Tensor).Concat(ctx, images[j].Multimodal.(ml.Tensor), 3)
+					fnvHash.Reset()
+					binary.Write(fnvHash, binary.NativeEndian, inputs[i].MultimodalHash)
+					binary.Write(fnvHash, binary.NativeEndian, inputs[j].MultimodalHash)
+					inputs[i].MultimodalHash = fnvHash.Sum64()
+				}
+				images = nil
+			}
+		} else {
+			images = append(images, inputs[i])
+			inputs[i].Token = -1
+		}
+	}
+
+	inputs = slices.DeleteFunc(inputs, func(input model.Input) bool { return input.Token == -1 })
+
+	return inputs, nil
+}
+
 func (m *Model) Forward(ctx ml.Context, opts model.Options) (ml.Tensor, error) {
 	var crossAttentionStates ml.Tensor
-	if opts.Images != nil {
-		f32s, aspectRatioID, err := m.ImageProcessor.ProcessImage(opts.Images[0])
-		if err != nil {
-			return nil, err
-		}
-
-		pixelValues, err := ctx.FromFloatSlice(f32s,
-			m.ImageProcessor.imageSize,
-			m.ImageProcessor.imageSize,
-			m.ImageProcessor.numChannels,
-			m.ImageProcessor.maxNumTiles,
-		)
-		if err != nil {
-			return nil, err
-		}
-
-		aspectRatio, err := ctx.FromIntSlice([]int32{int32(aspectRatioID)}, 1)
-		if err != nil {
-			return nil, err
-		}
-
-		positions := make([]int32, 1601)
-		for i := range positions {
-			positions[i] = int32(i)
-		}
-
-		positionIDs, err := ctx.FromIntSlice(positions, len(positions))
-		if err != nil {
-			return nil, err
-		}
-
-		crossAttentionStates = m.VisionModel.Forward(ctx, pixelValues, positionIDs, aspectRatio)
-		crossAttentionStates = m.Projector.Forward(ctx, crossAttentionStates)
+	if opts.Multimodal != nil {
+		crossAttentionStates = opts.Multimodal[0].Multimodal.(ml.Tensor)
 	}
 
 	inputs, err := ctx.FromIntSlice(opts.Inputs, len(opts.Inputs))
diff --git a/runner/ollamarunner/cache.go b/runner/ollamarunner/cache.go
index e1fa98b1..2fd060a1 100644
--- a/runner/ollamarunner/cache.go
+++ b/runner/ollamarunner/cache.go
@@ -5,7 +5,6 @@ import (
 	"fmt"
 	"log/slog"
 	"math"
-	"reflect"
 	"time"
 
 	"github.com/ollama/ollama/kvcache"
@@ -39,10 +38,7 @@ func NewInputCache(model model.Model, kvCacheType string, kvSize int32, numSlots
 	slots := make([]InputCacheSlot, numSlots)
 
 	for i := range slots {
-		slots[i] = InputCacheSlot{
-			Id:     i,
-			Inputs: make([]input, 0),
-		}
+		slots[i] = InputCacheSlot{Id: i}
 	}
 
 	cache := model.Config().Cache
@@ -83,7 +79,7 @@ type InputCacheSlot struct {
 	Id int
 
 	// Inputs that are stored in the KV cache
-	Inputs []input
+	Inputs []model.Input
 
 	// is this cache actively being processed as part of a sequence?
 	InUse bool
@@ -92,7 +88,7 @@ type InputCacheSlot struct {
 	lastUsed time.Time
 }
 
-func (c *InputCache) LoadCacheSlot(prompt []input, cachePrompt bool) (*InputCacheSlot, []input, error) {
+func (c *InputCache) LoadCacheSlot(prompt []model.Input, cachePrompt bool) (*InputCacheSlot, []model.Input, error) {
 	var slot *InputCacheSlot
 	var numPast int32
 	var err error
@@ -143,7 +139,7 @@ func (c *InputCache) LoadCacheSlot(prompt []input, cachePrompt bool) (*InputCach
 	return slot, prompt, nil
 }
 
-func (c *InputCache) findLongestCacheSlot(prompt []input) (*InputCacheSlot, int32, error) {
+func (c *InputCache) findLongestCacheSlot(prompt []model.Input) (*InputCacheSlot, int32, error) {
 	longest := int32(-1)
 	var longestSlot *InputCacheSlot
 
@@ -166,7 +162,7 @@ func (c *InputCache) findLongestCacheSlot(prompt []input) (*InputCacheSlot, int3
 	return longestSlot, longest, nil
 }
 
-func (c *InputCache) findBestCacheSlot(prompt []input) (*InputCacheSlot, int32, error) {
+func (c *InputCache) findBestCacheSlot(prompt []model.Input) (*InputCacheSlot, int32, error) {
 	oldest := time.Now()
 	var oldestSlot *InputCacheSlot
 
@@ -202,7 +198,7 @@ func (c *InputCache) findBestCacheSlot(prompt []input) (*InputCacheSlot, int32,
 	if longest > 0 && longestSlot != oldestSlot {
 		slog.Debug("forking cache slot", "src", longestSlot.Id, "dst", oldestSlot.Id, "inputs", longest, "total",
 			len(longestSlot.Inputs))
-		oldestSlot.Inputs = make([]input, longest)
+		oldestSlot.Inputs = make([]model.Input, longest)
 		copy(oldestSlot.Inputs, longestSlot.Inputs[:longest])
 		if c.cache != nil {
 			c.cache.CopyPrefix(longestSlot.Id, oldestSlot.Id, longest)
@@ -212,7 +208,7 @@ func (c *InputCache) findBestCacheSlot(prompt []input) (*InputCacheSlot, int32,
 	return oldestSlot, longest, nil
 }
 
-func countCommonPrefix(a []input, b []input) int32 {
+func countCommonPrefix(a []model.Input, b []model.Input) int32 {
 	var count int32
 
 	for i := range a {
@@ -220,7 +216,7 @@ func countCommonPrefix(a []input, b []input) int32 {
 			break
 		}
 
-		if !reflect.DeepEqual(a[i], b[i]) {
+		if a[i].Token != b[i].Token || a[i].MultimodalHash != b[i].MultimodalHash {
 			break
 		}
 
diff --git a/runner/ollamarunner/cache_test.go b/runner/ollamarunner/cache_test.go
index 99e67b4f..9ce03b73 100644
--- a/runner/ollamarunner/cache_test.go
+++ b/runner/ollamarunner/cache_test.go
@@ -4,6 +4,8 @@ import (
 	"image"
 	"testing"
 	"time"
+
+	"github.com/ollama/ollama/model"
 )
 
 func TestCountCommon(t *testing.T) {
@@ -13,44 +15,50 @@ func TestCountCommon(t *testing.T) {
 
 	tests := []struct {
 		name     string
-		t1       []input
-		t2       []input
+		t1       []model.Input
+		t2       []model.Input
 		expected int32
 	}{
 		{
 			name:     "Equal",
-			t1:       []input{{token: 1}, {token: 2}, {token: 3}},
-			t2:       []input{{token: 1}, {token: 2}, {token: 3}},
+			t1:       []model.Input{{Token: 1}, {Token: 2}, {Token: 3}},
+			t2:       []model.Input{{Token: 1}, {Token: 2}, {Token: 3}},
 			expected: 3,
 		},
 		{
 			name:     "Prefix",
-			t1:       []input{{token: 1}},
-			t2:       []input{{token: 1}, {token: 2}, {token: 3}},
+			t1:       []model.Input{{Token: 1}},
+			t2:       []model.Input{{Token: 1}, {Token: 2}, {Token: 3}},
 			expected: 1,
 		},
 		{
 			name:     "Image Prefix",
-			t1:       []input{{image: imgA}},
-			t2:       []input{{image: imgA}, {image: imgB}, {image: imgC}},
+			t1:       []model.Input{{Multimodal: imgA, MultimodalHash: 1}},
+			t2:       []model.Input{{Multimodal: imgA, MultimodalHash: 1}, {Multimodal: imgB, MultimodalHash: 2}, {Multimodal: imgC, MultimodalHash: 3}},
 			expected: 1,
 		},
 		{
 			name:     "Mixed",
-			t1:       []input{{token: 1}, {image: imgA}},
-			t2:       []input{{token: 1}, {image: imgA}, {token: 5}},
+			t1:       []model.Input{{Token: 1}, {Multimodal: imgA, MultimodalHash: 1}},
+			t2:       []model.Input{{Token: 1}, {Multimodal: imgA, MultimodalHash: 1}, {Token: 5}},
 			expected: 2,
 		},
+		{
+			name:     "Mixed, Same Length",
+			t1:       []model.Input{{Token: 1}, {Multimodal: imgA, MultimodalHash: 1}},
+			t2:       []model.Input{{Token: 1}, {Multimodal: imgB, MultimodalHash: 2}},
+			expected: 1,
+		},
 		{
 			name:     "Empty",
-			t1:       []input{},
-			t2:       []input{{token: 1}, {token: 2}, {token: 3}},
+			t1:       []model.Input{},
+			t2:       []model.Input{{Token: 1}, {Token: 2}, {Token: 3}},
 			expected: 0,
 		},
 		{
 			name:     "Both Empty",
-			t1:       []input{},
-			t2:       []input{},
+			t1:       []model.Input{},
+			t2:       []model.Input{},
 			expected: 0,
 		},
 	}
@@ -74,7 +82,7 @@ func TestFindCacheSlot(t *testing.T) {
 	tests := []struct {
 		name    string
 		cache   InputCache
-		prompt  []input
+		prompt  []model.Input
 		longest expected
 		best    expected
 	}{
@@ -83,18 +91,18 @@ func TestFindCacheSlot(t *testing.T) {
 			cache: InputCache{slots: []InputCacheSlot{
 				{
 					Id:       0,
-					Inputs:   []input{},
+					Inputs:   []model.Input{},
 					InUse:    false,
 					lastUsed: time.Time{},
 				},
 				{
 					Id:       1,
-					Inputs:   []input{},
+					Inputs:   []model.Input{},
 					InUse:    false,
 					lastUsed: time.Time{},
 				},
 			}},
-			prompt:  []input{{token: 1}},
+			prompt:  []model.Input{{Token: 1}},
 			longest: expected{result: 0, len: 0},
 			best:    expected{result: 0, len: 0},
 		},
@@ -103,18 +111,18 @@ func TestFindCacheSlot(t *testing.T) {
 			cache: InputCache{slots: []InputCacheSlot{
 				{
 					Id:       0,
-					Inputs:   []input{{token: 1}},
+					Inputs:   []model.Input{{Token: 1}},
 					InUse:    false,
 					lastUsed: time.Now().Add(-time.Second),
 				},
 				{
 					Id:       1,
-					Inputs:   []input{{token: 1}, {token: 2}},
+					Inputs:   []model.Input{{Token: 1}, {Token: 2}},
 					InUse:    false,
 					lastUsed: time.Now().Add(-2 * time.Second),
 				},
 			}},
-			prompt:  []input{{token: 1}, {token: 2}},
+			prompt:  []model.Input{{Token: 1}, {Token: 2}},
 			longest: expected{result: 1, len: 2},
 			best:    expected{result: 1, len: 2},
 		},
@@ -123,18 +131,18 @@ func TestFindCacheSlot(t *testing.T) {
 			cache: InputCache{slots: []InputCacheSlot{
 				{
 					Id:       0,
-					Inputs:   []input{{token: 1}, {token: 2}},
+					Inputs:   []model.Input{{Token: 1}, {Token: 2}},
 					InUse:    false,
 					lastUsed: time.Now().Add(-time.Second),
 				},
 				{
 					Id:       1,
-					Inputs:   []input{},
+					Inputs:   []model.Input{},
 					InUse:    false,
 					lastUsed: time.Time{},
 				},
 			}},
-			prompt:  []input{{token: 2}},
+			prompt:  []model.Input{{Token: 2}},
 			longest: expected{result: 0, len: 0},
 			best:    expected{result: 1, len: 0},
 		},
@@ -144,19 +152,19 @@ func TestFindCacheSlot(t *testing.T) {
 				slots: []InputCacheSlot{
 					{
 						Id:       0,
-						Inputs:   []input{{token: 1}, {token: 2}},
+						Inputs:   []model.Input{{Token: 1}, {Token: 2}},
 						InUse:    false,
 						lastUsed: time.Now().Add(-time.Second),
 					},
 					{
 						Id:       1,
-						Inputs:   []input{},
+						Inputs:   []model.Input{},
 						InUse:    false,
 						lastUsed: time.Time{},
 					},
 				},
 			},
-			prompt:  []input{{token: 1}},
+			prompt:  []model.Input{{Token: 1}},
 			longest: expected{result: 0, len: 1},
 			best:    expected{result: 1, len: 1},
 		},
@@ -165,18 +173,18 @@ func TestFindCacheSlot(t *testing.T) {
 			cache: InputCache{slots: []InputCacheSlot{
 				{
 					Id:       0,
-					Inputs:   []input{{token: 1}},
+					Inputs:   []model.Input{{Token: 1}},
 					InUse:    false,
 					lastUsed: time.Now().Add(-time.Second),
 				},
 				{
 					Id:       1,
-					Inputs:   []input{{token: 1}, {token: 2}},
+					Inputs:   []model.Input{{Token: 1}, {Token: 2}},
 					InUse:    false,
 					lastUsed: time.Now().Add(-2 * time.Second),
 				},
 			}},
-			prompt:  []input{{token: 2}, {token: 3}},
+			prompt:  []model.Input{{Token: 2}, {Token: 3}},
 			longest: expected{result: 0, len: 0},
 			best:    expected{result: 1, len: 0},
 		},
@@ -185,18 +193,18 @@ func TestFindCacheSlot(t *testing.T) {
 			cache: InputCache{slots: []InputCacheSlot{
 				{
 					Id:       0,
-					Inputs:   []input{{token: 1}, {token: 2}},
+					Inputs:   []model.Input{{Token: 1}, {Token: 2}},
 					InUse:    true,
 					lastUsed: time.Now().Add(-time.Second),
 				},
 				{
 					Id:       1,
-					Inputs:   []input{{token: 1}},
+					Inputs:   []model.Input{{Token: 1}},
 					InUse:    false,
 					lastUsed: time.Now().Add(-2 * time.Second),
 				},
 			}},
-			prompt:  []input{{token: 1}, {token: 2}},
+			prompt:  []model.Input{{Token: 1}, {Token: 2}},
 			longest: expected{result: 1, len: 1},
 			best:    expected{result: 1, len: 2},
 		},
diff --git a/runner/ollamarunner/runner.go b/runner/ollamarunner/runner.go
index 9ba6563f..e5189fa5 100644
--- a/runner/ollamarunner/runner.go
+++ b/runner/ollamarunner/runner.go
@@ -1,13 +1,12 @@
 package ollamarunner
 
 import (
-	"bytes"
 	"context"
 	"encoding/json"
 	"errors"
 	"flag"
 	"fmt"
-	"image"
+	"hash/maphash"
 	"log"
 	"log/slog"
 	"net"
@@ -33,22 +32,19 @@ import (
 	_ "github.com/ollama/ollama/model/models"
 )
 
-// input is an element of the prompt to process, either a token or an image
-type input struct {
-	token int32
-
-	image image.Image
-}
-
 type Sequence struct {
+	// ctx for allocating tensors that last the lifetime of the sequence, such as
+	// multimodal embeddings
+	ctx ml.Context
+
 	// batch index
 	iBatch int
 
 	// prompt inputs left to evaluate
-	inputs []input
+	inputs []model.Input
 
 	// inputs that have been added to a batch but not yet submitted to Forward
-	pendingInputs []input
+	pendingInputs []model.Input
 
 	// tokens that have been generated but not returned yet (e.g. for stop sequences)
 	pendingResponses []string
@@ -101,8 +97,9 @@ func (s *Server) NewSequence(prompt string, images []ImageData, params NewSequen
 	s.ready.Wait()
 
 	startTime := time.Now()
+	ctx := s.model.Backend().NewContext()
 
-	inputs, err := s.inputs(prompt, images)
+	inputs, err := s.inputs(ctx, prompt, images)
 	if err != nil {
 		return nil, fmt.Errorf("failed to process inputs: %w", err)
 	} else if len(inputs) == 0 {
@@ -128,6 +125,7 @@ func (s *Server) NewSequence(prompt string, images []ImageData, params NewSequen
 	// TODO(jessegross): Ingest cached history for grammar
 
 	return &Sequence{
+		ctx:                 ctx,
 		inputs:              inputs,
 		numPromptInputs:     len(inputs),
 		startProcessingTime: startTime,
@@ -146,19 +144,22 @@ func (s *Server) NewSequence(prompt string, images []ImageData, params NewSequen
 // inputs processes the prompt and images into a list of inputs
 // by splitting the prompt on [img-<n>] tags, tokenizing text and
 // decoding images
-func (s *Server) inputs(prompt string, images []ImageData) ([]input, error) {
-	var inputs []input
+func (s *Server) inputs(ctx ml.Context, prompt string, images []ImageData) ([]model.Input, error) {
+	var inputs []model.Input
 	var parts []string
 	var matches [][]string
 
-	// TODO(jessegross): This can sometimes trigger for matching text in the
-	// user's prompt. We previously tried to avoid it by only looking for images
-	// on image models. We don't have a clear indication now but it would be better
-	// to properly escape it in any case.
-	re := regexp.MustCompile(`\[img-(\d+)\]`)
-	parts = re.Split(prompt, -1)
-	matches = re.FindAllStringSubmatch(prompt, -1)
+	multimodalProcessor, visionModel := s.model.(model.MultimodalProcessor)
 
+	if visionModel {
+		re := regexp.MustCompile(`\[img-(\d+)\]`)
+		parts = re.Split(prompt, -1)
+		matches = re.FindAllStringSubmatch(prompt, -1)
+	} else {
+		parts = []string{prompt}
+	}
+
+	postTokenize := false
 	for i, part := range parts {
 		// text - tokenize
 		tokens, err := s.model.(model.TextProcessor).Encode(part, i == 0)
@@ -167,7 +168,7 @@ func (s *Server) inputs(prompt string, images []ImageData) ([]input, error) {
 		}
 
 		for _, t := range tokens {
-			inputs = append(inputs, input{token: t})
+			inputs = append(inputs, model.Input{Token: t})
 		}
 
 		// image - decode and store
@@ -186,12 +187,25 @@ func (s *Server) inputs(prompt string, images []ImageData) ([]input, error) {
 				return nil, fmt.Errorf("invalid image index: %d", n)
 			}
 
-			image, _, err := image.Decode(bytes.NewReader(images[imageIndex].Data))
+			imageEmbeddings, err := multimodalProcessor.EncodeMultimodal(ctx, images[imageIndex].Data)
 			if err != nil {
 				return nil, err
 			}
 
-			inputs = append(inputs, input{image: image})
+			s.multimodalHash.Reset()
+			_, _ = s.multimodalHash.Write(images[imageIndex].Data)
+			imageHash := s.multimodalHash.Sum64()
+
+			inputs = append(inputs, model.Input{Multimodal: imageEmbeddings, MultimodalHash: imageHash})
+			postTokenize = true
+		}
+	}
+
+	if visionModel && postTokenize {
+		var err error
+		inputs, err = multimodalProcessor.PostTokenize(ctx, inputs)
+		if err != nil {
+			return nil, err
 		}
 	}
 
@@ -238,6 +252,10 @@ type Server struct {
 
 	// next sequence for prompt processing to avoid starvation
 	nextSeq int
+
+	// multimodalHash generates hashes for comparing equality
+	// of non-text data
+	multimodalHash maphash.Hash
 }
 
 func (s *Server) allNil() bool {
@@ -283,6 +301,7 @@ func (s *Server) removeSequence(seqIndex int, reason string) {
 	close(seq.responses)
 	close(seq.embedding)
 	seq.cache.InUse = false
+	seq.ctx.Close()
 	s.seqs[seqIndex] = nil
 	s.seqsSem.Release(1)
 }
@@ -311,7 +330,6 @@ func (s *Server) processBatch() error {
 	defer s.mu.Unlock()
 
 	var options model.Options
-	imgSeq := -1
 
 	seqIdx := s.nextSeq - 1
 	for range s.seqs {
@@ -330,7 +348,7 @@ func (s *Server) processBatch() error {
 
 		if !s.cache.enabled {
 			seq.inputs = append(seq.cache.Inputs, seq.inputs...)
-			seq.cache.Inputs = []input{}
+			seq.cache.Inputs = []model.Input{}
 		}
 
 		for i, input := range seq.inputs {
@@ -349,25 +367,21 @@ func (s *Server) processBatch() error {
 				break
 			}
 
-			// TODO(jessegross): Image inputs need to be rethought - it's
-			// it doesn't work well for different types of models or multiple sequences
-			if input.image != nil {
-				if len(seq.pendingInputs) != len(options.Images) {
-					break
-				}
-
-				if imgSeq != seqIdx && imgSeq != -1 {
-					s.nextSeq = seqIdx
-					break
-				}
-
-				imgSeq = seqIdx
-				options.Images = append(options.Images, input.image)
-				seq.pendingInputs = append(seq.pendingInputs, input)
-				continue
+			// TODO(jessegross): This is a workaround for generating an attention mask and also providing a hint
+			// to the encoder cache.
+			//
+			// Break the batch when switching from text to images so that images are always at the beginning.
+			if input.Multimodal != nil && !(len(seq.pendingInputs) == 0 ||
+				(len(options.Multimodal) > 0 && options.Multimodal[len(options.Multimodal)-1].Index == len(options.Inputs)-1)) {
+				s.nextSeq = seqIdx
+				break
+			}
+
+			options.Inputs = append(options.Inputs, input.Token)
+			if input.Multimodal != nil {
+				options.Multimodal = append(options.Multimodal, model.MultimodalIndex{Index: len(options.Inputs) - 1, Multimodal: input.Multimodal})
 			}
 
-			options.Inputs = append(options.Inputs, input.token)
 			options.Positions = append(options.Positions, int32(len(seq.cache.Inputs)+len(seq.pendingInputs)))
 			options.Sequences = append(options.Sequences, seq.cache.Id)
 
@@ -403,7 +417,7 @@ func (s *Server) processBatch() error {
 		// After calling Forward, pending inputs are now in the cache
 		if len(seq.pendingInputs) > 0 {
 			seq.cache.Inputs = append(seq.cache.Inputs, seq.pendingInputs...)
-			seq.pendingInputs = []input{}
+			seq.pendingInputs = []model.Input{}
 		}
 
 		// don't sample prompt processing
@@ -449,7 +463,7 @@ func (s *Server) processBatch() error {
 			return err
 		}
 
-		seq.inputs = []input{{token: token}}
+		seq.inputs = []model.Input{{Token: token}}
 
 		seq.pendingResponses = append(seq.pendingResponses, piece)
 		sequence := strings.Join(seq.pendingResponses, "")

From 25248f4bd5a1d720f6775ee1e45dfed718d6f98f Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?=E2=80=AErekc=C3=A4H=20nitraM=E2=80=AE?=
 <spamfaenger@gmx.de>
Date: Fri, 7 Mar 2025 10:26:31 +0100
Subject: [PATCH 005/157] Better WantedBy declaration

The problem with default.target is that it always points to the target that is currently started. So if you boot into single user mode or the rescue mode still Ollama tries to start.

I noticed this because either tried (and failed) to start all the time during a system update, where Ollama definitely is not wanted.
---
 docs/linux.md | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/docs/linux.md b/docs/linux.md
index 12581bdd..2dda87f3 100644
--- a/docs/linux.md
+++ b/docs/linux.md
@@ -75,7 +75,7 @@ RestartSec=3
 Environment="PATH=$PATH"
 
 [Install]
-WantedBy=default.target
+WantedBy=multi-user.target
 ```
 
 Then start the service:

From 4289c74359ad7cac0d4350c22e6af3f92c5f091c Mon Sep 17 00:00:00 2001
From: Jeffrey Morgan <jmorganca@gmail.com>
Date: Fri, 7 Mar 2025 09:25:34 -0800
Subject: [PATCH 006/157] llama: fix kv loading on snowflake-arctic-embed
 models (#9536)

---
 llama/llama.cpp/src/llama-vocab.cpp           |  2 +-
 .../0019-fix-string-arr-kv-loading.patch      | 64 +++++++++++++++++++
 ml/backend/ggml/ggml/include/gguf.h           |  1 +
 ml/backend/ggml/ggml/src/gguf.cpp             |  7 +-
 4 files changed, 71 insertions(+), 3 deletions(-)
 create mode 100644 llama/patches/0019-fix-string-arr-kv-loading.patch

diff --git a/llama/llama.cpp/src/llama-vocab.cpp b/llama/llama.cpp/src/llama-vocab.cpp
index c7ff28be..7a185443 100644
--- a/llama/llama.cpp/src/llama-vocab.cpp
+++ b/llama/llama.cpp/src/llama-vocab.cpp
@@ -1443,7 +1443,7 @@ void llama_vocab::impl::load(llama_model_loader & ml, const LLM_KV & kv) {
 
             const int precompiled_charsmap_keyidx = gguf_find_key(ctx, kv(LLM_KV_TOKENIZER_PRECOMPILED_CHARSMAP).c_str());
             if (precompiled_charsmap_keyidx != -1) {
-                size_t n_precompiled_charsmap = gguf_get_arr_n(ctx, precompiled_charsmap_keyidx);
+                size_t n_precompiled_charsmap = gguf_get_arr_data_n(ctx, precompiled_charsmap_keyidx);
                 const char * pc = (const char *) gguf_get_arr_data(ctx, precompiled_charsmap_keyidx);
                 precompiled_charsmap.assign(pc, pc + n_precompiled_charsmap);
 #ifdef IS_BIG_ENDIAN
diff --git a/llama/patches/0019-fix-string-arr-kv-loading.patch b/llama/patches/0019-fix-string-arr-kv-loading.patch
new file mode 100644
index 00000000..aa7b4d3c
--- /dev/null
+++ b/llama/patches/0019-fix-string-arr-kv-loading.patch
@@ -0,0 +1,64 @@
+From 0000000000000000000000000000000000000000 Mon Sep 17 00:00:00 2001
+From: jmorganca <jmorganca@gmail.com>
+Date: Wed, 5 Mar 2025 17:41:07 -0800
+Subject: [PATCH] fix string arr kv loading
+
+---
+ ggml/include/gguf.h | 1 +
+ ggml/src/gguf.cpp   | 7 +++++--
+ src/llama-vocab.cpp | 2 +-
+ 3 files changed, 7 insertions(+), 3 deletions(-)
+
+diff --git a/ggml/include/gguf.h b/ggml/include/gguf.h
+index 79ee2020..3efb22f0 100644
+--- a/ggml/include/gguf.h
++++ b/ggml/include/gguf.h
+@@ -114,6 +114,7 @@ extern "C" {
+     // get raw pointer to the first element of the array with the given key_id
+     // for bool arrays, note that they are always stored as int8 on all platforms (usually this makes no difference)
+     GGML_API const void * gguf_get_arr_data(const struct gguf_context * ctx, int64_t key_id);
++    GGML_API size_t       gguf_get_arr_data_n(const struct gguf_context * ctx, int64_t key_id);
+ 
+     // get ith C string from array with given key_id
+     GGML_API const char * gguf_get_arr_str (const struct gguf_context * ctx, int64_t key_id, size_t i);
+diff --git a/ggml/src/gguf.cpp b/ggml/src/gguf.cpp
+index ab13669c..f75b923f 100644
+--- a/ggml/src/gguf.cpp
++++ b/ggml/src/gguf.cpp
+@@ -777,10 +777,14 @@ enum gguf_type gguf_get_arr_type(const struct gguf_context * ctx, int64_t key_id
+ 
+ const void * gguf_get_arr_data(const struct gguf_context * ctx, int64_t key_id) {
+     GGML_ASSERT(key_id >= 0 && key_id < gguf_get_n_kv(ctx));
+-    GGML_ASSERT(ctx->kv[key_id].get_type() != GGUF_TYPE_STRING);
+     return ctx->kv[key_id].data.data();
+ }
+ 
++size_t gguf_get_arr_data_n(const struct gguf_context * ctx, int64_t key_id) {
++    GGML_ASSERT(key_id >= 0 && key_id < gguf_get_n_kv(ctx));
++    return ctx->kv[key_id].data.size();
++}
++
+ const char * gguf_get_arr_str(const struct gguf_context * ctx, int64_t key_id, size_t i) {
+     GGML_ASSERT(key_id >= 0 && key_id < gguf_get_n_kv(ctx));
+     GGML_ASSERT(ctx->kv[key_id].get_type() == GGUF_TYPE_STRING);
+@@ -874,7 +878,6 @@ const char * gguf_get_val_str(const struct gguf_context * ctx, int64_t key_id) {
+ const void * gguf_get_val_data(const struct gguf_context * ctx, int64_t key_id) {
+     GGML_ASSERT(key_id >= 0 && key_id < gguf_get_n_kv(ctx));
+     GGML_ASSERT(ctx->kv[key_id].get_ne() == 1);
+-    GGML_ASSERT(ctx->kv[key_id].get_type() != GGUF_TYPE_STRING);
+     return ctx->kv[key_id].data.data();
+ }
+ 
+diff --git a/src/llama-vocab.cpp b/src/llama-vocab.cpp
+index c7ff28be..7a185443 100644
+--- a/src/llama-vocab.cpp
++++ b/src/llama-vocab.cpp
+@@ -1443,7 +1443,7 @@ void llama_vocab::impl::load(llama_model_loader & ml, const LLM_KV & kv) {
+ 
+             const int precompiled_charsmap_keyidx = gguf_find_key(ctx, kv(LLM_KV_TOKENIZER_PRECOMPILED_CHARSMAP).c_str());
+             if (precompiled_charsmap_keyidx != -1) {
+-                size_t n_precompiled_charsmap = gguf_get_arr_n(ctx, precompiled_charsmap_keyidx);
++                size_t n_precompiled_charsmap = gguf_get_arr_data_n(ctx, precompiled_charsmap_keyidx);
+                 const char * pc = (const char *) gguf_get_arr_data(ctx, precompiled_charsmap_keyidx);
+                 precompiled_charsmap.assign(pc, pc + n_precompiled_charsmap);
+ #ifdef IS_BIG_ENDIAN
diff --git a/ml/backend/ggml/ggml/include/gguf.h b/ml/backend/ggml/ggml/include/gguf.h
index 79ee2020..3efb22f0 100644
--- a/ml/backend/ggml/ggml/include/gguf.h
+++ b/ml/backend/ggml/ggml/include/gguf.h
@@ -114,6 +114,7 @@ extern "C" {
     // get raw pointer to the first element of the array with the given key_id
     // for bool arrays, note that they are always stored as int8 on all platforms (usually this makes no difference)
     GGML_API const void * gguf_get_arr_data(const struct gguf_context * ctx, int64_t key_id);
+    GGML_API size_t       gguf_get_arr_data_n(const struct gguf_context * ctx, int64_t key_id);
 
     // get ith C string from array with given key_id
     GGML_API const char * gguf_get_arr_str (const struct gguf_context * ctx, int64_t key_id, size_t i);
diff --git a/ml/backend/ggml/ggml/src/gguf.cpp b/ml/backend/ggml/ggml/src/gguf.cpp
index ab13669c..f75b923f 100644
--- a/ml/backend/ggml/ggml/src/gguf.cpp
+++ b/ml/backend/ggml/ggml/src/gguf.cpp
@@ -777,10 +777,14 @@ enum gguf_type gguf_get_arr_type(const struct gguf_context * ctx, int64_t key_id
 
 const void * gguf_get_arr_data(const struct gguf_context * ctx, int64_t key_id) {
     GGML_ASSERT(key_id >= 0 && key_id < gguf_get_n_kv(ctx));
-    GGML_ASSERT(ctx->kv[key_id].get_type() != GGUF_TYPE_STRING);
     return ctx->kv[key_id].data.data();
 }
 
+size_t gguf_get_arr_data_n(const struct gguf_context * ctx, int64_t key_id) {
+    GGML_ASSERT(key_id >= 0 && key_id < gguf_get_n_kv(ctx));
+    return ctx->kv[key_id].data.size();
+}
+
 const char * gguf_get_arr_str(const struct gguf_context * ctx, int64_t key_id, size_t i) {
     GGML_ASSERT(key_id >= 0 && key_id < gguf_get_n_kv(ctx));
     GGML_ASSERT(ctx->kv[key_id].get_type() == GGUF_TYPE_STRING);
@@ -874,7 +878,6 @@ const char * gguf_get_val_str(const struct gguf_context * ctx, int64_t key_id) {
 const void * gguf_get_val_data(const struct gguf_context * ctx, int64_t key_id) {
     GGML_ASSERT(key_id >= 0 && key_id < gguf_get_n_kv(ctx));
     GGML_ASSERT(ctx->kv[key_id].get_ne() == 1);
-    GGML_ASSERT(ctx->kv[key_id].get_type() != GGUF_TYPE_STRING);
     return ctx->kv[key_id].data.data();
 }
 

From 1f6986e91902b1308a8dc6be45418b7db9ccc0e9 Mon Sep 17 00:00:00 2001
From: Breaker <iBreaker@users.noreply.github.com>
Date: Sat, 8 Mar 2025 01:30:07 +0800
Subject: [PATCH 007/157] readme: add QwQ to the supported models list (#9565)

---
 README.md | 1 +
 1 file changed, 1 insertion(+)

diff --git a/README.md b/README.md
index 5aa4801e..1162f891 100644
--- a/README.md
+++ b/README.md
@@ -54,6 +54,7 @@ Here are some example models that can be downloaded:
 
 | Model              | Parameters | Size  | Download                         |
 | ------------------ | ---------- | ----- | -------------------------------- |
+| QwQ                | 32B        | 20GB  | `ollama run qwq`                 |
 | DeepSeek-R1        | 7B         | 4.7GB | `ollama run deepseek-r1`         |
 | DeepSeek-R1        | 671B       | 404GB | `ollama run deepseek-r1:671b`    |
 | Llama 3.3          | 70B        | 43GB  | `ollama run llama3.3`            |

From 0682dae0275af6ab376cfa346ef27562b574684d Mon Sep 17 00:00:00 2001
From: Parth Sareen <parth.sareen@ollama.com>
Date: Fri, 7 Mar 2025 12:37:48 -0800
Subject: [PATCH 008/157] sample: improve ollama engine sampler performance
 (#9374)

This change bring in various interface cleanups along with greatly improving the performance of the sampler.

Tested with llama3.2 on local machine.
Improves performance from ~ 70 tokens/s -> 135 tokens/s with topK(40) enabled.
Without topK performance is ~ 110 tokens/s
---
 go.mod                            |   2 +-
 runner/ollamarunner/runner.go     |  10 +-
 sample/samplers.go                | 166 +++++++++++--------
 sample/samplers_benchmark_test.go | 104 ++++++++++++
 sample/samplers_test.go           | 155 ++++--------------
 sample/transforms.go              | 263 ++++++++++++++++++++----------
 sample/transforms_test.go         | 203 +++++++++++++++++------
 7 files changed, 572 insertions(+), 331 deletions(-)
 create mode 100644 sample/samplers_benchmark_test.go

diff --git a/go.mod b/go.mod
index c45c9892..cc578900 100644
--- a/go.mod
+++ b/go.mod
@@ -25,7 +25,6 @@ require (
 	github.com/pdevine/tensor v0.0.0-20240510204454-f88f4562727c
 	golang.org/x/image v0.22.0
 	golang.org/x/tools v0.30.0
-	gonum.org/v1/gonum v0.15.0
 )
 
 require (
@@ -45,6 +44,7 @@ require (
 	github.com/xtgo/set v1.0.0 // indirect
 	go4.org/unsafe/assume-no-moving-gc v0.0.0-20231121144256-b99613f794b6 // indirect
 	golang.org/x/xerrors v0.0.0-20200804184101-5ec99f83aff1 // indirect
+	gonum.org/v1/gonum v0.15.0 // indirect
 	gorgonia.org/vecf32 v0.9.0 // indirect
 	gorgonia.org/vecf64 v0.9.0 // indirect
 )
diff --git a/runner/ollamarunner/runner.go b/runner/ollamarunner/runner.go
index e5189fa5..81e06562 100644
--- a/runner/ollamarunner/runner.go
+++ b/runner/ollamarunner/runner.go
@@ -589,11 +589,19 @@ func (s *Server) completion(w http.ResponseWriter, r *http.Request) {
 		return
 	}
 
+	sampler := sample.NewSampler(
+		req.Temperature,
+		req.TopK,
+		req.TopP,
+		req.MinP,
+		req.Seed,
+	)
+
 	seq, err := s.NewSequence(req.Prompt, req.Images, NewSequenceParams{
 		numPredict: req.NumPredict,
 		stop:       req.Stop,
 		numKeep:    int32(req.NumKeep),
-		sampler:    sample.Greedy(), // TODO: add support for different samplers when performance is optimized
+		sampler:    sampler,
 		embedding:  false,
 	})
 	if err != nil {
diff --git a/sample/samplers.go b/sample/samplers.go
index 1b8a5edd..a5a0507c 100644
--- a/sample/samplers.go
+++ b/sample/samplers.go
@@ -2,76 +2,103 @@ package sample
 
 import (
 	"errors"
-	"math"
-
-	"golang.org/x/exp/rand"
-	"gonum.org/v1/gonum/stat/sampleuv"
+	"math/rand/v2"
+	"slices"
 )
 
+// Sampler is not thread-safe. Each goroutine should have its own instance
 type Sampler interface {
 	Sample([]float32) (int32, error)
 }
 
+// logit represents information about a single token during sampling
+type logit struct {
+	id    int32   // The token's unique identifier
+	value float32 // The raw logit or probability from the model
+}
+
 type weighted struct {
-	src        rand.Source
-	transforms []Transform
+	rng         *rand.Rand
+	tokens      []logit
+	topK        int
+	topP        float32
+	minP        float32
+	temperature float32
 }
 
-// TODO(parthsareen): remove uv sample dependency https://github.com/ollama/ollama/issues/9279
-func Weighted(seed *uint64, transforms ...Transform) Sampler {
-	var src rand.Source
-	if seed != nil {
-		src = rand.NewSource(*seed)
+func (s *weighted) Sample(logits []float32) (int32, error) {
+	if len(s.tokens) < len(logits) {
+		s.tokens = make([]logit, len(logits))
 	}
-	return weighted{src: src, transforms: transforms}
-}
 
-func (s weighted) Sample(logits []float32) (int32, error) {
-	logits64 := make([]float64, len(logits))
+	tokens := s.tokens[:len(logits)]
+
 	for i, v := range logits {
-		logits64[i] = float64(v)
+		tokens[i].id = int32(i)
+		tokens[i].value = v
 	}
 
-	for _, t := range s.transforms {
-		logits64 = t.Apply(logits64)
+	// Tokens are sorted by logits in TopK or SortTokens
+	if s.topK > 0 {
+		tokens = topK(tokens, s.topK)
+	} else {
+		sortLogits(tokens)
 	}
 
-	logitsCopy := make([]float64, 0, len(logits))
-	indices := make([]int, 0, len(logits))
-	for i, logit := range logits64 {
-		if !math.IsInf(logit, -1) {
-			logitsCopy = append(logitsCopy, logit)
-			indices = append(indices, i)
+	tokens = temperature(tokens, s.temperature)
+	tokens = softmax(tokens)
+
+	tokens = topP(tokens, s.topP)
+	tokens = minP(tokens, s.minP)
+
+	if len(tokens) == 0 {
+		return -1, errors.New("no valid logits found for weighted sampling")
+	}
+
+	var r float32
+	if s.rng != nil {
+		r = s.rng.Float32()
+	} else {
+		r = rand.Float32()
+	}
+
+	// Calculate cumulative sum of probabilities
+	var sum float32
+	for i := range tokens {
+		sum += tokens[i].value
+		tokens[i].value = sum
+	}
+	r *= tokens[len(tokens)-1].value
+
+	idx, _ := slices.BinarySearchFunc(tokens, r, func(token logit, target float32) int {
+		// Compare cumulative probabilities
+		if token.value < target {
+			return -1
 		}
+		// First token that exceeds target
+		return 1
+	})
+
+	if idx >= len(tokens) {
+		idx = len(tokens) - 1
 	}
 
-	if len(logitsCopy) == 0 {
-		return -1, errors.New("no valid logits found for weighed sampling")
-	}
-
-	probs := softmax(logitsCopy)
-	w := sampleuv.NewWeighted(probs, s.src)
-	if idx, ok := w.Take(); ok {
-		return int32(indices[idx]), nil
-	}
-	return -1, errors.New("weighted sampler failed, no valid token found")
+	return tokens[idx].id, nil
 }
 
 type greedy struct{}
 
-func Greedy() Sampler {
-	return greedy{}
-}
-
-// Sample returns the index of the maximum value in logits.
+// Greedy sample returns the index of the maximum value in logits.
 func (s greedy) Sample(logits []float32) (int32, error) {
 	if len(logits) == 0 {
 		return -1, errors.New("no logits provided for greedy sampling")
 	}
 
 	maxIdx := 0
-	for i := range logits {
-		if logits[i] > logits[maxIdx] {
+	maxVal := logits[0]
+	for i := 1; i < len(logits); i++ {
+		if logits[i] > maxVal {
+			maxVal = logits[i]
 			maxIdx = i
 		}
 	}
@@ -80,41 +107,40 @@ func (s greedy) Sample(logits []float32) (int32, error) {
 }
 
 // TODO(parthsareen): update sampler interface to use json unmarshal https://github.com/ollama/ollama/issues/9278
-func NewSampler(temperature float32, topK int, topP float32, minP float32, seed int) (Sampler, error) {
+func NewSampler(temperature float32, topK int, topP float32, minP float32, seed int) Sampler {
 	if temperature == 0 {
-		return Greedy(), nil
+		return &greedy{}
 	}
 
-	if temperature < 0 || temperature > 2 {
-		return nil, errors.New("temperature must be between 0 and 2")
+	var rng *rand.Rand
+	if seed != -1 {
+		// PCG requires two parameters: sequence and stream
+		// Use original seed for sequence
+		sequence := uint64(seed)
+		// Use golden ratio hash to generate statistically independent seeds
+		rng = rand.New(rand.NewPCG(sequence, sequence^0x9E3779B9))
+	}
+	temperature = max(temperature, 1)
+
+	if topP < 0.0 {
+		topP = 0.0
+	}
+	if topP >= 1.0 {
+		topP = 1.0
 	}
 
-	transforms := []Transform{Temperature(temperature)}
-
-	if topK != 0 {
-		if topK <= 0 {
-			return nil, errors.New("topK must be greater than 0")
-		}
-		transforms = append(transforms, TopK(topK))
+	if minP < 0.0 {
+		minP = 0.0
+	}
+	if minP >= 1.0 {
+		minP = 1.0
 	}
 
-	if topP != 0 {
-		if topP < 0 || topP >= 1 {
-			return nil, errors.New("topP must be between 0 and 1")
-		}
-		transforms = append(transforms, TopP(topP))
+	return &weighted{
+		rng:         rng,
+		topK:        topK,
+		topP:        topP,
+		minP:        minP,
+		temperature: temperature,
 	}
-
-	if minP != 0 {
-		if minP < 0 || minP >= 1 {
-			return nil, errors.New("minP must be between 0 and 1")
-		}
-		transforms = append(transforms, MinP(minP))
-	}
-
-	if seed >= 0 {
-		seed64 := uint64(seed)
-		return Weighted(&seed64, transforms...), nil
-	}
-	return Weighted(nil, transforms...), nil
 }
diff --git a/sample/samplers_benchmark_test.go b/sample/samplers_benchmark_test.go
new file mode 100644
index 00000000..41c0b487
--- /dev/null
+++ b/sample/samplers_benchmark_test.go
@@ -0,0 +1,104 @@
+package sample
+
+import (
+	"fmt"
+	"math/rand"
+	"testing"
+)
+
+func BenchmarkWeightedSampler(b *testing.B) {
+	sizes := []int{10, 100, 1000, 10000}
+
+	for _, size := range sizes {
+		b.Run(fmt.Sprintf("Size %d", size), func(b *testing.B) {
+			logits := make([]float32, size)
+			for i := range logits {
+				logits[i] = float32(rand.Float64()*10 - 5)
+			}
+
+			sampler := NewSampler(0.8, 0, 0, 0, 42)
+			b.ResetTimer()
+			for b.Loop() {
+				_, err := sampler.Sample(logits)
+				if err != nil {
+					b.Fatalf("Sampling failed: %v", err)
+				}
+			}
+		})
+	}
+
+	configs := []struct {
+		name        string
+		temperature float32
+		topK        int
+		topP        float32
+		minP        float32
+		seed        int
+	}{
+		{"Greedy", 0, -1, 0, 0, -1},
+		{"Temperature", 0.8, -1, 0, 0, -1},
+		{"TopK", 0.8, 50, 0, 0, -1},
+		{"TopP", 0.8, -1, 0.9, 0, -1},
+		{"MinP", 0.8, -1, 0, 0.05, -1},
+		{"WithSeed", 0.8, 50, 0, 0, 42},
+	}
+
+	// Fixed size for common vocab size
+	size := 128000
+	logits := make([]float32, size)
+	for i := range logits {
+		logits[i] = float32(rand.Float64()*10 - 5)
+	}
+
+	for _, tc := range configs {
+		b.Run("Config"+tc.name, func(b *testing.B) {
+			sampler := NewSampler(tc.temperature, tc.topK, tc.topP, tc.minP, tc.seed)
+			sampler.Sample(logits)
+
+			b.ResetTimer()
+
+			for b.Loop() {
+				_, err := sampler.Sample(logits)
+				if err != nil {
+					b.Fatalf("Sampling failed: %v", err)
+				}
+			}
+		})
+	}
+
+	// Test with combined transforms separately - topK influences performance greatly
+	b.Run("TransformCombined", func(b *testing.B) {
+		sampler := NewSampler(0.8, 50, 0.9, 0.05, 42)
+		b.ResetTimer()
+
+		for b.Loop() {
+			_, err := sampler.Sample(logits)
+			if err != nil {
+				b.Fatalf("Sampling failed: %v", err)
+			}
+		}
+	})
+}
+
+func BenchmarkGreedySampler(b *testing.B) {
+	sizes := []int{10, 100, 1000, 10000, 100000}
+
+	for _, size := range sizes {
+		b.Run(fmt.Sprintf("Size %d", size), func(b *testing.B) {
+			logits := make([]float32, size)
+			for i := range logits {
+				logits[i] = float32(rand.Float64()*10 - 5)
+			}
+
+			sampler := NewSampler(0, -1, 0, 0, -1)
+			b.ResetTimer()
+
+			for b.Loop() {
+				_, err := sampler.Sample(logits)
+				if err != nil {
+					b.Fatalf("Sampling failed: %v", err)
+				}
+			}
+		})
+	}
+}
diff --git a/sample/samplers_test.go b/sample/samplers_test.go
index 32364a3b..dbbee17b 100644
--- a/sample/samplers_test.go
+++ b/sample/samplers_test.go
@@ -1,15 +1,14 @@
 package sample
 
 import (
-	"math"
 	"math/rand/v2"
 	"testing"
-
-	"github.com/google/go-cmp/cmp"
 )
 
 func TestWeighted(t *testing.T) {
-	got, err := Weighted(nil).Sample([]float32{float32(math.Inf(-1)), 2, float32(math.Inf(-1)), float32(math.Inf(-1))})
+	logits := []float32{-10, 3, -10, -10}
+	sampler := NewSampler(0, 0, 0, 0, 0)
+	got, err := sampler.Sample(logits)
 	if err != nil {
 		t.Error(err)
 		return
@@ -19,64 +18,19 @@ func TestWeighted(t *testing.T) {
 		t.Errorf("index mismatch: want %d, got %d", want, got)
 	}
 
-	got, err = Weighted(nil).Sample([]float32{float32(math.Inf(-1)), float32(math.Inf(-1)), float32(math.Inf(-1))})
-	if err == nil {
-		t.Error("expected error for no valid tokens, got index", got)
-	}
-
-	seed := uint64(42)
-	got, err = Weighted(&seed).Sample([]float32{1, 2, 3, 4})
+	logits = []float32{-100, -10, 0, 10}
+	sampler = NewSampler(0, 0, 0, 0, 0)
+	got, err = sampler.Sample(logits)
 	if err != nil {
 		t.Error(err)
 		return
 	}
-	// With seed 42, we expect a consistent sample
-	want = int32(3) // This will be deterministic due to the seed
+	want = int32(3) // Should pick highest probability with this r value
 	if want != got {
 		t.Errorf("index mismatch: want %d, got %d", want, got)
 	}
 }
 
-type testTransform struct {
-	id        int
-	callOrder *[]int
-}
-
-func (ts *testTransform) Apply(logits []float64) []float64 {
-	if ts.callOrder != nil {
-		*ts.callOrder = append(*ts.callOrder, ts.id)
-	}
-	return logits
-}
-
-func TestSample(t *testing.T) {
-	input := []float32{1, 2, 3, 4}
-
-	var callOrder []int
-	mock1 := &testTransform{
-		id:        1,
-		callOrder: &callOrder,
-	}
-	mock2 := &testTransform{
-		id:        2,
-		callOrder: &callOrder,
-	}
-	mock3 := &testTransform{
-		id:        3,
-		callOrder: &callOrder,
-	}
-
-	_, err := Weighted(nil, mock1, mock2, mock3).Sample(input)
-	if err != nil {
-		t.Error(err)
-		return
-	}
-	wantOrder := []int{1, 2, 3}
-	if diff := cmp.Diff(wantOrder, callOrder); diff != "" {
-		t.Errorf("call order mismatch (-want +got):\n%s", diff)
-	}
-}
-
 func TestNewSampler(t *testing.T) {
 	tests := []struct {
 		name        string
@@ -85,75 +39,41 @@ func TestNewSampler(t *testing.T) {
 		topP        float32
 		minP        float32
 		seed        int
-		wantErr     bool
+		wantGreedy  bool // Instead of wantErr, check if we get greedy sampler
 	}{
-		{
-			name: "no transforms",
-			// temperature is 0, so greedy should be used
-			wantErr: false,
-		},
 		{
 			name:        "temperature",
 			temperature: 0.5,
-			wantErr:     false,
+			wantGreedy:  false,
 		},
 		{
-			name:        "invalid temperature negative",
-			temperature: -1,
-			wantErr:     true,
-		},
-		{
-			name:        "invalid temperature too high",
-			temperature: 2.1,
-			wantErr:     true,
+			name:        "zero temperature - greedy",
+			temperature: 0,
+			wantGreedy:  true,
 		},
 		{
 			name:        "top k",
+			temperature: 0.1,
 			topK:        10,
-			temperature: 0.8,
-			wantErr:     false,
-		},
-		{
-			name:        "invalid top k negative",
-			topK:        -1,
-			temperature: 0.8,
-			wantErr:     true,
+			wantGreedy:  false,
 		},
 		{
 			name:        "top p",
+			temperature: 0.1,
 			topP:        0.9,
-			temperature: 0.8,
-			wantErr:     false,
-		},
-		{
-			name:        "invalid top p negative",
-			topP:        -0.1,
-			temperature: 0.8,
-			wantErr:     true,
-		},
-		{
-			name:        "invalid top p one",
-			topP:        1.0,
-			temperature: 0.8,
-			wantErr:     true,
+			wantGreedy:  false,
 		},
 		{
 			name:        "min p",
+			temperature: 0.1,
 			minP:        0.2,
-			temperature: 0.8,
-			wantErr:     false,
+			wantGreedy:  false,
 		},
 		{
-			name:        "invalid min p negative",
-			minP:        -0.1,
-			temperature: 0.8,
-			wantErr:     true,
-		},
-		{
-			name:        "invalid min p one",
-			minP:        1.0,
-			temperature: 0.8,
-			wantErr:     true,
+			name:        "seed - weighted",
+			temperature: 0.1,
+			seed:        42,
+			wantGreedy:  false,
 		},
 		{
 			name:        "default values",
@@ -162,16 +82,16 @@ func TestNewSampler(t *testing.T) {
 			topP:        0.9,
 			minP:        0.0,
 			seed:        0,
-			wantErr:     false,
+			wantGreedy:  false,
 		},
 		{
-			name:        "all zeroes",
+			name:        "all zeroes - greedy",
 			temperature: 0.0,
 			topK:        0,
 			topP:        0.0,
 			minP:        0.0,
 			seed:        0,
-			wantErr:     false, // all zeroes means no transforms
+			wantGreedy:  true,
 		},
 		{
 			name:        "all transforms",
@@ -180,33 +100,28 @@ func TestNewSampler(t *testing.T) {
 			topP:        0.95,
 			minP:        0.1,
 			seed:        42,
-			wantErr:     false,
+			wantGreedy:  false,
 		},
 	}
-
 	for _, tt := range tests {
 		t.Run(tt.name, func(t *testing.T) {
-			_, err := NewSampler(tt.temperature, tt.topK, tt.topP, tt.minP, tt.seed)
-			if (err != nil) != tt.wantErr {
-				t.Errorf("NewSampler() error = %v, wantErr %v", err, tt.wantErr)
+			sampler := NewSampler(tt.temperature, tt.topK, tt.topP, tt.minP, tt.seed)
+			_, isGreedy := sampler.(*greedy)
+			if isGreedy != tt.wantGreedy {
+				t.Errorf("NewSampler() got greedy = %v, want %v", isGreedy, tt.wantGreedy)
 			}
 		})
 	}
 }
 
 func BenchmarkSample(b *testing.B) {
-	transforms := []Transform{
-		Temperature(0.5),
-		TopK(10),
-		TopP(0.9),
-		MinP(0.2),
-	}
-
+	weighted := NewSampler(0.5, 10, 0.9, 0.2, -1)
 	samplers := map[string]Sampler{
-		"Greedy":   Greedy(),
-		"Weighted": Weighted(nil, transforms...),
+		"Greedy":   NewSampler(0, 0, 0, 0, 0), // Use NewSampler with temp=0 for greedy
+		"Weighted": weighted,
 	}
 
+	// Generate random logits for benchmarking
 	logits := make([]float32, 1<<16)
 	for i := range logits {
 		logits[i] = rand.Float32()
@@ -215,7 +130,7 @@ func BenchmarkSample(b *testing.B) {
 	for name, s := range samplers {
 		b.Run(name, func(b *testing.B) {
 			b.ResetTimer()
-			for range b.N {
+			for b.Loop() {
 				if _, err := s.Sample(logits); err != nil {
 					b.Error(err)
 				}
diff --git a/sample/transforms.go b/sample/transforms.go
index 2dc6ebae..f1f4f3b1 100644
--- a/sample/transforms.go
+++ b/sample/transforms.go
@@ -1,120 +1,203 @@
 package sample
 
 import (
-	"cmp"
 	"math"
 	"slices"
-
-	pq "github.com/emirpasic/gods/v2/queues/priorityqueue"
 )
 
-type Transform interface {
-	Apply([]float64) []float64
-}
-
-// TODO(parthsareen): potentially cache softmax values
-func softmax(logits []float64) []float64 {
-	var sum float64
-	probs := make([]float64, len(logits))
-	for i, v := range logits {
-		probs[i] = math.Exp(v)
-		sum += probs[i]
+func softmax(ts []logit) []logit {
+	var sum float32
+	for i, v := range ts {
+		ts[i].value = float32(math.Exp(float64(v.value)))
+		sum += ts[i].value
 	}
 
-	for i := range probs {
-		probs[i] /= sum
+	for i := range ts {
+		ts[i].value /= sum
 	}
 
-	return probs
+	return ts
 }
 
-type Temperature float64
+func temperature(ti []logit, t float32) []logit {
+	if t == 1 {
+		return ti
+	}
 
-func (t Temperature) Apply(logits []float64) []float64 {
-	temp := math.Max(float64(t), 1e-7)
+	temp := max(t, 1e-7)
+	maxLogit := float32(math.Inf(-1))
+	for _, token := range ti {
+		if token.value > maxLogit {
+			maxLogit = token.value
+		}
+	}
 
 	// subtracting max logit to avoid under/overflow
-	maxLogit := slices.Max(logits)
-	for i := range logits {
-		logits[i] = (logits[i] - maxLogit) / temp
+	for i := range ti {
+		ti[i].value = (ti[i].value - maxLogit) / temp
 	}
 
-	return logits
+	return ti
 }
 
-type logitMap struct {
-	index int
-	logit float64
-}
-
-type TopK int
-
-// TODO(parthsareen): avoid having to check all logits after this transform
-func (k TopK) Apply(logits []float64) []float64 {
-	if int(k) >= len(logits) {
-		return logits
-	}
-	q := pq.NewWith(func(a, b logitMap) int {
-		return -cmp.Compare(a.logit, b.logit)
-	})
-
-	for i, logit := range logits {
-		q.Enqueue(logitMap{index: i, logit: logit})
-	}
-
-	validLogits := make(map[int]float64)
-	for range k {
-		logitMap, _ := q.Dequeue()
-		validLogits[logitMap.index] = logitMap.logit
-	}
-
-	for i := range logits {
-		if _, ok := validLogits[i]; !ok {
-			logits[i] = math.Inf(-1)
-		}
-	}
-
-	return logits
-}
-
-type TopP float64
-
-func (p TopP) Apply(logits []float64) []float64 {
-	probs := softmax(logits)
-	indices := make([]int, len(probs))
-	for i := range indices {
-		indices[i] = i
-	}
-
-	// sort in descending order
-	slices.SortFunc(indices, func(i, j int) int {
-		return cmp.Compare(probs[j], probs[i])
-	})
-
-	var sum float64
-	for i, idx := range indices {
-		sum += probs[idx]
-		if sum > float64(p) {
-			for _, idx := range indices[i+1:] {
-				logits[idx] = math.Inf(-1)
-			}
+// siftDown maintains a min-heap property by recursively moving larger elements down the heap.
+//
+// The heap is represented as an array where for any node at index i:
+// - Left child is at index 2i + 1
+// - Right child is at index 2i + 2
+// - Parent is at index (i-1)/2
+//
+// The function compares a node with its children and:
+// 1. Finds the smallest value between the node and its children
+// 2. If the node is not the smallest, swaps it with its smallest child
+// 3. Continues this process down the affected path until the min-heap property is restored
+func siftDown(data []logit, start, end int) {
+	root := start
+	for {
+		child := 2*root + 1
+		if child >= end {
 			break
 		}
+		// Find smaller child (we want min heap)
+		if child+1 < end && data[child+1].value < data[child].value {
+			child++
+		}
+		// Exit if root is already smaller than children
+		if data[root].value <= data[child].value {
+			break
+		}
+		// Swap with smaller child and continue
+		data[root], data[child] = data[child], data[root]
+		root = child
 	}
-	return logits
 }
 
-type MinP float64
+// topK limits the number of tokens considered to the k highest logits
+func topK(ts []logit, k int) []logit {
+	if k >= len(ts) {
+		return ts
+	}
+	// Heapify + siftDown - O(nlog(k))
+	// Build min-heap of first k elements
+	heap := ts[:k]
+	for i := k/2 - 1; i >= 0; i-- {
+		siftDown(heap, i, k)
+	}
 
-func (p MinP) Apply(logits []float64) []float64 {
-	probs := softmax(logits)
-	threshold := slices.Max(probs) * float64(p)
-
-	for i, prob := range probs {
-		if prob < threshold {
-			logits[i] = math.Inf(-1)
+	// Process remaining elements - if larger than heap root, replace root
+	for i := k; i < len(ts); i++ {
+		if ts[i].value > heap[0].value {
+			heap[0] = ts[i]
+			siftDown(heap, 0, k)
 		}
 	}
 
-	return logits
+	slices.Reverse(heap)
+
+	ts = heap
+	return ts
+}
+
+// topP limits tokens to those with cumulative probability p
+func topP(ts []logit, p float32) []logit {
+	if p == 1.0 {
+		return ts
+	}
+
+	// Find cutoff index where cumulative sum exceeds p
+	var sum float32
+	for i, t := range ts {
+		sum += t.value
+		if sum > float32(p) {
+			ts = ts[:i+1]
+			return ts
+		}
+	}
+
+	return ts
+}
+
+// minP limits tokens to those with cumulative probability p
+func minP(ts []logit, p float32) []logit {
+	if p == 1.0 {
+		return ts
+	}
+
+	maxProb := float32(math.Inf(-1))
+	for _, token := range ts {
+		if token.value > maxProb {
+			maxProb = token.value
+		}
+	}
+
+	threshold := maxProb * float32(p)
+
+	// Filter tokens in-place
+	validTokens := ts[:0]
+	for i, token := range ts {
+		if token.value >= threshold {
+			validTokens = append(validTokens, ts[i])
+		}
+	}
+
+	ts = validTokens
+	return ts
+}
+
+// TODO(parthsareen): possibly replace with simpler implementation https://github.com/ollama/ollama/issues/9584
+// Conting sort implementation to sort tokens by logits
+func sortLogits(tokens []logit) {
+	if len(tokens) <= 1 {
+		return
+	}
+
+	// Find max/min in a single pass
+	minLogit, maxLogit := tokens[0].value, tokens[0].value
+	for _, t := range tokens[1:] {
+		if t.value < minLogit {
+			minLogit = t.value
+		} else if t.value > maxLogit {
+			maxLogit = t.value
+		}
+	}
+
+	// Calculate scaling to map to uint32 range
+	logitRange := maxLogit - minLogit
+	if logitRange < 1e-6 {
+		return // All values effectively equal
+	}
+
+	// Count frequencies directly from tokens
+	const maxInt = (1 << 24) - 1 // Use 24 bits for good granularity
+	var counts [256]int          // For first byte
+
+	// First pass: count frequencies
+	for _, t := range tokens {
+		// Map to [0, maxInt] range
+		score := min(uint32((t.value-minLogit)*float32(maxInt)/logitRange), maxInt)
+		counts[score>>16]++
+	}
+
+	// Calculate offsets
+	var offset int
+	for i := range counts {
+		count := counts[i]
+		counts[i] = offset
+		offset += count
+	}
+
+	// Second pass: place elements in correct position
+	output := make([]logit, len(tokens))
+	// Track current positions
+	countsCopy := counts
+
+	for i, t := range tokens {
+		score := min(uint32((t.value-minLogit)*float32(maxInt)/logitRange), maxInt)
+
+		pos := countsCopy[score>>16]
+		countsCopy[score>>16]++
+		output[len(tokens)-1-pos] = tokens[i]
+	}
+
+	copy(tokens, output)
 }
diff --git a/sample/transforms_test.go b/sample/transforms_test.go
index 05f76a27..950d79b3 100644
--- a/sample/transforms_test.go
+++ b/sample/transforms_test.go
@@ -4,77 +4,182 @@ import (
 	"math"
 	"math/rand/v2"
 	"testing"
-
-	"github.com/google/go-cmp/cmp"
 )
 
-func TestTemperature(t *testing.T) {
-	got := Temperature(0.5).Apply([]float64{2, -1, 4, -3, 1, -2, 0})
-	want := []float64{-4, -10, 0, -14, -6, -12, -8}
-	if diff := cmp.Diff(want, got); diff != "" {
-		t.Errorf("logits mismatch (-want +got):\n%s", diff)
+// Helper to convert float64 slice to logit slice
+func toLogits(values []float64) []logit {
+	tokens := make([]logit, len(values))
+	for i, v := range values {
+		tokens[i] = logit{
+			id:    int32(i),
+			value: float32(v),
+		}
+	}
+	return tokens
+}
+
+// Helper to compare logit slices
+func compareLogits(t *testing.T, name string, want []float64, got []logit) {
+	t.Helper()
+	if len(want) != len(got) {
+		t.Errorf("%s: length mismatch: want %d, got %d", name, len(want), len(got))
+		return
+	}
+	for i := range want {
+		if math.Abs(float64(got[i].value)-want[i]) > 1e-6 {
+			t.Errorf("%s: index %d: want %f, got %f", name, i, want[i], got[i].value)
+		}
 	}
 }
 
-func TestSoftmax(t *testing.T) {
-	got := softmax([]float64{-3, -2, -1, 0, 1, 2, 4})
+func TestTemperature(t *testing.T) {
+	input := []float64{2, -1, 4, -3, 1, -2, 0}
+	want := []float64{-4, -10, 0, -14, -6, -12, -8} // (logit - max logit) / temp
 
-	want := []float64{0.000751406628089903, 0.0020425349829204676, 0.005552185728064613, 0.015092405572827691, 0.04102541181635154, 0.11151863144543739, 0.8240174238263085}
-	if diff := cmp.Diff(want, got); diff != "" {
-		t.Errorf("probs mismatch (-want +got):\n%s", diff)
+	got := temperature(toLogits(input), 0.5)
+	compareLogits(t, "Temperature", want, got)
+}
+
+func TestSoftmax(t *testing.T) {
+	input := []float64{-3, -2, -1, 0, 1, 2, 4}
+	got := softmax(toLogits(input))
+
+	// Check probabilities sum to 1
+	var sum float32
+	for _, token := range got {
+		sum += token.value
+	}
+	if math.Abs(float64(sum)-1.0) > 1e-6 {
+		t.Errorf("probabilities don't sum to 1: got %f", sum)
+	}
+
+	// Check relative ordering is preserved
+	for i := 1; i < len(got); i++ {
+		if got[i].value < got[i-1].value {
+			t.Errorf("probability ordering not preserved at index %d", i)
+		}
 	}
 }
 
 func TestTopK(t *testing.T) {
-	got := TopK(3).Apply([]float64{-3, -2, -1, 0, 1, 2, 4})
-	want := []float64{math.Inf(-1), math.Inf(-1), math.Inf(-1), math.Inf(-1), 1, 2, 4}
-	if diff := cmp.Diff(want, got); diff != "" {
-		t.Errorf("logits mismatch (-want +got):\n%s", diff)
-	}
+	input := []float64{-3, -2, -1, 0, 1, 2, 4}
 
-	got = TopK(10).Apply([]float64{-3, -2, -1, 0, 1, 2, 4})
-
-	want = []float64{-3, -2, -1, 0, 1, 2, 4}
-	if diff := cmp.Diff(want, got); diff != "" {
-		t.Errorf("logits mismatch (-want +got):\n%s", diff)
+	// Test k=3
+	got := topK(toLogits(input), 3)
+	if len(got) != 3 {
+		t.Errorf("topK(3): wrong length: want 3, got %d", len(got))
 	}
+	// Should keep highest 3 values: 4, 2, 1
+	want := []float64{4, 2, 1}
+	compareLogits(t, "topK(3)", want, got)
+
+	// Test k > len
+	got = topK(toLogits(input), 10)
+	compareLogits(t, "topK(10)", input, got)
 }
 
 func TestTopP(t *testing.T) {
-	got := TopP(0.9).Apply([]float64{-3, -2, -1, 0, 1, 2, 4})
-	want := []float64{math.Inf(-1), math.Inf(-1), math.Inf(-1), math.Inf(-1), math.Inf(-1), 2, 4}
-	if diff := cmp.Diff(want, got); diff != "" {
-		t.Errorf("logits mismatch (-want +got):\n%s", diff)
+	input := []float64{-3, -2, -1, 0, 1, 2, 4}
+	tokens := toLogits(input)
+
+	// First apply temperature and softmax to get probabilities
+	tokens = temperature(tokens, 1)
+	tokens = softmax(tokens)
+	sortLogits(tokens)
+
+	// Then apply topP
+	got := topP(tokens, 0.95)
+
+	// Should keep tokens until cumsum > 0.95
+	if len(got) > 3 {
+		t.Errorf("topP(0.95): kept too many tokens: got %d", len(got))
+		t.Logf("got: %v", got)
 	}
 }
 
 func TestMinP(t *testing.T) {
-	got := MinP(0.2).Apply([]float64{-3, -2, -1, 0, 1, 2, 4, 3})
-	want := []float64{math.Inf(-1), math.Inf(-1), math.Inf(-1), math.Inf(-1), math.Inf(-1), math.Inf(-1), 4, 3}
-	if diff := cmp.Diff(want, got); diff != "" {
-		t.Errorf("logits mismatch (-want +got):\n%s", diff)
+	input := []float64{-3, -2, -1, 0, 1, 2, 4, 3}
+	tokens := toLogits(input)
+
+	// First apply temperature and softmax
+	tokens = temperature(tokens, 1)
+	tokens = softmax(tokens)
+
+	// Then apply minP
+	got := minP(tokens, 0.2)
+
+	// Should keep tokens with prob >= 0.2 * max_prob
+	if len(got) > 3 {
+		t.Errorf("minP(0.2): kept too many tokens: got %d", len(got))
 	}
 }
 
-func BenchmarkTransform(b *testing.B) {
-	transforms := map[string]Transform{
-		"Temperature": Temperature(0.5),
-		"TopK":        TopK(10),
-		"TopP":        TopP(0.9),
-		"MinP":        MinP(0.2),
+func TestSortLogits(t *testing.T) {
+	input := []float64{3, 1, 4, 2, -1, 0, -2}
+	tokens := toLogits(input)
+
+	sortLogits(tokens)
+
+	for i := 1; i < len(tokens); i++ {
+		if tokens[i].value > tokens[i-1].value {
+			t.Errorf("sortLogits: tokens not sorted in descending order at index %d: %f > %f",
+				i, tokens[i].value, tokens[i-1].value)
+		}
 	}
 
-	logits := make([]float64, 1<<16)
-	for i := range logits {
-		logits[i] = rand.Float64()
-	}
-
-	for name, transform := range transforms {
-		b.Run(name, func(b *testing.B) {
-			b.ResetTimer()
-			for range b.N {
-				transform.Apply(logits)
-			}
-		})
-	}
+	want := []float64{4, 3, 2, 1, 0, -1, -2}
+	compareLogits(t, "sortLogits", want, tokens)
+}
+
+func BenchmarkTransforms(b *testing.B) {
+	// Generate random logits
+	tokens := make([]logit, 1<<16)
+	for i := range tokens {
+		tokens[i] = logit{
+			id:    int32(i),
+			value: rand.Float32(),
+		}
+	}
+
+	tokensCopy := make([]logit, len(tokens))
+
+	b.Run("Temperature", func(b *testing.B) {
+		b.ResetTimer()
+		for b.Loop() {
+			copy(tokensCopy, tokens)
+			temperature(tokensCopy, 0.5)
+		}
+	})
+
+	b.Run("TopK", func(b *testing.B) {
+		b.ResetTimer()
+		for b.Loop() {
+			copy(tokensCopy, tokens)
+			topK(tokensCopy, 10)
+		}
+	})
+
+	b.Run("TopP", func(b *testing.B) {
+		b.ResetTimer()
+		for b.Loop() {
+			copy(tokensCopy, tokens)
+			topP(tokensCopy, 0.9)
+		}
+	})
+
+	b.Run("MinP", func(b *testing.B) {
+		b.ResetTimer()
+		for b.Loop() {
+			copy(tokensCopy, tokens)
+			minP(tokensCopy, 0.2)
+		}
+	})
+
+	b.Run("SortTokens", func(b *testing.B) {
+		b.ResetTimer()
+		for b.Loop() {
+			copy(tokensCopy, tokens)
+			sortLogits(tokensCopy)
+		}
+	})
 }

From bab6f34dc0f441c6a18b7cbc2465e1b386cf613e Mon Sep 17 00:00:00 2001
From: Michael Yang <mxyng@pm.me>
Date: Wed, 19 Feb 2025 14:26:40 -0800
Subject: [PATCH 009/157] ml/backend/ggml: update model loading for
 hybrid/multi backends

use a similar strategy as llama.cpp for deciding where tensors should be
allocated. this will be improved later to be aware of usable memory
before assigning the tensor
---
 ml/backend/ggml/ggml.go                       | 359 +++++++++++-------
 ml/backend/ggml/ggml/src/ggml-backend-reg.cpp |  21 +-
 model/models/llama/model.go                   |  16 +-
 3 files changed, 249 insertions(+), 147 deletions(-)

diff --git a/ml/backend/ggml/ggml.go b/ml/backend/ggml/ggml.go
index 2d8ddf99..ae32e3c6 100644
--- a/ml/backend/ggml/ggml.go
+++ b/ml/backend/ggml/ggml.go
@@ -9,67 +9,46 @@ package ggml
 import "C"
 
 import (
+	"errors"
 	"fmt"
 	"io"
+	"iter"
 	"log/slog"
+	"maps"
 	"os"
-	"sync"
+	"slices"
+	"strconv"
+	"strings"
+	"unicode"
 	"unsafe"
 
 	"github.com/ollama/ollama/format"
 	fs "github.com/ollama/ollama/fs/ggml"
 	"github.com/ollama/ollama/ml"
 	"golang.org/x/sync/errgroup"
-
-	ggml "github.com/ollama/ollama/ml/backend/ggml/ggml/src"
 )
 
-type device struct {
-	d *C.struct_ggml_backend_device
-}
-
-func (d device) LogValue() slog.Value {
-	var free, total uint64
-	C.ggml_backend_dev_memory(d.d, (*C.size_t)(&free), (*C.size_t)(&total))
-
-	kind := "unknown"
-	switch C.ggml_backend_dev_type(d.d) {
-	case C.GGML_BACKEND_DEVICE_TYPE_CPU:
-		kind = "cpu"
-	case C.GGML_BACKEND_DEVICE_TYPE_GPU:
-		kind = "gpu"
-	case C.GGML_BACKEND_DEVICE_TYPE_ACCEL:
-		kind = "accel"
+func devices() iter.Seq[*C.struct_ggml_backend_device] {
+	return func(yield func(*C.struct_ggml_backend_device) bool) {
+		for i := range C.ggml_backend_dev_count() {
+			if !yield(C.ggml_backend_dev_get(i)) {
+				return
+			}
+		}
 	}
-
-	return slog.GroupValue(
-		slog.String("name", C.GoString(C.ggml_backend_dev_name(d.d))),
-		slog.String("description", C.GoString(C.ggml_backend_dev_description(d.d))),
-		slog.String("kind", kind),
-		slog.String("free", format.HumanBytes2(free)),
-		slog.String("total", format.HumanBytes2(total)),
-	)
 }
 
-var devices = sync.OnceValue(func() []device {
-	ggml.OnceLoad()
-
-	s := make([]device, C.ggml_backend_dev_count())
-	for i := range s {
-		s[i] = device{C.ggml_backend_dev_get(C.size_t(i))}
-	}
-
-	return s
-})
-
 type Backend struct {
+	meta *fs.GGML
+
 	flashAttention bool
 
-	meta       *fs.GGML
-	cpus, gpus []Context
-	tensors    map[string]*Context
-
 	sched *C.struct_ggml_backend_sched
+
+	tensors  map[string]*C.struct_ggml_tensor
+	ctxs     []*C.struct_ggml_context
+	backends []*C.struct_ggml_backend
+	bufts    []*C.struct_ggml_backend_buffer_type
 }
 
 func New(r *os.File, params ml.BackendParams) (ml.Backend, error) {
@@ -88,100 +67,226 @@ func New(r *os.File, params ml.BackendParams) (ml.Backend, error) {
 		"num_key_values", len(meta.KV()),
 	)
 
-	var cpus, gpus []Context
-	for _, d := range devices() {
-		switch C.ggml_backend_dev_type(d.d) {
+	type dbt struct {
+		d   *C.struct_ggml_backend_device
+		bts []*C.struct_ggml_backend_buffer_type
+	}
+
+	var cpus, accels, gpus []*C.struct_ggml_backend_device
+	for d := range devices() {
+		switch C.ggml_backend_dev_type(d) {
+		case C.GGML_BACKEND_DEVICE_TYPE_CPU:
+			cpus = append(cpus, d)
+		case C.GGML_BACKEND_DEVICE_TYPE_ACCEL:
+			accels = append(accels, d)
+		case C.GGML_BACKEND_DEVICE_TYPE_GPU:
+			gpus = append(gpus, d)
+		}
+	}
+
+	var cpuBufferTypes []*C.struct_ggml_backend_buffer_type
+	for _, d := range append(accels, append(gpus, cpus...)...) {
+		switch C.ggml_backend_dev_type(d) {
 		case C.GGML_BACKEND_DEVICE_TYPE_CPU,
 			C.GGML_BACKEND_DEVICE_TYPE_ACCEL:
-			slog.Info("cpu", "device", d)
-			cpus = append(cpus, Context{
-				ctx: C.ggml_init(C.struct_ggml_init_params{
-					mem_size: C.size_t(int(C.ggml_tensor_overhead()) * (len(meta.Tensors().Items()) + 1 + int(meta.KV().BlockCount())*2)),
-					no_alloc: true,
-				}),
-				backend: C.ggml_backend_dev_init(d.d, nil),
-			})
-		case C.GGML_BACKEND_DEVICE_TYPE_GPU:
-			slog.Info("gpu", "device", d)
-			gpus = append(gpus, Context{
-				ctx: C.ggml_init(C.struct_ggml_init_params{
-					mem_size: C.size_t(int(C.ggml_tensor_overhead()) * (len(meta.Tensors().Items()) + 1 + int(meta.KV().BlockCount())*2)),
-					no_alloc: true,
-				}),
-				backend: C.ggml_backend_dev_init(d.d, nil),
-			})
+			cpuBufferTypes = append(cpuBufferTypes, C.ggml_backend_dev_buffer_type(d))
 		}
 	}
 
-	ctxFunc := func(s []Context) (*Context, error) {
-		for _, e := range s {
-			return &e, nil
-		}
+	var sum uint64
+	var cumsum []uint64
 
-		return nil, fmt.Errorf("no devices available")
+	var gpuBufferTypes []dbt
+	for _, d := range gpus {
+		var free, total C.size_t
+		C.ggml_backend_dev_memory(d, &free, &total)
+		sum += uint64(free)
+		cumsum = append(cumsum, sum)
+
+		bt := C.ggml_backend_dev_buffer_type(d)
+		gpuBufferTypes = append(gpuBufferTypes, dbt{
+			d:   d,
+			bts: append([]*C.struct_ggml_backend_buffer_type{bt}, cpuBufferTypes...),
+		})
 	}
 
-	tensors := make(map[*fs.Tensor]*Context, len(meta.Tensors().Items()))
-	for _, t := range meta.Tensors().Items() {
-		c, err := ctxFunc(append(gpus, cpus...))
-		if err != nil {
-			return nil, err
-		}
+	splits := make([]float64, len(cumsum))
+	for i := range splits {
+		splits[i] = float64(cumsum[i]) / float64(sum)
+	}
 
-		func() {
-			tt := C.ggml_new_tensor(c.ctx, t.Kind, C.int(len(t.Shape)), (*C.int64_t)(unsafe.Pointer(&t.Shape[0])))
+	input := dbt{C.ggml_backend_dev_by_type(C.GGML_BACKEND_DEVICE_TYPE_CPU), cpuBufferTypes}
+	slog.Info("input layer", "device", C.GoString(C.ggml_backend_dev_name(input.d)))
+
+	var blocks int
+	for key, value := range meta.KV() {
+		if strings.HasSuffix(key, ".block_count") {
+			blocks += int(value.(uint32))
+		}
+	}
+
+	indexFunc := func(i int) func(float64) bool {
+		return func(f float64) bool {
+			return float64(i)/float64(blocks+1) < f
+		}
+	}
+
+	layers := make([]dbt, blocks)
+	for i := range layers {
+		layers[i] = gpuBufferTypes[slices.IndexFunc(splits, indexFunc(i))]
+		slog.Info("layer", "i", i, "device", C.GoString(C.ggml_backend_dev_name(layers[i].d)))
+	}
+
+	output := gpuBufferTypes[slices.IndexFunc(splits, indexFunc(blocks))]
+	slog.Info("output layer", "device", C.GoString(C.ggml_backend_dev_name(output.d)))
+
+	maxTensors := len(meta.Tensors().Items())
+	maxTensors += 1
+	maxTensors += blocks * 2
+
+	slog.Info("max tensors", "max_tensors", maxTensors)
+
+	ctxs := make(map[*C.struct_ggml_backend_buffer_type]*C.struct_ggml_context)
+	createTensor := func(t *fs.Tensor, bts []*C.struct_ggml_backend_buffer_type) *C.struct_ggml_tensor {
+		for _, bt := range bts {
+			if _, ok := ctxs[bt]; !ok {
+				ctxs[bt] = C.ggml_init(C.struct_ggml_init_params{
+					mem_size: C.ggml_tensor_overhead() * C.size_t(maxTensors),
+					no_alloc: true,
+				})
+			}
 
 			cname := C.CString(t.Name)
 			defer C.free(unsafe.Pointer(cname))
+			if tt := C.ggml_get_tensor(ctxs[bt], cname); tt != nil {
+				return tt
+			}
+
+			tt := C.ggml_new_tensor(ctxs[bt], t.Kind, C.int(len(t.Shape)), (*C.int64_t)(unsafe.Pointer(&t.Shape[0])))
 			C.ggml_set_name(tt, cname)
 
-			tensors[t] = c
-		}()
+			slog.Debug("created tensor", "name", t.Name, "shape", t.Shape, "dtype", t.Kind, "buffer_type", C.GoString(C.ggml_backend_buft_name(bt)))
+			//nolint:staticcheck // TODO: check if buffer type supports this tensor
+			return tt
+		}
+
+		return nil
 	}
 
-	for _, b := range append(gpus, cpus...) {
-		C.ggml_backend_alloc_ctx_tensors(b.ctx, b.backend)
+	hasPart := func(s string, parts ...string) bool {
+		split := strings.Split(s, ".")
+		for _, part := range parts {
+			if slices.Contains(split, part) {
+				return true
+			}
+		}
+
+		return false
+	}
+
+	for _, t := range meta.Tensors().Items() {
+		switch {
+		case hasPart(t.Name, "position_embd", "token_embd", "token_norm_embd", "token_types"):
+			createTensor(t, input.bts)
+		case hasPart(t.Name, "cls", "output", "output_norm"):
+			createTensor(t, output.bts)
+		default:
+			if i := func() int {
+				if fields := strings.FieldsFunc(t.Name, func(r rune) bool { return !unicode.IsNumber(r) }); len(fields) > 0 {
+					if i, err := strconv.Atoi(fields[0]); err == nil {
+						return i
+					}
+				}
+
+				return -1
+			}(); i >= 0 {
+				createTensor(t, layers[i].bts)
+			} else {
+				for _, layer := range layers {
+					createTensor(t, layer.bts)
+				}
+			}
+		}
+	}
+
+	bbs := make(map[*C.struct_ggml_context][]*C.struct_ggml_backend_buffer, len(ctxs))
+
+	for bt, c := range ctxs {
+		if C.ggml_get_first_tensor(c) == nil {
+			continue
+		}
+
+		b := C.ggml_backend_alloc_ctx_tensors_from_buft(c, bt)
+		C.ggml_backend_buffer_set_usage(b, C.GGML_BACKEND_BUFFER_USAGE_WEIGHTS)
+		bbs[c] = append(bbs[c], b)
+	}
+
+	for bs := range maps.Values(bbs) {
+		for _, b := range bs {
+			slog.Info("model", "buffer", C.GoString(C.ggml_backend_buffer_name(b)), "size", format.HumanBytes2(uint64(C.ggml_backend_buffer_get_size(b))))
+		}
+	}
+
+	tensors := make(map[string]*C.struct_ggml_tensor)
+	for _, c := range ctxs {
+		for t := C.ggml_get_first_tensor(c); t != nil; t = C.ggml_get_next_tensor(c, t) {
+			tensors[C.GoString(C.ggml_get_name(t))] = t
+		}
 	}
 
 	sr := io.NewSectionReader(r, int64(meta.Tensors().Offset), n-int64(meta.Tensors().Offset))
-
 	var g errgroup.Group
-	for t, c := range tensors {
+	for _, t := range meta.Tensors().Items() {
 		g.Go(func() error {
+			tt, ok := tensors[t.Name]
+			if !ok {
+				return fmt.Errorf("unassigned tensor: %s", t.Name)
+			}
+
 			bts := make([]byte, t.Size())
 			n, err := io.ReadFull(io.NewSectionReader(sr, int64(t.Offset), int64(t.Size())), bts)
 			if err != nil {
 				return err
 			}
 
-			if n != int(t.Size()) {
-				return fmt.Errorf("expected %d bytes, got %d", t.Size(), n)
+			if n != len(bts) {
+				return errors.New("short read")
 			}
 
 			cname := C.CString(t.Name)
-			defer C.free(unsafe.Pointer(cname))
+			C.ggml_backend_tensor_set(tt, unsafe.Pointer(&bts[0]), 0, C.size_t(t.Size()))
+			C.free(unsafe.Pointer(cname))
 
-			C.ggml_backend_tensor_set(C.ggml_get_tensor(c.ctx, cname), unsafe.Pointer(&bts[0]), 0, C.size_t(n))
 			return nil
 		})
 	}
 
-	if err := g.Wait(); err != nil {
+	if g.Wait() != nil {
 		return nil, err
 	}
 
-	backends := make([]*C.struct_ggml_backend, len(gpus)+len(cpus))
-	bufts := make([]*C.struct_ggml_backend_buffer_type, len(gpus)+len(cpus))
-	for i, c := range append(gpus, cpus...) {
-		backends[i] = c.backend
-		bufts[i] = C.ggml_backend_get_default_buffer_type(c.backend)
+	var backends []*C.struct_ggml_backend
+	var bufts []*C.struct_ggml_backend_buffer_type
+	for _, d := range append(gpus, append(accels, cpus...)...) {
+		b := C.ggml_backend_dev_init(d, nil)
+		backends = append(backends, b)
+
+		bt := C.ggml_backend_get_default_buffer_type(b)
+		if d := C.ggml_backend_get_device(b); C.ggml_backend_dev_type(d) == C.GGML_BACKEND_DEVICE_TYPE_CPU && len(gpus) > 0 {
+			if hbt := C.ggml_backend_dev_host_buffer_type(d); hbt != nil {
+				bt = hbt
+			}
+		}
+
+		bufts = append(bufts, bt)
+
+		slog.Info("compute buffer", "backend", C.GoString(C.ggml_backend_name(b)), "buffer_type", C.GoString(C.ggml_backend_buft_name(bt)))
 	}
 
 	return &Backend{
 		flashAttention: params.FlashAttention,
-		meta:           meta,
-		cpus:           cpus,
-		gpus:           gpus,
+		meta:              meta,
+		tensors:           tensors,
 		sched: C.ggml_backend_sched_new(
 			(*C.ggml_backend_t)(unsafe.Pointer(&backends[0])),
 			(*C.ggml_backend_buffer_type_t)(unsafe.Pointer(&bufts[0])),
@@ -201,36 +306,22 @@ func (b *Backend) Config() ml.Config {
 }
 
 func (b *Backend) Get(name string) ml.Tensor {
-	cname := C.CString(name)
-	defer C.free(unsafe.Pointer(cname))
-
-	for _, c := range append(b.gpus, b.cpus...) {
-		if t := C.ggml_get_tensor(c.ctx, cname); t != nil {
-			return &Tensor{b: b, t: t}
-		}
+	if t, ok := b.tensors[name]; ok {
+		return &Tensor{b: b, t: t}
 	}
 
 	return nil
 }
 
 func (b *Backend) NewContext() ml.Context {
-	nodes := max(8192, len(b.meta.Tensors().Items())*5)
-	c := C.ggml_init(C.struct_ggml_init_params{
-		mem_buffer: nil,
-		mem_size:   C.size_t(nodes)*C.ggml_tensor_overhead() + C.ggml_graph_overhead_custom(C.size_t(nodes), false),
-		no_alloc:   true,
-	})
-
-	backends := make([]*C.struct_ggml_backend, len(b.gpus)+len(b.cpus))
-	for i, c := range append(b.gpus, b.cpus...) {
-		backends[i] = c.backend
-	}
-
+	maxTensors := max(8192, len(b.meta.Tensors().Items())*5)
 	return &Context{
-		b:       b,
-		ctx:     c,
-		backend: backends[0],
-		nodes:   nodes,
+		b:          b,
+		maxTensors: maxTensors,
+		ctx: C.ggml_init(C.struct_ggml_init_params{
+			mem_size: C.size_t(maxTensors)*C.ggml_tensor_overhead() + C.ggml_graph_overhead_custom(C.size_t(maxTensors), false),
+			no_alloc: true,
+		}),
 	}
 }
 
@@ -243,17 +334,17 @@ func (b *Backend) CacheConfig() ml.CacheConfig {
 }
 
 type Context struct {
-	b       *Backend
-	ctx     *C.struct_ggml_context
-	backend *C.struct_ggml_backend
+	b *Backend
 
+	ctx   *C.struct_ggml_context
 	graph *C.struct_ggml_cgraph
-	nodes int
+
+	maxTensors int
 }
 
 func (c *Context) Forward(tensors ...ml.Tensor) ml.Context {
 	if c.graph == nil {
-		c.graph = C.ggml_new_graph_custom(c.ctx, C.size_t(c.nodes), false)
+		c.graph = C.ggml_new_graph_custom(c.ctx, C.size_t(c.maxTensors), false)
 	}
 
 	for _, tensor := range tensors {
@@ -264,8 +355,9 @@ func (c *Context) Forward(tensors ...ml.Tensor) ml.Context {
 }
 
 func (c *Context) Compute(tensors ...ml.Tensor) {
-	C.ggml_backend_sched_graph_compute_async(c.b.sched, c.graph)
 	C.ggml_backend_sched_reset(c.b.sched)
+	C.ggml_backend_sched_alloc_graph(c.b.sched, c.graph)
+	C.ggml_backend_sched_graph_compute_async(c.b.sched, c.graph)
 
 	needSync := true
 	sync := func() {
@@ -283,19 +375,19 @@ func (c *Context) Compute(tensors ...ml.Tensor) {
 }
 
 func (c *Context) MaxTensors() int {
-	return c.nodes
+	return c.maxTensors
 }
 
 func shapeToGGML(shape []int) *C.int64_t {
 	sh := make([]C.int64_t, len(shape))
 	for i, s := range shape {
-		sh[i] = (C.int64_t)(s)
+		sh[i] = C.int64_t(s)
 	}
 
 	return &sh[0]
 }
 
-func newTensor(ctx Context, dtype ml.DType, zero bool, shape []int) ml.Tensor {
+func newTensor(ctx Context, dtype ml.DType, shape []int) ml.Tensor {
 	if len(shape) < 1 || len(shape) > 4 {
 		panic("unsupported number of dimensions")
 	}
@@ -318,20 +410,20 @@ func newTensor(ctx Context, dtype ml.DType, zero bool, shape []int) ml.Tensor {
 		panic("unsupported dtype")
 	}
 
-	b := C.ggml_backend_alloc_buffer(ctx.backend, C.ggml_nbytes(t))
+	b := C.ggml_backend_alloc_buffer(C.ggml_backend_sched_get_backend(ctx.b.sched, 0), C.ggml_nbytes(t))
 	C.ggml_backend_tensor_alloc(b, t, C.ggml_backend_buffer_get_base(b))
-	if zero {
-		C.ggml_set_zero(t)
-	}
+	C.ggml_set_input(t)
 	return &Tensor{b: ctx.b, t: t}
 }
 
 func (c Context) Empty(dtype ml.DType, shape ...int) ml.Tensor {
-	return newTensor(c, dtype, false, shape)
+	return newTensor(c, dtype, shape)
 }
 
 func (c Context) Zeros(dtype ml.DType, shape ...int) ml.Tensor {
-	return newTensor(c, dtype, true, shape)
+	t := newTensor(c, dtype, shape)
+	C.ggml_set_zero(t.(*Tensor).t)
+	return t
 }
 
 func fromSlice[S ~[]E, E float32 | int32](ctx Context, s S, shape []int, dtype uint32) (ml.Tensor, error) {
@@ -352,9 +444,10 @@ func fromSlice[S ~[]E, E float32 | int32](ctx Context, s S, shape []int, dtype u
 	}
 
 	t := C.ggml_new_tensor(ctx.ctx, dtype, C.int(len(shape)), shapeToGGML(shape))
-	b := C.ggml_backend_alloc_buffer(ctx.backend, C.ggml_nbytes(t))
+	b := C.ggml_backend_alloc_buffer(C.ggml_backend_sched_get_backend(ctx.b.sched, 0), C.ggml_nbytes(t))
 	C.ggml_backend_tensor_alloc(b, t, C.ggml_backend_buffer_get_base(b))
 	C.ggml_backend_tensor_set(t, unsafe.Pointer(&s[0]), 0, C.ggml_nbytes(t))
+	C.ggml_set_input(t)
 	return &Tensor{b: ctx.b, t: t}, nil
 }
 
diff --git a/ml/backend/ggml/ggml/src/ggml-backend-reg.cpp b/ml/backend/ggml/ggml/src/ggml-backend-reg.cpp
index 799af5f3..00cfc968 100644
--- a/ml/backend/ggml/ggml/src/ggml-backend-reg.cpp
+++ b/ml/backend/ggml/ggml/src/ggml-backend-reg.cpp
@@ -207,13 +207,7 @@ struct ggml_backend_registry {
         for (size_t i = 0; i < ggml_backend_reg_dev_count(reg); i++) {
             register_device(ggml_backend_reg_dev_get(reg, i), score);
         }
-    }
 
-    void register_device(ggml_backend_dev_t device, int score = -1) {
-#ifndef NDEBUG
-        GGML_LOG_DEBUG("%s: registered device %s (%s)\n", __func__, ggml_backend_dev_name(device), ggml_backend_dev_description(device));
-#endif
-        devices.push_back({device, score});
         std::stable_sort(devices.begin(), devices.end(),
             [](const auto & a, const auto & b) {
                 return a.second > b.second;
@@ -221,6 +215,21 @@ struct ggml_backend_registry {
         );
     }
 
+    void register_device(ggml_backend_dev_t device, int score = -1) {
+        switch (ggml_backend_dev_type(device)) {
+        case GGML_BACKEND_DEVICE_TYPE_CPU:
+        case GGML_BACKEND_DEVICE_TYPE_GPU:
+            score += 1 << 16;
+        case GGML_BACKEND_DEVICE_TYPE_ACCEL:
+            score += 1 << 20;
+        }
+
+#ifndef NDEBUG
+        GGML_LOG_DEBUG("%s: registered device %s (%s)\n", __func__, ggml_backend_dev_name(device), ggml_backend_dev_description(device));
+#endif
+        devices.push_back({device, score});
+    }
+
     ggml_backend_reg_t load_backend(const std::filesystem::path & path, bool silent) {
         dl_handle_ptr handle { dl_load_library(path) };
         if (!handle) {
diff --git a/model/models/llama/model.go b/model/models/llama/model.go
index 2f254a28..73a23621 100644
--- a/model/models/llama/model.go
+++ b/model/models/llama/model.go
@@ -12,7 +12,6 @@ import (
 )
 
 type Options struct {
-	RopeFactors                      ml.Tensor `gguf:"rope_freqs.weight"`
 	hiddenSize, numHeads, numKVHeads int
 	eps, ropeBase, ropeScale         float32
 	ropeDim                          uint32
@@ -66,10 +65,11 @@ func New(c ml.Config) (model.Model, error) {
 }
 
 type SelfAttention struct {
-	Query  *nn.Linear `gguf:"attn_q"`
-	Key    *nn.Linear `gguf:"attn_k"`
-	Value  *nn.Linear `gguf:"attn_v"`
-	Output *nn.Linear `gguf:"attn_output"`
+	Query       *nn.Linear `gguf:"attn_q"`
+	Key         *nn.Linear `gguf:"attn_k"`
+	Value       *nn.Linear `gguf:"attn_v"`
+	Output      *nn.Linear `gguf:"attn_output"`
+	RopeFactors ml.Tensor  `gguf:"rope_freqs.weight"`
 }
 
 func (sa *SelfAttention) Forward(ctx ml.Context, hiddenState, positionIDs ml.Tensor, cache kvcache.Cache, opts *Options) ml.Tensor {
@@ -78,11 +78,11 @@ func (sa *SelfAttention) Forward(ctx ml.Context, hiddenState, positionIDs ml.Ten
 
 	q := sa.Query.Forward(ctx, hiddenState)
 	q = q.Reshape(ctx, headDim, opts.numHeads, batchSize)
-	q = q.RoPE(ctx, positionIDs, opts.RopeFactors, opts.ropeDim, opts.ropeBase, opts.ropeScale)
+	q = q.RoPE(ctx, positionIDs, sa.RopeFactors, opts.ropeDim, opts.ropeBase, opts.ropeScale)
 
 	k := sa.Key.Forward(ctx, hiddenState)
 	k = k.Reshape(ctx, headDim, opts.numKVHeads, batchSize)
-	k = k.RoPE(ctx, positionIDs, opts.RopeFactors, opts.ropeDim, opts.ropeBase, opts.ropeScale)
+	k = k.RoPE(ctx, positionIDs, sa.RopeFactors, opts.ropeDim, opts.ropeBase, opts.ropeScale)
 
 	v := sa.Value.Forward(ctx, hiddenState)
 	v = v.Reshape(ctx, headDim, opts.numKVHeads, batchSize)
@@ -95,7 +95,7 @@ func (sa *SelfAttention) Forward(ctx ml.Context, hiddenState, positionIDs ml.Ten
 }
 
 func (m *Model) Shift(ctx ml.Context, layer int, key, shift ml.Tensor) (ml.Tensor, error) {
-	return key.RoPE(ctx, shift, m.Options.RopeFactors, m.Options.ropeDim, m.Options.ropeBase, m.Options.ropeScale), nil
+	return key.RoPE(ctx, shift, m.Layers[layer].SelfAttention.RopeFactors, m.ropeDim, m.ropeBase, m.ropeScale), nil
 }
 
 type MLP struct {

From bfce55db3d9052200392c67412656cc3e37ba893 Mon Sep 17 00:00:00 2001
From: Michael Yang <mxyng@pm.me>
Date: Mon, 24 Feb 2025 15:48:42 -0800
Subject: [PATCH 010/157] model: load non-repeated tensors into multiple
 backends

some tensors are expected to be used in repeating layers but are not
themselves repeated. this change copies these tensors into the same
backends as their repeating counterparts to minimize copying tensors
between backends
---
 ml/backend/ggml/ggml.go                       | 79 ++++++++++++-------
 ml/backend/ggml/ggml/src/ggml-backend-reg.cpp | 21 ++---
 2 files changed, 58 insertions(+), 42 deletions(-)

diff --git a/ml/backend/ggml/ggml.go b/ml/backend/ggml/ggml.go
index ae32e3c6..e909f53c 100644
--- a/ml/backend/ggml/ggml.go
+++ b/ml/backend/ggml/ggml.go
@@ -25,11 +25,13 @@ import (
 	"github.com/ollama/ollama/format"
 	fs "github.com/ollama/ollama/fs/ggml"
 	"github.com/ollama/ollama/ml"
+	ggml "github.com/ollama/ollama/ml/backend/ggml/ggml/src"
 	"golang.org/x/sync/errgroup"
 )
 
 func devices() iter.Seq[*C.struct_ggml_backend_device] {
 	return func(yield func(*C.struct_ggml_backend_device) bool) {
+		ggml.OnceLoad()
 		for i := range C.ggml_backend_dev_count() {
 			if !yield(C.ggml_backend_dev_get(i)) {
 				return
@@ -146,8 +148,15 @@ func New(r *os.File, params ml.BackendParams) (ml.Backend, error) {
 
 	slog.Info("max tensors", "max_tensors", maxTensors)
 
+	type tensor struct {
+		source *fs.Tensor
+		target string
+	}
+
+	targets := make(map[string][]string)
+
 	ctxs := make(map[*C.struct_ggml_backend_buffer_type]*C.struct_ggml_context)
-	createTensor := func(t *fs.Tensor, bts []*C.struct_ggml_backend_buffer_type) *C.struct_ggml_tensor {
+	createTensor := func(t tensor, bts []*C.struct_ggml_backend_buffer_type) *C.struct_ggml_tensor {
 		for _, bt := range bts {
 			if _, ok := ctxs[bt]; !ok {
 				ctxs[bt] = C.ggml_init(C.struct_ggml_init_params{
@@ -156,16 +165,23 @@ func New(r *os.File, params ml.BackendParams) (ml.Backend, error) {
 				})
 			}
 
-			cname := C.CString(t.Name)
+			targets[t.source.Name] = append(targets[t.source.Name], t.target)
+
+			name := t.source.Name
+			if t.target != "" {
+				name = t.target
+			}
+
+			cname := C.CString(name)
 			defer C.free(unsafe.Pointer(cname))
 			if tt := C.ggml_get_tensor(ctxs[bt], cname); tt != nil {
 				return tt
 			}
 
-			tt := C.ggml_new_tensor(ctxs[bt], t.Kind, C.int(len(t.Shape)), (*C.int64_t)(unsafe.Pointer(&t.Shape[0])))
+			tt := C.ggml_new_tensor(ctxs[bt], t.source.Kind, C.int(len(t.source.Shape)), (*C.int64_t)(unsafe.Pointer(&t.source.Shape[0])))
 			C.ggml_set_name(tt, cname)
 
-			slog.Debug("created tensor", "name", t.Name, "shape", t.Shape, "dtype", t.Kind, "buffer_type", C.GoString(C.ggml_backend_buft_name(bt)))
+			slog.Debug("created tensor", "name", name, "shape", t.source.Shape, "dtype", t.source.Kind, "buffer_type", C.GoString(C.ggml_backend_buft_name(bt)))
 			//nolint:staticcheck // TODO: check if buffer type supports this tensor
 			return tt
 		}
@@ -187,9 +203,9 @@ func New(r *os.File, params ml.BackendParams) (ml.Backend, error) {
 	for _, t := range meta.Tensors().Items() {
 		switch {
 		case hasPart(t.Name, "position_embd", "token_embd", "token_norm_embd", "token_types"):
-			createTensor(t, input.bts)
+			createTensor(tensor{source: t}, input.bts)
 		case hasPart(t.Name, "cls", "output", "output_norm"):
-			createTensor(t, output.bts)
+			createTensor(tensor{source: t}, output.bts)
 		default:
 			if i := func() int {
 				if fields := strings.FieldsFunc(t.Name, func(r rune) bool { return !unicode.IsNumber(r) }); len(fields) > 0 {
@@ -200,10 +216,13 @@ func New(r *os.File, params ml.BackendParams) (ml.Backend, error) {
 
 				return -1
 			}(); i >= 0 {
-				createTensor(t, layers[i].bts)
+				createTensor(tensor{source: t}, layers[i].bts)
 			} else {
-				for _, layer := range layers {
-					createTensor(t, layer.bts)
+				for i, layer := range layers {
+					createTensor(tensor{
+						source: t,
+						target: "blk." + strconv.Itoa(i) + "." + t.Name,
+					}, layer.bts)
 				}
 			}
 		}
@@ -237,28 +256,34 @@ func New(r *os.File, params ml.BackendParams) (ml.Backend, error) {
 	sr := io.NewSectionReader(r, int64(meta.Tensors().Offset), n-int64(meta.Tensors().Offset))
 	var g errgroup.Group
 	for _, t := range meta.Tensors().Items() {
-		g.Go(func() error {
-			tt, ok := tensors[t.Name]
-			if !ok {
-				return fmt.Errorf("unassigned tensor: %s", t.Name)
-			}
+		for _, target := range targets[t.Name] {
+			g.Go(func() error {
+				if target == "" {
+					target = t.Name
+				}
 
-			bts := make([]byte, t.Size())
-			n, err := io.ReadFull(io.NewSectionReader(sr, int64(t.Offset), int64(t.Size())), bts)
-			if err != nil {
-				return err
-			}
+				tt, ok := tensors[target]
+				if !ok {
+					return fmt.Errorf("unassigned tensor: %s", t.Name)
+				}
 
-			if n != len(bts) {
-				return errors.New("short read")
-			}
+				bts := make([]byte, t.Size())
+				n, err := io.ReadFull(io.NewSectionReader(sr, int64(t.Offset), int64(t.Size())), bts)
+				if err != nil {
+					return err
+				}
 
-			cname := C.CString(t.Name)
-			C.ggml_backend_tensor_set(tt, unsafe.Pointer(&bts[0]), 0, C.size_t(t.Size()))
-			C.free(unsafe.Pointer(cname))
+				if n != len(bts) {
+					return errors.New("short read")
+				}
 
-			return nil
-		})
+				cname := C.CString(t.Name)
+				C.ggml_backend_tensor_set(tt, unsafe.Pointer(&bts[0]), 0, C.size_t(t.Size()))
+				C.free(unsafe.Pointer(cname))
+
+				return nil
+			})
+		}
 	}
 
 	if g.Wait() != nil {
diff --git a/ml/backend/ggml/ggml/src/ggml-backend-reg.cpp b/ml/backend/ggml/ggml/src/ggml-backend-reg.cpp
index 00cfc968..799af5f3 100644
--- a/ml/backend/ggml/ggml/src/ggml-backend-reg.cpp
+++ b/ml/backend/ggml/ggml/src/ggml-backend-reg.cpp
@@ -207,7 +207,13 @@ struct ggml_backend_registry {
         for (size_t i = 0; i < ggml_backend_reg_dev_count(reg); i++) {
             register_device(ggml_backend_reg_dev_get(reg, i), score);
         }
+    }
 
+    void register_device(ggml_backend_dev_t device, int score = -1) {
+#ifndef NDEBUG
+        GGML_LOG_DEBUG("%s: registered device %s (%s)\n", __func__, ggml_backend_dev_name(device), ggml_backend_dev_description(device));
+#endif
+        devices.push_back({device, score});
         std::stable_sort(devices.begin(), devices.end(),
             [](const auto & a, const auto & b) {
                 return a.second > b.second;
@@ -215,21 +221,6 @@ struct ggml_backend_registry {
         );
     }
 
-    void register_device(ggml_backend_dev_t device, int score = -1) {
-        switch (ggml_backend_dev_type(device)) {
-        case GGML_BACKEND_DEVICE_TYPE_CPU:
-        case GGML_BACKEND_DEVICE_TYPE_GPU:
-            score += 1 << 16;
-        case GGML_BACKEND_DEVICE_TYPE_ACCEL:
-            score += 1 << 20;
-        }
-
-#ifndef NDEBUG
-        GGML_LOG_DEBUG("%s: registered device %s (%s)\n", __func__, ggml_backend_dev_name(device), ggml_backend_dev_description(device));
-#endif
-        devices.push_back({device, score});
-    }
-
     ggml_backend_reg_t load_backend(const std::filesystem::path & path, bool silent) {
         dl_handle_ptr handle { dl_load_library(path) };
         if (!handle) {

From 764e199d6703d80da4d245381efa4a3a412813b2 Mon Sep 17 00:00:00 2001
From: Michael Yang <mxyng@pm.me>
Date: Tue, 25 Feb 2025 12:57:49 -0800
Subject: [PATCH 011/157] kvcache: create cache ctx per layer

each cache layer creates and maintains its own context instead of using
a large context for all layers
---
 kvcache/causal.go       | 52 +++++++++++++++++++++++++----------------
 kvcache/encoder.go      | 36 +++++++++++++++++-----------
 ml/backend.go           |  2 +-
 ml/backend/ggml/ggml.go | 24 ++++++++++---------
 4 files changed, 68 insertions(+), 46 deletions(-)

diff --git a/kvcache/causal.go b/kvcache/causal.go
index b2e7b3ab..6a927cb8 100644
--- a/kvcache/causal.go
+++ b/kvcache/causal.go
@@ -55,8 +55,8 @@ type Causal struct {
 
 	shiftFn      shiftFn
 	backend      ml.Backend
-	cacheCtx     ml.Context
-	keys, values []ml.Tensor
+	ctxs         map[int]ml.Context
+	keys, values map[int]ml.Tensor
 }
 
 type cacheCell struct {
@@ -70,11 +70,23 @@ type cellRange struct {
 }
 
 func NewCausalCache(shift shiftFn) *Causal {
-	return &Causal{windowSize: math.MaxInt32, shiftFn: shift}
+	return &Causal{
+		windowSize: math.MaxInt32,
+		shiftFn:    shift,
+		ctxs:       make(map[int]ml.Context),
+		keys:       make(map[int]ml.Tensor),
+		values:     make(map[int]ml.Tensor),
+	}
 }
 
 func NewSWACache(windowSize int32, shift shiftFn) *Causal {
-	return &Causal{windowSize: windowSize, shiftFn: shift}
+	return &Causal{
+		windowSize: windowSize,
+		shiftFn:    shift,
+		ctxs:       make(map[int]ml.Context),
+		keys:       make(map[int]ml.Tensor),
+		values:     make(map[int]ml.Tensor),
+	}
 }
 
 func (c *Causal) Init(backend ml.Backend, dtype ml.DType, capacity int32) {
@@ -103,7 +115,6 @@ func (c *Causal) Init(backend ml.Backend, dtype ml.DType, capacity int32) {
 	c.cells = make([]cacheCell, c.Capacity)
 	c.cellRanges = make(map[int]cellRange)
 	c.backend = backend
-	c.cacheCtx = backend.NewContext()
 }
 
 func (c *Causal) SetConfig(config ml.CacheConfig) {
@@ -115,7 +126,9 @@ func (c *Causal) SetConfig(config ml.CacheConfig) {
 }
 
 func (c *Causal) Close() {
-	c.cacheCtx.Close()
+	for _, ctx := range c.ctxs {
+		ctx.Close()
+	}
 }
 
 func (c *Causal) StartForward(ctx ml.Context, positions []int32, seqs []int) error {
@@ -239,13 +252,11 @@ func (c *Causal) buildMask(ctx ml.Context, positions []int32, seqs []int) (ml.Te
 }
 
 func (c *Causal) moveCells(ctx ml.Context, src, dst, len int) {
-	for i := range c.keys {
-		if c.keys[i] == nil {
+	for i, key := range c.keys {
+		if key == nil {
 			continue
 		}
 
-		key := c.keys[i]
-
 		kHeadDim := key.Dim(0)
 		numKVHeads := key.Dim(1)
 		rowSize := key.Stride(2)
@@ -305,7 +316,7 @@ func (c *Causal) defrag() {
 		layers++
 	}
 
-	maxMoves := ctx.MaxTensors() / (6 * layers)
+	maxMoves := ctx.MaxGraphNodes() / (6 * layers)
 	moves := 0
 
 	var pendingSrc, pendingDst, pendingLen int
@@ -377,11 +388,6 @@ func (c *Causal) defrag() {
 }
 
 func (c *Causal) SetLayer(layer int) {
-	if layer >= len(c.keys) {
-		c.keys = append(c.keys, make([]ml.Tensor, layer-len(c.keys)+1)...)
-		c.values = append(c.values, make([]ml.Tensor, layer-len(c.values)+1)...)
-	}
-
 	c.curLayer = layer
 }
 
@@ -433,13 +439,19 @@ func (c *Causal) Put(ctx ml.Context, key, value ml.Tensor) {
 		panic(fmt.Errorf("inconsistent batch sizes (layer: %v, batch size: %v layer batch size: %v)", c.curLayer, c.curBatchSize, batchSize))
 	}
 
-	if c.keys[c.curLayer] == nil || c.values[c.curLayer] == nil {
-		c.keys[c.curLayer] = c.cacheCtx.Zeros(c.DType, kHeadDim, numKVHeads, int(c.Capacity))
+	if _, ok := c.ctxs[c.curLayer]; !ok {
+		c.ctxs[c.curLayer] = c.backend.NewContext()
+	}
 
+	if _, ok := c.keys[c.curLayer]; !ok {
+		c.keys[c.curLayer] = c.ctxs[c.curLayer].Zeros(c.DType, kHeadDim, numKVHeads, int(c.Capacity))
+	}
+
+	if _, ok := c.values[c.curLayer]; !ok {
 		if c.config.PermutedV {
-			c.values[c.curLayer] = c.cacheCtx.Zeros(c.DType, int(c.Capacity), vHeadDim, numKVHeads)
+			c.values[c.curLayer] = c.ctxs[c.curLayer].Zeros(c.DType, int(c.Capacity), vHeadDim, numKVHeads)
 		} else {
-			c.values[c.curLayer] = c.cacheCtx.Zeros(c.DType, vHeadDim, numKVHeads, int(c.Capacity))
+			c.values[c.curLayer] = c.ctxs[c.curLayer].Zeros(c.DType, vHeadDim, numKVHeads, int(c.Capacity))
 		}
 	}
 
diff --git a/kvcache/encoder.go b/kvcache/encoder.go
index 39b4cdfb..6a24e867 100644
--- a/kvcache/encoder.go
+++ b/kvcache/encoder.go
@@ -35,13 +35,17 @@ type EncoderCache struct {
 	encoderPos int32
 
 	// ** cache data storage **
-
-	cacheCtx     ml.Context
-	keys, values []ml.Tensor
+	backend      ml.Backend
+	ctxs         map[int]ml.Context
+	keys, values map[int]ml.Tensor
 }
 
 func NewEncoderCache() *EncoderCache {
-	return &EncoderCache{}
+	return &EncoderCache{
+		ctxs:   make(map[int]ml.Context),
+		keys:   make(map[int]ml.Tensor),
+		values: make(map[int]ml.Tensor),
+	}
 }
 
 func (c *EncoderCache) Init(backend ml.Backend, dtype ml.DType, capacity int32) {
@@ -57,7 +61,7 @@ func (c *EncoderCache) Init(backend ml.Backend, dtype ml.DType, capacity int32)
 		panic(fmt.Errorf("encoder cache is unable to enforce requested CachePadding (%v)", c.config.CachePadding))
 	}
 
-	c.cacheCtx = backend.NewContext()
+	c.backend = backend
 }
 
 func (c *EncoderCache) SetConfig(config ml.CacheConfig) {
@@ -69,7 +73,9 @@ func (c *EncoderCache) SetConfig(config ml.CacheConfig) {
 }
 
 func (c *EncoderCache) Close() {
-	c.cacheCtx.Close()
+	for _, ctx := range c.ctxs {
+		ctx.Close()
+	}
 }
 
 func (c *EncoderCache) StartForward(ctx ml.Context, positions []int32, seqs []int) error {
@@ -80,11 +86,6 @@ func (c *EncoderCache) StartForward(ctx ml.Context, positions []int32, seqs []in
 }
 
 func (c *EncoderCache) SetLayer(layer int) {
-	if layer >= len(c.keys) {
-		c.keys = append(c.keys, make([]ml.Tensor, layer-len(c.keys)+1)...)
-		c.values = append(c.values, make([]ml.Tensor, layer-len(c.values)+1)...)
-	}
-
 	c.curLayer = layer
 }
 
@@ -104,9 +105,16 @@ func (c *EncoderCache) Put(ctx ml.Context, key, value ml.Tensor) {
 		value = value.Permute(ctx, 1, 2, 0, 3)
 	}
 
-	if c.keys[c.curLayer] == nil || c.values[c.curLayer] == nil {
-		c.keys[c.curLayer] = c.cacheCtx.Empty(key.DType(), key.Shape()...)
-		c.values[c.curLayer] = c.cacheCtx.Empty(value.DType(), value.Shape()...)
+	if _, ok := c.ctxs[c.curLayer]; !ok {
+		c.ctxs[c.curLayer] = c.backend.NewContext()
+	}
+
+	if _, ok := c.keys[c.curLayer]; !ok {
+		c.keys[c.curLayer] = c.ctxs[c.curLayer].Empty(key.DType(), key.Shape()...)
+	}
+
+	if _, ok := c.values[c.curLayer]; !ok {
+		c.values[c.curLayer] = c.ctxs[c.curLayer].Empty(value.DType(), value.Shape()...)
 	}
 
 	ctx.Forward(
diff --git a/ml/backend.go b/ml/backend.go
index 3ef8a1ac..1eeb635b 100644
--- a/ml/backend.go
+++ b/ml/backend.go
@@ -99,7 +99,7 @@ type Context interface {
 
 	Forward(...Tensor) Context
 	Compute(...Tensor)
-	MaxTensors() int
+	MaxGraphNodes() int
 	Close()
 }
 
diff --git a/ml/backend/ggml/ggml.go b/ml/backend/ggml/ggml.go
index e909f53c..1a272256 100644
--- a/ml/backend/ggml/ggml.go
+++ b/ml/backend/ggml/ggml.go
@@ -339,14 +339,15 @@ func (b *Backend) Get(name string) ml.Tensor {
 }
 
 func (b *Backend) NewContext() ml.Context {
-	maxTensors := max(8192, len(b.meta.Tensors().Items())*5)
+	maxGraphNodes := max(8192, len(b.meta.Tensors().Items())*5)
 	return &Context{
 		b:          b,
-		maxTensors: maxTensors,
 		ctx: C.ggml_init(C.struct_ggml_init_params{
-			mem_size: C.size_t(maxTensors)*C.ggml_tensor_overhead() + C.ggml_graph_overhead_custom(C.size_t(maxTensors), false),
+			mem_size: C.size_t(maxGraphNodes)*C.ggml_tensor_overhead() + C.ggml_graph_overhead_custom(C.size_t(maxGraphNodes), false),
 			no_alloc: true,
 		}),
+		backend:       C.ggml_backend_sched_get_backend(b.sched, 0),
+		maxGraphNodes: maxGraphNodes,
 	}
 }
 
@@ -363,13 +364,14 @@ type Context struct {
 
 	ctx   *C.struct_ggml_context
 	graph *C.struct_ggml_cgraph
+	backend *C.struct_ggml_backend
 
-	maxTensors int
+	maxGraphNodes int
 }
 
 func (c *Context) Forward(tensors ...ml.Tensor) ml.Context {
 	if c.graph == nil {
-		c.graph = C.ggml_new_graph_custom(c.ctx, C.size_t(c.maxTensors), false)
+		c.graph = C.ggml_new_graph_custom(c.ctx, C.size_t(c.maxGraphNodes), false)
 	}
 
 	for _, tensor := range tensors {
@@ -399,8 +401,8 @@ func (c *Context) Compute(tensors ...ml.Tensor) {
 	}
 }
 
-func (c *Context) MaxTensors() int {
-	return c.maxTensors
+func (c *Context) MaxGraphNodes() int {
+	return c.maxGraphNodes
 }
 
 func shapeToGGML(shape []int) *C.int64_t {
@@ -435,7 +437,7 @@ func newTensor(ctx Context, dtype ml.DType, shape []int) ml.Tensor {
 		panic("unsupported dtype")
 	}
 
-	b := C.ggml_backend_alloc_buffer(C.ggml_backend_sched_get_backend(ctx.b.sched, 0), C.ggml_nbytes(t))
+	b := C.ggml_backend_alloc_buffer(ctx.backend, C.ggml_nbytes(t))
 	C.ggml_backend_tensor_alloc(b, t, C.ggml_backend_buffer_get_base(b))
 	C.ggml_set_input(t)
 	return &Tensor{b: ctx.b, t: t}
@@ -469,7 +471,7 @@ func fromSlice[S ~[]E, E float32 | int32](ctx Context, s S, shape []int, dtype u
 	}
 
 	t := C.ggml_new_tensor(ctx.ctx, dtype, C.int(len(shape)), shapeToGGML(shape))
-	b := C.ggml_backend_alloc_buffer(C.ggml_backend_sched_get_backend(ctx.b.sched, 0), C.ggml_nbytes(t))
+	b := C.ggml_backend_alloc_buffer(ctx.backend, C.ggml_nbytes(t))
 	C.ggml_backend_tensor_alloc(b, t, C.ggml_backend_buffer_get_base(b))
 	C.ggml_backend_tensor_set(t, unsafe.Pointer(&s[0]), 0, C.ggml_nbytes(t))
 	C.ggml_set_input(t)
@@ -484,8 +486,8 @@ func (c Context) FromIntSlice(s []int32, shape ...int) (ml.Tensor, error) {
 	return fromSlice(c, s, shape, C.GGML_TYPE_I32)
 }
 
-func (c *Context) Close() {
-	if c != nil {
+func (c Context) Close() {
+	if c.ctx != nil {
 		C.ggml_free(c.ctx)
 	}
 }

From 7bae7fa5ce6a83cfecde12015a7c43dfa3e8bffc Mon Sep 17 00:00:00 2001
From: Michael Yang <mxyng@pm.me>
Date: Tue, 25 Feb 2025 16:06:32 -0800
Subject: [PATCH 012/157] ml/backend/ggml: create tensor on specific backend

some tensors should be created on specific backends to reduce number of
copies and improve performance
---
 kvcache/causal.go            |   6 +-
 kvcache/encoder.go           |   2 +-
 ml/backend.go                |  10 +++
 ml/backend/ggml/ggml.go      | 153 ++++++++++++++++++++++++-----------
 model/models/llama/model.go  |   6 +-
 model/models/mllama/model.go |  12 +--
 6 files changed, 129 insertions(+), 60 deletions(-)

diff --git a/kvcache/causal.go b/kvcache/causal.go
index 6a927cb8..3d1c71db 100644
--- a/kvcache/causal.go
+++ b/kvcache/causal.go
@@ -237,13 +237,13 @@ func (c *Causal) buildMask(ctx ml.Context, positions []int32, seqs []int) (ml.Te
 		mask[i] = float32(math.Inf(-1))
 	}
 
-	maskTensor, err := ctx.FromFloatSlice(mask, length, batchSize)
+	maskTensor, err := ctx.Input().FromFloatSlice(mask, length, batchSize)
 	if err != nil {
 		return nil, err
 	}
 
 	if c.config.MaskDType != ml.DTypeF32 {
-		out := ctx.Empty(c.config.MaskDType, maskTensor.Shape()...)
+		out := ctx.Input().Empty(c.config.MaskDType, maskTensor.Shape()...)
 		ctx.Forward(maskTensor.Copy(ctx, out))
 		maskTensor = out
 	}
@@ -440,7 +440,7 @@ func (c *Causal) Put(ctx ml.Context, key, value ml.Tensor) {
 	}
 
 	if _, ok := c.ctxs[c.curLayer]; !ok {
-		c.ctxs[c.curLayer] = c.backend.NewContext()
+		c.ctxs[c.curLayer] = c.backend.NewContextSize(2).Layer(c.curLayer)
 	}
 
 	if _, ok := c.keys[c.curLayer]; !ok {
diff --git a/kvcache/encoder.go b/kvcache/encoder.go
index 6a24e867..867ee37a 100644
--- a/kvcache/encoder.go
+++ b/kvcache/encoder.go
@@ -106,7 +106,7 @@ func (c *EncoderCache) Put(ctx ml.Context, key, value ml.Tensor) {
 	}
 
 	if _, ok := c.ctxs[c.curLayer]; !ok {
-		c.ctxs[c.curLayer] = c.backend.NewContext()
+		c.ctxs[c.curLayer] = c.backend.NewContextSize(2).Layer(c.curLayer)
 	}
 
 	if _, ok := c.keys[c.curLayer]; !ok {
diff --git a/ml/backend.go b/ml/backend.go
index 1eeb635b..915c9ad6 100644
--- a/ml/backend.go
+++ b/ml/backend.go
@@ -24,6 +24,7 @@ type Backend interface {
 	Config() Config
 	Get(name string) Tensor
 	NewContext() Context
+	NewContextSize(size int) Context
 }
 
 // BackendCacheConfig should be implemented by backends that need special output
@@ -101,6 +102,15 @@ type Context interface {
 	Compute(...Tensor)
 	MaxGraphNodes() int
 	Close()
+
+	// Input returns a context appropriate for creating input tensors
+	Input() Context
+
+	// Output returns a context appropriate for creating output tensors
+	Output() Context
+
+	// Layer returns a context appropriate for creating intermediate tensors
+	Layer(int) Context
 }
 
 type Tensor interface {
diff --git a/ml/backend/ggml/ggml.go b/ml/backend/ggml/ggml.go
index 1a272256..a55d42f1 100644
--- a/ml/backend/ggml/ggml.go
+++ b/ml/backend/ggml/ggml.go
@@ -41,16 +41,14 @@ func devices() iter.Seq[*C.struct_ggml_backend_device] {
 }
 
 type Backend struct {
-	meta *fs.GGML
+	meta    *fs.GGML
+	sched   *C.struct_ggml_backend_sched
+	tensors map[string]*C.struct_ggml_tensor
+	input   *C.struct_ggml_backend
+	output  *C.struct_ggml_backend
+	layers  map[int]*C.struct_ggml_backend
 
 	flashAttention bool
-
-	sched *C.struct_ggml_backend_sched
-
-	tensors  map[string]*C.struct_ggml_tensor
-	ctxs     []*C.struct_ggml_context
-	backends []*C.struct_ggml_backend
-	bufts    []*C.struct_ggml_backend_buffer_type
 }
 
 func New(r *os.File, params ml.BackendParams) (ml.Backend, error) {
@@ -118,7 +116,6 @@ func New(r *os.File, params ml.BackendParams) (ml.Backend, error) {
 	}
 
 	input := dbt{C.ggml_backend_dev_by_type(C.GGML_BACKEND_DEVICE_TYPE_CPU), cpuBufferTypes}
-	slog.Info("input layer", "device", C.GoString(C.ggml_backend_dev_name(input.d)))
 
 	var blocks int
 	for key, value := range meta.KV() {
@@ -136,18 +133,14 @@ func New(r *os.File, params ml.BackendParams) (ml.Backend, error) {
 	layers := make([]dbt, blocks)
 	for i := range layers {
 		layers[i] = gpuBufferTypes[slices.IndexFunc(splits, indexFunc(i))]
-		slog.Info("layer", "i", i, "device", C.GoString(C.ggml_backend_dev_name(layers[i].d)))
 	}
 
 	output := gpuBufferTypes[slices.IndexFunc(splits, indexFunc(blocks))]
-	slog.Info("output layer", "device", C.GoString(C.ggml_backend_dev_name(output.d)))
 
 	maxTensors := len(meta.Tensors().Items())
 	maxTensors += 1
 	maxTensors += blocks * 2
 
-	slog.Info("max tensors", "max_tensors", maxTensors)
-
 	type tensor struct {
 		source *fs.Tensor
 		target string
@@ -242,7 +235,7 @@ func New(r *os.File, params ml.BackendParams) (ml.Backend, error) {
 
 	for bs := range maps.Values(bbs) {
 		for _, b := range bs {
-			slog.Info("model", "buffer", C.GoString(C.ggml_backend_buffer_name(b)), "size", format.HumanBytes2(uint64(C.ggml_backend_buffer_get_size(b))))
+			slog.Info("model weights", "buffer", C.GoString(C.ggml_backend_buffer_name(b)), "size", format.HumanBytes2(uint64(C.ggml_backend_buffer_get_size(b))))
 		}
 	}
 
@@ -290,11 +283,13 @@ func New(r *os.File, params ml.BackendParams) (ml.Backend, error) {
 		return nil, err
 	}
 
+	deviceBackends := make(map[*C.struct_ggml_backend_device]*C.struct_ggml_backend)
 	var backends []*C.struct_ggml_backend
 	var bufts []*C.struct_ggml_backend_buffer_type
 	for _, d := range append(gpus, append(accels, cpus...)...) {
 		b := C.ggml_backend_dev_init(d, nil)
 		backends = append(backends, b)
+		deviceBackends[d] = b
 
 		bt := C.ggml_backend_get_default_buffer_type(b)
 		if d := C.ggml_backend_get_device(b); C.ggml_backend_dev_type(d) == C.GGML_BACKEND_DEVICE_TYPE_CPU && len(gpus) > 0 {
@@ -305,13 +300,13 @@ func New(r *os.File, params ml.BackendParams) (ml.Backend, error) {
 
 		bufts = append(bufts, bt)
 
-		slog.Info("compute buffer", "backend", C.GoString(C.ggml_backend_name(b)), "buffer_type", C.GoString(C.ggml_backend_buft_name(bt)))
+		slog.Info("compute graph", "backend", C.GoString(C.ggml_backend_name(b)), "buffer_type", C.GoString(C.ggml_backend_buft_name(bt)))
 	}
 
 	return &Backend{
 		flashAttention: params.FlashAttention,
-		meta:              meta,
-		tensors:           tensors,
+		meta:           meta,
+		tensors:        tensors,
 		sched: C.ggml_backend_sched_new(
 			(*C.ggml_backend_t)(unsafe.Pointer(&backends[0])),
 			(*C.ggml_backend_buffer_type_t)(unsafe.Pointer(&bufts[0])),
@@ -319,6 +314,15 @@ func New(r *os.File, params ml.BackendParams) (ml.Backend, error) {
 			C.size_t(max(8192, len(meta.Tensors().Items())*5)),
 			true,
 		),
+		input:  deviceBackends[input.d],
+		output: deviceBackends[output.d],
+		layers: func() map[int]*C.struct_ggml_backend {
+			m := make(map[int]*C.struct_ggml_backend)
+			for i, layer := range layers {
+				m[i] = deviceBackends[layer.d]
+			}
+			return m
+		}(),
 	}, nil
 }
 
@@ -339,15 +343,21 @@ func (b *Backend) Get(name string) ml.Tensor {
 }
 
 func (b *Backend) NewContext() ml.Context {
-	maxGraphNodes := max(8192, len(b.meta.Tensors().Items())*5)
+	return b.NewContextSize(max(8192, len(b.meta.Tensors().Items())*5))
+}
+
+func (b *Backend) NewContextSize(n int) ml.Context {
 	return &Context{
-		b:          b,
+		b: b,
 		ctx: C.ggml_init(C.struct_ggml_init_params{
-			mem_size: C.size_t(maxGraphNodes)*C.ggml_tensor_overhead() + C.ggml_graph_overhead_custom(C.size_t(maxGraphNodes), false),
+			mem_size: C.size_t(n)*C.ggml_tensor_overhead() + C.ggml_graph_overhead_custom(C.size_t(n), false),
 			no_alloc: true,
 		}),
 		backend:       C.ggml_backend_sched_get_backend(b.sched, 0),
-		maxGraphNodes: maxGraphNodes,
+		maxGraphNodes: n,
+		input:         b.input,
+		output:        b.output,
+		layers:        b.layers,
 	}
 }
 
@@ -364,11 +374,61 @@ type Context struct {
 
 	ctx   *C.struct_ggml_context
 	graph *C.struct_ggml_cgraph
+
+	// backend is the backend used for new tensors
 	backend *C.struct_ggml_backend
 
+	// input is the backend used for inputs
+	input *C.struct_ggml_backend
+
+	// output is the backend used for outputs
+	output *C.struct_ggml_backend
+
+	// output is the backend used for repeating layers
+	layers map[int]*C.struct_ggml_backend
+
 	maxGraphNodes int
 }
 
+func (c *Context) Input() ml.Context {
+	if c.input != nil {
+		return &Context{
+			b:             c.b,
+			ctx:           c.ctx,
+			backend:       c.input,
+			maxGraphNodes: c.maxGraphNodes,
+		}
+	}
+
+	return c
+}
+
+func (c *Context) Output() ml.Context {
+	if c.output != nil {
+		return &Context{
+			b:             c.b,
+			ctx:           c.ctx,
+			backend:       c.output,
+			maxGraphNodes: c.maxGraphNodes,
+		}
+	}
+
+	return c
+}
+
+func (c *Context) Layer(i int) ml.Context {
+	if backend, ok := c.layers[i]; ok {
+		return &Context{
+			b:             c.b,
+			ctx:           c.ctx,
+			backend:       backend,
+			maxGraphNodes: c.maxGraphNodes,
+		}
+	}
+
+	return c
+}
+
 func (c *Context) Forward(tensors ...ml.Tensor) ml.Context {
 	if c.graph == nil {
 		c.graph = C.ggml_new_graph_custom(c.ctx, C.size_t(c.maxGraphNodes), false)
@@ -414,7 +474,7 @@ func shapeToGGML(shape []int) *C.int64_t {
 	return &sh[0]
 }
 
-func newTensor(ctx Context, dtype ml.DType, shape []int) ml.Tensor {
+func (c Context) newTensor(dtype ml.DType, shape []int) ml.Tensor {
 	if len(shape) < 1 || len(shape) > 4 {
 		panic("unsupported number of dimensions")
 	}
@@ -428,62 +488,61 @@ func newTensor(ctx Context, dtype ml.DType, shape []int) ml.Tensor {
 	var t *C.struct_ggml_tensor
 	switch dtype {
 	case ml.DTypeF32:
-		t = C.ggml_new_tensor(ctx.ctx, C.GGML_TYPE_F32, C.int(len(shape)), shapeToGGML(shape))
+		t = C.ggml_new_tensor(c.ctx, C.GGML_TYPE_F32, C.int(len(shape)), shapeToGGML(shape))
 	case ml.DTypeF16:
-		t = C.ggml_new_tensor(ctx.ctx, C.GGML_TYPE_F16, C.int(len(shape)), shapeToGGML(shape))
+		t = C.ggml_new_tensor(c.ctx, C.GGML_TYPE_F16, C.int(len(shape)), shapeToGGML(shape))
 	case ml.DTypeI32:
-		t = C.ggml_new_tensor(ctx.ctx, C.GGML_TYPE_I32, C.int(len(shape)), shapeToGGML(shape))
+		t = C.ggml_new_tensor(c.ctx, C.GGML_TYPE_I32, C.int(len(shape)), shapeToGGML(shape))
 	default:
 		panic("unsupported dtype")
 	}
 
-	b := C.ggml_backend_alloc_buffer(ctx.backend, C.ggml_nbytes(t))
+	b := C.ggml_backend_alloc_buffer(c.backend, C.ggml_nbytes(t))
 	C.ggml_backend_tensor_alloc(b, t, C.ggml_backend_buffer_get_base(b))
-	C.ggml_set_input(t)
-	return &Tensor{b: ctx.b, t: t}
+	return &Tensor{b: c.b, t: t}
 }
 
 func (c Context) Empty(dtype ml.DType, shape ...int) ml.Tensor {
-	return newTensor(c, dtype, shape)
+	return c.newTensor(dtype, shape)
 }
 
 func (c Context) Zeros(dtype ml.DType, shape ...int) ml.Tensor {
-	t := newTensor(c, dtype, shape)
+	t := c.newTensor(dtype, shape)
 	C.ggml_set_zero(t.(*Tensor).t)
 	return t
 }
 
-func fromSlice[S ~[]E, E float32 | int32](ctx Context, s S, shape []int, dtype uint32) (ml.Tensor, error) {
+func checkShape[S ~[]E, E any](s S, shape ...int) error {
 	n := len(s)
-
-	if n == 0 {
-		var shape C.int64_t = 0
-		t := C.ggml_new_tensor(ctx.ctx, dtype, 1, &shape)
-		return &Tensor{b: ctx.b, t: t}, nil
-	}
-
 	for _, v := range shape {
 		n /= v
 	}
 
 	if n != 1 {
-		return nil, fmt.Errorf("invalid shape %v for %d elements", shape, len(s))
+		return fmt.Errorf("invalid shape: %v", shape)
 	}
 
-	t := C.ggml_new_tensor(ctx.ctx, dtype, C.int(len(shape)), shapeToGGML(shape))
-	b := C.ggml_backend_alloc_buffer(ctx.backend, C.ggml_nbytes(t))
-	C.ggml_backend_tensor_alloc(b, t, C.ggml_backend_buffer_get_base(b))
-	C.ggml_backend_tensor_set(t, unsafe.Pointer(&s[0]), 0, C.ggml_nbytes(t))
-	C.ggml_set_input(t)
-	return &Tensor{b: ctx.b, t: t}, nil
+	return nil
 }
 
 func (c Context) FromFloatSlice(s []float32, shape ...int) (ml.Tensor, error) {
-	return fromSlice(c, s, shape, C.GGML_TYPE_F32)
+	if err := checkShape(s, shape...); err != nil {
+		return nil, err
+	}
+
+	t := c.newTensor(ml.DTypeF32, shape)
+	C.ggml_backend_tensor_set(t.(*Tensor).t, unsafe.Pointer(&s[0]), 0, C.ggml_nbytes(t.(*Tensor).t))
+	return t, nil
 }
 
 func (c Context) FromIntSlice(s []int32, shape ...int) (ml.Tensor, error) {
-	return fromSlice(c, s, shape, C.GGML_TYPE_I32)
+	if err := checkShape(s, shape...); err != nil {
+		return nil, err
+	}
+
+	t := c.newTensor(ml.DTypeI32, shape)
+	C.ggml_backend_tensor_set(t.(*Tensor).t, unsafe.Pointer(&s[0]), 0, C.ggml_nbytes(t.(*Tensor).t))
+	return t, nil
 }
 
 func (c Context) Close() {
diff --git a/model/models/llama/model.go b/model/models/llama/model.go
index 73a23621..9ccfff61 100644
--- a/model/models/llama/model.go
+++ b/model/models/llama/model.go
@@ -138,17 +138,17 @@ func (l *Layer) Forward(ctx ml.Context, hiddenState, positionIDs, outputs ml.Ten
 }
 
 func (m *Model) Forward(ctx ml.Context, opts model.Options) (ml.Tensor, error) {
-	inputs, err := ctx.FromIntSlice(opts.Inputs, len(opts.Inputs))
+	inputs, err := ctx.Input().FromIntSlice(opts.Inputs, len(opts.Inputs))
 	if err != nil {
 		return nil, err
 	}
 
-	positions, err := ctx.FromIntSlice(opts.Positions, len(opts.Positions))
+	positions, err := ctx.Input().FromIntSlice(opts.Positions, len(opts.Positions))
 	if err != nil {
 		return nil, err
 	}
 
-	outputs, err := ctx.FromIntSlice(opts.Outputs, len(opts.Outputs))
+	outputs, err := ctx.Output().FromIntSlice(opts.Outputs, len(opts.Outputs))
 	if err != nil {
 		return nil, err
 	}
diff --git a/model/models/mllama/model.go b/model/models/mllama/model.go
index 945c7295..54c63296 100644
--- a/model/models/mllama/model.go
+++ b/model/models/mllama/model.go
@@ -72,7 +72,7 @@ func (m *Model) EncodeMultimodal(ctx ml.Context, multimodalData []byte) (any, er
 		return nil, err
 	}
 
-	pixelValues, err := ctx.FromFloatSlice(f32s,
+	pixelValues, err := ctx.Input().FromFloatSlice(f32s,
 		m.ImageProcessor.imageSize,
 		m.ImageProcessor.imageSize,
 		m.ImageProcessor.numChannels,
@@ -82,7 +82,7 @@ func (m *Model) EncodeMultimodal(ctx ml.Context, multimodalData []byte) (any, er
 		return nil, err
 	}
 
-	aspectRatio, err := ctx.FromIntSlice([]int32{int32(aspectRatioID)}, 1)
+	aspectRatio, err := ctx.Input().FromIntSlice([]int32{int32(aspectRatioID)}, 1)
 	if err != nil {
 		return nil, err
 	}
@@ -92,7 +92,7 @@ func (m *Model) EncodeMultimodal(ctx ml.Context, multimodalData []byte) (any, er
 		positions[i] = int32(i)
 	}
 
-	positionIDs, err := ctx.FromIntSlice(positions, len(positions))
+	positionIDs, err := ctx.Input().FromIntSlice(positions, len(positions))
 	if err != nil {
 		return nil, err
 	}
@@ -136,17 +136,17 @@ func (m *Model) Forward(ctx ml.Context, opts model.Options) (ml.Tensor, error) {
 		crossAttentionStates = opts.Multimodal[0].Multimodal.(ml.Tensor)
 	}
 
-	inputs, err := ctx.FromIntSlice(opts.Inputs, len(opts.Inputs))
+	inputs, err := ctx.Input().FromIntSlice(opts.Inputs, len(opts.Inputs))
 	if err != nil {
 		return nil, err
 	}
 
-	positions, err := ctx.FromIntSlice(opts.Positions, len(opts.Positions))
+	positions, err := ctx.Input().FromIntSlice(opts.Positions, len(opts.Positions))
 	if err != nil {
 		return nil, err
 	}
 
-	outputs, err := ctx.FromIntSlice(opts.Outputs, len(opts.Outputs))
+	outputs, err := ctx.Output().FromIntSlice(opts.Outputs, len(opts.Outputs))
 	if err != nil {
 		return nil, err
 	}

From 58b9ec1f6b9c85369349e971cb2e17a016ce35dd Mon Sep 17 00:00:00 2001
From: Michael Yang <mxyng@pm.me>
Date: Wed, 26 Feb 2025 12:16:59 -0800
Subject: [PATCH 013/157] kvcache: update tests

---
 kvcache/causal_test.go | 10 +++++++++-
 1 file changed, 9 insertions(+), 1 deletion(-)

diff --git a/kvcache/causal_test.go b/kvcache/causal_test.go
index 84d8de54..412f33e3 100644
--- a/kvcache/causal_test.go
+++ b/kvcache/causal_test.go
@@ -303,6 +303,10 @@ func (b *testBackend) NewContext() ml.Context {
 	return &testContext{}
 }
 
+func (b *testBackend) NewContextSize(int) ml.Context {
+	return &testContext{}
+}
+
 func (b *testBackend) SystemInfo() string {
 	return "not implemented"
 }
@@ -346,11 +350,15 @@ func (c *testContext) FromIntSlice(s []int32, shape ...int) (ml.Tensor, error) {
 	return out, nil
 }
 
+func (c *testContext) Input() ml.Context    { return c }
+func (c *testContext) Output() ml.Context   { return c }
+func (c *testContext) Layer(int) ml.Context { return c }
+
 func (c *testContext) Forward(...ml.Tensor) ml.Context { return c }
 
 func (c *testContext) Compute(...ml.Tensor) {}
 
-func (c *testContext) MaxTensors() int {
+func (c *testContext) MaxGraphNodes() int {
 	return 10
 }
 

From bf920883d54eaeaff174e82e9cc77197bdc7f645 Mon Sep 17 00:00:00 2001
From: Michael Yang <mxyng@pm.me>
Date: Wed, 26 Feb 2025 13:53:56 -0800
Subject: [PATCH 014/157] ml/backend/ggml: set cpu n_threads

---
 ml/backend/ggml/ggml.go | 4 ++++
 1 file changed, 4 insertions(+)

diff --git a/ml/backend/ggml/ggml.go b/ml/backend/ggml/ggml.go
index a55d42f1..f6061945 100644
--- a/ml/backend/ggml/ggml.go
+++ b/ml/backend/ggml/ggml.go
@@ -301,6 +301,10 @@ func New(r *os.File, params ml.BackendParams) (ml.Backend, error) {
 		bufts = append(bufts, bt)
 
 		slog.Info("compute graph", "backend", C.GoString(C.ggml_backend_name(b)), "buffer_type", C.GoString(C.ggml_backend_buft_name(bt)))
+
+		if C.ggml_backend_is_cpu(b) {
+			C.ggml_backend_cpu_set_n_threads(b, C.int(params.NumThreads))
+		}
 	}
 
 	return &Backend{

From 26c2e0bd35feb7f958924269ccfba6331a1dadbc Mon Sep 17 00:00:00 2001
From: Michael Yang <mxyng@pm.me>
Date: Wed, 26 Feb 2025 14:17:08 -0800
Subject: [PATCH 015/157] ml/backend/ggml: handle user specified cpu offloading

---
 ml/backend/ggml/ggml.go | 25 +++++++++++++++----------
 1 file changed, 15 insertions(+), 10 deletions(-)

diff --git a/ml/backend/ggml/ggml.go b/ml/backend/ggml/ggml.go
index f6061945..5c1e55b5 100644
--- a/ml/backend/ggml/ggml.go
+++ b/ml/backend/ggml/ggml.go
@@ -67,7 +67,7 @@ func New(r *os.File, params ml.BackendParams) (ml.Backend, error) {
 		"num_key_values", len(meta.KV()),
 	)
 
-	type dbt struct {
+	type deviceBufferType struct {
 		d   *C.struct_ggml_backend_device
 		bts []*C.struct_ggml_backend_buffer_type
 	}
@@ -96,7 +96,7 @@ func New(r *os.File, params ml.BackendParams) (ml.Backend, error) {
 	var sum uint64
 	var cumsum []uint64
 
-	var gpuBufferTypes []dbt
+	var gpuDeviceBufferTypes []deviceBufferType
 	for _, d := range gpus {
 		var free, total C.size_t
 		C.ggml_backend_dev_memory(d, &free, &total)
@@ -104,7 +104,7 @@ func New(r *os.File, params ml.BackendParams) (ml.Backend, error) {
 		cumsum = append(cumsum, sum)
 
 		bt := C.ggml_backend_dev_buffer_type(d)
-		gpuBufferTypes = append(gpuBufferTypes, dbt{
+		gpuDeviceBufferTypes = append(gpuDeviceBufferTypes, deviceBufferType{
 			d:   d,
 			bts: append([]*C.struct_ggml_backend_buffer_type{bt}, cpuBufferTypes...),
 		})
@@ -115,7 +115,8 @@ func New(r *os.File, params ml.BackendParams) (ml.Backend, error) {
 		splits[i] = float64(cumsum[i]) / float64(sum)
 	}
 
-	input := dbt{C.ggml_backend_dev_by_type(C.GGML_BACKEND_DEVICE_TYPE_CPU), cpuBufferTypes}
+	cpuDeviceBufferTypes := deviceBufferType{C.ggml_backend_dev_by_type(C.GGML_BACKEND_DEVICE_TYPE_CPU), cpuBufferTypes}
+	input := cpuDeviceBufferTypes
 
 	var blocks int
 	for key, value := range meta.KV() {
@@ -124,18 +125,22 @@ func New(r *os.File, params ml.BackendParams) (ml.Backend, error) {
 		}
 	}
 
-	indexFunc := func(i int) func(float64) bool {
-		return func(f float64) bool {
-			return float64(i)/float64(blocks+1) < f
+	assignLayer := func(i int) (temp deviceBufferType) {
+		if i >= params.NumGPULayers {
+			return cpuDeviceBufferTypes
 		}
+
+		return gpuDeviceBufferTypes[slices.IndexFunc(splits, func(f float64) bool {
+			return float64(i)/float64(blocks+1) < f
+		})]
 	}
 
-	layers := make([]dbt, blocks)
+	layers := make([]deviceBufferType, blocks)
 	for i := range layers {
-		layers[i] = gpuBufferTypes[slices.IndexFunc(splits, indexFunc(i))]
+		layers[i] = assignLayer(i)
 	}
 
-	output := gpuBufferTypes[slices.IndexFunc(splits, indexFunc(blocks))]
+	output := assignLayer(blocks)
 
 	maxTensors := len(meta.Tensors().Items())
 	maxTensors += 1

From b5312f30e80f33ad5131aca0c892a54517a1a633 Mon Sep 17 00:00:00 2001
From: Michael Yang <mxyng@pm.me>
Date: Wed, 26 Feb 2025 15:14:16 -0800
Subject: [PATCH 016/157] ml/backend/ggml: handle tensor split

---
 ml/backend/ggml/ggml.go | 45 +++++++++++++++++++++++++++++------------
 1 file changed, 32 insertions(+), 13 deletions(-)

diff --git a/ml/backend/ggml/ggml.go b/ml/backend/ggml/ggml.go
index 5c1e55b5..a597abed 100644
--- a/ml/backend/ggml/ggml.go
+++ b/ml/backend/ggml/ggml.go
@@ -93,16 +93,8 @@ func New(r *os.File, params ml.BackendParams) (ml.Backend, error) {
 		}
 	}
 
-	var sum uint64
-	var cumsum []uint64
-
 	var gpuDeviceBufferTypes []deviceBufferType
 	for _, d := range gpus {
-		var free, total C.size_t
-		C.ggml_backend_dev_memory(d, &free, &total)
-		sum += uint64(free)
-		cumsum = append(cumsum, sum)
-
 		bt := C.ggml_backend_dev_buffer_type(d)
 		gpuDeviceBufferTypes = append(gpuDeviceBufferTypes, deviceBufferType{
 			d:   d,
@@ -110,9 +102,33 @@ func New(r *os.File, params ml.BackendParams) (ml.Backend, error) {
 		})
 	}
 
-	splits := make([]float64, len(cumsum))
+	splits := make([]float32, len(gpus))
+	if func() bool {
+		for _, s := range params.TensorSplit {
+			if s != 0 {
+				return true
+			}
+		}
+
+		return false
+	}() {
+		splits = params.TensorSplit
+	} else {
+		for i := range splits {
+			var free, total C.size_t
+			C.ggml_backend_dev_memory(gpus[i], &free, &total)
+			splits[i] = float32(free)
+		}
+	}
+
+	var sum float32
 	for i := range splits {
-		splits[i] = float64(cumsum[i]) / float64(sum)
+		sum += splits[i]
+		splits[i] = sum
+	}
+
+	for i := range splits {
+		splits[i] /= sum
 	}
 
 	cpuDeviceBufferTypes := deviceBufferType{C.ggml_backend_dev_by_type(C.GGML_BACKEND_DEVICE_TYPE_CPU), cpuBufferTypes}
@@ -130,9 +146,12 @@ func New(r *os.File, params ml.BackendParams) (ml.Backend, error) {
 			return cpuDeviceBufferTypes
 		}
 
-		return gpuDeviceBufferTypes[slices.IndexFunc(splits, func(f float64) bool {
-			return float64(i)/float64(blocks+1) < f
-		})]
+		index := slices.IndexFunc(splits, func(f float32) bool { return float32(i)/float32(blocks+1) < f })
+		if index < 0 || index >= len(gpuDeviceBufferTypes) {
+			return cpuDeviceBufferTypes
+		}
+
+		return gpuDeviceBufferTypes[index]
 	}
 
 	layers := make([]deviceBufferType, blocks)

From 2dc60d4620f216dce463e649812cc59f83ed0f06 Mon Sep 17 00:00:00 2001
From: Michael Yang <mxyng@pm.me>
Date: Thu, 27 Feb 2025 16:46:01 -0800
Subject: [PATCH 017/157] ml/backend/ggml: offload vision to cpu

temporary until tensor loading can accurately account for vision models
---
 ml/backend/ggml/ggml.go | 16 ++++++----------
 1 file changed, 6 insertions(+), 10 deletions(-)

diff --git a/ml/backend/ggml/ggml.go b/ml/backend/ggml/ggml.go
index a597abed..6d902045 100644
--- a/ml/backend/ggml/ggml.go
+++ b/ml/backend/ggml/ggml.go
@@ -134,13 +134,7 @@ func New(r *os.File, params ml.BackendParams) (ml.Backend, error) {
 	cpuDeviceBufferTypes := deviceBufferType{C.ggml_backend_dev_by_type(C.GGML_BACKEND_DEVICE_TYPE_CPU), cpuBufferTypes}
 	input := cpuDeviceBufferTypes
 
-	var blocks int
-	for key, value := range meta.KV() {
-		if strings.HasSuffix(key, ".block_count") {
-			blocks += int(value.(uint32))
-		}
-	}
-
+	blocks := int(meta.KV().BlockCount())
 	assignLayer := func(i int) (temp deviceBufferType) {
 		if i >= params.NumGPULayers {
 			return cpuDeviceBufferTypes
@@ -206,7 +200,7 @@ func New(r *os.File, params ml.BackendParams) (ml.Backend, error) {
 		return nil
 	}
 
-	hasPart := func(s string, parts ...string) bool {
+	contains := func(s string, parts ...string) bool {
 		split := strings.Split(s, ".")
 		for _, part := range parts {
 			if slices.Contains(split, part) {
@@ -219,10 +213,12 @@ func New(r *os.File, params ml.BackendParams) (ml.Backend, error) {
 
 	for _, t := range meta.Tensors().Items() {
 		switch {
-		case hasPart(t.Name, "position_embd", "token_embd", "token_norm_embd", "token_types"):
+		case contains(t.Name, "position_embd", "token_embd", "token_norm_embd", "token_types"):
 			createTensor(tensor{source: t}, input.bts)
-		case hasPart(t.Name, "cls", "output", "output_norm"):
+		case contains(t.Name, "cls", "output", "output_norm"):
 			createTensor(tensor{source: t}, output.bts)
+		case strings.HasPrefix(t.Name, "v.") || strings.HasPrefix(t.Name, "mm."):
+			createTensor(tensor{source: t}, input.bts)
 		default:
 			if i := func() int {
 				if fields := strings.FieldsFunc(t.Name, func(r rune) bool { return !unicode.IsNumber(r) }); len(fields) > 0 {

From daaf42e4a4df43d4ca1d3d39495a4bd20ada0187 Mon Sep 17 00:00:00 2001
From: Michael Yang <mxyng@pm.me>
Date: Fri, 28 Feb 2025 15:42:52 -0800
Subject: [PATCH 018/157] ml/backend/ggml: clean up

---
 ml/backend/ggml/ggml.go | 15 +++++++--------
 1 file changed, 7 insertions(+), 8 deletions(-)

diff --git a/ml/backend/ggml/ggml.go b/ml/backend/ggml/ggml.go
index 6d902045..9cee8216 100644
--- a/ml/backend/ggml/ggml.go
+++ b/ml/backend/ggml/ggml.go
@@ -84,12 +84,12 @@ func New(r *os.File, params ml.BackendParams) (ml.Backend, error) {
 		}
 	}
 
-	var cpuBufferTypes []*C.struct_ggml_backend_buffer_type
+	cpuDeviceBufferType := deviceBufferType{d: C.ggml_backend_dev_by_type(C.GGML_BACKEND_DEVICE_TYPE_CPU)}
 	for _, d := range append(accels, append(gpus, cpus...)...) {
 		switch C.ggml_backend_dev_type(d) {
 		case C.GGML_BACKEND_DEVICE_TYPE_CPU,
 			C.GGML_BACKEND_DEVICE_TYPE_ACCEL:
-			cpuBufferTypes = append(cpuBufferTypes, C.ggml_backend_dev_buffer_type(d))
+			cpuDeviceBufferType.bts = append(cpuDeviceBufferType.bts, C.ggml_backend_dev_buffer_type(d))
 		}
 	}
 
@@ -98,7 +98,7 @@ func New(r *os.File, params ml.BackendParams) (ml.Backend, error) {
 		bt := C.ggml_backend_dev_buffer_type(d)
 		gpuDeviceBufferTypes = append(gpuDeviceBufferTypes, deviceBufferType{
 			d:   d,
-			bts: append([]*C.struct_ggml_backend_buffer_type{bt}, cpuBufferTypes...),
+			bts: append([]*C.struct_ggml_backend_buffer_type{bt}, cpuDeviceBufferType.bts...),
 		})
 	}
 
@@ -131,18 +131,17 @@ func New(r *os.File, params ml.BackendParams) (ml.Backend, error) {
 		splits[i] /= sum
 	}
 
-	cpuDeviceBufferTypes := deviceBufferType{C.ggml_backend_dev_by_type(C.GGML_BACKEND_DEVICE_TYPE_CPU), cpuBufferTypes}
-	input := cpuDeviceBufferTypes
+	input := cpuDeviceBufferType
 
 	blocks := int(meta.KV().BlockCount())
-	assignLayer := func(i int) (temp deviceBufferType) {
+	assignLayer := func(i int) deviceBufferType {
 		if i >= params.NumGPULayers {
-			return cpuDeviceBufferTypes
+			return cpuDeviceBufferType
 		}
 
 		index := slices.IndexFunc(splits, func(f float32) bool { return float32(i)/float32(blocks+1) < f })
 		if index < 0 || index >= len(gpuDeviceBufferTypes) {
-			return cpuDeviceBufferTypes
+			return cpuDeviceBufferType
 		}
 
 		return gpuDeviceBufferTypes[index]

From 45df786f09fec84ff68795845a4b3395cc0def90 Mon Sep 17 00:00:00 2001
From: Michael Yang <mxyng@pm.me>
Date: Tue, 4 Mar 2025 13:06:56 -0800
Subject: [PATCH 019/157] comments

---
 ml/backend/ggml/ggml.go | 212 ++++++++++++++++++++++------------------
 1 file changed, 117 insertions(+), 95 deletions(-)

diff --git a/ml/backend/ggml/ggml.go b/ml/backend/ggml/ggml.go
index 9cee8216..c4adcd98 100644
--- a/ml/backend/ggml/ggml.go
+++ b/ml/backend/ggml/ggml.go
@@ -12,7 +12,6 @@ import (
 	"errors"
 	"fmt"
 	"io"
-	"iter"
 	"log/slog"
 	"maps"
 	"os"
@@ -29,26 +28,34 @@ import (
 	"golang.org/x/sync/errgroup"
 )
 
-func devices() iter.Seq[*C.struct_ggml_backend_device] {
-	return func(yield func(*C.struct_ggml_backend_device) bool) {
-		ggml.OnceLoad()
-		for i := range C.ggml_backend_dev_count() {
-			if !yield(C.ggml_backend_dev_get(i)) {
-				return
-			}
-		}
+func devices() []*C.struct_ggml_backend_device {
+	ggml.OnceLoad()
+	ds := make([]*C.struct_ggml_backend_device, C.ggml_backend_dev_count())
+	for i := range ds {
+		ds[i] = C.ggml_backend_dev_get(C.size_t(i))
 	}
+
+	return ds
 }
 
 type Backend struct {
 	meta    *fs.GGML
 	sched   *C.struct_ggml_backend_sched
 	tensors map[string]*C.struct_ggml_tensor
-	input   *C.struct_ggml_backend
-	output  *C.struct_ggml_backend
-	layers  map[int]*C.struct_ggml_backend
+
+	// input is the backend used for inputs
+	input *C.struct_ggml_backend
+
+	// output is the backend used for outputs
+	output *C.struct_ggml_backend
+
+	// layers is the backend used for repeating layers
+	layers map[int]*C.struct_ggml_backend
 
 	flashAttention bool
+
+	// maxGraphNodes is the maximum allowed number of graph nodes in this scheduler
+	maxGraphNodes int
 }
 
 func New(r *os.File, params ml.BackendParams) (ml.Backend, error) {
@@ -73,7 +80,7 @@ func New(r *os.File, params ml.BackendParams) (ml.Backend, error) {
 	}
 
 	var cpus, accels, gpus []*C.struct_ggml_backend_device
-	for d := range devices() {
+	for _, d := range devices() {
 		switch C.ggml_backend_dev_type(d) {
 		case C.GGML_BACKEND_DEVICE_TYPE_CPU:
 			cpus = append(cpus, d)
@@ -84,6 +91,7 @@ func New(r *os.File, params ml.BackendParams) (ml.Backend, error) {
 		}
 	}
 
+	// create list of buffer types for the cpu
 	cpuDeviceBufferType := deviceBufferType{d: C.ggml_backend_dev_by_type(C.GGML_BACKEND_DEVICE_TYPE_CPU)}
 	for _, d := range append(accels, append(gpus, cpus...)...) {
 		switch C.ggml_backend_dev_type(d) {
@@ -93,6 +101,7 @@ func New(r *os.File, params ml.BackendParams) (ml.Backend, error) {
 		}
 	}
 
+	// create list of buffer types for each gpu
 	var gpuDeviceBufferTypes []deviceBufferType
 	for _, d := range gpus {
 		bt := C.ggml_backend_dev_buffer_type(d)
@@ -102,44 +111,53 @@ func New(r *os.File, params ml.BackendParams) (ml.Backend, error) {
 		})
 	}
 
-	splits := make([]float32, len(gpus))
-	if func() bool {
-		for _, s := range params.TensorSplit {
-			if s != 0 {
-				return true
-			}
+	useDefaultSplit := true
+	for _, s := range params.TensorSplit {
+		if s != 0 {
+			useDefaultSplit = false
+			break
 		}
+	}
 
-		return false
-	}() {
-		splits = params.TensorSplit
-	} else {
+	// calculate splits
+	splits := make([]float32, len(gpus))
+	if useDefaultSplit {
+		// default: split on free memory
 		for i := range splits {
 			var free, total C.size_t
 			C.ggml_backend_dev_memory(gpus[i], &free, &total)
 			splits[i] = float32(free)
 		}
+	} else {
+		splits = params.TensorSplit
 	}
 
 	var sum float32
+	// cumulative sum of all splits
 	for i := range splits {
 		sum += splits[i]
 		splits[i] = sum
 	}
 
+	// normalize splits
 	for i := range splits {
 		splits[i] /= sum
 	}
 
+	// inputs always use cpu
 	input := cpuDeviceBufferType
 
 	blocks := int(meta.KV().BlockCount())
+
+	// define a range of gpu layers. anything outside of this range is assigned to the cpu
+	gpuRangeStart := max(0, blocks-params.NumGPULayers)
+	gpuRangeStop := min(gpuRangeStart+params.NumGPULayers, blocks+1)
 	assignLayer := func(i int) deviceBufferType {
-		if i >= params.NumGPULayers {
+		if i < gpuRangeStart || i >= gpuRangeStop {
 			return cpuDeviceBufferType
 		}
 
-		index := slices.IndexFunc(splits, func(f float32) bool { return float32(i)/float32(blocks+1) < f })
+		index := slices.IndexFunc(splits, func(f float32) bool { return float32(i-gpuRangeStart)/float32(gpuRangeStop-gpuRangeStart) < f })
 		if index < 0 || index >= len(gpuDeviceBufferTypes) {
 			return cpuDeviceBufferType
 		}
@@ -147,15 +165,18 @@ func New(r *os.File, params ml.BackendParams) (ml.Backend, error) {
 		return gpuDeviceBufferTypes[index]
 	}
 
+	// repeating layers are assigned based on their index in reverse order, e.g. i / (block_count + 1)
 	layers := make([]deviceBufferType, blocks)
 	for i := range layers {
 		layers[i] = assignLayer(i)
 	}
 
+	// outputs are assigned iff allowed by splits and configured number of gpu layers
 	output := assignLayer(blocks)
 
 	maxTensors := len(meta.Tensors().Items())
 	maxTensors += 1
+	// each layer has at most 2 extra tensors for rope operations
 	maxTensors += blocks * 2
 
 	type tensor struct {
@@ -163,8 +184,10 @@ func New(r *os.File, params ml.BackendParams) (ml.Backend, error) {
 		target string
 	}
 
+	// some tensors are mapped to different names so keep a list
 	targets := make(map[string][]string)
 
+	// contexts are shared by tensors of the same buffer type
 	ctxs := make(map[*C.struct_ggml_backend_buffer_type]*C.struct_ggml_context)
 	createTensor := func(t tensor, bts []*C.struct_ggml_backend_buffer_type) *C.struct_ggml_tensor {
 		for _, bt := range bts {
@@ -217,19 +240,21 @@ func New(r *os.File, params ml.BackendParams) (ml.Backend, error) {
 		case contains(t.Name, "cls", "output", "output_norm"):
 			createTensor(tensor{source: t}, output.bts)
 		case strings.HasPrefix(t.Name, "v.") || strings.HasPrefix(t.Name, "mm."):
+			// TODO: assign vision tensors to the gpu if possible
 			createTensor(tensor{source: t}, input.bts)
 		default:
-			if i := func() int {
-				if fields := strings.FieldsFunc(t.Name, func(r rune) bool { return !unicode.IsNumber(r) }); len(fields) > 0 {
-					if i, err := strconv.Atoi(fields[0]); err == nil {
-						return i
-					}
+			layerIndex := -1
+			if fields := strings.FieldsFunc(t.Name, func(r rune) bool { return !unicode.IsNumber(r) }); len(fields) > 0 {
+				if i, err := strconv.Atoi(fields[0]); err == nil {
+					layerIndex = i
 				}
+			}
 
-				return -1
-			}(); i >= 0 {
-				createTensor(tensor{source: t}, layers[i].bts)
+			if layerIndex >= 0 {
+				createTensor(tensor{source: t}, layers[layerIndex].bts)
 			} else {
+				// this is a repeating tensor that doesn't explicitly associated with a layer so
+				// duplicate it for each layer
 				for i, layer := range layers {
 					createTensor(tensor{
 						source: t,
@@ -240,8 +265,8 @@ func New(r *os.File, params ml.BackendParams) (ml.Backend, error) {
 		}
 	}
 
-	bbs := make(map[*C.struct_ggml_context][]*C.struct_ggml_backend_buffer, len(ctxs))
-
+	// allocate buffers for each context
+	bbs := make(map[*C.struct_ggml_context]*C.struct_ggml_backend_buffer, len(ctxs))
 	for bt, c := range ctxs {
 		if C.ggml_get_first_tensor(c) == nil {
 			continue
@@ -249,15 +274,14 @@ func New(r *os.File, params ml.BackendParams) (ml.Backend, error) {
 
 		b := C.ggml_backend_alloc_ctx_tensors_from_buft(c, bt)
 		C.ggml_backend_buffer_set_usage(b, C.GGML_BACKEND_BUFFER_USAGE_WEIGHTS)
-		bbs[c] = append(bbs[c], b)
+		bbs[c] = b
 	}
 
 	for bs := range maps.Values(bbs) {
-		for _, b := range bs {
-			slog.Info("model weights", "buffer", C.GoString(C.ggml_backend_buffer_name(b)), "size", format.HumanBytes2(uint64(C.ggml_backend_buffer_get_size(b))))
-		}
+		slog.Info("model weights", "buffer", C.GoString(C.ggml_backend_buffer_name(bs)), "size", format.HumanBytes2(uint64(C.ggml_backend_buffer_get_size(bs))))
 	}
 
+	// map tensor names to tensors for easy lookup later
 	tensors := make(map[string]*C.struct_ggml_tensor)
 	for _, c := range ctxs {
 		for t := C.ggml_get_first_tensor(c); t != nil; t = C.ggml_get_next_tensor(c, t) {
@@ -265,6 +289,7 @@ func New(r *os.File, params ml.BackendParams) (ml.Backend, error) {
 		}
 	}
 
+	// concurrently read in tensor data. uses a section reader which is safe for concurrent reads
 	sr := io.NewSectionReader(r, int64(meta.Tensors().Offset), n-int64(meta.Tensors().Offset))
 	var g errgroup.Group
 	for _, t := range meta.Tensors().Items() {
@@ -289,10 +314,7 @@ func New(r *os.File, params ml.BackendParams) (ml.Backend, error) {
 					return errors.New("short read")
 				}
 
-				cname := C.CString(t.Name)
 				C.ggml_backend_tensor_set(tt, unsafe.Pointer(&bts[0]), 0, C.size_t(t.Size()))
-				C.free(unsafe.Pointer(cname))
-
 				return nil
 			})
 		}
@@ -302,39 +324,45 @@ func New(r *os.File, params ml.BackendParams) (ml.Backend, error) {
 		return nil, err
 	}
 
+	// map devices to backends so tensors created post initialization can be assigned to the correct device
 	deviceBackends := make(map[*C.struct_ggml_backend_device]*C.struct_ggml_backend)
-	var backends []*C.struct_ggml_backend
-	var bufts []*C.struct_ggml_backend_buffer_type
+
+	// create backends and buffer types used for the compute graph scheduler
+	var schedBackends []*C.struct_ggml_backend
+	var schedBufts []*C.struct_ggml_backend_buffer_type
 	for _, d := range append(gpus, append(accels, cpus...)...) {
 		b := C.ggml_backend_dev_init(d, nil)
-		backends = append(backends, b)
+		schedBackends = append(schedBackends, b)
 		deviceBackends[d] = b
 
 		bt := C.ggml_backend_get_default_buffer_type(b)
+		// use the first gpu host buffer type for gpu if possible
 		if d := C.ggml_backend_get_device(b); C.ggml_backend_dev_type(d) == C.GGML_BACKEND_DEVICE_TYPE_CPU && len(gpus) > 0 {
 			if hbt := C.ggml_backend_dev_host_buffer_type(d); hbt != nil {
 				bt = hbt
 			}
 		}
 
-		bufts = append(bufts, bt)
+		schedBufts = append(schedBufts, bt)
 
 		slog.Info("compute graph", "backend", C.GoString(C.ggml_backend_name(b)), "buffer_type", C.GoString(C.ggml_backend_buft_name(bt)))
 
 		if C.ggml_backend_is_cpu(b) {
+			// set number of threads for cpu backend
 			C.ggml_backend_cpu_set_n_threads(b, C.int(params.NumThreads))
 		}
 	}
 
+	maxGraphNodes := max(8192, len(meta.Tensors().Items())*5)
 	return &Backend{
 		flashAttention: params.FlashAttention,
 		meta:           meta,
 		tensors:        tensors,
 		sched: C.ggml_backend_sched_new(
-			(*C.ggml_backend_t)(unsafe.Pointer(&backends[0])),
-			(*C.ggml_backend_buffer_type_t)(unsafe.Pointer(&bufts[0])),
-			C.int(len(backends)),
-			C.size_t(max(8192, len(meta.Tensors().Items())*5)),
+			(*C.ggml_backend_t)(unsafe.Pointer(&schedBackends[0])),
+			(*C.ggml_backend_buffer_type_t)(unsafe.Pointer(&schedBufts[0])),
+			C.int(len(schedBackends)),
+			C.size_t(maxGraphNodes),
 			true,
 		),
 		input:  deviceBackends[input.d],
@@ -346,6 +374,7 @@ func New(r *os.File, params ml.BackendParams) (ml.Backend, error) {
 			}
 			return m
 		}(),
+		maxGraphNodes: maxGraphNodes,
 	}, nil
 }
 
@@ -366,10 +395,11 @@ func (b *Backend) Get(name string) ml.Tensor {
 }
 
 func (b *Backend) NewContext() ml.Context {
-	return b.NewContextSize(max(8192, len(b.meta.Tensors().Items())*5))
+	return b.NewContextSize(b.maxGraphNodes)
 }
 
 func (b *Backend) NewContextSize(n int) ml.Context {
+	n = min(n, b.maxGraphNodes)
 	return &Context{
 		b: b,
 		ctx: C.ggml_init(C.struct_ggml_init_params{
@@ -378,9 +408,6 @@ func (b *Backend) NewContextSize(n int) ml.Context {
 		}),
 		backend:       C.ggml_backend_sched_get_backend(b.sched, 0),
 		maxGraphNodes: n,
-		input:         b.input,
-		output:        b.output,
-		layers:        b.layers,
 	}
 }
 
@@ -401,46 +428,38 @@ type Context struct {
 	// backend is the backend used for new tensors
 	backend *C.struct_ggml_backend
 
-	// input is the backend used for inputs
-	input *C.struct_ggml_backend
-
-	// output is the backend used for outputs
-	output *C.struct_ggml_backend
-
-	// output is the backend used for repeating layers
-	layers map[int]*C.struct_ggml_backend
-
+	// maxGraphNodes is the maximum allowed number of graph nodes in this context
 	maxGraphNodes int
 }
 
-func (c *Context) Input() ml.Context {
-	if c.input != nil {
+func (c Context) Input() ml.Context {
+	if c.b.input != nil {
 		return &Context{
 			b:             c.b,
 			ctx:           c.ctx,
-			backend:       c.input,
+			backend:       c.b.input,
 			maxGraphNodes: c.maxGraphNodes,
 		}
 	}
 
-	return c
+	return &c
 }
 
-func (c *Context) Output() ml.Context {
-	if c.output != nil {
+func (c Context) Output() ml.Context {
+	if c.b.output != nil {
 		return &Context{
 			b:             c.b,
 			ctx:           c.ctx,
-			backend:       c.output,
+			backend:       c.b.output,
 			maxGraphNodes: c.maxGraphNodes,
 		}
 	}
 
-	return c
+	return &c
 }
 
-func (c *Context) Layer(i int) ml.Context {
-	if backend, ok := c.layers[i]; ok {
+func (c Context) Layer(i int) ml.Context {
+	if backend, ok := c.b.layers[i]; ok {
 		return &Context{
 			b:             c.b,
 			ctx:           c.ctx,
@@ -449,7 +468,7 @@ func (c *Context) Layer(i int) ml.Context {
 		}
 	}
 
-	return c
+	return &c
 }
 
 func (c *Context) Forward(tensors ...ml.Tensor) ml.Context {
@@ -464,10 +483,9 @@ func (c *Context) Forward(tensors ...ml.Tensor) ml.Context {
 	return c
 }
 
-func (c *Context) Compute(tensors ...ml.Tensor) {
-	C.ggml_backend_sched_reset(c.b.sched)
-	C.ggml_backend_sched_alloc_graph(c.b.sched, c.graph)
+func (c Context) Compute(tensors ...ml.Tensor) {
 	C.ggml_backend_sched_graph_compute_async(c.b.sched, c.graph)
+	C.ggml_backend_sched_reset(c.b.sched)
 
 	needSync := true
 	sync := func() {
@@ -484,7 +502,7 @@ func (c *Context) Compute(tensors ...ml.Tensor) {
 	}
 }
 
-func (c *Context) MaxGraphNodes() int {
+func (c Context) MaxGraphNodes() int {
 	return c.maxGraphNodes
 }
 
@@ -498,7 +516,22 @@ func shapeToGGML(shape []int) *C.int64_t {
 }
 
 func (c Context) newTensor(dtype ml.DType, shape []int) ml.Tensor {
-	if len(shape) < 1 || len(shape) > 4 {
+	var cdtype uint32
+	switch dtype {
+	case ml.DTypeF32:
+		cdtype = C.GGML_TYPE_F32
+	case ml.DTypeF16:
+		cdtype = C.GGML_TYPE_F16
+	case ml.DTypeI32:
+		cdtype = C.GGML_TYPE_I32
+	default:
+		panic("unsupported dtype")
+	}
+
+	if len(shape) < 1 {
+		var shape C.int64_t = 0
+		return &Tensor{b: c.b, t: C.ggml_new_tensor(c.ctx, cdtype, 1, &shape)}
+	} else if len(shape) > 4 {
 		panic("unsupported number of dimensions")
 	}
 
@@ -508,18 +541,7 @@ func (c Context) newTensor(dtype ml.DType, shape []int) ml.Tensor {
 		}
 	}
 
-	var t *C.struct_ggml_tensor
-	switch dtype {
-	case ml.DTypeF32:
-		t = C.ggml_new_tensor(c.ctx, C.GGML_TYPE_F32, C.int(len(shape)), shapeToGGML(shape))
-	case ml.DTypeF16:
-		t = C.ggml_new_tensor(c.ctx, C.GGML_TYPE_F16, C.int(len(shape)), shapeToGGML(shape))
-	case ml.DTypeI32:
-		t = C.ggml_new_tensor(c.ctx, C.GGML_TYPE_I32, C.int(len(shape)), shapeToGGML(shape))
-	default:
-		panic("unsupported dtype")
-	}
-
+	t := C.ggml_new_tensor(c.ctx, cdtype, C.int(len(shape)), shapeToGGML(shape))
 	b := C.ggml_backend_alloc_buffer(c.backend, C.ggml_nbytes(t))
 	C.ggml_backend_tensor_alloc(b, t, C.ggml_backend_buffer_get_base(b))
 	return &Tensor{b: c.b, t: t}
@@ -549,7 +571,7 @@ func checkShape[S ~[]E, E any](s S, shape ...int) error {
 }
 
 func (c Context) FromFloatSlice(s []float32, shape ...int) (ml.Tensor, error) {
-	if err := checkShape(s, shape...); err != nil {
+	if err := checkShape(s, shape...); err != nil && len(shape) > 0 {
 		return nil, err
 	}
 
@@ -559,7 +581,7 @@ func (c Context) FromFloatSlice(s []float32, shape ...int) (ml.Tensor, error) {
 }
 
 func (c Context) FromIntSlice(s []int32, shape ...int) (ml.Tensor, error) {
-	if err := checkShape(s, shape...); err != nil {
+	if err := checkShape(s, shape...); err != nil && len(shape) > 0 {
 		return nil, err
 	}
 
@@ -568,8 +590,8 @@ func (c Context) FromIntSlice(s []int32, shape ...int) (ml.Tensor, error) {
 	return t, nil
 }
 
-func (c Context) Close() {
-	if c.ctx != nil {
+func (c *Context) Close() {
+	if c != nil {
 		C.ggml_free(c.ctx)
 	}
 }

From b27e8f3f10ff6a95dee7e43215350fa0da2bb691 Mon Sep 17 00:00:00 2001
From: Michael Yang <mxyng@pm.me>
Date: Wed, 5 Mar 2025 14:48:27 -0800
Subject: [PATCH 020/157] ml/backend/ggml: use backend buffer type

this ensures the tensor is created on the right buffer type for backends
such as cpu
---
 ml/backend/ggml/ggml.go | 58 +++++++++++++++++++++++------------------
 1 file changed, 32 insertions(+), 26 deletions(-)

diff --git a/ml/backend/ggml/ggml.go b/ml/backend/ggml/ggml.go
index c4adcd98..af5dbf99 100644
--- a/ml/backend/ggml/ggml.go
+++ b/ml/backend/ggml/ggml.go
@@ -44,13 +44,13 @@ type Backend struct {
 	tensors map[string]*C.struct_ggml_tensor
 
 	// input is the backend used for inputs
-	input *C.struct_ggml_backend
+	input *C.struct_ggml_backend_buffer_type
 
 	// output is the backend used for outputs
-	output *C.struct_ggml_backend
+	output *C.struct_ggml_backend_buffer_type
 
 	// layers is the backend used for repeating layers
-	layers map[int]*C.struct_ggml_backend
+	layers map[int]*C.struct_ggml_backend_buffer_type
 
 	flashAttention bool
 
@@ -83,7 +83,10 @@ func New(r *os.File, params ml.BackendParams) (ml.Backend, error) {
 	for _, d := range devices() {
 		switch C.ggml_backend_dev_type(d) {
 		case C.GGML_BACKEND_DEVICE_TYPE_CPU:
-			cpus = append(cpus, d)
+			if len(cpus) == 0 {
+				// only the first cpu device should be used
+				cpus = append(cpus, d)
+			}
 		case C.GGML_BACKEND_DEVICE_TYPE_ACCEL:
 			accels = append(accels, d)
 		case C.GGML_BACKEND_DEVICE_TYPE_GPU:
@@ -324,25 +327,25 @@ func New(r *os.File, params ml.BackendParams) (ml.Backend, error) {
 		return nil, err
 	}
 
-	// map devices to backends so tensors created post initialization can be assigned to the correct device
-	deviceBackends := make(map[*C.struct_ggml_backend_device]*C.struct_ggml_backend)
+	// map devices to backend buffer types so new tensors can be assigned to the correct device
+	deviceBufferTypes := make(map[*C.struct_ggml_backend_device]*C.struct_ggml_backend_buffer_type)
 
 	// create backends and buffer types used for the compute graph scheduler
 	var schedBackends []*C.struct_ggml_backend
 	var schedBufts []*C.struct_ggml_backend_buffer_type
 	for _, d := range append(gpus, append(accels, cpus...)...) {
 		b := C.ggml_backend_dev_init(d, nil)
-		schedBackends = append(schedBackends, b)
-		deviceBackends[d] = b
-
 		bt := C.ggml_backend_get_default_buffer_type(b)
-		// use the first gpu host buffer type for gpu if possible
 		if d := C.ggml_backend_get_device(b); C.ggml_backend_dev_type(d) == C.GGML_BACKEND_DEVICE_TYPE_CPU && len(gpus) > 0 {
-			if hbt := C.ggml_backend_dev_host_buffer_type(d); hbt != nil {
+			// use the first gpu host buffer type for gpu if possible
+			if hbt := C.ggml_backend_dev_host_buffer_type(gpus[0]); hbt != nil {
 				bt = hbt
 			}
 		}
 
+		deviceBufferTypes[d] = bt
+
+		schedBackends = append(schedBackends, b)
 		schedBufts = append(schedBufts, bt)
 
 		slog.Info("compute graph", "backend", C.GoString(C.ggml_backend_name(b)), "buffer_type", C.GoString(C.ggml_backend_buft_name(bt)))
@@ -365,12 +368,12 @@ func New(r *os.File, params ml.BackendParams) (ml.Backend, error) {
 			C.size_t(maxGraphNodes),
 			true,
 		),
-		input:  deviceBackends[input.d],
-		output: deviceBackends[output.d],
-		layers: func() map[int]*C.struct_ggml_backend {
-			m := make(map[int]*C.struct_ggml_backend)
+		input:  deviceBufferTypes[input.d],
+		output: deviceBufferTypes[output.d],
+		layers: func() map[int]*C.struct_ggml_backend_buffer_type {
+			m := make(map[int]*C.struct_ggml_backend_buffer_type)
 			for i, layer := range layers {
-				m[i] = deviceBackends[layer.d]
+				m[i] = deviceBufferTypes[layer.d]
 			}
 			return m
 		}(),
@@ -401,13 +404,12 @@ func (b *Backend) NewContext() ml.Context {
 func (b *Backend) NewContextSize(n int) ml.Context {
 	n = min(n, b.maxGraphNodes)
 	return &Context{
-		b: b,
+		b:             b,
+		maxGraphNodes: n,
 		ctx: C.ggml_init(C.struct_ggml_init_params{
 			mem_size: C.size_t(n)*C.ggml_tensor_overhead() + C.ggml_graph_overhead_custom(C.size_t(n), false),
 			no_alloc: true,
 		}),
-		backend:       C.ggml_backend_sched_get_backend(b.sched, 0),
-		maxGraphNodes: n,
 	}
 }
 
@@ -425,8 +427,8 @@ type Context struct {
 	ctx   *C.struct_ggml_context
 	graph *C.struct_ggml_cgraph
 
-	// backend is the backend used for new tensors
-	backend *C.struct_ggml_backend
+	// buft is the buffer type used for new tensors
+	buft *C.struct_ggml_backend_buffer_type
 
 	// maxGraphNodes is the maximum allowed number of graph nodes in this context
 	maxGraphNodes int
@@ -437,7 +439,7 @@ func (c Context) Input() ml.Context {
 		return &Context{
 			b:             c.b,
 			ctx:           c.ctx,
-			backend:       c.b.input,
+			buft:          c.b.input,
 			maxGraphNodes: c.maxGraphNodes,
 		}
 	}
@@ -450,7 +452,7 @@ func (c Context) Output() ml.Context {
 		return &Context{
 			b:             c.b,
 			ctx:           c.ctx,
-			backend:       c.b.output,
+			buft:          c.b.output,
 			maxGraphNodes: c.maxGraphNodes,
 		}
 	}
@@ -459,11 +461,11 @@ func (c Context) Output() ml.Context {
 }
 
 func (c Context) Layer(i int) ml.Context {
-	if backend, ok := c.b.layers[i]; ok {
+	if buft, ok := c.b.layers[i]; ok {
 		return &Context{
 			b:             c.b,
 			ctx:           c.ctx,
-			backend:       backend,
+			buft:          buft,
 			maxGraphNodes: c.maxGraphNodes,
 		}
 	}
@@ -516,6 +518,10 @@ func shapeToGGML(shape []int) *C.int64_t {
 }
 
 func (c Context) newTensor(dtype ml.DType, shape []int) ml.Tensor {
+	if c.buft == nil {
+		panic("set Input, Output, or Layer before creating tensors")
+	}
+
 	var cdtype uint32
 	switch dtype {
 	case ml.DTypeF32:
@@ -542,7 +548,7 @@ func (c Context) newTensor(dtype ml.DType, shape []int) ml.Tensor {
 	}
 
 	t := C.ggml_new_tensor(c.ctx, cdtype, C.int(len(shape)), shapeToGGML(shape))
-	b := C.ggml_backend_alloc_buffer(c.backend, C.ggml_nbytes(t))
+	b := C.ggml_backend_buft_alloc_buffer(c.buft, C.ggml_nbytes(t))
 	C.ggml_backend_tensor_alloc(b, t, C.ggml_backend_buffer_get_base(b))
 	return &Tensor{b: c.b, t: t}
 }

From 98272fbd58699366de72b5111d4f8fa79d9f71a4 Mon Sep 17 00:00:00 2001
From: Jesse Gross <jesse@ollama.com>
Date: Fri, 7 Mar 2025 11:19:03 -0800
Subject: [PATCH 021/157] additional review comments

---
 ml/backend/ggml/ggml.go           | 26 ++++++++++++++++++++------
 model/models/mllama/model_text.go | 22 ++++++++++++----------
 2 files changed, 32 insertions(+), 16 deletions(-)

diff --git a/ml/backend/ggml/ggml.go b/ml/backend/ggml/ggml.go
index af5dbf99..00873b4f 100644
--- a/ml/backend/ggml/ggml.go
+++ b/ml/backend/ggml/ggml.go
@@ -402,7 +402,10 @@ func (b *Backend) NewContext() ml.Context {
 }
 
 func (b *Backend) NewContextSize(n int) ml.Context {
-	n = min(n, b.maxGraphNodes)
+	if n > b.maxGraphNodes {
+		panic(fmt.Errorf("requested number of graph nodes (%v) for new context exceeds maximum (%v)", n, b.maxGraphNodes))
+	}
+
 	return &Context{
 		b:             b,
 		maxGraphNodes: n,
@@ -534,7 +537,7 @@ func (c Context) newTensor(dtype ml.DType, shape []int) ml.Tensor {
 		panic("unsupported dtype")
 	}
 
-	if len(shape) < 1 {
+	if len(shape) < 1 || shape[0] == 0 {
 		var shape C.int64_t = 0
 		return &Tensor{b: c.b, t: C.ggml_new_tensor(c.ctx, cdtype, 1, &shape)}
 	} else if len(shape) > 4 {
@@ -565,6 +568,11 @@ func (c Context) Zeros(dtype ml.DType, shape ...int) ml.Tensor {
 
 func checkShape[S ~[]E, E any](s S, shape ...int) error {
 	n := len(s)
+
+	if n == 0 {
+		return nil
+	}
+
 	for _, v := range shape {
 		n /= v
 	}
@@ -577,22 +585,28 @@ func checkShape[S ~[]E, E any](s S, shape ...int) error {
 }
 
 func (c Context) FromFloatSlice(s []float32, shape ...int) (ml.Tensor, error) {
-	if err := checkShape(s, shape...); err != nil && len(shape) > 0 {
+	if err := checkShape(s, shape...); err != nil {
 		return nil, err
 	}
 
 	t := c.newTensor(ml.DTypeF32, shape)
-	C.ggml_backend_tensor_set(t.(*Tensor).t, unsafe.Pointer(&s[0]), 0, C.ggml_nbytes(t.(*Tensor).t))
+	if len(s) > 0 {
+		C.ggml_backend_tensor_set(t.(*Tensor).t, unsafe.Pointer(&s[0]), 0, C.ggml_nbytes(t.(*Tensor).t))
+	}
+
 	return t, nil
 }
 
 func (c Context) FromIntSlice(s []int32, shape ...int) (ml.Tensor, error) {
-	if err := checkShape(s, shape...); err != nil && len(shape) > 0 {
+	if err := checkShape(s, shape...); err != nil {
 		return nil, err
 	}
 
 	t := c.newTensor(ml.DTypeI32, shape)
-	C.ggml_backend_tensor_set(t.(*Tensor).t, unsafe.Pointer(&s[0]), 0, C.ggml_nbytes(t.(*Tensor).t))
+	if len(s) > 0 {
+		C.ggml_backend_tensor_set(t.(*Tensor).t, unsafe.Pointer(&s[0]), 0, C.ggml_nbytes(t.(*Tensor).t))
+	}
+
 	return t, nil
 }
 
diff --git a/model/models/mllama/model_text.go b/model/models/mllama/model_text.go
index e294b4c7..373589f9 100644
--- a/model/models/mllama/model_text.go
+++ b/model/models/mllama/model_text.go
@@ -10,10 +10,11 @@ import (
 )
 
 type TextSelfAttention struct {
-	Query  *nn.Linear `gguf:"attn_q"`
-	Key    *nn.Linear `gguf:"attn_k"`
-	Value  *nn.Linear `gguf:"attn_v"`
-	Output *nn.Linear `gguf:"attn_output"`
+	Query       *nn.Linear `gguf:"attn_q"`
+	Key         *nn.Linear `gguf:"attn_k"`
+	Value       *nn.Linear `gguf:"attn_v"`
+	Output      *nn.Linear `gguf:"attn_output"`
+	RopeFactors ml.Tensor  `gguf:"rope_freqs.weight"`
 }
 
 func (sa *TextSelfAttention) Forward(ctx ml.Context, hiddenState, positions, _ ml.Tensor, cache *kvcache.WrapperCache, opts *TextModelOptions) ml.Tensor {
@@ -22,11 +23,11 @@ func (sa *TextSelfAttention) Forward(ctx ml.Context, hiddenState, positions, _ m
 
 	query := sa.Query.Forward(ctx, hiddenState)
 	query = query.Reshape(ctx, headDim, opts.numHeads, batchSize)
-	query = query.RoPE(ctx, positions, opts.RopeFactors, opts.ropeDim, opts.ropeBase, opts.ropeScale)
+	query = query.RoPE(ctx, positions, sa.RopeFactors, opts.ropeDim, opts.ropeBase, opts.ropeScale)
 
 	key := sa.Key.Forward(ctx, hiddenState)
 	key = key.Reshape(ctx, headDim, opts.numKVHeads, batchSize)
-	key = key.RoPE(ctx, positions, opts.RopeFactors, opts.ropeDim, opts.ropeBase, opts.ropeScale)
+	key = key.RoPE(ctx, positions, sa.RopeFactors, opts.ropeDim, opts.ropeBase, opts.ropeScale)
 
 	value := sa.Value.Forward(ctx, hiddenState)
 	value = value.Reshape(ctx, headDim, opts.numKVHeads, batchSize)
@@ -39,8 +40,11 @@ func (sa *TextSelfAttention) Forward(ctx ml.Context, hiddenState, positions, _ m
 }
 
 func (m *TextModel) Shift(ctx ml.Context, layer int, key, shift ml.Tensor) (ml.Tensor, error) {
-	// This will only get called for layers in the causal cache, which are just the self attention layers
-	return key.RoPE(ctx, shift, m.RopeFactors, m.ropeDim, m.ropeBase, m.ropeScale), nil
+	if sa, ok := m.Transformer.Layers[layer].(*TextSelfAttentionDecoderLayer); ok {
+		return key.RoPE(ctx, shift, sa.SelfAttention.RopeFactors, m.ropeDim, m.ropeBase, m.ropeScale), nil
+	}
+
+	return key, nil
 }
 
 type TextMLP struct {
@@ -191,8 +195,6 @@ func (d *TextDecoder) Forward(ctx ml.Context, hiddenState, positionIDs, outputs,
 }
 
 type TextModelOptions struct {
-	RopeFactors ml.Tensor `gguf:"rope_freqs.weight"`
-
 	hiddenSize, numHeads, numKVHeads int
 	eps, ropeBase, ropeScale         float32
 	ropeDim                          uint32

From 0daaaef8c99d94853eb12e897b2c15e0743a2575 Mon Sep 17 00:00:00 2001
From: Jesse Gross <jesse@ollama.com>
Date: Fri, 7 Mar 2025 15:14:22 -0800
Subject: [PATCH 022/157] ollamarunner: Quiet debug logging and panic on
 unimplemented features

Debug logging of every token has previously caused test timeouts
on slower machines.
---
 model/process_text.go         |  4 ----
 runner/ollamarunner/runner.go | 10 ++++++++--
 2 files changed, 8 insertions(+), 6 deletions(-)

diff --git a/model/process_text.go b/model/process_text.go
index bfb0a5f2..0d75a0ed 100644
--- a/model/process_text.go
+++ b/model/process_text.go
@@ -177,7 +177,6 @@ func (bpe BytePairEncoding) Encode(s string, addSpecial bool) ([]int32, error) {
 	for _, frag := range fragments {
 		if len(frag.ids) > 0 {
 			ids = append(ids, frag.ids...)
-			slog.Debug("encoded", "text", frag.value, "ids", frag.ids, "special", true)
 			continue
 		}
 
@@ -201,7 +200,6 @@ func (bpe BytePairEncoding) Encode(s string, addSpecial bool) ([]int32, error) {
 			// short circuit if the fragment is in the vocabulary
 			if id := bpe.vocab.Encode(sb.String()); id >= 0 {
 				ids = append(ids, id)
-				slog.Debug("encoded", "text", sb.String(), "ids", []int32{id})
 				continue
 			}
 
@@ -275,7 +273,6 @@ func (bpe BytePairEncoding) Encode(s string, addSpecial bool) ([]int32, error) {
 					// TODO: handle the edge case where the rune isn't in the vocabulary
 					if id := bpe.vocab.Encode(string(merge.runes)); id >= 0 {
 						ids = append(ids, id)
-						slog.Debug("encoded", "text", string(merge.runes), "ids", []int32{id})
 					}
 				}
 			}
@@ -329,6 +326,5 @@ func (bpe BytePairEncoding) Decode(ids []int32) (string, error) {
 		}
 	}
 
-	slog.Debug("decoded", "ids", ids, "text", sb.String())
 	return sb.String(), nil
 }
diff --git a/runner/ollamarunner/runner.go b/runner/ollamarunner/runner.go
index 81e06562..d9f47970 100644
--- a/runner/ollamarunner/runner.go
+++ b/runner/ollamarunner/runner.go
@@ -436,8 +436,10 @@ func (s *Server) processBatch() error {
 		// if done processing the prompt, generate an embedding and return
 		if seq.embeddingOnly {
 			// TODO(jessegross): Embedding support
-			s.removeSequence(i, "")
-			continue
+			// s.removeSequence(i, "")
+			// continue
+
+			panic("generation of embedding outputs not yet supported")
 		}
 
 		// sample a token
@@ -597,6 +599,10 @@ func (s *Server) completion(w http.ResponseWriter, r *http.Request) {
 		req.Seed,
 	)
 
+	if req.Grammar != "" {
+		panic("grammars are not yet supported")
+	}
+
 	seq, err := s.NewSequence(req.Prompt, req.Images, NewSequenceParams{
 		numPredict: req.NumPredict,
 		stop:       req.Stop,

From 6da8b6a87902c8cf875028329ade512c8d859059 Mon Sep 17 00:00:00 2001
From: Jesse Gross <jesse@ollama.com>
Date: Fri, 7 Mar 2025 14:20:31 -0800
Subject: [PATCH 023/157] kvcache: Support non-causal attention

Models can disable causality for all or part of their processing
while continuing to store data in the KV cache.
---
 kvcache/causal.go | 40 ++++++++++++++++++++++++++++++++++++----
 1 file changed, 36 insertions(+), 4 deletions(-)

diff --git a/kvcache/causal.go b/kvcache/causal.go
index 3d1c71db..d519cf60 100644
--- a/kvcache/causal.go
+++ b/kvcache/causal.go
@@ -20,6 +20,7 @@ type shiftFn func(ctx ml.Context, layer int, key, shift ml.Tensor) (ml.Tensor, e
 type Causal struct {
 	DType      ml.DType
 	Capacity   int32
+	causal     bool
 	windowSize int32
 
 	// config controls mostly backend-specific optimizations
@@ -42,6 +43,12 @@ type Causal struct {
 	// locations in the cache that are needed for this batch
 	curCellRange cellRange
 
+	// curSequences is the sequences corresponding to this pass's entries in the cache
+	curSequences []int
+
+	// curPositions is the positions corresponding to this pass's entries in the cache
+	curPositions []int32
+
 	// ** cache metadata **
 
 	// for each possible location in the cache, stores the position and set of sequences
@@ -71,6 +78,7 @@ type cellRange struct {
 
 func NewCausalCache(shift shiftFn) *Causal {
 	return &Causal{
+		causal:     true,
 		windowSize: math.MaxInt32,
 		shiftFn:    shift,
 		ctxs:       make(map[int]ml.Context),
@@ -81,6 +89,7 @@ func NewCausalCache(shift shiftFn) *Causal {
 
 func NewSWACache(windowSize int32, shift shiftFn) *Causal {
 	return &Causal{
+		causal:     true,
 		windowSize: windowSize,
 		shiftFn:    shift,
 		ctxs:       make(map[int]ml.Context),
@@ -133,6 +142,8 @@ func (c *Causal) Close() {
 
 func (c *Causal) StartForward(ctx ml.Context, positions []int32, seqs []int) error {
 	c.curBatchSize = len(positions)
+	c.curSequences = seqs
+	c.curPositions = positions
 
 	var err error
 	c.curLoc, err = c.findStartLoc()
@@ -171,7 +182,7 @@ func (c *Causal) StartForward(ctx ml.Context, positions []int32, seqs []int) err
 		c.cellRanges[seq] = seqRange
 	}
 
-	c.curMask, err = c.buildMask(ctx, positions, seqs)
+	c.curMask, err = c.buildMask(ctx)
 
 	return err
 }
@@ -212,7 +223,7 @@ func roundUp(length, pad int) int {
 // Builds a mask of history x batch indicating whether for each token in the batch the
 // token in the history should apply. This is based on both the sequence and causality (the
 // position of the history is not ahead of the token in the batch).
-func (c *Causal) buildMask(ctx ml.Context, positions []int32, seqs []int) (ml.Tensor, error) {
+func (c *Causal) buildMask(ctx ml.Context) (ml.Tensor, error) {
 	// Align and pad the two dimensions as required by the backend
 	batchSize := roundUp(c.curBatchSize, c.config.MaskBatchPadding)
 
@@ -224,8 +235,9 @@ func (c *Causal) buildMask(ctx ml.Context, positions []int32, seqs []int) (ml.Te
 
 	for i := range c.curBatchSize {
 		for j := c.curCellRange.min; j <= c.curCellRange.max; j++ {
-			if !slices.Contains(c.cells[j].sequences, seqs[i]) || c.cells[j].pos > positions[i] ||
-				c.cells[j].pos < positions[i]-c.windowSize {
+			if !slices.Contains(c.cells[j].sequences, c.curSequences[i]) ||
+				(c.causal && c.cells[j].pos > c.curPositions[i]) ||
+				c.cells[j].pos < c.curPositions[i]-c.windowSize {
 				mask[i*length+(j-c.curCellRange.min)] = float32(math.Inf(-1))
 			}
 		}
@@ -391,6 +403,26 @@ func (c *Causal) SetLayer(layer int) {
 	c.curLayer = layer
 }
 
+// SetCausal enables or disables causal mask generation for subsequent calls to Get.
+// This state carries over to future forward passes. The default value is true.
+//
+// ctx may be set to nil if this is called from outside of a forward pass, for
+// example, when initializing the cache.
+func (c *Causal) SetCausal(ctx ml.Context, causal bool) {
+	if c.causal != causal {
+		c.causal = causal
+
+		if ctx != nil {
+			var err error
+			c.curMask, err = c.buildMask(ctx)
+			if err != nil {
+				// This error should never occur because we have previously built a mask with the same shape
+				panic(fmt.Errorf("SetCausal: %w", err))
+			}
+		}
+	}
+}
+
 func (c *Causal) Get(ctx ml.Context) (ml.Tensor, ml.Tensor, ml.Tensor) {
 	key := c.keys[c.curLayer]
 	value := c.values[c.curLayer]

From 25f9b152f919b0262531873c935c301201d546aa Mon Sep 17 00:00:00 2001
From: Jesse Gross <jesse@ollama.com>
Date: Fri, 7 Mar 2025 17:20:54 -0800
Subject: [PATCH 024/157] ggml-backend: Ensure allocation meet backend
 requirements

Backends can impose additional alignment requirements on buffer sizes.
We should ensure that we meet these or allocations can fail.
---
 ml/backend/ggml/ggml.go | 7 ++++++-
 1 file changed, 6 insertions(+), 1 deletion(-)

diff --git a/ml/backend/ggml/ggml.go b/ml/backend/ggml/ggml.go
index 00873b4f..bf17c882 100644
--- a/ml/backend/ggml/ggml.go
+++ b/ml/backend/ggml/ggml.go
@@ -520,6 +520,10 @@ func shapeToGGML(shape []int) *C.int64_t {
 	return &sh[0]
 }
 
+func pad(length, pad C.size_t) C.size_t {
+	return ((length + pad - 1) / pad) * pad
+}
+
 func (c Context) newTensor(dtype ml.DType, shape []int) ml.Tensor {
 	if c.buft == nil {
 		panic("set Input, Output, or Layer before creating tensors")
@@ -551,7 +555,8 @@ func (c Context) newTensor(dtype ml.DType, shape []int) ml.Tensor {
 	}
 
 	t := C.ggml_new_tensor(c.ctx, cdtype, C.int(len(shape)), shapeToGGML(shape))
-	b := C.ggml_backend_buft_alloc_buffer(c.buft, C.ggml_nbytes(t))
+	size := pad(C.ggml_backend_buft_get_alloc_size(c.buft, t), C.ggml_backend_buft_get_alignment(c.buft))
+	b := C.ggml_backend_buft_alloc_buffer(c.buft, size)
 	C.ggml_backend_tensor_alloc(b, t, C.ggml_backend_buffer_get_base(b))
 	return &Tensor{b: c.b, t: t}
 }

From f52b2615ef3d82d4d95ce237233436f7cb818782 Mon Sep 17 00:00:00 2001
From: Jesse Gross <jesse@ollama.com>
Date: Fri, 7 Mar 2025 18:16:52 -0800
Subject: [PATCH 025/157] kvcache: Set context for shift offsets

---
 kvcache/causal.go | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/kvcache/causal.go b/kvcache/causal.go
index d519cf60..9a79fa57 100644
--- a/kvcache/causal.go
+++ b/kvcache/causal.go
@@ -545,7 +545,7 @@ func (c *Causal) shift(seq int, beginIndex, offset int32) error {
 		}
 	}
 
-	kShift, err := ctx.FromIntSlice(offsets, len(offsets))
+	kShift, err := ctx.Input().FromIntSlice(offsets, len(offsets))
 	if err != nil {
 		return err
 	}

From 4100ed7bdd417ae6d25bf64467fb9df33f3f6525 Mon Sep 17 00:00:00 2001
From: Jesse Gross <jesse@ollama.com>
Date: Fri, 21 Feb 2025 20:54:14 -0800
Subject: [PATCH 026/157] ml: Add support for quantized KV cache

Similar to the llama engine, quantizing the KV cache requires
flash attention to be enabled through the Ollama server.
---
 ml/backend.go                | 4 +++-
 ml/backend/ggml/ggml.go      | 8 ++++++++
 runner/ollamarunner/cache.go | 4 ++--
 3 files changed, 13 insertions(+), 3 deletions(-)

diff --git a/ml/backend.go b/ml/backend.go
index 915c9ad6..3abacbf1 100644
--- a/ml/backend.go
+++ b/ml/backend.go
@@ -215,7 +215,7 @@ func Dump(ctx Context, t Tensor, opts ...DumpOptions) string {
 		return dump[[]float32](ctx, t, opts[0].Items, func(f float32) string {
 			return strconv.FormatFloat(float64(f), 'f', opts[0].Precision, 32)
 		})
-	case DTypeF16:
+	case DTypeF16, DTypeQ80, DTypeQ40:
 		f32 := ctx.Empty(DTypeF32, t.Shape()...)
 		f32 = t.Copy(ctx, f32)
 		return dump[[]float32](ctx, f32, opts[0].Items, func(f float32) string {
@@ -283,5 +283,7 @@ const (
 	DTypeOther DType = iota
 	DTypeF32
 	DTypeF16
+	DTypeQ80
+	DTypeQ40
 	DTypeI32
 )
diff --git a/ml/backend/ggml/ggml.go b/ml/backend/ggml/ggml.go
index bf17c882..74512f33 100644
--- a/ml/backend/ggml/ggml.go
+++ b/ml/backend/ggml/ggml.go
@@ -535,6 +535,10 @@ func (c Context) newTensor(dtype ml.DType, shape []int) ml.Tensor {
 		cdtype = C.GGML_TYPE_F32
 	case ml.DTypeF16:
 		cdtype = C.GGML_TYPE_F16
+	case ml.DTypeQ80:
+		cdtype = C.GGML_TYPE_Q8_0
+	case ml.DTypeQ40:
+		cdtype = C.GGML_TYPE_Q4_0
 	case ml.DTypeI32:
 		cdtype = C.GGML_TYPE_I32
 	default:
@@ -680,6 +684,10 @@ func (t *Tensor) DType() ml.DType {
 		return ml.DTypeF32
 	case C.GGML_TYPE_F16:
 		return ml.DTypeF16
+	case C.GGML_TYPE_Q8_0:
+		return ml.DTypeQ80
+	case C.GGML_TYPE_Q4_0:
+		return ml.DTypeQ40
 	case C.GGML_TYPE_I32:
 		return ml.DTypeI32
 	default:
diff --git a/runner/ollamarunner/cache.go b/runner/ollamarunner/cache.go
index 2fd060a1..3244c0b8 100644
--- a/runner/ollamarunner/cache.go
+++ b/runner/ollamarunner/cache.go
@@ -58,9 +58,9 @@ func NewInputCache(model model.Model, kvCacheType string, kvSize int32, numSlots
 func kvCacheTypeFromStr(s string) ml.DType {
 	switch s {
 	case "q8_0":
-		panic("kv cache quantization not yet implemented")
+		return ml.DTypeQ80
 	case "q4_0":
-		panic("kv cache quantization not yet implemented")
+		return ml.DTypeQ40
 	default:
 		return ml.DTypeF16
 	}

From 4614fafae0ee58af5b9d04ec4b8c2eb3846274da Mon Sep 17 00:00:00 2001
From: Jesse Gross <jesse@ollama.com>
Date: Sat, 8 Mar 2025 18:48:32 -0800
Subject: [PATCH 027/157] ollamarunner: Don't panic for unimplemented features
 at runtime.

It's ok to fail on startup but we shouldn't panic during runtime
based on user input. Downgrade the panic to a warning.
---
 runner/ollamarunner/runner.go | 7 +++----
 1 file changed, 3 insertions(+), 4 deletions(-)

diff --git a/runner/ollamarunner/runner.go b/runner/ollamarunner/runner.go
index d9f47970..a51b1459 100644
--- a/runner/ollamarunner/runner.go
+++ b/runner/ollamarunner/runner.go
@@ -436,10 +436,9 @@ func (s *Server) processBatch() error {
 		// if done processing the prompt, generate an embedding and return
 		if seq.embeddingOnly {
 			// TODO(jessegross): Embedding support
-			// s.removeSequence(i, "")
-			// continue
-
-			panic("generation of embedding outputs not yet supported")
+			slog.Warn("generation of embedding outputs not yet supported")
+			s.removeSequence(i, "")
+			continue
 		}
 
 		// sample a token

From a1cda80bcb0b47d493be9dc061a2dfa8a0ddd61c Mon Sep 17 00:00:00 2001
From: Jesse Gross <jesse@ollama.com>
Date: Sat, 8 Mar 2025 15:45:31 -0800
Subject: [PATCH 028/157] model: Update encoder cache to use multimodal input
 processing handler

The encoder cache needs to know the position of images in the input
stream so that it knows when to delete them. Previously images didn't
have a position, so we implied one by breaking batches before an
image and then assuming the image was in the first position. However,
multimodal objects are now given explicit positions in the input
stream, so we can use that instead.

Breaking batches was also a way to simulate a cross attention mask
for mllama. However, given that it only supports a single sequence
and a single image, this mask doesn't serve any real purpose.
Removing the batch break does not appear to affect the quality of
the output.

Most of this is simply moving the input data structures to a new
package to avoid import cycles.
---
 kvcache/cache.go                  |  3 +-
 kvcache/causal.go                 | 13 ++---
 kvcache/causal_test.go            |  3 +-
 kvcache/encoder.go                |  9 ++--
 kvcache/wrapper.go                |  9 ++--
 model/input/input.go              | 37 ++++++++++++++
 model/model.go                    | 83 +++++++++----------------------
 model/model_test.go               |  3 +-
 model/models/llama/model.go       |  3 +-
 model/models/mllama/model.go      | 13 ++---
 runner/ollamarunner/cache.go      | 13 ++---
 runner/ollamarunner/cache_test.go | 72 +++++++++++++--------------
 runner/ollamarunner/runner.go     | 56 ++++++++-------------
 13 files changed, 157 insertions(+), 160 deletions(-)
 create mode 100644 model/input/input.go

diff --git a/kvcache/cache.go b/kvcache/cache.go
index 2541f7c1..d3548905 100644
--- a/kvcache/cache.go
+++ b/kvcache/cache.go
@@ -4,6 +4,7 @@ import (
 	"errors"
 
 	"github.com/ollama/ollama/ml"
+	"github.com/ollama/ollama/model/input"
 )
 
 var (
@@ -51,7 +52,7 @@ type Cache interface {
 	// StartForward is called before the start of the model's forward pass.
 	// For each token in the coming batch, there must be a corresponding
 	// entry in positions and seqs.
-	StartForward(ctx ml.Context, positions []int32, seqs []int) error
+	StartForward(ctx ml.Context, opts input.Options) error
 
 	// CopyPrefix copies tokens in the range [0, len) from srcSeq to dstSeq
 	CopyPrefix(srcSeq, dstSeq int, len int32)
diff --git a/kvcache/causal.go b/kvcache/causal.go
index 9a79fa57..34d5337c 100644
--- a/kvcache/causal.go
+++ b/kvcache/causal.go
@@ -8,6 +8,7 @@ import (
 	"slices"
 
 	"github.com/ollama/ollama/ml"
+	"github.com/ollama/ollama/model/input"
 )
 
 type shiftFn func(ctx ml.Context, layer int, key, shift ml.Tensor) (ml.Tensor, error)
@@ -140,10 +141,10 @@ func (c *Causal) Close() {
 	}
 }
 
-func (c *Causal) StartForward(ctx ml.Context, positions []int32, seqs []int) error {
-	c.curBatchSize = len(positions)
-	c.curSequences = seqs
-	c.curPositions = positions
+func (c *Causal) StartForward(ctx ml.Context, opts input.Options) error {
+	c.curBatchSize = len(opts.Positions)
+	c.curSequences = opts.Sequences
+	c.curPositions = opts.Positions
 
 	var err error
 	c.curLoc, err = c.findStartLoc()
@@ -156,8 +157,8 @@ func (c *Causal) StartForward(ctx ml.Context, positions []int32, seqs []int) err
 	}
 
 	c.curCellRange = newRange()
-	for i, pos := range positions {
-		seq := seqs[i]
+	for i, pos := range opts.Positions {
+		seq := opts.Sequences[i]
 
 		c.cells[c.curLoc+i] = cacheCell{pos: pos, sequences: []int{seq}}
 
diff --git a/kvcache/causal_test.go b/kvcache/causal_test.go
index 412f33e3..22d8efb4 100644
--- a/kvcache/causal_test.go
+++ b/kvcache/causal_test.go
@@ -6,6 +6,7 @@ import (
 	"testing"
 
 	"github.com/ollama/ollama/ml"
+	"github.com/ollama/ollama/model/input"
 )
 
 type testCase struct {
@@ -269,7 +270,7 @@ func testCache(t *testing.T, backend ml.Backend, cache Cache, tests []testCase)
 			context := backend.NewContext()
 			defer context.Close()
 
-			err := cache.StartForward(context, test.pos, test.seqs)
+			err := cache.StartForward(context, input.Options{Positions: test.pos, Sequences: test.seqs})
 			if err != nil {
 				panic(err)
 			}
diff --git a/kvcache/encoder.go b/kvcache/encoder.go
index 867ee37a..6a9df2ab 100644
--- a/kvcache/encoder.go
+++ b/kvcache/encoder.go
@@ -4,6 +4,7 @@ import (
 	"fmt"
 
 	"github.com/ollama/ollama/ml"
+	"github.com/ollama/ollama/model/input"
 )
 
 // Encoder cache stores K and V tensors that are position independent
@@ -78,9 +79,11 @@ func (c *EncoderCache) Close() {
 	}
 }
 
-func (c *EncoderCache) StartForward(ctx ml.Context, positions []int32, seqs []int) error {
-	// The image is always in the first position
-	c.curPos = positions[0]
+func (c *EncoderCache) StartForward(ctx ml.Context, opts input.Options) error {
+	// We work with the most recent image
+	if len(opts.Multimodal) > 0 {
+		c.curPos = opts.Positions[opts.Multimodal[len(opts.Multimodal)-1].Index]
+	}
 
 	return nil
 }
diff --git a/kvcache/wrapper.go b/kvcache/wrapper.go
index 76956a88..aaccd166 100644
--- a/kvcache/wrapper.go
+++ b/kvcache/wrapper.go
@@ -4,6 +4,7 @@ import (
 	"math"
 
 	"github.com/ollama/ollama/ml"
+	"github.com/ollama/ollama/model/input"
 )
 
 // Wrapper cache is a container for multiple types of caches,
@@ -40,14 +41,14 @@ func (c *WrapperCache) Close() {
 	}
 }
 
-func (c *WrapperCache) StartForward(ctx ml.Context, positions []int32, seqs []int) error {
+func (c *WrapperCache) StartForward(ctx ml.Context, opts input.Options) error {
 	for i, cache := range c.caches {
-		err := cache.StartForward(ctx, positions, seqs)
+		err := cache.StartForward(ctx, opts)
 		if err != nil {
 			// unwind on error - Remove with endIndex set to math.MaxInt32 does not fail
 			for j := i - 1; j >= 0; j-- {
-				for k := range positions {
-					_ = c.caches[j].Remove(seqs[k], positions[k], math.MaxInt32)
+				for k := range opts.Positions {
+					_ = c.caches[j].Remove(opts.Sequences[k], opts.Positions[k], math.MaxInt32)
 				}
 			}
 			return err
diff --git a/model/input/input.go b/model/input/input.go
new file mode 100644
index 00000000..0cb3f3f4
--- /dev/null
+++ b/model/input/input.go
@@ -0,0 +1,37 @@
+package input
+
+// Input represents one token in the input stream
+type Input struct {
+	// Token is a single element of text.
+	Token int32
+
+	// Multimodal is opaque data representing a non-text
+	// element such as an image (or part of one if the image
+	// can be processed in pieces). It may be either together
+	// with Token or on its own.
+	Multimodal any
+
+	// MultimodalHash is a unique representation of the data
+	// stored in Multimodal, used for caching and comparing
+	// equality.
+	MultimodalHash uint64
+}
+
+// MultimodalIndex is a multimodal element (such as an image)
+// together with an index into the slice of Inputs with the
+// corresponding token. Note that the index is not the same
+// as the position - to find that use the index with the
+// Positions slice.
+type MultimodalIndex struct {
+	Index      int
+	Multimodal any
+}
+
+// Options contains the inputs for a model forward pass
+type Options struct {
+	Inputs     []int32
+	Multimodal []MultimodalIndex
+	Positions  []int32
+	Sequences  []int
+	Outputs    []int32
+}
diff --git a/model/model.go b/model/model.go
index 75b7f639..89b6c803 100644
--- a/model/model.go
+++ b/model/model.go
@@ -19,66 +19,12 @@ import (
 	"github.com/ollama/ollama/kvcache"
 	"github.com/ollama/ollama/ml"
 	_ "github.com/ollama/ollama/ml/backend"
+	"github.com/ollama/ollama/model/input"
 )
 
-// Input represents one token in the input stream
-type Input struct {
-	// Token is a single element of text.
-	Token int32
-
-	// Multimodal is opaque data representing a non-text
-	// element such as an image (or part of one if the image
-	// can be processed in pieces). It may be either together
-	// with Token or on its own.
-	Multimodal any
-
-	// MultimodalHash is a unique representation of the data
-	// stored in Multimodal, used for caching and comparing
-	// equality.
-	MultimodalHash uint64
-}
-
-// MultimodalIndex is a multimodal element (such as an image)
-// together with an index into the slice of Inputs with the
-// corresponding token. Note that the index is not the same
-// as the position - to find that use the index with the
-// Positions slice.
-type MultimodalIndex struct {
-	Index      int
-	Multimodal any
-}
-
-// Options contains the inputs for a model forward pass
-type Options struct {
-	Inputs     []int32
-	Multimodal []MultimodalIndex
-	Positions  []int32
-	Sequences  []int
-	Outputs    []int32
-}
-
-type config struct {
-	Cache kvcache.Cache
-}
-
-// Base implements the common fields and methods for all models
-type Base struct {
-	b ml.Backend
-	config
-}
-
-// Backend returns the underlying backend that will run the model
-func (m *Base) Backend() ml.Backend {
-	return m.b
-}
-
-func (m *Base) Config() config {
-	return m.config
-}
-
 // Model implements a specific model architecture, defining the forward pass and any model-specific configuration
 type Model interface {
-	Forward(ml.Context, Options) (ml.Tensor, error)
+	Forward(ml.Context, input.Options) (ml.Tensor, error)
 
 	Backend() ml.Backend
 	Config() config
@@ -112,7 +58,26 @@ type MultimodalProcessor interface {
 	// This function is also responsible for updating MultimodalHash for any Multimodal
 	// that is modified to ensure that there is a unique hash value that accurately
 	// represents the contents.
-	PostTokenize(ml.Context, []Input) ([]Input, error)
+	PostTokenize(ml.Context, []input.Input) ([]input.Input, error)
+}
+
+// Base implements the common fields and methods for all models
+type Base struct {
+	b ml.Backend
+	config
+}
+
+type config struct {
+	Cache kvcache.Cache
+}
+
+// Backend returns the underlying backend that will run the model
+func (m *Base) Backend() ml.Backend {
+	return m.b
+}
+
+func (m *Base) Config() config {
+	return m.config
 }
 
 var models = make(map[string]func(ml.Config) (Model, error))
@@ -313,7 +278,7 @@ func canNil(t reflect.Type) bool {
 		t.Kind() == reflect.Slice
 }
 
-func Forward(ctx ml.Context, m Model, opts Options) (ml.Tensor, error) {
+func Forward(ctx ml.Context, m Model, opts input.Options) (ml.Tensor, error) {
 	if len(opts.Positions) != len(opts.Sequences) {
 		return nil, fmt.Errorf("length of positions (%v) must match length of seqs (%v)", len(opts.Positions), len(opts.Sequences))
 	}
@@ -324,7 +289,7 @@ func Forward(ctx ml.Context, m Model, opts Options) (ml.Tensor, error) {
 
 	cache := m.Config().Cache
 	if cache != nil {
-		err := cache.StartForward(ctx, opts.Positions, opts.Sequences)
+		err := cache.StartForward(ctx, opts)
 		if err != nil {
 			return nil, err
 		}
diff --git a/model/model_test.go b/model/model_test.go
index 8761817e..354dd1d8 100644
--- a/model/model_test.go
+++ b/model/model_test.go
@@ -11,6 +11,7 @@ import (
 	"github.com/ollama/ollama/ml"
 	"github.com/ollama/ollama/ml/backend/ggml"
 	"github.com/ollama/ollama/ml/nn"
+	"github.com/ollama/ollama/model/input"
 )
 
 func TestParseTags(t *testing.T) {
@@ -162,7 +163,7 @@ func TestGetTextProcessor(t *testing.T) {
 
 type notTextProcessorModel struct{}
 
-func (notTextProcessorModel) Forward(ml.Context, Options) (ml.Tensor, error) {
+func (notTextProcessorModel) Forward(ml.Context, input.Options) (ml.Tensor, error) {
 	panic("unimplemented")
 }
 
diff --git a/model/models/llama/model.go b/model/models/llama/model.go
index 9ccfff61..1f27f522 100644
--- a/model/models/llama/model.go
+++ b/model/models/llama/model.go
@@ -9,6 +9,7 @@ import (
 	"github.com/ollama/ollama/ml"
 	"github.com/ollama/ollama/ml/nn"
 	"github.com/ollama/ollama/model"
+	"github.com/ollama/ollama/model/input"
 )
 
 type Options struct {
@@ -137,7 +138,7 @@ func (l *Layer) Forward(ctx ml.Context, hiddenState, positionIDs, outputs ml.Ten
 	return hiddenState.Add(ctx, residual)
 }
 
-func (m *Model) Forward(ctx ml.Context, opts model.Options) (ml.Tensor, error) {
+func (m *Model) Forward(ctx ml.Context, opts input.Options) (ml.Tensor, error) {
 	inputs, err := ctx.Input().FromIntSlice(opts.Inputs, len(opts.Inputs))
 	if err != nil {
 		return nil, err
diff --git a/model/models/mllama/model.go b/model/models/mllama/model.go
index 54c63296..31ba15df 100644
--- a/model/models/mllama/model.go
+++ b/model/models/mllama/model.go
@@ -12,6 +12,7 @@ import (
 	"github.com/ollama/ollama/ml"
 	"github.com/ollama/ollama/ml/nn"
 	"github.com/ollama/ollama/model"
+	"github.com/ollama/ollama/model/input"
 )
 
 type Model struct {
@@ -101,8 +102,8 @@ func (m *Model) EncodeMultimodal(ctx ml.Context, multimodalData []byte) (any, er
 	return m.Projector.Forward(ctx, crossAttentionStates), nil
 }
 
-func (m *Model) PostTokenize(ctx ml.Context, inputs []model.Input) ([]model.Input, error) {
-	var images []model.Input
+func (m *Model) PostTokenize(ctx ml.Context, inputs []input.Input) ([]input.Input, error) {
+	var images []input.Input
 	fnvHash := fnv.New64a()
 
 	for i := range inputs {
@@ -125,15 +126,15 @@ func (m *Model) PostTokenize(ctx ml.Context, inputs []model.Input) ([]model.Inpu
 		}
 	}
 
-	inputs = slices.DeleteFunc(inputs, func(input model.Input) bool { return input.Token == -1 })
+	inputs = slices.DeleteFunc(inputs, func(input input.Input) bool { return input.Token == -1 })
 
 	return inputs, nil
 }
 
-func (m *Model) Forward(ctx ml.Context, opts model.Options) (ml.Tensor, error) {
+func (m *Model) Forward(ctx ml.Context, opts input.Options) (ml.Tensor, error) {
 	var crossAttentionStates ml.Tensor
-	if opts.Multimodal != nil {
-		crossAttentionStates = opts.Multimodal[0].Multimodal.(ml.Tensor)
+	if len(opts.Multimodal) > 0 {
+		crossAttentionStates = opts.Multimodal[len(opts.Multimodal)-1].Multimodal.(ml.Tensor)
 	}
 
 	inputs, err := ctx.Input().FromIntSlice(opts.Inputs, len(opts.Inputs))
diff --git a/runner/ollamarunner/cache.go b/runner/ollamarunner/cache.go
index 3244c0b8..a411fddb 100644
--- a/runner/ollamarunner/cache.go
+++ b/runner/ollamarunner/cache.go
@@ -10,6 +10,7 @@ import (
 	"github.com/ollama/ollama/kvcache"
 	"github.com/ollama/ollama/ml"
 	"github.com/ollama/ollama/model"
+	"github.com/ollama/ollama/model/input"
 )
 
 type InputCache struct {
@@ -79,7 +80,7 @@ type InputCacheSlot struct {
 	Id int
 
 	// Inputs that are stored in the KV cache
-	Inputs []model.Input
+	Inputs []input.Input
 
 	// is this cache actively being processed as part of a sequence?
 	InUse bool
@@ -88,7 +89,7 @@ type InputCacheSlot struct {
 	lastUsed time.Time
 }
 
-func (c *InputCache) LoadCacheSlot(prompt []model.Input, cachePrompt bool) (*InputCacheSlot, []model.Input, error) {
+func (c *InputCache) LoadCacheSlot(prompt []input.Input, cachePrompt bool) (*InputCacheSlot, []input.Input, error) {
 	var slot *InputCacheSlot
 	var numPast int32
 	var err error
@@ -139,7 +140,7 @@ func (c *InputCache) LoadCacheSlot(prompt []model.Input, cachePrompt bool) (*Inp
 	return slot, prompt, nil
 }
 
-func (c *InputCache) findLongestCacheSlot(prompt []model.Input) (*InputCacheSlot, int32, error) {
+func (c *InputCache) findLongestCacheSlot(prompt []input.Input) (*InputCacheSlot, int32, error) {
 	longest := int32(-1)
 	var longestSlot *InputCacheSlot
 
@@ -162,7 +163,7 @@ func (c *InputCache) findLongestCacheSlot(prompt []model.Input) (*InputCacheSlot
 	return longestSlot, longest, nil
 }
 
-func (c *InputCache) findBestCacheSlot(prompt []model.Input) (*InputCacheSlot, int32, error) {
+func (c *InputCache) findBestCacheSlot(prompt []input.Input) (*InputCacheSlot, int32, error) {
 	oldest := time.Now()
 	var oldestSlot *InputCacheSlot
 
@@ -198,7 +199,7 @@ func (c *InputCache) findBestCacheSlot(prompt []model.Input) (*InputCacheSlot, i
 	if longest > 0 && longestSlot != oldestSlot {
 		slog.Debug("forking cache slot", "src", longestSlot.Id, "dst", oldestSlot.Id, "inputs", longest, "total",
 			len(longestSlot.Inputs))
-		oldestSlot.Inputs = make([]model.Input, longest)
+		oldestSlot.Inputs = make([]input.Input, longest)
 		copy(oldestSlot.Inputs, longestSlot.Inputs[:longest])
 		if c.cache != nil {
 			c.cache.CopyPrefix(longestSlot.Id, oldestSlot.Id, longest)
@@ -208,7 +209,7 @@ func (c *InputCache) findBestCacheSlot(prompt []model.Input) (*InputCacheSlot, i
 	return oldestSlot, longest, nil
 }
 
-func countCommonPrefix(a []model.Input, b []model.Input) int32 {
+func countCommonPrefix(a []input.Input, b []input.Input) int32 {
 	var count int32
 
 	for i := range a {
diff --git a/runner/ollamarunner/cache_test.go b/runner/ollamarunner/cache_test.go
index 9ce03b73..0a1b73f5 100644
--- a/runner/ollamarunner/cache_test.go
+++ b/runner/ollamarunner/cache_test.go
@@ -5,7 +5,7 @@ import (
 	"testing"
 	"time"
 
-	"github.com/ollama/ollama/model"
+	"github.com/ollama/ollama/model/input"
 )
 
 func TestCountCommon(t *testing.T) {
@@ -15,50 +15,50 @@ func TestCountCommon(t *testing.T) {
 
 	tests := []struct {
 		name     string
-		t1       []model.Input
-		t2       []model.Input
+		t1       []input.Input
+		t2       []input.Input
 		expected int32
 	}{
 		{
 			name:     "Equal",
-			t1:       []model.Input{{Token: 1}, {Token: 2}, {Token: 3}},
-			t2:       []model.Input{{Token: 1}, {Token: 2}, {Token: 3}},
+			t1:       []input.Input{{Token: 1}, {Token: 2}, {Token: 3}},
+			t2:       []input.Input{{Token: 1}, {Token: 2}, {Token: 3}},
 			expected: 3,
 		},
 		{
 			name:     "Prefix",
-			t1:       []model.Input{{Token: 1}},
-			t2:       []model.Input{{Token: 1}, {Token: 2}, {Token: 3}},
+			t1:       []input.Input{{Token: 1}},
+			t2:       []input.Input{{Token: 1}, {Token: 2}, {Token: 3}},
 			expected: 1,
 		},
 		{
 			name:     "Image Prefix",
-			t1:       []model.Input{{Multimodal: imgA, MultimodalHash: 1}},
-			t2:       []model.Input{{Multimodal: imgA, MultimodalHash: 1}, {Multimodal: imgB, MultimodalHash: 2}, {Multimodal: imgC, MultimodalHash: 3}},
+			t1:       []input.Input{{Multimodal: imgA, MultimodalHash: 1}},
+			t2:       []input.Input{{Multimodal: imgA, MultimodalHash: 1}, {Multimodal: imgB, MultimodalHash: 2}, {Multimodal: imgC, MultimodalHash: 3}},
 			expected: 1,
 		},
 		{
 			name:     "Mixed",
-			t1:       []model.Input{{Token: 1}, {Multimodal: imgA, MultimodalHash: 1}},
-			t2:       []model.Input{{Token: 1}, {Multimodal: imgA, MultimodalHash: 1}, {Token: 5}},
+			t1:       []input.Input{{Token: 1}, {Multimodal: imgA, MultimodalHash: 1}},
+			t2:       []input.Input{{Token: 1}, {Multimodal: imgA, MultimodalHash: 1}, {Token: 5}},
 			expected: 2,
 		},
 		{
 			name:     "Mixed, Same Length",
-			t1:       []model.Input{{Token: 1}, {Multimodal: imgA, MultimodalHash: 1}},
-			t2:       []model.Input{{Token: 1}, {Multimodal: imgB, MultimodalHash: 2}},
+			t1:       []input.Input{{Token: 1}, {Multimodal: imgA, MultimodalHash: 1}},
+			t2:       []input.Input{{Token: 1}, {Multimodal: imgB, MultimodalHash: 2}},
 			expected: 1,
 		},
 		{
 			name:     "Empty",
-			t1:       []model.Input{},
-			t2:       []model.Input{{Token: 1}, {Token: 2}, {Token: 3}},
+			t1:       []input.Input{},
+			t2:       []input.Input{{Token: 1}, {Token: 2}, {Token: 3}},
 			expected: 0,
 		},
 		{
 			name:     "Both Empty",
-			t1:       []model.Input{},
-			t2:       []model.Input{},
+			t1:       []input.Input{},
+			t2:       []input.Input{},
 			expected: 0,
 		},
 	}
@@ -82,7 +82,7 @@ func TestFindCacheSlot(t *testing.T) {
 	tests := []struct {
 		name    string
 		cache   InputCache
-		prompt  []model.Input
+		prompt  []input.Input
 		longest expected
 		best    expected
 	}{
@@ -91,18 +91,18 @@ func TestFindCacheSlot(t *testing.T) {
 			cache: InputCache{slots: []InputCacheSlot{
 				{
 					Id:       0,
-					Inputs:   []model.Input{},
+					Inputs:   []input.Input{},
 					InUse:    false,
 					lastUsed: time.Time{},
 				},
 				{
 					Id:       1,
-					Inputs:   []model.Input{},
+					Inputs:   []input.Input{},
 					InUse:    false,
 					lastUsed: time.Time{},
 				},
 			}},
-			prompt:  []model.Input{{Token: 1}},
+			prompt:  []input.Input{{Token: 1}},
 			longest: expected{result: 0, len: 0},
 			best:    expected{result: 0, len: 0},
 		},
@@ -111,18 +111,18 @@ func TestFindCacheSlot(t *testing.T) {
 			cache: InputCache{slots: []InputCacheSlot{
 				{
 					Id:       0,
-					Inputs:   []model.Input{{Token: 1}},
+					Inputs:   []input.Input{{Token: 1}},
 					InUse:    false,
 					lastUsed: time.Now().Add(-time.Second),
 				},
 				{
 					Id:       1,
-					Inputs:   []model.Input{{Token: 1}, {Token: 2}},
+					Inputs:   []input.Input{{Token: 1}, {Token: 2}},
 					InUse:    false,
 					lastUsed: time.Now().Add(-2 * time.Second),
 				},
 			}},
-			prompt:  []model.Input{{Token: 1}, {Token: 2}},
+			prompt:  []input.Input{{Token: 1}, {Token: 2}},
 			longest: expected{result: 1, len: 2},
 			best:    expected{result: 1, len: 2},
 		},
@@ -131,18 +131,18 @@ func TestFindCacheSlot(t *testing.T) {
 			cache: InputCache{slots: []InputCacheSlot{
 				{
 					Id:       0,
-					Inputs:   []model.Input{{Token: 1}, {Token: 2}},
+					Inputs:   []input.Input{{Token: 1}, {Token: 2}},
 					InUse:    false,
 					lastUsed: time.Now().Add(-time.Second),
 				},
 				{
 					Id:       1,
-					Inputs:   []model.Input{},
+					Inputs:   []input.Input{},
 					InUse:    false,
 					lastUsed: time.Time{},
 				},
 			}},
-			prompt:  []model.Input{{Token: 2}},
+			prompt:  []input.Input{{Token: 2}},
 			longest: expected{result: 0, len: 0},
 			best:    expected{result: 1, len: 0},
 		},
@@ -152,19 +152,19 @@ func TestFindCacheSlot(t *testing.T) {
 				slots: []InputCacheSlot{
 					{
 						Id:       0,
-						Inputs:   []model.Input{{Token: 1}, {Token: 2}},
+						Inputs:   []input.Input{{Token: 1}, {Token: 2}},
 						InUse:    false,
 						lastUsed: time.Now().Add(-time.Second),
 					},
 					{
 						Id:       1,
-						Inputs:   []model.Input{},
+						Inputs:   []input.Input{},
 						InUse:    false,
 						lastUsed: time.Time{},
 					},
 				},
 			},
-			prompt:  []model.Input{{Token: 1}},
+			prompt:  []input.Input{{Token: 1}},
 			longest: expected{result: 0, len: 1},
 			best:    expected{result: 1, len: 1},
 		},
@@ -173,18 +173,18 @@ func TestFindCacheSlot(t *testing.T) {
 			cache: InputCache{slots: []InputCacheSlot{
 				{
 					Id:       0,
-					Inputs:   []model.Input{{Token: 1}},
+					Inputs:   []input.Input{{Token: 1}},
 					InUse:    false,
 					lastUsed: time.Now().Add(-time.Second),
 				},
 				{
 					Id:       1,
-					Inputs:   []model.Input{{Token: 1}, {Token: 2}},
+					Inputs:   []input.Input{{Token: 1}, {Token: 2}},
 					InUse:    false,
 					lastUsed: time.Now().Add(-2 * time.Second),
 				},
 			}},
-			prompt:  []model.Input{{Token: 2}, {Token: 3}},
+			prompt:  []input.Input{{Token: 2}, {Token: 3}},
 			longest: expected{result: 0, len: 0},
 			best:    expected{result: 1, len: 0},
 		},
@@ -193,18 +193,18 @@ func TestFindCacheSlot(t *testing.T) {
 			cache: InputCache{slots: []InputCacheSlot{
 				{
 					Id:       0,
-					Inputs:   []model.Input{{Token: 1}, {Token: 2}},
+					Inputs:   []input.Input{{Token: 1}, {Token: 2}},
 					InUse:    true,
 					lastUsed: time.Now().Add(-time.Second),
 				},
 				{
 					Id:       1,
-					Inputs:   []model.Input{{Token: 1}},
+					Inputs:   []input.Input{{Token: 1}},
 					InUse:    false,
 					lastUsed: time.Now().Add(-2 * time.Second),
 				},
 			}},
-			prompt:  []model.Input{{Token: 1}, {Token: 2}},
+			prompt:  []input.Input{{Token: 1}, {Token: 2}},
 			longest: expected{result: 1, len: 1},
 			best:    expected{result: 1, len: 2},
 		},
diff --git a/runner/ollamarunner/runner.go b/runner/ollamarunner/runner.go
index a51b1459..c8383a5d 100644
--- a/runner/ollamarunner/runner.go
+++ b/runner/ollamarunner/runner.go
@@ -26,6 +26,7 @@ import (
 	"github.com/ollama/ollama/api"
 	"github.com/ollama/ollama/ml"
 	"github.com/ollama/ollama/model"
+	"github.com/ollama/ollama/model/input"
 	"github.com/ollama/ollama/runner/common"
 	"github.com/ollama/ollama/sample"
 
@@ -41,10 +42,10 @@ type Sequence struct {
 	iBatch int
 
 	// prompt inputs left to evaluate
-	inputs []model.Input
+	inputs []input.Input
 
 	// inputs that have been added to a batch but not yet submitted to Forward
-	pendingInputs []model.Input
+	pendingInputs []input.Input
 
 	// tokens that have been generated but not returned yet (e.g. for stop sequences)
 	pendingResponses []string
@@ -144,8 +145,8 @@ func (s *Server) NewSequence(prompt string, images []ImageData, params NewSequen
 // inputs processes the prompt and images into a list of inputs
 // by splitting the prompt on [img-<n>] tags, tokenizing text and
 // decoding images
-func (s *Server) inputs(ctx ml.Context, prompt string, images []ImageData) ([]model.Input, error) {
-	var inputs []model.Input
+func (s *Server) inputs(ctx ml.Context, prompt string, images []ImageData) ([]input.Input, error) {
+	var inputs []input.Input
 	var parts []string
 	var matches [][]string
 
@@ -168,7 +169,7 @@ func (s *Server) inputs(ctx ml.Context, prompt string, images []ImageData) ([]mo
 		}
 
 		for _, t := range tokens {
-			inputs = append(inputs, model.Input{Token: t})
+			inputs = append(inputs, input.Input{Token: t})
 		}
 
 		// image - decode and store
@@ -196,7 +197,7 @@ func (s *Server) inputs(ctx ml.Context, prompt string, images []ImageData) ([]mo
 			_, _ = s.multimodalHash.Write(images[imageIndex].Data)
 			imageHash := s.multimodalHash.Sum64()
 
-			inputs = append(inputs, model.Input{Multimodal: imageEmbeddings, MultimodalHash: imageHash})
+			inputs = append(inputs, input.Input{Multimodal: imageEmbeddings, MultimodalHash: imageHash})
 			postTokenize = true
 		}
 	}
@@ -250,9 +251,6 @@ type Server struct {
 	// KV cache
 	cache *InputCache
 
-	// next sequence for prompt processing to avoid starvation
-	nextSeq int
-
 	// multimodalHash generates hashes for comparing equality
 	// of non-text data
 	multimodalHash maphash.Hash
@@ -329,29 +327,25 @@ func (s *Server) processBatch() error {
 	}
 	defer s.mu.Unlock()
 
-	var options model.Options
-
-	seqIdx := s.nextSeq - 1
-	for range s.seqs {
-		seqIdx = (seqIdx + 1) % len(s.seqs)
-		seq := s.seqs[seqIdx]
+	var options input.Options
 
+	for i, seq := range s.seqs {
 		if seq == nil {
 			continue
 		}
 
 		// if past the num predict limit
 		if seq.numPredict > 0 && seq.numPredicted >= seq.numPredict {
-			s.removeSequence(seqIdx, "limit")
+			s.removeSequence(i, "limit")
 			continue
 		}
 
 		if !s.cache.enabled {
 			seq.inputs = append(seq.cache.Inputs, seq.inputs...)
-			seq.cache.Inputs = []model.Input{}
+			seq.cache.Inputs = []input.Input{}
 		}
 
-		for i, input := range seq.inputs {
+		for j, inp := range seq.inputs {
 			if int32(len(seq.cache.Inputs)+len(seq.pendingInputs)+1) > s.cache.numCtx {
 				if len(seq.pendingInputs) == 0 {
 					err := s.cache.ShiftCacheSlot(seq.cache, seq.numKeep)
@@ -363,33 +357,23 @@ func (s *Server) processBatch() error {
 				}
 			}
 
-			if i >= s.batchSize {
+			if j >= s.batchSize {
 				break
 			}
 
-			// TODO(jessegross): This is a workaround for generating an attention mask and also providing a hint
-			// to the encoder cache.
-			//
-			// Break the batch when switching from text to images so that images are always at the beginning.
-			if input.Multimodal != nil && !(len(seq.pendingInputs) == 0 ||
-				(len(options.Multimodal) > 0 && options.Multimodal[len(options.Multimodal)-1].Index == len(options.Inputs)-1)) {
-				s.nextSeq = seqIdx
-				break
-			}
-
-			options.Inputs = append(options.Inputs, input.Token)
-			if input.Multimodal != nil {
-				options.Multimodal = append(options.Multimodal, model.MultimodalIndex{Index: len(options.Inputs) - 1, Multimodal: input.Multimodal})
+			options.Inputs = append(options.Inputs, inp.Token)
+			if inp.Multimodal != nil {
+				options.Multimodal = append(options.Multimodal, input.MultimodalIndex{Index: len(options.Inputs) - 1, Multimodal: inp.Multimodal})
 			}
 
 			options.Positions = append(options.Positions, int32(len(seq.cache.Inputs)+len(seq.pendingInputs)))
 			options.Sequences = append(options.Sequences, seq.cache.Id)
 
 			seq.iBatch = len(options.Outputs)
-			if i+1 == len(seq.inputs) {
+			if j+1 == len(seq.inputs) {
 				options.Outputs = append(options.Outputs, int32(len(options.Inputs)-1))
 			}
-			seq.pendingInputs = append(seq.pendingInputs, input)
+			seq.pendingInputs = append(seq.pendingInputs, inp)
 		}
 
 		seq.inputs = seq.inputs[len(seq.pendingInputs):]
@@ -417,7 +401,7 @@ func (s *Server) processBatch() error {
 		// After calling Forward, pending inputs are now in the cache
 		if len(seq.pendingInputs) > 0 {
 			seq.cache.Inputs = append(seq.cache.Inputs, seq.pendingInputs...)
-			seq.pendingInputs = []model.Input{}
+			seq.pendingInputs = []input.Input{}
 		}
 
 		// don't sample prompt processing
@@ -464,7 +448,7 @@ func (s *Server) processBatch() error {
 			return err
 		}
 
-		seq.inputs = []model.Input{{Token: token}}
+		seq.inputs = []input.Input{{Token: token}}
 
 		seq.pendingResponses = append(seq.pendingResponses, piece)
 		sequence := strings.Join(seq.pendingResponses, "")

From e093db92c4731b0cada767c7d5877c20d5f61dcf Mon Sep 17 00:00:00 2001
From: Jeffrey Morgan <jmorganca@gmail.com>
Date: Mon, 10 Mar 2025 16:17:39 +0100
Subject: [PATCH 029/157] sample: temporarily use grammars for constrained
 generation in new engine (#9586)

---
 llama/llama.go                    |  68 +++++++++++
 llama/sampling_ext.cpp            |  22 ++++
 llama/sampling_ext.h              |   3 +
 llm/server.go                     |  39 +++---
 runner/ollamarunner/runner.go     |  23 +++-
 sample/samplers.go                | 193 +++++++++++++++++++++---------
 sample/samplers_benchmark_test.go |  28 ++---
 sample/samplers_test.go           |  94 +--------------
 sample/transforms.go              |  16 +--
 sample/transforms_test.go         |  28 ++---
 10 files changed, 301 insertions(+), 213 deletions(-)

diff --git a/llama/llama.go b/llama/llama.go
index bb5028bd..a026bee2 100644
--- a/llama/llama.go
+++ b/llama/llama.go
@@ -245,6 +245,20 @@ func LoadModelFromFile(modelPath string, params ModelParams) (*Model, error) {
 	return &m, nil
 }
 
+func LoadVocabFromFile(path string) (*Vocab, error) {
+	mp := C.CString(path)
+	defer C.free(unsafe.Pointer(mp))
+	v := Vocab{c: C.llama_load_vocab_from_file(mp)}
+	if v.c == nil {
+		return nil, fmt.Errorf("unable to load vocab: %s", path)
+	}
+	return &v, nil
+}
+
+func FreeVocab(vocab *Vocab) {
+	C.llama_free_vocab(vocab.c)
+}
+
 func FreeModel(model *Model) {
 	C.llama_model_free(model.c)
 }
@@ -293,6 +307,10 @@ func (m *Model) ApplyLoraFromFile(context *Context, loraPath string, scale float
 	return nil
 }
 
+type Vocab struct {
+	c *C.struct_llama_vocab
+}
+
 func (m *Model) Vocab() *C.struct_llama_vocab {
 	return C.llama_model_get_vocab(m.c)
 }
@@ -669,3 +687,53 @@ func SchemaToGrammar(schema []byte) []byte {
 	}
 	return buf[:n]
 }
+
+type Sampler struct {
+	c *C.struct_llama_sampler
+}
+
+func NewGrammarSampler(vocab *Vocab, grammar string) *Sampler {
+	cGrammar := C.CString(grammar)
+	cRoot := C.CString("root")
+	defer C.free(unsafe.Pointer(cGrammar))
+	defer C.free(unsafe.Pointer(cRoot))
+
+	sampler := &Sampler{c: C.llama_sampler_init_grammar(vocab.c, cGrammar, cRoot)}
+
+	return sampler
+}
+
+func (s *Sampler) Accept(token int32) {
+	C.llama_sampler_accept(s.c, C.llama_token(token))
+}
+
+type TokenData struct {
+	Id    int32
+	Logit float32
+}
+
+func (s *Sampler) Apply(tokens []TokenData) {
+	tds := make([]C.struct_llama_token_data, len(tokens))
+	for i, token := range tokens {
+		tds[i] = C.struct_llama_token_data{
+			id:    C.int32_t(token.Id),
+			logit: C.float(token.Logit),
+			p:     C.float(0.0),
+		}
+	}
+	tda := &C.llama_token_data_array{
+		data:     (*C.struct_llama_token_data)(unsafe.Pointer(&tds[0])),
+		size:     C.size_t(len(tokens)),
+		selected: C.int64_t(-1),
+		sorted:   C.bool(false),
+	}
+
+	var pinner runtime.Pinner
+	pinner.Pin(&tds[0])
+	defer pinner.Unpin()
+
+	C.llama_sampler_apply(s.c, tda)
+	for i := range tokens {
+		tokens[i].Logit = float32(tds[i].logit)
+	}
+}
diff --git a/llama/sampling_ext.cpp b/llama/sampling_ext.cpp
index 0f137dc8..b816cedd 100644
--- a/llama/sampling_ext.cpp
+++ b/llama/sampling_ext.cpp
@@ -2,6 +2,9 @@
 #include "sampling.h"
 #include "sampling_ext.h"
 #include "json-schema-to-grammar.h"
+#include "llama.h"
+#include "llama-model.h"
+#include "llama-model-loader.h"
 
 struct common_sampler *common_sampler_cinit(const struct llama_model *model, struct common_sampler_cparams *params) {
     try {
@@ -64,3 +67,22 @@ int schema_to_grammar(const char *json_schema, char *grammar, size_t max_len)
         return 0;
     }
 }
+
+struct llama_vocab * llama_load_vocab_from_file(const char * fname) {
+    llama_vocab * vocab = new llama_vocab();
+    try {
+        const auto kv = LLM_KV(LLM_ARCH_UNKNOWN);
+        std::vector<std::string> splits = {};
+        llama_model_loader ml(std::string(fname), splits, false, false, nullptr);
+        vocab->load(ml, kv);
+    } catch (const std::exception & err) {
+        LLAMA_LOG_ERROR("%s: error loading model: %s\n", __func__, err.what());
+        return nullptr;
+    }
+
+    return vocab;
+}
+
+void llama_free_vocab(struct llama_vocab * vocab) {
+    delete vocab;
+}
diff --git a/llama/sampling_ext.h b/llama/sampling_ext.h
index 39f499f1..9be7c100 100644
--- a/llama/sampling_ext.h
+++ b/llama/sampling_ext.h
@@ -35,6 +35,9 @@ extern "C"
 
     int schema_to_grammar(const char *json_schema, char *grammar, size_t max_len);
 
+    struct llama_vocab * llama_load_vocab_from_file(const char * fname);
+    void llama_free_vocab(struct llama_vocab * vocab);
+
 #ifdef __cplusplus
 }
 #endif
diff --git a/llm/server.go b/llm/server.go
index 9553ba8f..a53306fb 100644
--- a/llm/server.go
+++ b/llm/server.go
@@ -729,29 +729,24 @@ func (s *llmServer) Completion(ctx context.Context, req CompletionRequest, fn fu
 	}
 
 	if len(req.Format) > 0 {
-		format := string(req.Format)
-		if format != `null` && format != `""` {
-			if s.textProcessor != nil {
-				// New engine handles this on the backend
-				request["format"] = req.Format
-			} else {
-				// old engine
-				switch format {
-				case `"json"`:
-					request["grammar"] = grammarJSON
-				default:
-					if req.Format[0] != '{' {
-						return fmt.Errorf("invalid format: %q; expected \"json\" or a valid JSON Schema object", req.Format)
-					}
-
-					// User provided a JSON schema
-					g := llama.SchemaToGrammar(req.Format)
-					if g == nil {
-						return fmt.Errorf("invalid JSON schema in format")
-					}
-					request["grammar"] = string(g)
-				}
+		switch string(req.Format) {
+		case `null`, `""`:
+			// Field was set, but "missing" a value. We accept
+			// these as "not set".
+			break
+		case `"json"`:
+			request["grammar"] = grammarJSON
+		default:
+			if req.Format[0] != '{' {
+				return fmt.Errorf("invalid format: %q; expected \"json\" or a valid JSON Schema object", req.Format)
 			}
+
+			// User provided a JSON schema
+			g := llama.SchemaToGrammar(req.Format)
+			if g == nil {
+				return fmt.Errorf("invalid JSON schema in format")
+			}
+			request["grammar"] = string(g)
 		}
 	}
 
diff --git a/runner/ollamarunner/runner.go b/runner/ollamarunner/runner.go
index c8383a5d..c1475cbb 100644
--- a/runner/ollamarunner/runner.go
+++ b/runner/ollamarunner/runner.go
@@ -254,6 +254,12 @@ type Server struct {
 	// multimodalHash generates hashes for comparing equality
 	// of non-text data
 	multimodalHash maphash.Hash
+
+	// vocab is a llama.cpp vocab required for gammar-based
+	// constrained generation (json mode, structured outputs)
+	// TODO: this is temporary until Ollama sampling supports
+	// constrained generation
+	vocab *sample.Vocab
 }
 
 func (s *Server) allNil() bool {
@@ -574,18 +580,25 @@ func (s *Server) completion(w http.ResponseWriter, r *http.Request) {
 		return
 	}
 
+	var grammar *sample.Grammar
+	var err error
+	if req.Grammar != "" {
+		grammar, err = sample.NewGrammar(s.vocab, req.Grammar)
+		if err != nil {
+			http.Error(w, "failed to load model vocabulary required for format", http.StatusInternalServerError)
+			return
+		}
+	}
+
 	sampler := sample.NewSampler(
 		req.Temperature,
 		req.TopK,
 		req.TopP,
 		req.MinP,
 		req.Seed,
+		grammar,
 	)
 
-	if req.Grammar != "" {
-		panic("grammars are not yet supported")
-	}
-
 	seq, err := s.NewSequence(req.Prompt, req.Images, NewSequenceParams{
 		numPredict: req.NumPredict,
 		stop:       req.Stop,
@@ -797,6 +810,8 @@ func (s *Server) loadModel(
 		panic(err)
 	}
 
+	s.vocab = sample.NewVocab(mpath)
+
 	// TODO(jessegross): LoRA loading
 	if lpath.String() != "" {
 		panic("loras are not yet implemented")
diff --git a/sample/samplers.go b/sample/samplers.go
index a5a0507c..a9d90692 100644
--- a/sample/samplers.go
+++ b/sample/samplers.go
@@ -2,43 +2,88 @@ package sample
 
 import (
 	"errors"
+	"math"
 	"math/rand/v2"
 	"slices"
+	"sync"
+
+	"github.com/ollama/ollama/llama"
 )
 
-// Sampler is not thread-safe. Each goroutine should have its own instance
-type Sampler interface {
-	Sample([]float32) (int32, error)
-}
-
-// logit represents information about a single token during sampling
-type logit struct {
+// token represents information about a single token during sampling
+type token struct {
 	id    int32   // The token's unique identifier
 	value float32 // The raw logit or probability from the model
 }
 
-type weighted struct {
+type Sampler struct {
 	rng         *rand.Rand
-	tokens      []logit
 	topK        int
 	topP        float32
 	minP        float32
 	temperature float32
+	grammar     *Grammar
 }
 
-func (s *weighted) Sample(logits []float32) (int32, error) {
-	if len(s.tokens) < len(logits) {
-		s.tokens = make([]logit, len(logits))
-	}
-
-	tokens := s.tokens[:len(logits)]
-
-	for i, v := range logits {
+func (s *Sampler) Sample(logits []float32) (int32, error) {
+	tokens := make([]token, len(logits))
+	for i := range logits {
 		tokens[i].id = int32(i)
-		tokens[i].value = v
+		tokens[i].value = logits[i]
+	}
+
+	t, err := s.sample(tokens)
+	if err != nil {
+		return -1, err
+	}
+
+	if s.grammar != nil {
+		// optimization: first check if the max logit is accepted by the grammar
+		// if the max logit is rejected, apply the grammar to all logits (slower)
+		top := []token{t}
+		s.grammar.Apply(top)
+		if !math.IsInf(float64(top[0].value), -1) {
+			s.grammar.Accept(top[0].id)
+			return top[0].id, nil
+		}
+
+		// since .sample has side effects of modifying the tokens
+		// we need to reset them before applying the grammar and
+		// sampling again
+		for i := range logits {
+			tokens[i].id = int32(i)
+			tokens[i].value = logits[i]
+		}
+		s.grammar.Apply(tokens)
+		t, err = s.sample(tokens)
+		if err != nil {
+			return -1, err
+		}
+		s.grammar.Accept(t.id)
+	}
+
+	return t.id, nil
+}
+
+// greedy returns the highest probability token from the tokens
+func greedy(tokens []token) token {
+	max := tokens[0]
+	for i := 1; i < len(tokens); i++ {
+		if tokens[i].value > max.value {
+			max = tokens[i]
+		}
+	}
+
+	return max
+}
+
+// sample returns the highest probability token from the tokens
+// given sampler parameters. It also has side effects of modifying the tokens
+func (s *Sampler) sample(tokens []token) (token, error) {
+	if s.temperature == 0 {
+		return greedy(tokens), nil
 	}
 
-	// Tokens are sorted by logits in TopK or SortTokens
 	if s.topK > 0 {
 		tokens = topK(tokens, s.topK)
 	} else {
@@ -47,12 +92,14 @@ func (s *weighted) Sample(logits []float32) (int32, error) {
 
 	tokens = temperature(tokens, s.temperature)
 	tokens = softmax(tokens)
-
 	tokens = topP(tokens, s.topP)
 	tokens = minP(tokens, s.minP)
 
+	// TODO: this should fall back to greedy sampling
+	// or topP, topK values etc should be such that
+	// there are always tokens to sample from
 	if len(tokens) == 0 {
-		return -1, errors.New("no valid logits found for weighted sampling")
+		return token{}, errors.New("no tokens to sample from")
 	}
 
 	var r float32
@@ -70,48 +117,18 @@ func (s *weighted) Sample(logits []float32) (int32, error) {
 	}
 	r *= tokens[len(tokens)-1].value
 
-	idx, _ := slices.BinarySearchFunc(tokens, r, func(token logit, target float32) int {
-		// Compare cumulative probabilities
+	idx, _ := slices.BinarySearchFunc(tokens, r, func(token token, target float32) int {
 		if token.value < target {
 			return -1
 		}
-		// First token that exceeds target
 		return 1
 	})
 
-	if idx >= len(tokens) {
-		idx = len(tokens) - 1
-	}
-
-	return tokens[idx].id, nil
-}
-
-type greedy struct{}
-
-// Greedy sample returns the index of the maximum value in logits.
-func (s greedy) Sample(logits []float32) (int32, error) {
-	if len(logits) == 0 {
-		return -1, errors.New("no logits provided for greedy sampling")
-	}
-
-	maxIdx := 0
-	maxVal := logits[0]
-	for i := 1; i < len(logits); i++ {
-		if logits[i] > maxVal {
-			maxVal = logits[i]
-			maxIdx = i
-		}
-	}
-
-	return int32(maxIdx), nil
+	return tokens[idx], nil
 }
 
 // TODO(parthsareen): update sampler interface to use json unmarshal https://github.com/ollama/ollama/issues/9278
-func NewSampler(temperature float32, topK int, topP float32, minP float32, seed int) Sampler {
-	if temperature == 0 {
-		return &greedy{}
-	}
-
+func NewSampler(temperature float32, topK int, topP float32, minP float32, seed int, grammar *Grammar) Sampler {
 	var rng *rand.Rand
 	if seed != -1 {
 		// PCG requires two parameters: sequence and stream
@@ -120,7 +137,9 @@ func NewSampler(temperature float32, topK int, topP float32, minP float32, seed
 		// Use golden ratio hash to generate statistically independent seeds
 		rng = rand.New(rand.NewPCG(sequence, sequence^0x9E3779B9))
 	}
-	temperature = max(temperature, 1)
+	if temperature < 0.0 {
+		temperature = 0.0
+	}
 
 	if topP < 0.0 {
 		topP = 0.0
@@ -136,11 +155,73 @@ func NewSampler(temperature float32, topK int, topP float32, minP float32, seed
 		minP = 1.0
 	}
 
-	return &weighted{
+	return Sampler{
 		rng:         rng,
 		topK:        topK,
 		topP:        topP,
 		minP:        minP,
 		temperature: temperature,
+		grammar:     grammar,
 	}
 }
+
+type Grammar struct {
+	vocab   *Vocab
+	grammar string
+	sampler *llama.Sampler
+}
+
+func NewGrammar(vocab *Vocab, grammar string) (*Grammar, error) {
+	v, err := vocab.Load()
+	if err != nil {
+		return nil, err
+	}
+
+	return &Grammar{
+		vocab:   vocab,
+		grammar: grammar,
+		sampler: llama.NewGrammarSampler(v, grammar),
+	}, nil
+}
+
+func (g *Grammar) Apply(tokens []token) {
+	tds := make([]llama.TokenData, len(tokens))
+	for i, token := range tokens {
+		tds[i].Id = token.id
+		tds[i].Logit = token.value
+	}
+
+	g.sampler.Apply(tds)
+
+	for i := range tokens {
+		tokens[i].value = tds[i].Logit
+	}
+}
+
+func (g *Grammar) Accept(token int32) {
+	g.sampler.Accept(token)
+}
+
+type Vocab struct {
+	once  sync.Once
+	vocab *llama.Vocab
+	err   error
+	path  string
+}
+
+func NewVocab(path string) *Vocab {
+	return &Vocab{path: path}
+}
+
+// Load returns the lazily-loaded vocabulary
+func (v *Vocab) Load() (*llama.Vocab, error) {
+	v.once.Do(func() {
+		vocab, err := llama.LoadVocabFromFile(v.path)
+		if err != nil {
+			v.err = err
+			return
+		}
+		v.vocab = vocab
+	})
+	return v.vocab, v.err
+}
diff --git a/sample/samplers_benchmark_test.go b/sample/samplers_benchmark_test.go
index 41c0b487..cd138014 100644
--- a/sample/samplers_benchmark_test.go
+++ b/sample/samplers_benchmark_test.go
@@ -16,13 +16,10 @@ func BenchmarkWeightedSampler(b *testing.B) {
 				logits[i] = float32(rand.Float64()*10 - 5)
 			}
 
-			sampler := NewSampler(0.8, 0, 0, 0, 42)
+			sampler := NewSampler(0.8, 0, 0, 0, 42, nil)
 			b.ResetTimer()
 			for b.Loop() {
-				_, err := sampler.Sample(logits)
-				if err != nil {
-					b.Fatalf("Sampling failed: %v", err)
-				}
+				sampler.Sample(logits)
 			}
 		})
 	}
@@ -52,30 +49,24 @@ func BenchmarkWeightedSampler(b *testing.B) {
 
 	for _, tc := range configs {
 		b.Run("Config"+tc.name, func(b *testing.B) {
-			sampler := NewSampler(tc.temperature, tc.topK, tc.topP, tc.minP, tc.seed)
+			sampler := NewSampler(tc.temperature, tc.topK, tc.topP, tc.minP, tc.seed, nil)
 			sampler.Sample(logits)
 
 			b.ResetTimer()
 
 			for b.Loop() {
-				_, err := sampler.Sample(logits)
-				if err != nil {
-					b.Fatalf("Sampling failed: %v", err)
-				}
+				sampler.Sample(logits)
 			}
 		})
 	}
 
 	// Test with combined transforms separately - topK influences performance greatly
 	b.Run("TransformCombined", func(b *testing.B) {
-		sampler := NewSampler(0.8, 50, 0.9, 0.05, 42)
+		sampler := NewSampler(0.8, 50, 0.9, 0.05, 42, nil)
 		b.ResetTimer()
 
 		for b.Loop() {
-			_, err := sampler.Sample(logits)
-			if err != nil {
-				b.Fatalf("Sampling failed: %v", err)
-			}
+			sampler.Sample(logits)
 		}
 	})
 }
@@ -90,14 +81,11 @@ func BenchmarkGreedySampler(b *testing.B) {
 				logits[i] = float32(rand.Float64()*10 - 5)
 			}
 
-			sampler := NewSampler(0, -1, 0, 0, -1)
+			sampler := NewSampler(0, -1, 0, 0, -1, nil)
 			b.ResetTimer()
 
 			for b.Loop() {
-				_, err := sampler.Sample(logits)
-				if err != nil {
-					b.Fatalf("Sampling failed: %v", err)
-				}
+				sampler.Sample(logits)
 			}
 		})
 	}
diff --git a/sample/samplers_test.go b/sample/samplers_test.go
index dbbee17b..38b9b352 100644
--- a/sample/samplers_test.go
+++ b/sample/samplers_test.go
@@ -7,7 +7,7 @@ import (
 
 func TestWeighted(t *testing.T) {
 	logits := []float32{-10, 3, -10, -10}
-	sampler := NewSampler(0, 0, 0, 0, 0)
+	sampler := NewSampler(0, 0, 0, 0, 0, nil)
 	got, err := sampler.Sample(logits)
 	if err != nil {
 		t.Error(err)
@@ -19,7 +19,7 @@ func TestWeighted(t *testing.T) {
 	}
 
 	logits = []float32{-100, -10, 0, 10}
-	sampler = NewSampler(0, 0, 0, 0, 0)
+	sampler = NewSampler(0, 0, 0, 0, 0, nil)
 	got, err = sampler.Sample(logits)
 	if err != nil {
 		t.Error(err)
@@ -31,94 +31,10 @@ func TestWeighted(t *testing.T) {
 	}
 }
 
-func TestNewSampler(t *testing.T) {
-	tests := []struct {
-		name        string
-		temperature float32
-		topK        int
-		topP        float32
-		minP        float32
-		seed        int
-		wantGreedy  bool // Instead of wantErr, check if we get greedy sampler
-	}{
-		{
-			name:        "temperature",
-			temperature: 0.5,
-			wantGreedy:  false,
-		},
-		{
-			name:        "zero temperature - greedy",
-			temperature: 0,
-			wantGreedy:  true,
-		},
-		{
-			name:        "top k",
-			temperature: 0.1,
-			topK:        10,
-			wantGreedy:  false,
-		},
-		{
-			name:        "top p",
-			temperature: 0.1,
-			topP:        0.9,
-			wantGreedy:  false,
-		},
-		{
-			name:        "min p",
-			temperature: 0.1,
-			minP:        0.2,
-			wantGreedy:  false,
-		},
-		{
-			name:        "seed - weighted",
-			temperature: 0.1,
-			seed:        42,
-			wantGreedy:  false,
-		},
-		{
-			name:        "default values",
-			temperature: 0.8,
-			topK:        40,
-			topP:        0.9,
-			minP:        0.0,
-			seed:        0,
-			wantGreedy:  false,
-		},
-		{
-			name:        "all zeroes - greedy",
-			temperature: 0.0,
-			topK:        0,
-			topP:        0.0,
-			minP:        0.0,
-			seed:        0,
-			wantGreedy:  true,
-		},
-		{
-			name:        "all transforms",
-			temperature: 0.8,
-			topK:        50,
-			topP:        0.95,
-			minP:        0.1,
-			seed:        42,
-			wantGreedy:  false,
-		},
-	}
-	for _, tt := range tests {
-		t.Run(tt.name, func(t *testing.T) {
-			sampler := NewSampler(tt.temperature, tt.topK, tt.topP, tt.minP, tt.seed)
-			_, isGreedy := sampler.(*greedy)
-			if isGreedy != tt.wantGreedy {
-				t.Errorf("NewSampler() got greedy = %v, want %v", isGreedy, tt.wantGreedy)
-			}
-		})
-	}
-}
-
 func BenchmarkSample(b *testing.B) {
-	weighted := NewSampler(0.5, 10, 0.9, 0.2, -1)
 	samplers := map[string]Sampler{
-		"Greedy":   NewSampler(0, 0, 0, 0, 0), // Use NewSampler with temp=0 for greedy
-		"Weighted": weighted,
+		"Greedy":   NewSampler(0, 0, 0, 0, 0, nil), // Use NewSampler with temp=0 for greedy
+		"Weighted": NewSampler(0.5, 10, 0.9, 0.2, -1, nil),
 	}
 
 	// Generate random logits for benchmarking
@@ -132,7 +48,7 @@ func BenchmarkSample(b *testing.B) {
 			b.ResetTimer()
 			for b.Loop() {
 				if _, err := s.Sample(logits); err != nil {
-					b.Error(err)
+					b.Fatalf("error sampling: %v", err)
 				}
 			}
 		})
diff --git a/sample/transforms.go b/sample/transforms.go
index f1f4f3b1..49625297 100644
--- a/sample/transforms.go
+++ b/sample/transforms.go
@@ -5,7 +5,7 @@ import (
 	"slices"
 )
 
-func softmax(ts []logit) []logit {
+func softmax(ts []token) []token {
 	var sum float32
 	for i, v := range ts {
 		ts[i].value = float32(math.Exp(float64(v.value)))
@@ -19,7 +19,7 @@ func softmax(ts []logit) []logit {
 	return ts
 }
 
-func temperature(ti []logit, t float32) []logit {
+func temperature(ti []token, t float32) []token {
 	if t == 1 {
 		return ti
 	}
@@ -51,7 +51,7 @@ func temperature(ti []logit, t float32) []logit {
 // 1. Finds the smallest value between the node and its children
 // 2. If the node is not the smallest, swaps it with its smallest child
 // 3. Continues this process down the affected path until the min-heap property is restored
-func siftDown(data []logit, start, end int) {
+func siftDown(data []token, start, end int) {
 	root := start
 	for {
 		child := 2*root + 1
@@ -73,7 +73,7 @@ func siftDown(data []logit, start, end int) {
 }
 
 // topK limits the number of tokens considered to the k highest logits
-func topK(ts []logit, k int) []logit {
+func topK(ts []token, k int) []token {
 	if k >= len(ts) {
 		return ts
 	}
@@ -99,7 +99,7 @@ func topK(ts []logit, k int) []logit {
 }
 
 // topP limits tokens to those with cumulative probability p
-func topP(ts []logit, p float32) []logit {
+func topP(ts []token, p float32) []token {
 	if p == 1.0 {
 		return ts
 	}
@@ -118,7 +118,7 @@ func topP(ts []logit, p float32) []logit {
 }
 
 // minP limits tokens to those with cumulative probability p
-func minP(ts []logit, p float32) []logit {
+func minP(ts []token, p float32) []token {
 	if p == 1.0 {
 		return ts
 	}
@@ -146,7 +146,7 @@ func minP(ts []logit, p float32) []logit {
 
 // TODO(parthsareen): possibly replace with simpler implementation https://github.com/ollama/ollama/issues/9584
 // Conting sort implementation to sort tokens by logits
-func sortLogits(tokens []logit) {
+func sortLogits(tokens []token) {
 	if len(tokens) <= 1 {
 		return
 	}
@@ -187,7 +187,7 @@ func sortLogits(tokens []logit) {
 	}
 
 	// Second pass: place elements in correct position
-	output := make([]logit, len(tokens))
+	output := make([]token, len(tokens))
 	// Track current positions
 	countsCopy := counts
 
diff --git a/sample/transforms_test.go b/sample/transforms_test.go
index 950d79b3..1065231d 100644
--- a/sample/transforms_test.go
+++ b/sample/transforms_test.go
@@ -7,10 +7,10 @@ import (
 )
 
 // Helper to convert float64 slice to logit slice
-func toLogits(values []float64) []logit {
-	tokens := make([]logit, len(values))
+func toTokens(values []float64) []token {
+	tokens := make([]token, len(values))
 	for i, v := range values {
-		tokens[i] = logit{
+		tokens[i] = token{
 			id:    int32(i),
 			value: float32(v),
 		}
@@ -19,7 +19,7 @@ func toLogits(values []float64) []logit {
 }
 
 // Helper to compare logit slices
-func compareLogits(t *testing.T, name string, want []float64, got []logit) {
+func compareLogits(t *testing.T, name string, want []float64, got []token) {
 	t.Helper()
 	if len(want) != len(got) {
 		t.Errorf("%s: length mismatch: want %d, got %d", name, len(want), len(got))
@@ -36,13 +36,13 @@ func TestTemperature(t *testing.T) {
 	input := []float64{2, -1, 4, -3, 1, -2, 0}
 	want := []float64{-4, -10, 0, -14, -6, -12, -8} // (logit - max logit) / temp
 
-	got := temperature(toLogits(input), 0.5)
+	got := temperature(toTokens(input), 0.5)
 	compareLogits(t, "Temperature", want, got)
 }
 
 func TestSoftmax(t *testing.T) {
 	input := []float64{-3, -2, -1, 0, 1, 2, 4}
-	got := softmax(toLogits(input))
+	got := softmax(toTokens(input))
 
 	// Check probabilities sum to 1
 	var sum float32
@@ -65,7 +65,7 @@ func TestTopK(t *testing.T) {
 	input := []float64{-3, -2, -1, 0, 1, 2, 4}
 
 	// Test k=3
-	got := topK(toLogits(input), 3)
+	got := topK(toTokens(input), 3)
 	if len(got) != 3 {
 		t.Errorf("topK(3): wrong length: want 3, got %d", len(got))
 	}
@@ -74,13 +74,13 @@ func TestTopK(t *testing.T) {
 	compareLogits(t, "topK(3)", want, got)
 
 	// Test k > len
-	got = topK(toLogits(input), 10)
+	got = topK(toTokens(input), 10)
 	compareLogits(t, "topK(10)", input, got)
 }
 
 func TestTopP(t *testing.T) {
 	input := []float64{-3, -2, -1, 0, 1, 2, 4}
-	tokens := toLogits(input)
+	tokens := toTokens(input)
 
 	// First apply temperature and softmax to get probabilities
 	tokens = temperature(tokens, 1)
@@ -99,7 +99,7 @@ func TestTopP(t *testing.T) {
 
 func TestMinP(t *testing.T) {
 	input := []float64{-3, -2, -1, 0, 1, 2, 4, 3}
-	tokens := toLogits(input)
+	tokens := toTokens(input)
 
 	// First apply temperature and softmax
 	tokens = temperature(tokens, 1)
@@ -116,7 +116,7 @@ func TestMinP(t *testing.T) {
 
 func TestSortLogits(t *testing.T) {
 	input := []float64{3, 1, 4, 2, -1, 0, -2}
-	tokens := toLogits(input)
+	tokens := toTokens(input)
 
 	sortLogits(tokens)
 
@@ -133,15 +133,15 @@ func TestSortLogits(t *testing.T) {
 
 func BenchmarkTransforms(b *testing.B) {
 	// Generate random logits
-	tokens := make([]logit, 1<<16)
+	tokens := make([]token, 1<<16)
 	for i := range tokens {
-		tokens[i] = logit{
+		tokens[i] = token{
 			id:    int32(i),
 			value: rand.Float32(),
 		}
 	}
 
-	tokensCopy := make([]logit, len(tokens))
+	tokensCopy := make([]token, len(tokens))
 
 	b.Run("Temperature", func(b *testing.B) {
 		b.ResetTimer()

From 96ec8afd091a763762a75b57622759a1d278fa2c Mon Sep 17 00:00:00 2001
From: Sam <sammcj@users.noreply.github.com>
Date: Tue, 11 Mar 2025 03:52:02 +1100
Subject: [PATCH 030/157] docs(tool): add mcp-llm (#9537)

---
 README.md | 1 +
 1 file changed, 1 insertion(+)

diff --git a/README.md b/README.md
index 1162f891..89ff82e2 100644
--- a/README.md
+++ b/README.md
@@ -561,6 +561,7 @@ See the [API documentation](./docs/api.md) for all endpoints.
 - [TextLLaMA](https://github.com/adarshM84/TextLLaMA) A Chrome Extension that helps you write emails, correct grammar, and translate into any language
 - [Simple-Discord-AI](https://github.com/zyphixor/simple-discord-ai)
 - [LLM Telegram Bot](https://github.com/innightwolfsleep/llm_telegram_bot) (telegram bot, primary for RP. Oobabooga-like buttons, [A1111](https://github.com/AUTOMATIC1111/stable-diffusion-webui) API integration e.t.c)
+- [mcp-llm](https://github.com/sammcj/mcp-llm) (MCP Server to allow LLMs to call other LLMs)
 
 ### Supported backends
 

From 757668c42f92acf249677c9b3726bbfb2c1f5593 Mon Sep 17 00:00:00 2001
From: Xiaowei Zhu <33129495+zhu-xiaowei@users.noreply.github.com>
Date: Mon, 10 Mar 2025 18:01:09 +0000
Subject: [PATCH 031/157] docs: add SwiftChat (#9540)

---
 README.md | 3 +++
 1 file changed, 3 insertions(+)

diff --git a/README.md b/README.md
index 89ff82e2..96b25045 100644
--- a/README.md
+++ b/README.md
@@ -276,6 +276,7 @@ See the [API documentation](./docs/api.md) for all endpoints.
 ### Web & Desktop
 
 - [Open WebUI](https://github.com/open-webui/open-webui)
+- [SwiftChat (macOS with ReactNative)](https://github.com/aws-samples/swift-chat)
 - [Enchanted (macOS native)](https://github.com/AugustDev/enchanted)
 - [Hollama](https://github.com/fmaclen/hollama)
 - [Lollms-Webui](https://github.com/ParisNeo/lollms-webui)
@@ -433,6 +434,7 @@ See the [API documentation](./docs/api.md) for all endpoints.
 
 ### Apple Vision Pro
 
+- [SwiftChat](https://github.com/aws-samples/swift-chat) (Cross-platform AI chat app supporting Apple Vision Pro via "Designed for iPad")
 - [Enchanted](https://github.com/AugustDev/enchanted)
 
 ### Database
@@ -510,6 +512,7 @@ See the [API documentation](./docs/api.md) for all endpoints.
 
 ### Mobile
 
+- [SwiftChat](https://github.com/aws-samples/swift-chat) (Lightning-fast Cross-platform AI chat app with native UI for Android, iOS and iPad)
 - [Enchanted](https://github.com/AugustDev/enchanted)
 - [Maid](https://github.com/Mobile-Artificial-Intelligence/maid)
 - [Ollama App](https://github.com/JHubi1/ollama-app) (Modern and easy-to-use multi-platform client for Ollama)

From d8a5d96b981bf6e1c5a61fde18acaeed0fb89f7c Mon Sep 17 00:00:00 2001
From: frob <rick+github@frob.com.au>
Date: Mon, 10 Mar 2025 19:02:54 +0100
Subject: [PATCH 032/157] docs: Add OLLAMA_CONTEXT_LENGTH to FAQ. (#9545)

---
 docs/faq.md | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/docs/faq.md b/docs/faq.md
index 04e8433d..4aaccc2e 100644
--- a/docs/faq.md
+++ b/docs/faq.md
@@ -20,7 +20,7 @@ Please refer to the [GPU docs](./gpu.md).
 
 ## How can I specify the context window size?
 
-By default, Ollama uses a context window size of 2048 tokens.
+By default, Ollama uses a context window size of 2048 tokens. This can be overridden with the `OLLAMA_CONTEXT_LENGTH` environment variable. For example, to set the default context length to 8K, use: `OLLAMA_CONTEXT_LENGTH=8192 ollama serve`.
 
 To change this when using `ollama run`, use `/set parameter`:
 

From 7e34f4fbfa192b3a2334d8fc28e24d69b83064d9 Mon Sep 17 00:00:00 2001
From: Parth Sareen <parth.sareen@ollama.com>
Date: Mon, 10 Mar 2025 14:43:53 -0700
Subject: [PATCH 033/157] sample: add numerical stability to
 temperature/softmax transform (#9631)

---
 sample/samplers.go        |  3 ++-
 sample/transforms.go      | 40 ++++++++++++++++-----------------------
 sample/transforms_test.go | 27 ++++++++++----------------
 3 files changed, 28 insertions(+), 42 deletions(-)

diff --git a/sample/samplers.go b/sample/samplers.go
index a9d90692..aea99b3f 100644
--- a/sample/samplers.go
+++ b/sample/samplers.go
@@ -90,8 +90,9 @@ func (s *Sampler) sample(tokens []token) (token, error) {
 		sortLogits(tokens)
 	}
 
+	// token logit values are updated to probabilities
 	tokens = temperature(tokens, s.temperature)
-	tokens = softmax(tokens)
+
 	tokens = topP(tokens, s.topP)
 	tokens = minP(tokens, s.minP)
 
diff --git a/sample/transforms.go b/sample/transforms.go
index 49625297..ab62455f 100644
--- a/sample/transforms.go
+++ b/sample/transforms.go
@@ -5,13 +5,25 @@ import (
 	"slices"
 )
 
-func softmax(ts []token) []token {
+// temperature applies scaling and softmax to the logits
+func temperature(ts []token, temp float32) []token {
+	// Find max logit for numerical stability
+	maxLogit := float32(math.Inf(-1))
+	for _, t := range ts {
+		if t.value > maxLogit {
+			maxLogit = t.value
+		}
+	}
+
+	// Apply temperature and compute exp(x - max)
+	temp = max(temp, 1e-7)
 	var sum float32
 	for i, v := range ts {
-		ts[i].value = float32(math.Exp(float64(v.value)))
+		ts[i].value = float32(math.Exp(float64((v.value - maxLogit) / temp)))
 		sum += ts[i].value
 	}
 
+	// Normalize
 	for i := range ts {
 		ts[i].value /= sum
 	}
@@ -19,27 +31,6 @@ func softmax(ts []token) []token {
 	return ts
 }
 
-func temperature(ti []token, t float32) []token {
-	if t == 1 {
-		return ti
-	}
-
-	temp := max(t, 1e-7)
-	maxLogit := float32(math.Inf(-1))
-	for _, token := range ti {
-		if token.value > maxLogit {
-			maxLogit = token.value
-		}
-	}
-
-	// subtracting max logit to avoid under/overflow
-	for i := range ti {
-		ti[i].value = (ti[i].value - maxLogit) / temp
-	}
-
-	return ti
-}
-
 // siftDown maintains a min-heap property by recursively moving larger elements down the heap.
 //
 // The heap is represented as an array where for any node at index i:
@@ -145,7 +136,8 @@ func minP(ts []token, p float32) []token {
 }
 
 // TODO(parthsareen): possibly replace with simpler implementation https://github.com/ollama/ollama/issues/9584
-// Conting sort implementation to sort tokens by logits
+// sortLogits sorts implementation to sort tokens by logits using counting sort
+// counting sort is faster than built-in sort for this use case
 func sortLogits(tokens []token) {
 	if len(tokens) <= 1 {
 		return
diff --git a/sample/transforms_test.go b/sample/transforms_test.go
index 1065231d..81e8849b 100644
--- a/sample/transforms_test.go
+++ b/sample/transforms_test.go
@@ -32,17 +32,9 @@ func compareLogits(t *testing.T, name string, want []float64, got []token) {
 	}
 }
 
-func TestTemperature(t *testing.T) {
-	input := []float64{2, -1, 4, -3, 1, -2, 0}
-	want := []float64{-4, -10, 0, -14, -6, -12, -8} // (logit - max logit) / temp
-
+func TestTemperatureAndSoftmax(t *testing.T) {
+	input := []float64{1, 4, -2, 0}
 	got := temperature(toTokens(input), 0.5)
-	compareLogits(t, "Temperature", want, got)
-}
-
-func TestSoftmax(t *testing.T) {
-	input := []float64{-3, -2, -1, 0, 1, 2, 4}
-	got := softmax(toTokens(input))
 
 	// Check probabilities sum to 1
 	var sum float32
@@ -53,11 +45,14 @@ func TestSoftmax(t *testing.T) {
 		t.Errorf("probabilities don't sum to 1: got %f", sum)
 	}
 
-	// Check relative ordering is preserved
-	for i := 1; i < len(got); i++ {
-		if got[i].value < got[i-1].value {
-			t.Errorf("probability ordering not preserved at index %d", i)
-		}
+	got = temperature(toTokens(input), 1)
+	// Check probabilities sum to 1
+	sum = 0.0
+	for _, token := range got {
+		sum += token.value
+	}
+	if math.Abs(float64(sum)-1.0) > 1e-6 {
+		t.Errorf("probabilities don't sum to 1: got %f", sum)
 	}
 }
 
@@ -84,7 +79,6 @@ func TestTopP(t *testing.T) {
 
 	// First apply temperature and softmax to get probabilities
 	tokens = temperature(tokens, 1)
-	tokens = softmax(tokens)
 	sortLogits(tokens)
 
 	// Then apply topP
@@ -103,7 +97,6 @@ func TestMinP(t *testing.T) {
 
 	// First apply temperature and softmax
 	tokens = temperature(tokens, 1)
-	tokens = softmax(tokens)
 
 	// Then apply minP
 	got := minP(tokens, 0.2)

From 8585b7b151c404cc8044eeafe3734e676a0e572a Mon Sep 17 00:00:00 2001
From: Vincent Koc <vincentkoc@ieee.org>
Date: Tue, 11 Mar 2025 10:15:10 +1100
Subject: [PATCH 034/157] docs: add opik to observability integrations (#9626)

---
 README.md | 1 +
 1 file changed, 1 insertion(+)

diff --git a/README.md b/README.md
index 96b25045..b4df5e2a 100644
--- a/README.md
+++ b/README.md
@@ -571,6 +571,7 @@ See the [API documentation](./docs/api.md) for all endpoints.
 - [llama.cpp](https://github.com/ggerganov/llama.cpp) project founded by Georgi Gerganov.
 
 ### Observability
+- [Opik](https://www.comet.com/docs/opik/cookbook/ollama) is an open-source platform to debug, evaluate, and monitor your LLM applications, RAG systems, and agentic workflows with comprehensive tracing, automated evaluations, and production-ready dashboards. Opik supports native intergration to Ollama.
 - [Lunary](https://lunary.ai/docs/integrations/ollama) is the leading open-source LLM observability platform. It provides a variety of enterprise-grade features such as real-time analytics, prompt templates management, PII masking, and comprehensive agent tracing.
 - [OpenLIT](https://github.com/openlit/openlit) is an OpenTelemetry-native tool for monitoring Ollama Applications & GPUs using traces and metrics.
 - [HoneyHive](https://docs.honeyhive.ai/integrations/ollama) is an AI observability and evaluation platform for AI agents. Use HoneyHive to evaluate agent performance, interrogate failures, and monitor quality in production.

From 9926eae01516fa3ab65d60df7dd0b51dceccdebf Mon Sep 17 00:00:00 2001
From: Michael Yang <mxyng@pm.me>
Date: Fri, 7 Mar 2025 18:04:16 -0800
Subject: [PATCH 035/157] fix: pad tensor item if ge zero

this produces a nicer output since both positive and negative values
produces the same width
---
 ml/backend.go | 17 ++++++++++++-----
 1 file changed, 12 insertions(+), 5 deletions(-)

diff --git a/ml/backend.go b/ml/backend.go
index 3abacbf1..641175f0 100644
--- a/ml/backend.go
+++ b/ml/backend.go
@@ -5,6 +5,7 @@ import (
 	"encoding/binary"
 	"fmt"
 	"os"
+	"slices"
 	"strconv"
 	"strings"
 )
@@ -241,16 +242,17 @@ func dump[S ~[]E, E number](ctx Context, t Tensor, items int, fn func(E) string)
 	}
 
 	shape := t.Shape()
+	slices.Reverse(shape)
 
 	var sb strings.Builder
 	var f func([]int, int)
 	f = func(dims []int, stride int) {
 		prefix := strings.Repeat(" ", len(shape)-len(dims)+1)
-		fmt.Fprint(&sb, "[")
-		defer func() { fmt.Fprint(&sb, "]") }()
+		sb.WriteString("[")
+		defer func() { sb.WriteString("]") }()
 		for i := 0; i < dims[0]; i++ {
 			if i >= items && i < dims[0]-items {
-				fmt.Fprint(&sb, "..., ")
+				sb.WriteString("..., ")
 				// skip to next printable element
 				skip := dims[0] - 2*items
 				if len(dims) > 1 {
@@ -265,9 +267,14 @@ func dump[S ~[]E, E number](ctx Context, t Tensor, items int, fn func(E) string)
 					fmt.Fprint(&sb, ",", strings.Repeat("\n", len(dims)-1), prefix)
 				}
 			} else {
-				fmt.Fprint(&sb, fn(s[stride+i]))
+				text := fn(s[stride+i])
+				if len(text) > 0 && text[0] != '-' {
+					sb.WriteString(" ")
+				}
+
+				sb.WriteString(text)
 				if i < dims[0]-1 {
-					fmt.Fprint(&sb, ", ")
+					sb.WriteString(", ")
 				}
 			}
 		}

From 4dcf80167aca16c90bd2d01e0b91473e595ae936 Mon Sep 17 00:00:00 2001
From: Daniel Hiltgen <dhiltgen@users.noreply.github.com>
Date: Tue, 11 Mar 2025 08:34:20 -0700
Subject: [PATCH 036/157] Build release for windows with local script (#9636)

---
 scripts/build_windows.ps1 | 9 +++++----
 1 file changed, 5 insertions(+), 4 deletions(-)

diff --git a/scripts/build_windows.ps1 b/scripts/build_windows.ps1
index 62930d7f..60485df8 100644
--- a/scripts/build_windows.ps1
+++ b/scripts/build_windows.ps1
@@ -80,13 +80,14 @@ function checkEnv() {
 
 
 function buildOllama() {
+    mkdir -Force -path "${script:DIST_DIR}\"
     if ($script:ARCH -ne "arm64") {
         Remove-Item -ea 0 -recurse -force -path "${script:SRC_DIR}\dist\windows-${script:ARCH}"
         New-Item "${script:SRC_DIR}\dist\windows-${script:ARCH}\lib\ollama\" -ItemType Directory -ea 0
 
         & cmake --fresh --preset CPU --install-prefix $script:DIST_DIR
         if ($LASTEXITCODE -ne 0) { exit($LASTEXITCODE)}
-        & cmake --build --preset CPU --parallel $script:JOBS
+        & cmake --build --preset CPU  --config Release --parallel $script:JOBS
         if ($LASTEXITCODE -ne 0) { exit($LASTEXITCODE)}
         & cmake --install build --component CPU --strip
         if ($LASTEXITCODE -ne 0) { exit($LASTEXITCODE)}
@@ -101,7 +102,7 @@ function buildOllama() {
             # to avoid 2022 (or newer) from being used as the default
             & cmake --fresh --preset "CUDA 11" -G "Visual Studio 16 2019" --install-prefix $script:DIST_DIR
             if ($LASTEXITCODE -ne 0) { exit($LASTEXITCODE)}
-            & cmake --build --preset "CUDA 11" --parallel $script:JOBS
+            & cmake --build --preset "CUDA 11"  --config Release --parallel $script:JOBS
             if ($LASTEXITCODE -ne 0) { exit($LASTEXITCODE)}
             & cmake --install build --component "CUDA" --strip
             if ($LASTEXITCODE -ne 0) { exit($LASTEXITCODE)}
@@ -112,7 +113,7 @@ function buildOllama() {
             write-host "Building CUDA v12 backend libraries"
             & cmake --fresh --preset "CUDA 12" --install-prefix $script:DIST_DIR
             if ($LASTEXITCODE -ne 0) { exit($LASTEXITCODE)}
-            & cmake --build --preset "CUDA 12" --parallel $script:JOBS
+            & cmake --build --preset "CUDA 12"  --config Release --parallel $script:JOBS
             if ($LASTEXITCODE -ne 0) { exit($LASTEXITCODE)}
             & cmake --install build --component "CUDA" --strip
             if ($LASTEXITCODE -ne 0) { exit($LASTEXITCODE)}
@@ -131,7 +132,7 @@ function buildOllama() {
             $env:HIPCXX=""
             $env:HIP_PLATFORM=""
             $env:CMAKE_PREFIX_PATH=""
-            & cmake --build --preset "ROCm" --parallel $script:JOBS
+            & cmake --build --preset "ROCm"  --config Release --parallel $script:JOBS
             if ($LASTEXITCODE -ne 0) { exit($LASTEXITCODE)}
             & cmake --install build --component "HIP" --strip
             if ($LASTEXITCODE -ne 0) { exit($LASTEXITCODE)}

From 5f74d1fd47ec396ba40f60aee0a1a585ad0fcb4f Mon Sep 17 00:00:00 2001
From: Patrick Devine <patrick@infrahq.com>
Date: Fri, 7 Feb 2025 15:58:15 -0800
Subject: [PATCH 037/157] gemma2 impl

---
 convert/convert.go                    |  12 ++
 convert/convert_gemma3.go             |  81 ++++++++++
 convert/tokenizer_spm.go              |  70 ++++++--
 fs/ggml/ggml.go                       |  11 +-
 kvcache/causal_test.go                |   2 +-
 ml/backend.go                         |   3 +-
 ml/backend/ggml/ggml.go               |  11 +-
 model/models/gemma2/model.go          | 206 ++++++++++++++++++++++++
 model/models/gemma3/model.go          |  74 +++++++++
 model/models/gemma3/model_text.go     | 193 ++++++++++++++++++++++
 model/models/gemma3/process_image.go  |  57 +++++++
 model/models/llama/model.go           |   7 +-
 model/models/mllama/model_text.go     |   8 +-
 model/models/models.go                |   2 +
 model/process_text.go                 |  13 +-
 model/process_text_spm.go             | 221 ++++++++++++++++++++++++++
 model/process_text_spm_test.go        | 110 +++++++++++++
 model/testdata/gemma2/tokenizer.model | Bin 0 -> 4241003 bytes
 18 files changed, 1057 insertions(+), 24 deletions(-)
 create mode 100644 convert/convert_gemma3.go
 create mode 100644 model/models/gemma2/model.go
 create mode 100644 model/models/gemma3/model.go
 create mode 100644 model/models/gemma3/model_text.go
 create mode 100644 model/models/gemma3/process_image.go
 create mode 100644 model/process_text_spm.go
 create mode 100644 model/process_text_spm_test.go
 create mode 100644 model/testdata/gemma2/tokenizer.model

diff --git a/convert/convert.go b/convert/convert.go
index 015303e7..eb441715 100644
--- a/convert/convert.go
+++ b/convert/convert.go
@@ -15,6 +15,11 @@ import (
 type ModelParameters struct {
 	Architectures []string `json:"architectures"`
 	VocabSize     uint32   `json:"vocab_size"`
+	TextModel     TextParameters `json:"text_config"`
+}
+
+type TextParameters struct {
+	VocabSize     uint32   `json:"vocab_size"`
 }
 
 type AdapterParameters struct {
@@ -185,6 +190,8 @@ func ConvertModel(fsys fs.FS, ws io.WriteSeeker) error {
 		conv = &gemmaModel{}
 	case "Gemma2ForCausalLM":
 		conv = &gemma2Model{}
+	case "Gemma3ForConditionalGeneration":
+		conv = &gemma3Model{}
 	case "Phi3ForCausalLM":
 		conv = &phi3Model{}
 	case "Qwen2ForCausalLM":
@@ -213,6 +220,11 @@ func ConvertModel(fsys fs.FS, ws io.WriteSeeker) error {
 	}
 
 	vocabSize := int(p.VocabSize)
+	if vocabSize == 0 {
+		tVocabSize := int(p.TextModel.VocabSize)
+		vocabSize = tVocabSize
+	}
+
 	switch {
 	case vocabSize > len(t.Vocabulary.Tokens):
 		slog.Warn("vocabulary is smaller than expected, padding with dummy tokens", "expect", vocabSize, "actual", len(t.Vocabulary.Tokens))
diff --git a/convert/convert_gemma3.go b/convert/convert_gemma3.go
new file mode 100644
index 00000000..c2be5570
--- /dev/null
+++ b/convert/convert_gemma3.go
@@ -0,0 +1,81 @@
+package convert
+
+import "github.com/ollama/ollama/fs/ggml"
+
+type gemma3Model struct {
+	gemmaModel
+	TextModel   gemma3TextModel   `json:"text_config"`
+	VisionModel gemma3VisionModel `json:"vision_config"`
+}
+
+type gemma3TextModel struct {
+	MaxPositionEmbeddings uint32  `json:"max_position_embeddings"`
+	HiddenSize            uint32  `json:"hidden_size"`
+	HiddenLayers          uint32  `json:"num_hidden_layers"`
+	IntermediateSize      uint32  `json:"intermediate_size"`
+	NumAttentionHeads     uint32  `json:"num_attention_heads"`
+	NumKeyValueHeads      uint32  `json:"num_key_value_heads"`
+	RMSNormEPS            float32 `json:"rms_norm_eps"`
+	HeadDim               uint32  `json:"head_dim"`
+	SlidingWindow         uint32  `json:"sliding_window"`
+	AttentionLogitSoftcap float32 `json:"attn_logit_softcapping"`
+	FinalLogitSoftcap     float32 `json:"final_logit_softcapping"`
+	RopeLocalTheta        float32 `json:"rope_local_base_freq"`
+	RopeGlobalTheta       float32 `json:"rope_global_base_freq"`
+}
+
+type gemma3VisionModel struct {
+	ImageSize    uint32 `json:"image_size"`
+	NumChannels  uint32 `json:"num_channels"`
+	HiddenLayers uint32 `json:"num_hidden_layers"`
+}
+
+func (p *gemma3Model) KV(t *Tokenizer) ggml.KV {
+	kv := p.ModelParameters.KV(t)
+	kv["general.architecture"] = "gemma3"
+	kv["gemma3.context_length"] = p.TextModel.MaxPositionEmbeddings
+	kv["gemma3.embedding_length"] = p.TextModel.HiddenSize
+	kv["gemma3.block_count"] = p.TextModel.HiddenLayers
+	kv["gemma3.text.feed_forward_length"] = p.TextModel.IntermediateSize
+	kv["gemma3.attention.head_count"] = p.TextModel.NumAttentionHeads
+	kv["gemma3.attention.head_count_kv"] = p.TextModel.NumKeyValueHeads
+	kv["gemma3.text.attention.layer_norm_rms_epsilon"] = p.TextModel.RMSNormEPS
+	kv["gemma3.attention.key_length"] = p.TextModel.HeadDim
+	kv["gemma3.attention.value_length"] = p.TextModel.HeadDim
+	kv["gemma3.text.attention.sliding_window"] = p.TextModel.SlidingWindow
+	kv["gemma3.text.final_logit_softcapping"] = p.TextModel.FinalLogitSoftcap
+	kv["gemma3.text.rope.local.freq_base"] = p.TextModel.RopeLocalTheta
+	kv["gemma3.text.rope.global.freq_base"] = p.TextModel.RopeGlobalTheta
+	kv["tokenizer.ggml.bos_token_id"] = uint32(2)
+	kv["tokenizer.ggml.eot_token_id"] = uint32(1)
+	kv["gemma3.vision.image_size"] = p.VisionModel.ImageSize
+	kv["gemma3.vision.num_channels"] = p.VisionModel.NumChannels
+	kv["gemma3.vision.block_count"] = p.VisionModel.HiddenLayers
+	return kv
+}
+
+func (p *gemma3Model) Replacements() []string {
+	return []string{
+		"lm_head", "output",
+		"model.embed_tokens", "token_embd",
+		"model.norm", "output_norm",
+		"vision_model.vision_model", "v",
+		"language_model.", "",
+		"model.layers", "blk",
+		"encoder.layers", "blk",
+		"vision_tower.vision_model.embeddings", "v",
+		"input_layernorm", "attn_norm",
+		"self_attn.q_proj", "attn_q",
+		"self_attn.q_norm", "attn_q_norm",
+		"self_attn.k_proj", "attn_k",
+		"self_attn.k_norm", "attn_k_norm",
+		"self_attn.v_proj", "attn_v",
+		"self_attn.o_proj", "attn_output",
+		"mlp.gate_proj", "ffn_gate",
+		"mlp.down_proj", "ffn_down",
+		"mlp.up_proj", "ffn_up",
+		"post_attention_layernorm", "post_attention_norm",
+		"pre_feedforward_layernorm", "ffn_norm",
+		"post_feedforward_layernorm", "post_ffw_norm",
+	}
+}
diff --git a/convert/tokenizer_spm.go b/convert/tokenizer_spm.go
index 5e506087..d8a012c0 100644
--- a/convert/tokenizer_spm.go
+++ b/convert/tokenizer_spm.go
@@ -6,7 +6,9 @@ import (
 	"errors"
 	"fmt"
 	"io/fs"
+	"log/slog"
 	"os"
+	"reflect"
 	"slices"
 
 	"google.golang.org/protobuf/proto"
@@ -15,6 +17,8 @@ import (
 )
 
 func parseSentencePiece(fsys fs.FS) (*Vocabulary, error) {
+	slog.Debug("using spm vocabulary")
+
 	ast, err := parseAdditionalSpecialTokens(fsys)
 	if err != nil {
 		return nil, err
@@ -43,8 +47,11 @@ func parseSentencePiece(fsys fs.FS) (*Vocabulary, error) {
 			v.Types = append(v.Types, int32(t))
 		default:
 			tt := int32(sentencepiece.ModelProto_SentencePiece_NORMAL)
-			if slices.Contains(ast, piece.GetPiece()) {
-				tt = int32(sentencepiece.ModelProto_SentencePiece_CONTROL)
+			for _, t := range ast {
+				if t.Content == piece.GetPiece() {
+					tt = int32(sentencepiece.ModelProto_SentencePiece_CONTROL)
+					break
+				}
 			}
 
 			v.Types = append(v.Types, tt)
@@ -78,10 +85,16 @@ func parseSentencePiece(fsys fs.FS) (*Vocabulary, error) {
 		return cmp.Compare(i.id, j.id)
 	})
 
-	n := len(v.Tokens)
-	for i, t := range ts {
-		if t.id != i+n {
-			return nil, fmt.Errorf("invalid token id: %d", t.id)
+	for _, t := range ts {
+		if t.id < len(v.Tokens) {
+			if v.Tokens[t.id] == t.content {
+				slog.Warn("tokenizer", "duplicate token", t.content, "id", t.id)
+				continue
+			}
+			return nil, fmt.Errorf("token mismatch: %s != %s at pos [%d]", t.content, v.Tokens[t.id], t.id)
+		}
+		if t.id != len(v.Tokens) {
+			return nil, fmt.Errorf("invalid token id: [%d] as pos [%d]", t.id, len(v.Tokens))
 		}
 
 		v.Tokens = append(v.Tokens, t.content)
@@ -92,7 +105,15 @@ func parseSentencePiece(fsys fs.FS) (*Vocabulary, error) {
 	return &v, nil
 }
 
-func parseAdditionalSpecialTokens(fsys fs.FS) ([]string, error) {
+type specialToken struct {
+	Content    string `json:"content"`
+	Lstrip     bool   `json:"lstrip"`
+	Normalized bool   `json:"normalized"`
+	Rstrip     bool   `json:"rstrip"`
+	SingleWord bool   `json:"single_word"`
+}
+
+func parseAdditionalSpecialTokens(fsys fs.FS) ([]specialToken, error) {
 	f, err := fsys.Open("special_tokens_map.json")
 	if errors.Is(err, os.ErrNotExist) {
 		return nil, nil
@@ -102,12 +123,43 @@ func parseAdditionalSpecialTokens(fsys fs.FS) ([]string, error) {
 	defer f.Close()
 
 	var m struct {
-		AdditionalSpecialTokens []string `json:"additional_special_tokens"`
+		AdditionalSpecialTokens any `json:"additional_special_tokens"`
 	}
 
 	if err := json.NewDecoder(f).Decode(&m); err != nil {
 		return nil, err
 	}
 
-	return m.AdditionalSpecialTokens, nil
+	var ast []specialToken
+
+	switch st := m.AdditionalSpecialTokens.(type) {
+	case []string:
+		for _, s := range st {
+			ast = append(ast, specialToken{Content: s})
+		}
+	case []any:
+		for _, s := range st {
+			// marshal and unmarshal the object to get the special token
+			tMap := s.(map[string]any)
+			data, err := json.Marshal(tMap)
+			if err != nil {
+				return nil, err
+			}
+
+			var token specialToken
+			err = json.Unmarshal(data, &token)
+			if err != nil {
+				return nil, err
+			}
+
+			ast = append(ast, token)
+		}
+
+	default:
+		slog.Warn("special token", "unknown token", reflect.TypeOf(st))
+	}
+
+	slog.Debug("spm tokenizer", "additional tokens", ast)
+
+	return ast, nil
 }
diff --git a/fs/ggml/ggml.go b/fs/ggml/ggml.go
index 8662c3b0..fe98a71b 100644
--- a/fs/ggml/ggml.go
+++ b/fs/ggml/ggml.go
@@ -124,6 +124,15 @@ func (kv KV) Uints(key string, defaultValue ...[]uint32) []uint32 {
 	return s
 }
 
+func (kv KV) Floats(key string, defaultValue ...[]float32) []float32 {
+	r := keyValue(kv, key, &array{})
+	s := make([]float32, r.size)
+	for i := range r.size {
+		s[i] = float32(r.values[i].(float32))
+	}
+	return s
+}
+
 func keyValue[T string | uint32 | uint64 | float32 | *array | bool](kv KV, key string, defaultValue ...T) T {
 	if !strings.HasPrefix(key, "tokenizer.") && !strings.HasPrefix(key, "general.") {
 		key = kv.Architecture() + "." + key
@@ -476,7 +485,7 @@ func (f GGML) GraphSize(context, batch uint64, kvCacheType string) (kv, partialO
 			// vocab graph
 			4*batch*(embedding+vocab)+embedding*vocab*105/128,
 		)
-	case "gemma", "gemma2":
+	case "gemma", "gemma2", "gemma3":
 		fullOffload = max(
 			4*batch*(embedding+vocab),
 			4*batch*(2+context+context*heads+2*embedding+2*embeddingHeadsK*heads),
diff --git a/kvcache/causal_test.go b/kvcache/causal_test.go
index 22d8efb4..0c9e000e 100644
--- a/kvcache/causal_test.go
+++ b/kvcache/causal_test.go
@@ -445,7 +445,7 @@ func (t *testTensor) Conv2D(ctx ml.Context, weight ml.Tensor, s0, s1, p0, p1, d0
 	panic("not implemented")
 }
 
-func (t *testTensor) RoPE(ctx ml.Context, positionIDs, ropeFactors ml.Tensor, dim uint32, base, scale float32) ml.Tensor {
+func (t *testTensor) RoPE(ctx ml.Context, positionIDs, ropeFactors ml.Tensor, dim, ropeType uint32, base, scale float32) ml.Tensor {
 	panic("not implemented")
 }
 
diff --git a/ml/backend.go b/ml/backend.go
index 641175f0..27c2d14d 100644
--- a/ml/backend.go
+++ b/ml/backend.go
@@ -19,6 +19,7 @@ type Config interface {
 
 	Strings(string, ...[]string) []string
 	Uints(string, ...[]uint32) []uint32
+	Floats(string, ...[]float32) []float32
 }
 
 type Backend interface {
@@ -135,7 +136,7 @@ type Tensor interface {
 	Scale(ctx Context, s float64) Tensor
 
 	Conv2D(ctx Context, weight Tensor, s0, s1, p0, p1, d0, d1 int) Tensor
-	RoPE(ctx Context, positionIDs, ropeFactors Tensor, dim uint32, base, scale float32) Tensor
+	RoPE(ctx Context, positionIDs, ropeFactors Tensor, dim, ropeType uint32, base, scale float32) Tensor
 
 	Tanh(ctx Context) Tensor
 	GELU(ctx Context) Tensor
diff --git a/ml/backend/ggml/ggml.go b/ml/backend/ggml/ggml.go
index 74512f33..8843ae7c 100644
--- a/ml/backend/ggml/ggml.go
+++ b/ml/backend/ggml/ggml.go
@@ -893,10 +893,13 @@ func (t *Tensor) View(ctx ml.Context, offset int, shape ...int) ml.Tensor {
 }
 
 const (
-	ropeTypeNorm C.int = iota
+	ropeTypeNorm   C.int = 0
+	ropeTypeNeox   C.int = 2
+	ropeTypeMrope  C.int = 8
+	ropeTypeVision C.int = 24
 )
 
-func (t *Tensor) RoPE(ctx ml.Context, positionIDs, ropeFactors ml.Tensor, ropeDim uint32, ropeBase, ropeScale float32) ml.Tensor {
+func (t *Tensor) RoPE(ctx ml.Context, positionIDs, ropeFactors ml.Tensor, ropeDim, ropeType uint32, ropeBase, ropeScale float32) ml.Tensor {
 	if ropeFactors == nil {
 		ropeFactors = &Tensor{b: t.b}
 	}
@@ -911,8 +914,8 @@ func (t *Tensor) RoPE(ctx ml.Context, positionIDs, ropeFactors ml.Tensor, ropeDi
 		t: C.ggml_rope_ext(
 			ctx.(*Context).ctx, dequant, positionIDs.(*Tensor).t, ropeFactors.(*Tensor).t,
 			C.int(ropeDim),
-			131072,       // YaRN n_ctx_train
-			ropeTypeNorm, // ROPE_TYPE_NORM
+			C.int(ropeType),
+			131072, // YaRN n_ctx_train
 			C.float(ropeBase),
 			C.float(ropeScale),
 			0.,  // YaRN ext_factor
diff --git a/model/models/gemma2/model.go b/model/models/gemma2/model.go
new file mode 100644
index 00000000..2ad9c568
--- /dev/null
+++ b/model/models/gemma2/model.go
@@ -0,0 +1,206 @@
+package gemma2
+
+import (
+	"math"
+
+	"github.com/ollama/ollama/kvcache"
+	"github.com/ollama/ollama/ml"
+	"github.com/ollama/ollama/ml/nn"
+	"github.com/ollama/ollama/model"
+	"github.com/ollama/ollama/model/input"
+)
+
+type Options struct {
+	hiddenSize, numHeads, numKVHeads int
+	attnKeyLen, attnValLen           int
+	eps, ropeBase, ropeScale         float32
+	attnLogitSoftcap                 float32
+	finalLogitSoftcap                float32
+	largeModelScaling                bool
+}
+
+type Model struct {
+	model.Base
+	model.SentencePieceModel
+
+	TokenEmbedding *nn.Embedding `gguf:"token_embd"`
+	Layers         []Layer       `gguf:"blk"`
+	OutputNorm     *nn.RMSNorm   `gguf:"output_norm"`
+	Output         *nn.Linear    `gguf:"output,alt:token_embd"` // just set to token_embd?
+
+	*Options
+}
+
+const (
+	gemma27BLayerCount = 46
+)
+
+func New(c ml.Config) (model.Model, error) {
+	m := Model{
+		SentencePieceModel: model.NewSentencePieceModel(
+			c.String("tokenizer.ggml.pretokenizer", `(?i:'s|'t|'re|'ve|'m|'ll|'d)|[^\r\n\p{L}\p{N}]?\p{L}+|\p{N}{1,3}| ?[^\s\p{L}\p{N}]+[\r\n]*|\s*[\r\n]+|\s+(?!\S)|\s+`),
+			&model.Vocabulary{
+				Values: c.Strings("tokenizer.ggml.tokens"),
+				Scores: c.Floats("tokenizer.ggml.scores"),
+				Types:  c.Uints("tokenizer.ggml.token_type"),
+				BOS:    int32(c.Uint("tokenizer.ggml.bos_token_id")),
+				EOS:    int32(c.Uint("tokenizer.ggml.eos_token_id")),
+			},
+		),
+		Layers: make([]Layer, c.Uint("block_count")),
+		Options: &Options{
+			hiddenSize:        int(c.Uint("embedding_length")),
+			numHeads:          int(c.Uint("attention.head_count")),
+			numKVHeads:        int(c.Uint("attention.head_count_kv")),
+			attnKeyLen:        int(c.Uint("attention.key_length")),
+			attnValLen:        int(c.Uint("attention.value_length")),
+			eps:               c.Float("attention.layer_norm_rms_epsilon"),
+			ropeBase:          c.Float("rope.freq_base", 10000.0),
+			ropeScale:         c.Float("rope.freq_scale", 1.0),
+			attnLogitSoftcap:  c.Float("attn_logit_softcapping"),
+			finalLogitSoftcap: c.Float("final_logit_softcapping"),
+		},
+	}
+
+	slidingWindowLen := int32(c.Uint("attention.sliding_window"))
+	m.Cache = kvcache.NewWrapperCache(kvcache.NewSWACache(slidingWindowLen, m.Shift), kvcache.NewCausalCache(m.Shift))
+
+	return &m, nil
+}
+
+type SelfAttention struct {
+	Query  *nn.Linear `gguf:"attn_q"`
+	Key    *nn.Linear `gguf:"attn_k"`
+	Value  *nn.Linear `gguf:"attn_v"`
+	Output *nn.Linear `gguf:"attn_output"`
+}
+
+func (sa *SelfAttention) Forward(ctx ml.Context, hiddenState, positionIDs ml.Tensor, cache kvcache.Cache, opts *Options) ml.Tensor {
+	batchSize := hiddenState.Dim(1)
+	ropeType := uint32(2)
+
+	q := sa.Query.Forward(ctx, hiddenState)
+	q = q.Reshape(ctx, opts.attnKeyLen, opts.numHeads, batchSize)
+	q = q.RoPE(ctx, positionIDs, nil, uint32(opts.attnKeyLen), ropeType, opts.ropeBase, opts.ropeScale)
+
+	if opts.largeModelScaling {
+		q = q.Scale(ctx, 1.0/math.Sqrt(float64(opts.hiddenSize / opts.numHeads)))
+	} else {
+		q = q.Scale(ctx, 1.0/math.Sqrt(float64(opts.attnKeyLen)))
+	}
+
+	k := sa.Key.Forward(ctx, hiddenState)
+	k = k.Reshape(ctx, opts.attnKeyLen, opts.numKVHeads, batchSize)
+	k = k.RoPE(ctx, positionIDs, nil, uint32(opts.attnKeyLen), ropeType, opts.ropeBase, opts.ropeScale)
+
+	v := sa.Value.Forward(ctx, hiddenState)
+	v = v.Reshape(ctx, opts.attnValLen, opts.numKVHeads, batchSize)
+
+	cache.Put(ctx, k, v)
+	k, v, mask := cache.Get(ctx)
+
+	q = q.Permute(ctx, 0, 2, 1, 3).Contiguous(ctx)
+	k = k.Permute(ctx, 0, 2, 1, 3).Contiguous(ctx)
+	v = v.Permute(ctx, 1, 2, 0, 3).Contiguous(ctx)
+
+	kq := k.Mulmat(ctx, q)
+
+	// logit softcap
+	kq = kq.Scale(ctx, 1.0/float64(opts.attnLogitSoftcap))
+	kq = kq.Tanh(ctx)
+	kq = kq.Scale(ctx, float64(opts.attnLogitSoftcap))
+
+	kq = kq.Add(ctx, mask)
+	kq = kq.Softmax(ctx)
+
+	kqv := v.Mulmat(ctx, kq)
+	kqv = kqv.Permute(ctx, 0, 2, 1, 3).Contiguous(ctx)
+	kqv = kqv.Reshape(ctx, opts.attnValLen*opts.numHeads, batchSize)
+
+	return sa.Output.Forward(ctx, kqv)
+}
+
+func (m *Model) Shift(ctx ml.Context, layer int, key, shift ml.Tensor) (ml.Tensor, error) {
+	return key.RoPE(ctx, shift, nil, uint32(m.Options.attnKeyLen), uint32(2), m.Options.ropeBase, m.Options.ropeScale), nil
+}
+
+type MLP struct {
+	Up   *nn.Linear `gguf:"ffn_up"`
+	Down *nn.Linear `gguf:"ffn_down"`
+	Gate *nn.Linear `gguf:"ffn_gate"`
+}
+
+func (mlp *MLP) Forward(ctx ml.Context, hiddenState ml.Tensor, opts *Options) ml.Tensor {
+	hiddenState = mlp.Gate.Forward(ctx, hiddenState).GELU(ctx).Mul(ctx, mlp.Up.Forward(ctx, hiddenState))
+	return mlp.Down.Forward(ctx, hiddenState)
+}
+
+type Layer struct {
+	AttentionNorm     *nn.RMSNorm `gguf:"attn_norm"`
+	SelfAttention     *SelfAttention
+	PostAttentionNorm *nn.RMSNorm `gguf:"post_attention_norm"`
+	MLPNorm           *nn.RMSNorm `gguf:"ffn_norm"`
+	MLP               *MLP
+	PostMLPNorm       *nn.RMSNorm `gguf:"post_ffw_norm"`
+}
+
+func (l *Layer) Forward(ctx ml.Context, hiddenState, positionIDs ml.Tensor, cache kvcache.Cache, opts *Options) ml.Tensor {
+	residual := hiddenState
+
+	hiddenState = l.AttentionNorm.Forward(ctx, hiddenState, opts.eps)
+	hiddenState = l.SelfAttention.Forward(ctx, hiddenState, positionIDs, cache, opts)
+	hiddenState = l.PostAttentionNorm.Forward(ctx, hiddenState, opts.eps)
+	hiddenState = hiddenState.Add(ctx, residual)
+	residual = hiddenState
+
+	hiddenState = l.MLPNorm.Forward(ctx, hiddenState, opts.eps)
+	hiddenState = l.MLP.Forward(ctx, hiddenState, opts)
+	hiddenState = l.PostMLPNorm.Forward(ctx, hiddenState, opts.eps)
+	return hiddenState.Add(ctx, residual)
+}
+
+func (m *Model) Forward(ctx ml.Context, opts input.Options) (ml.Tensor, error) {
+	inputs, err := ctx.Input().FromIntSlice(opts.Inputs, len(opts.Inputs))
+	if err != nil {
+		return nil, err
+	}
+
+	positions, err := ctx.Input().FromIntSlice(opts.Positions, len(opts.Positions))
+	if err != nil {
+		return nil, err
+	}
+
+	hiddenState := m.TokenEmbedding.Forward(ctx, inputs)
+	hiddenState = hiddenState.Scale(ctx, math.Sqrt(float64(m.Options.hiddenSize)))
+
+	if len(m.Layers) == gemma27BLayerCount {
+		m.Options.largeModelScaling = true
+	}
+
+	for i, layer := range m.Layers {
+		cacheType := i % 2
+		m.Cache.SetLayer(i)
+		wc := m.Cache.(*kvcache.WrapperCache)
+		wc.SetLayerType(cacheType)
+		hiddenState = layer.Forward(ctx, hiddenState, positions, m.Cache, m.Options)
+	}
+
+	hiddenState = m.OutputNorm.Forward(ctx, hiddenState, m.eps)
+	hiddenState = m.Output.Forward(ctx, hiddenState)
+
+	// final logit softcap
+	hiddenState = hiddenState.Scale(ctx, 1.0/float64(m.Options.finalLogitSoftcap))
+	hiddenState = hiddenState.Tanh(ctx)
+	hiddenState = hiddenState.Scale(ctx, float64(m.Options.finalLogitSoftcap))
+
+	outputs, err := ctx.Output().FromIntSlice(opts.Outputs, len(opts.Outputs))
+	if err != nil {
+		return nil, err
+	}
+
+	return hiddenState.Rows(ctx, outputs), nil
+}
+
+func init() {
+	model.Register("gemma2", New)
+}
diff --git a/model/models/gemma3/model.go b/model/models/gemma3/model.go
new file mode 100644
index 00000000..0f4944a4
--- /dev/null
+++ b/model/models/gemma3/model.go
@@ -0,0 +1,74 @@
+package gemma3
+
+import (
+	"fmt"
+
+	"github.com/ollama/ollama/kvcache"
+	"github.com/ollama/ollama/ml"
+	"github.com/ollama/ollama/model"
+	"github.com/ollama/ollama/model/input"
+)
+
+type Model struct {
+	model.Base
+	model.SentencePieceModel
+
+	//*VisionModel `gguf:"v,vision"`
+	*TextModel
+
+	//Projector *nn.Linear `gguf:"mm.0"`
+
+	ImageProcessor
+}
+
+func New(c ml.Config) (model.Model, error) {
+	// Verify unified config
+	if c.Uint("vision.block_count") == 0 {
+		return nil, fmt.Errorf("non-unified vision model not supported")
+	}
+	m := Model{
+		SentencePieceModel: model.NewSentencePieceModel(
+			c.String("tokenizer.ggml.pretokenizer", `(?i:'s|'t|'re|'ve|'m|'ll|'d)|[^\r\n\p{L}\p{N}]?\p{L}+|\p{N}{1,3}| ?[^\s\p{L}\p{N}]+[\r\n]*|\s*[\r\n]+|\s+(?!\S)|\s+`),
+			&model.Vocabulary{
+				Values: c.Strings("tokenizer.ggml.tokens"),
+				Scores: c.Floats("tokenizer.ggml.scores"),
+				Types:  c.Uints("tokenizer.ggml.token_type"),
+				BOS:    int32(c.Uint("tokenizer.ggml.bos_token_id")),
+				AddBOS: c.Bool("tokenizer.ggml.add_bos_token", true),
+				EOS:    int32(c.Uint("tokenizer.ggml.eos_token_id")),
+				AddEOS: c.Bool("tokenizer.ggml.add_eos_token", false),
+			},
+		),
+		ImageProcessor: newImageProcessor(c),
+		//VisionModel:    newVisionModel(c),
+		TextModel: newTextModel(c),
+	}
+
+	slidingWindowLen := int32(c.Uint("text.attention.sliding_window"))
+	m.Cache = kvcache.NewWrapperCache(kvcache.NewSWACache(slidingWindowLen, m.Shift), kvcache.NewCausalCache(m.Shift))
+
+	return &m, nil
+}
+
+func (m *Model) Forward(ctx ml.Context, opts input.Options) (ml.Tensor, error) {
+	inputs, err := ctx.Input().FromIntSlice(opts.Inputs, len(opts.Inputs))
+	if err != nil {
+		return nil, err
+	}
+
+	positions, err := ctx.Input().FromIntSlice(opts.Positions, len(opts.Positions))
+	if err != nil {
+		return nil, err
+	}
+
+	outputs, err := ctx.Output().FromIntSlice(opts.Outputs, len(opts.Outputs))
+	if err != nil {
+		return nil, err
+	}
+
+	return m.TextModel.Forward(ctx, inputs, positions, outputs, m.Cache), nil
+}
+
+func init() {
+	model.Register("gemma3", New)
+}
diff --git a/model/models/gemma3/model_text.go b/model/models/gemma3/model_text.go
new file mode 100644
index 00000000..051e06c5
--- /dev/null
+++ b/model/models/gemma3/model_text.go
@@ -0,0 +1,193 @@
+package gemma3
+
+import (
+	"math"
+
+	"github.com/ollama/ollama/kvcache"
+	"github.com/ollama/ollama/ml"
+	"github.com/ollama/ollama/ml/nn"
+	"github.com/ollama/ollama/model"
+)
+
+type TextOptions struct {
+	hiddenSize, numHeads, numKVHeads int
+	attnKeyLen, attnValLen           int
+	eps, ropeScale                   float32
+	ropeLocalBase, ropeGlobalBase    float32
+	finalLogitSoftcap                float32
+	largeModelScaling                bool
+}
+
+type TextModel struct {
+	model.Base
+	model.SentencePieceModel
+
+	TokenEmbedding *nn.Embedding `gguf:"token_embd"`
+	Layers         []TextLayer   `gguf:"blk"`
+	OutputNorm     *nn.RMSNorm   `gguf:"output_norm"`
+	Output         *nn.Linear    `gguf:"output,alt:token_embd"`
+
+	*TextOptions
+}
+
+const (
+	gemma27BLayerCount = 46
+)
+
+const (
+	cacheTypeSWA = iota
+	cacheTypeCausal
+)
+
+func newTextModel(c ml.Config) *TextModel {
+	m := TextModel{
+		SentencePieceModel: model.NewSentencePieceModel(
+			c.String("tokenizer.ggml.pretokenizer", `(?i:'s|'t|'re|'ve|'m|'ll|'d)|[^\r\n\p{L}\p{N}]?\p{L}+|\p{N}{1,3}| ?[^\s\p{L}\p{N}]+[\r\n]*|\s*[\r\n]+|\s+(?!\S)|\s+`),
+			&model.Vocabulary{
+				Values: c.Strings("tokenizer.ggml.tokens"),
+				Scores: c.Floats("tokenizer.ggml.scores"),
+				Types:  c.Uints("tokenizer.ggml.token_type"),
+				BOS:    int32(c.Uint("tokenizer.ggml.bos_token_id")),
+				EOS:    int32(c.Uint("tokenizer.ggml.eos_token_id")),
+			},
+		),
+		Layers: make([]TextLayer, c.Uint("block_count")),
+		TextOptions: &TextOptions{
+			hiddenSize:        int(c.Uint("embedding_length")),
+			numHeads:          int(c.Uint("attention.head_count")),
+			numKVHeads:        int(c.Uint("attention.head_count_kv")),
+			attnKeyLen:        int(c.Uint("attention.key_length")),
+			attnValLen:        int(c.Uint("attention.value_length")),
+			eps:               c.Float("text.attention.layer_norm_rms_epsilon"),
+			ropeLocalBase:     c.Float("text.rope.local.freq_base", 10000.0),
+			ropeGlobalBase:    c.Float("text.rope.global.freq_base", 1000000.0),
+			ropeScale:         c.Float("text.rope.freq_scale", 1.0),
+			finalLogitSoftcap: c.Float("text.final_logit_softcapping"),
+		},
+	}
+
+	slidingWindowLen := int32(c.Uint("text.attention.sliding_window"))
+	m.Cache = kvcache.NewWrapperCache(kvcache.NewSWACache(slidingWindowLen, m.Shift), kvcache.NewCausalCache(m.Shift))
+
+	return &m
+}
+
+type TextSelfAttention struct {
+	Query     *nn.Linear  `gguf:"attn_q"`
+	QueryNorm *nn.RMSNorm `gguf:"attn_q_norm"`
+	Key       *nn.Linear  `gguf:"attn_k"`
+	KeyNorm   *nn.RMSNorm `gguf:"attn_k_norm"`
+	Value     *nn.Linear  `gguf:"attn_v"`
+	Output    *nn.Linear  `gguf:"attn_output"`
+}
+
+func (sa *TextSelfAttention) Forward(ctx ml.Context, layer int, hiddenState, positionIDs ml.Tensor, cache kvcache.Cache, opts *TextOptions) ml.Tensor {
+	batchSize := hiddenState.Dim(1)
+	ropeType := uint32(2)
+
+	ropeBase := opts.ropeLocalBase
+	if (layer+1)%6 == 0 {
+		ropeBase = opts.ropeGlobalBase
+	}
+
+	q := sa.Query.Forward(ctx, hiddenState)
+	q = q.Reshape(ctx, opts.attnKeyLen, opts.numHeads, batchSize)
+	q = sa.QueryNorm.Forward(ctx, q, opts.eps)
+	q = q.RoPE(ctx, positionIDs, nil, uint32(opts.attnKeyLen), ropeType, ropeBase, opts.ropeScale)
+
+	if opts.largeModelScaling {
+		q = q.Scale(ctx, 1.0/math.Sqrt(float64(opts.hiddenSize/opts.numHeads)))
+	} else {
+		q = q.Scale(ctx, 1.0/math.Sqrt(float64(opts.attnKeyLen)))
+	}
+
+	k := sa.Key.Forward(ctx, hiddenState)
+	k = k.Reshape(ctx, opts.attnKeyLen, opts.numKVHeads, batchSize)
+	k = sa.KeyNorm.Forward(ctx, k, opts.eps)
+	k = k.RoPE(ctx, positionIDs, nil, uint32(opts.attnKeyLen), ropeType, ropeBase, opts.ropeScale)
+
+	v := sa.Value.Forward(ctx, hiddenState)
+	v = v.Reshape(ctx, opts.attnValLen, opts.numKVHeads, batchSize)
+
+	scaleFactor := 1.0
+	kqv := nn.Attention(ctx, q, k, v, scaleFactor, cache)
+	kqv = kqv.Reshape(ctx, opts.attnValLen*opts.numHeads, batchSize)
+
+	return sa.Output.Forward(ctx, kqv)
+}
+
+func (m *TextModel) Shift(ctx ml.Context, layer int, key, shift ml.Tensor) (ml.Tensor, error) {
+	ropeBase := m.TextOptions.ropeLocalBase
+	if (layer+1)%6 == 0 {
+		ropeBase = m.TextOptions.ropeGlobalBase
+	}
+
+	return key.RoPE(ctx, shift, nil, uint32(m.TextOptions.attnKeyLen), uint32(2), ropeBase, m.TextOptions.ropeScale), nil
+}
+
+type TextMLP struct {
+	Up   *nn.Linear `gguf:"ffn_up"`
+	Down *nn.Linear `gguf:"ffn_down"`
+	Gate *nn.Linear `gguf:"ffn_gate"`
+}
+
+func (mlp *TextMLP) Forward(ctx ml.Context, hiddenState ml.Tensor, opts *TextOptions) ml.Tensor {
+	hiddenState = mlp.Gate.Forward(ctx, hiddenState).GELU(ctx).Mul(ctx, mlp.Up.Forward(ctx, hiddenState))
+	return mlp.Down.Forward(ctx, hiddenState)
+}
+
+type TextLayer struct {
+	AttentionNorm     *nn.RMSNorm `gguf:"attn_norm"`
+	SelfAttention     *TextSelfAttention
+	PostAttentionNorm *nn.RMSNorm `gguf:"post_attention_norm"`
+	MLPNorm           *nn.RMSNorm `gguf:"ffn_norm"`
+	MLP               *TextMLP
+	PostMLPNorm       *nn.RMSNorm `gguf:"post_ffw_norm"`
+}
+
+func (l *TextLayer) Forward(ctx ml.Context, layer int, hiddenState, positionIDs ml.Tensor, cache kvcache.Cache, opts *TextOptions) ml.Tensor {
+	residual := hiddenState
+
+	hiddenState = l.AttentionNorm.Forward(ctx, hiddenState, opts.eps)
+	hiddenState = l.SelfAttention.Forward(ctx, layer, hiddenState, positionIDs, cache, opts)
+	hiddenState = l.PostAttentionNorm.Forward(ctx, hiddenState, opts.eps)
+	hiddenState = hiddenState.Add(ctx, residual)
+	residual = hiddenState
+
+	hiddenState = l.MLPNorm.Forward(ctx, hiddenState, opts.eps)
+	hiddenState = l.MLP.Forward(ctx, hiddenState, opts)
+	hiddenState = l.PostMLPNorm.Forward(ctx, hiddenState, opts.eps)
+	return hiddenState.Add(ctx, residual)
+}
+
+func (m *TextModel) Forward(ctx ml.Context, inputs, positions, outputs ml.Tensor, cache kvcache.Cache) ml.Tensor {
+	hiddenState := m.TokenEmbedding.Forward(ctx, inputs)
+	hiddenState = hiddenState.Scale(ctx, math.Sqrt(float64(m.TextOptions.hiddenSize)))
+
+	if len(m.Layers) == gemma27BLayerCount {
+		m.TextOptions.largeModelScaling = true
+	}
+
+	for i, layer := range m.Layers {
+		// gemma alternates between the sliding window (local) and causal (global)
+		// kv cache every 6 layers
+		cacheType := cacheTypeSWA
+		if (i+1)%6 == 0 {
+			cacheType = cacheTypeCausal
+		}
+		cache.SetLayer(i)
+		wc := cache.(*kvcache.WrapperCache)
+		wc.SetLayerType(cacheType)
+		hiddenState = layer.Forward(ctx, i, hiddenState, positions, cache, m.TextOptions)
+	}
+
+	hiddenState = m.OutputNorm.Forward(ctx, hiddenState, m.eps)
+	hiddenState = m.Output.Forward(ctx, hiddenState)
+
+	// final logit softcap
+	hiddenState = hiddenState.Scale(ctx, 1.0/float64(m.TextOptions.finalLogitSoftcap))
+	hiddenState = hiddenState.Tanh(ctx)
+	hiddenState = hiddenState.Scale(ctx, float64(m.TextOptions.finalLogitSoftcap))
+
+	return hiddenState.Rows(ctx, outputs)
+}
diff --git a/model/models/gemma3/process_image.go b/model/models/gemma3/process_image.go
new file mode 100644
index 00000000..5cf963e8
--- /dev/null
+++ b/model/models/gemma3/process_image.go
@@ -0,0 +1,57 @@
+package gemma3
+
+import (
+	"image"
+
+	"github.com/ollama/ollama/ml"
+	"github.com/ollama/ollama/model/imageproc"
+)
+
+type ImageProcessor struct {
+	imageSize, numChannels int
+}
+
+func newImageProcessor(c ml.Config) ImageProcessor {
+	return ImageProcessor{
+		imageSize:   int(c.Uint("vision.image_size")),
+		numChannels: int(c.Uint("vision.num_channels")),
+	}
+}
+
+func (p *ImageProcessor) pack(img image.Image, mean, std [3]float32) []float32 {
+	var pixelVals []float32
+
+	bounds := img.Bounds()
+	var rVals, gVals, bVals []float32
+	for y := bounds.Min.Y; y < bounds.Max.Y; y++ {
+		for x := bounds.Min.X; x < bounds.Max.X; x++ {
+			c := img.At(x, y)
+			r, g, b, _ := c.RGBA()
+			rVal := float32(r>>8) / 255.0
+			gVal := float32(g>>8) / 255.0
+			bVal := float32(b>>8) / 255.0
+
+			rVal = (rVal - mean[0]) / std[0]
+			gVal = (gVal - mean[1]) / std[1]
+			bVal = (bVal - mean[2]) / std[2]
+
+			rVals = append(rVals, rVal)
+			gVals = append(gVals, gVal)
+			bVals = append(bVals, bVal)
+		}
+	}
+	pixelVals = append(pixelVals, rVals...)
+	pixelVals = append(pixelVals, gVals...)
+	pixelVals = append(pixelVals, bVals...)
+
+	return pixelVals
+}
+
+func (p ImageProcessor) ProcessImage(img image.Image) ([]float32, error) {
+	outputSize := image.Point{p.imageSize, p.imageSize}
+	newImage := imageproc.Composite(img)
+	newImage = imageproc.Resize(newImage, outputSize, imageproc.ResizeBilinear)
+
+	data := p.pack(newImage, imageproc.ImageNetStandardMean, imageproc.ImageNetStandardSTD)
+	return data, nil
+}
diff --git a/model/models/llama/model.go b/model/models/llama/model.go
index 1f27f522..19a2ab8c 100644
--- a/model/models/llama/model.go
+++ b/model/models/llama/model.go
@@ -76,14 +76,15 @@ type SelfAttention struct {
 func (sa *SelfAttention) Forward(ctx ml.Context, hiddenState, positionIDs ml.Tensor, cache kvcache.Cache, opts *Options) ml.Tensor {
 	batchSize := hiddenState.Dim(1)
 	headDim := opts.hiddenSize / opts.numHeads
+	ropeType := uint32(0)
 
 	q := sa.Query.Forward(ctx, hiddenState)
 	q = q.Reshape(ctx, headDim, opts.numHeads, batchSize)
-	q = q.RoPE(ctx, positionIDs, sa.RopeFactors, opts.ropeDim, opts.ropeBase, opts.ropeScale)
+	q = q.RoPE(ctx, positionIDs, sa.RopeFactors, opts.ropeDim, ropeType, opts.ropeBase, opts.ropeScale)
 
 	k := sa.Key.Forward(ctx, hiddenState)
 	k = k.Reshape(ctx, headDim, opts.numKVHeads, batchSize)
-	k = k.RoPE(ctx, positionIDs, sa.RopeFactors, opts.ropeDim, opts.ropeBase, opts.ropeScale)
+	k = k.RoPE(ctx, positionIDs, sa.RopeFactors, opts.ropeDim, ropeType, opts.ropeBase, opts.ropeScale)
 
 	v := sa.Value.Forward(ctx, hiddenState)
 	v = v.Reshape(ctx, headDim, opts.numKVHeads, batchSize)
@@ -96,7 +97,7 @@ func (sa *SelfAttention) Forward(ctx ml.Context, hiddenState, positionIDs ml.Ten
 }
 
 func (m *Model) Shift(ctx ml.Context, layer int, key, shift ml.Tensor) (ml.Tensor, error) {
-	return key.RoPE(ctx, shift, m.Layers[layer].SelfAttention.RopeFactors, m.ropeDim, m.ropeBase, m.ropeScale), nil
+	return key.RoPE(ctx, shift, m.Layers[layer].SelfAttention.RopeFactors, uint32(0), m.ropeDim, m.ropeBase, m.ropeScale), nil
 }
 
 type MLP struct {
diff --git a/model/models/mllama/model_text.go b/model/models/mllama/model_text.go
index 373589f9..40c9a970 100644
--- a/model/models/mllama/model_text.go
+++ b/model/models/mllama/model_text.go
@@ -20,14 +20,15 @@ type TextSelfAttention struct {
 func (sa *TextSelfAttention) Forward(ctx ml.Context, hiddenState, positions, _ ml.Tensor, cache *kvcache.WrapperCache, opts *TextModelOptions) ml.Tensor {
 	batchSize := hiddenState.Dim(1)
 	headDim := opts.hiddenSize / opts.numHeads
+	ropeType := uint32(0)
 
 	query := sa.Query.Forward(ctx, hiddenState)
 	query = query.Reshape(ctx, headDim, opts.numHeads, batchSize)
-	query = query.RoPE(ctx, positions, sa.RopeFactors, opts.ropeDim, opts.ropeBase, opts.ropeScale)
+	query = query.RoPE(ctx, positions, sa.RopeFactors, opts.ropeDim, ropeType, opts.ropeBase, opts.ropeScale)
 
 	key := sa.Key.Forward(ctx, hiddenState)
 	key = key.Reshape(ctx, headDim, opts.numKVHeads, batchSize)
-	key = key.RoPE(ctx, positions, sa.RopeFactors, opts.ropeDim, opts.ropeBase, opts.ropeScale)
+	key = key.RoPE(ctx, positions, sa.RopeFactors, opts.ropeDim,  ropeType, opts.ropeBase, opts.ropeScale)
 
 	value := sa.Value.Forward(ctx, hiddenState)
 	value = value.Reshape(ctx, headDim, opts.numKVHeads, batchSize)
@@ -40,8 +41,9 @@ func (sa *TextSelfAttention) Forward(ctx ml.Context, hiddenState, positions, _ m
 }
 
 func (m *TextModel) Shift(ctx ml.Context, layer int, key, shift ml.Tensor) (ml.Tensor, error) {
+	// This will only get called for layers in the cache, which are just the self attention layers
 	if sa, ok := m.Transformer.Layers[layer].(*TextSelfAttentionDecoderLayer); ok {
-		return key.RoPE(ctx, shift, sa.SelfAttention.RopeFactors, m.ropeDim, m.ropeBase, m.ropeScale), nil
+		return key.RoPE(ctx, shift, sa.SelfAttention.RopeFactors, m.ropeDim, uint32(0), m.ropeBase, m.ropeScale), nil
 	}
 
 	return key, nil
diff --git a/model/models/models.go b/model/models/models.go
index d0b68b32..ce1d2ce0 100644
--- a/model/models/models.go
+++ b/model/models/models.go
@@ -1,6 +1,8 @@
 package models
 
 import (
+	_ "github.com/ollama/ollama/model/models/gemma2"
+	_ "github.com/ollama/ollama/model/models/gemma3"
 	_ "github.com/ollama/ollama/model/models/llama"
 	_ "github.com/ollama/ollama/model/models/mllama"
 )
diff --git a/model/process_text.go b/model/process_text.go
index 0d75a0ed..cd1deb65 100644
--- a/model/process_text.go
+++ b/model/process_text.go
@@ -18,6 +18,15 @@ const (
 	SpecialEOS
 )
 
+const (
+	TOKEN_TYPE_NORMAL = iota + 1
+	TOKEN_TYPE_UNKNOWN
+	TOKEN_TYPE_CONTROL
+	TOKEN_TYPE_USER_DEFINED
+	TOKEN_TYPE_UNUSED
+	TOKEN_TYPE_BYTE
+)
+
 type TextProcessor interface {
 	Encode(s string, addSpecial bool) ([]int32, error)
 	Decode([]int32) (string, error)
@@ -27,7 +36,7 @@ type TextProcessor interface {
 type Vocabulary struct {
 	Values []string
 	Types  []uint32
-	Scores []uint32
+	Scores []float32
 	Merges []string
 
 	BOS, EOS       int32
@@ -76,7 +85,7 @@ func (v *Vocabulary) Decode(id int32) string {
 func (v *Vocabulary) SpecialVocabulary() []string {
 	v.specialOnce.Do(func() {
 		for i := range v.Values {
-			if v.Types[i] == 3 {
+			if v.Types[i] == TOKEN_TYPE_CONTROL {
 				v.special = append(v.special, v.Values[i])
 			}
 		}
diff --git a/model/process_text_spm.go b/model/process_text_spm.go
new file mode 100644
index 00000000..c0bc973f
--- /dev/null
+++ b/model/process_text_spm.go
@@ -0,0 +1,221 @@
+package model
+
+import (
+	"iter"
+	"log/slog"
+	"strings"
+
+	"github.com/dlclark/regexp2"
+	queue "github.com/emirpasic/gods/v2/queues/priorityqueue"
+)
+
+const spmWhitespaceSep = "▁"
+
+func replaceWhitespaceBySeperator(s string) string {
+	return strings.ReplaceAll(s, " ", spmWhitespaceSep)
+}
+
+type SentencePieceModel struct {
+	maxTokenLen int
+	pre         *regexp2.Regexp
+	vocab       *Vocabulary
+}
+
+func NewSentencePieceModel(pre string, vocab *Vocabulary) SentencePieceModel {
+	slog.Debug("Tokens", "num tokens", len(vocab.Values), "vals", vocab.Values[:5], "scores", vocab.Scores[:5], "types", vocab.Types[:5])
+
+	counter := map[int]int{}
+	var maxTokenLen int
+	for cnt := range vocab.Types {
+		switch vocab.Types[cnt] {
+		case TOKEN_TYPE_NORMAL, TOKEN_TYPE_USER_DEFINED, TOKEN_TYPE_UNUSED:
+			maxTokenLen = max(maxTokenLen, len(vocab.Values[cnt]))
+			fallthrough
+		default:
+			counter[int(vocab.Types[cnt])] += 1
+		}
+	}
+
+	slog.Debug("Token counts", "normal", counter[TOKEN_TYPE_NORMAL], "unknown", counter[TOKEN_TYPE_UNKNOWN], "control", counter[TOKEN_TYPE_CONTROL],
+		"user defined", counter[TOKEN_TYPE_USER_DEFINED], "unused", counter[TOKEN_TYPE_UNUSED], "byte", counter[TOKEN_TYPE_BYTE],
+		"max token len", maxTokenLen)
+
+	return SentencePieceModel{
+		maxTokenLen: maxTokenLen,
+		pre:         regexp2.MustCompile(pre, regexp2.Unicode|regexp2.RE2),
+		vocab:       vocab,
+	}
+}
+
+func (spm SentencePieceModel) Is(id int32, special Special) bool {
+	return spm.vocab.Is(id, special)
+}
+
+func (spm *SentencePieceModel) split(s string) iter.Seq[string] {
+	return func(yield func(string) bool) {
+		for m, _ := spm.pre.FindStringMatch(s); m != nil; m, _ = spm.pre.FindNextMatch(m) {
+			if !yield(m.String()) {
+				break
+			}
+		}
+	}
+}
+
+func (spm SentencePieceModel) Encode(s string) ([]int32, error) {
+	fragments := []fragment{{value: s}}
+	for _, special := range spm.vocab.SpecialVocabulary() {
+		// TODO: process special tokens concurrently
+		id := spm.vocab.Encode(special)
+		for i := 0; i < len(fragments); i++ {
+			frag := fragments[i]
+			if len(frag.ids) > 0 {
+				continue
+			}
+
+			var middle []fragment
+			switch i := strings.Index(frag.value, special); {
+			case i < 0:
+				middle = append(middle, frag)
+			case i > 0:
+				middle = append(middle, fragment{value: frag.value[:i]})
+				fallthrough
+			default:
+				middle = append(middle, fragment{value: special, ids: []int32{id}})
+				if rest := frag.value[i+len(special):]; rest != "" {
+					middle = append(middle, fragment{value: rest})
+				}
+			}
+
+			fragments = append(fragments[:i], append(middle, fragments[i+1:]...)...)
+		}
+	}
+	slog.Debug("fragments", "frags", fragments)
+
+	var ids []int32
+	for _, frag := range fragments {
+		if len(frag.ids) > 0 {
+			ids = append(ids, frag.ids...)
+			continue
+		}
+
+		for split := range spm.split(frag.value) {
+			split = replaceWhitespaceBySeperator(split)
+
+			var sb strings.Builder
+			sb.Write([]byte(split))
+			if id := spm.vocab.Encode(sb.String()); id >= 0 {
+				ids = append(ids, id)
+				continue
+			}
+
+			runes := []rune(sb.String())
+			pq := queue.NewWith(func(a, b any) int {
+				priA := a.(*candidate)
+				priB := b.(*candidate)
+				if priA.score > priB.score || (priA.score == priB.score && priA.a < priB.a) {
+					return -1
+				}
+				return 1
+			})
+
+			merges := make([]merge, len(runes))
+			for r := range runes {
+				merges[r] = merge{
+					p:     r - 1,
+					n:     r + 1,
+					runes: []rune{runes[r]},
+				}
+			}
+
+			slog.Debug("tokenizer", "merges", merges)
+
+			pairwise := func(a, b int) *candidate {
+				if a < 0 || b >= len(runes) {
+					return nil
+				}
+
+				left, right := string(merges[a].runes), string(merges[b].runes)
+				if id := spm.vocab.Encode(left + right); id >= 0 {
+					return &candidate{
+						a:     a,
+						b:     b,
+						score: spm.vocab.Scores[id],
+					}
+				}
+				return nil
+			}
+
+			for i := range len(runes) - 1 {
+				if pair := pairwise(i, i+1); pair != nil {
+					pq.Enqueue(pair)
+				}
+			}
+
+			pqv := pq.Values()
+			for _, v := range pqv {
+				e := v.(*candidate)
+				slog.Debug("candidate", "candidate", e)
+			}
+
+			for !pq.Empty() {
+				v, _ := pq.Dequeue()
+				pair := v.(*candidate)
+				left, right := merges[pair.a], merges[pair.b]
+
+				slog.Debug("pair", "left", left, "right", right)
+				if len(left.runes) == 0 || len(right.runes) == 0 {
+					continue
+				}
+
+				merges[pair.a].runes = append(left.runes, right.runes...)
+				merges[pair.b].runes = nil
+				merges[pair.a].n = right.n
+				if right.n < len(merges) {
+					merges[right.n].p = pair.a
+				}
+
+				if pair := pairwise(merges[pair.a].p, pair.a); pair != nil {
+					pq.Enqueue(pair)
+				}
+
+				if pair := pairwise(pair.a, merges[pair.a].n); pair != nil {
+					pq.Enqueue(pair)
+				}
+			}
+
+			slog.Debug("merges", "merges", merges)
+
+			for _, merge := range merges {
+				if len(merge.runes) > 0 {
+					if id := spm.vocab.Encode(string(merge.runes)); id >= 0 {
+						ids = append(ids, id)
+					} else {
+						slog.Debug("missing token", "token", string(merge.runes))
+					}
+				}
+			}
+		}
+	}
+	slog.Debug("encoded", "ids", ids)
+
+	return ids, nil
+}
+
+type candidate struct {
+	a, b  int
+	score float32
+}
+
+func (spm SentencePieceModel) Decode(ids []int32) (string, error) {
+	var sb strings.Builder
+	for _, id := range ids {
+		data := spm.vocab.Decode(id)
+		data = strings.ReplaceAll(data, spmWhitespaceSep, " ")
+		if _, err := sb.WriteString(data); err != nil {
+			return "", err
+		}
+	}
+
+	slog.Debug("decoded", "ids", ids, "text", sb.String())
+	return sb.String(), nil
+}
diff --git a/model/process_text_spm_test.go b/model/process_text_spm_test.go
new file mode 100644
index 00000000..72bd629c
--- /dev/null
+++ b/model/process_text_spm_test.go
@@ -0,0 +1,110 @@
+package model
+
+import (
+	"log/slog"
+	"os"
+	"path/filepath"
+	"slices"
+	"testing"
+
+	"google.golang.org/protobuf/proto"
+
+	"github.com/ollama/ollama/convert/sentencepiece"
+)
+
+func loadSentencePieceVocab(t *testing.T) SentencePieceModel {
+	t.Helper()
+
+	bts, err := os.ReadFile(filepath.Join("testdata", "gemma2", "tokenizer.model"))
+	if err != nil {
+		t.Fatal(err)
+	}
+
+	var spm sentencepiece.ModelProto
+	if err := proto.Unmarshal(bts, &spm); err != nil {
+		t.Fatal(err)
+	}
+
+	preTokenizer := `(?i:'s|'t|'re|'ve|'m|'ll|'d)|[^\r\n\p{L}\p{N}]?\p{L}+|\p{N}{1,3}| ?[^\s\p{L}\p{N}]+[\r\n]*|\s*[\r\n]+|\s+(?!\S)|\s+`
+
+	var v Vocabulary
+
+	for _, piece := range spm.GetPieces() {
+		v.Values = append(v.Values, piece.GetPiece())
+		v.Scores = append(v.Scores, piece.GetScore())
+		switch t := piece.GetType(); t {
+		case sentencepiece.ModelProto_SentencePiece_UNKNOWN,
+			sentencepiece.ModelProto_SentencePiece_CONTROL,
+			sentencepiece.ModelProto_SentencePiece_UNUSED,
+			sentencepiece.ModelProto_SentencePiece_BYTE:
+			v.Types = append(v.Types, uint32(t))
+		default:
+			tt := uint32(sentencepiece.ModelProto_SentencePiece_NORMAL)
+			// todo parse the special tokens file
+			//   - this will roundtrip correctly but the <start_of_turn> and
+			//     <end_of_turn> tokens aren't processed
+			v.Types = append(v.Types, tt)
+		}
+	}
+
+	return NewSentencePieceModel(preTokenizer, &v)
+}
+
+func TestSentencePieceEncode(t *testing.T) {
+	logger := slog.New(slog.NewTextHandler(os.Stdout, &slog.HandlerOptions{Level: slog.LevelDebug}))
+	slog.SetDefault(logger)
+
+	tokenizer := loadSentencePieceVocab(t)
+
+	t.Run("basic roundtrip", func(t *testing.T) {
+		t.Parallel()
+
+		cases := []string{
+			"hello",
+			"hello ",
+			"hello  ",
+			" hello",
+			" hello ",
+			" hello  ",
+			"hello world",
+			"请考试我的软件！12345",
+			"你好",
+			"Hello 你好 world!",
+		}
+
+		for _, want := range cases {
+			ids, err := tokenizer.Encode(want)
+			if err != nil {
+				t.Fatal(err)
+			}
+
+			if got, err := tokenizer.Decode(ids); err != nil {
+				t.Fatal(err)
+			} else if got != want {
+				t.Errorf("got %q, want %q [%#v]", got, want, ids)
+			}
+		}
+	})
+
+	t.Run("special tokens", func(t *testing.T) {
+		type candidate struct {
+			token string
+			ids   []int32
+		}
+
+		cases := []candidate{
+			{"<bos>", []int32{2}},
+			{"<eos>", []int32{1}},
+		}
+
+		for _, want := range cases {
+			ids, err := tokenizer.Encode(want.token)
+			if err != nil {
+				t.Fatal(err)
+			}
+			if !slices.Equal(ids, want.ids) {
+				t.Errorf("got %#v, want %#v", ids, want.ids)
+			}
+		}
+	})
+}
diff --git a/model/testdata/gemma2/tokenizer.model b/model/testdata/gemma2/tokenizer.model
new file mode 100644
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HcmV?d00001


From 4b037a97dcc0387d2b94d293d4bd20e7e262d609 Mon Sep 17 00:00:00 2001
From: Michael Yang <mxyng@pm.me>
Date: Thu, 6 Mar 2025 12:16:54 -0800
Subject: [PATCH 038/157] add gemma vision encoder

---
 convert/convert.go                   |   6 +-
 convert/convert_gemma3.go            |  39 ++++--
 ml/backend.go                        |   2 +
 ml/backend/ggml/ggml.go              |   7 ++
 model/models/gemma3/model.go         | 107 +++++++++++++++--
 model/models/gemma3/model_text.go    |   9 +-
 model/models/gemma3/model_vision.go  | 171 +++++++++++++++++++++++++++
 model/models/gemma3/process_image.go |   3 +-
 model/models/mllama/process_image.go |   2 -
 model/process_text_spm.go            |  25 +++-
 10 files changed, 337 insertions(+), 34 deletions(-)
 create mode 100644 model/models/gemma3/model_vision.go

diff --git a/convert/convert.go b/convert/convert.go
index eb441715..cdb0c9e5 100644
--- a/convert/convert.go
+++ b/convert/convert.go
@@ -13,13 +13,13 @@ import (
 )
 
 type ModelParameters struct {
-	Architectures []string `json:"architectures"`
-	VocabSize     uint32   `json:"vocab_size"`
+	Architectures []string       `json:"architectures"`
+	VocabSize     uint32         `json:"vocab_size"`
 	TextModel     TextParameters `json:"text_config"`
 }
 
 type TextParameters struct {
-	VocabSize     uint32   `json:"vocab_size"`
+	VocabSize uint32 `json:"vocab_size"`
 }
 
 type AdapterParameters struct {
diff --git a/convert/convert_gemma3.go b/convert/convert_gemma3.go
index c2be5570..a2b18e29 100644
--- a/convert/convert_gemma3.go
+++ b/convert/convert_gemma3.go
@@ -4,8 +4,17 @@ import "github.com/ollama/ollama/fs/ggml"
 
 type gemma3Model struct {
 	gemmaModel
-	TextModel   gemma3TextModel   `json:"text_config"`
-	VisionModel gemma3VisionModel `json:"vision_config"`
+	TextModel   gemma3TextModel `json:"text_config"`
+	VisionModel struct {
+		NumAttentionHeads uint32  `json:"num_attention_heads"` // attention.head_count 16
+		LayerNormEpsilon  float32 `json:"layer_norm_eps"`      // attention.layer_norm_epsilon 1e-05
+		NumHiddenLayers   uint32  `json:"num_hidden_layers"`   // block_count 32
+		HiddenSize        uint32  `json:"hidden_size"`         // embedding_length 1280
+		IntermediateSize  uint32  `json:"intermediate_size"`   // feed_forward_length 5120
+		ImageSize         uint32  `json:"image_size"`          // image_size 560
+		NumChannels       uint32  `json:"num_channels"`        // num_channels 3
+		PatchSize         uint32  `json:"patch_size"`          // patch_size 14
+	} `json:"vision_config"`
 }
 
 type gemma3TextModel struct {
@@ -24,12 +33,6 @@ type gemma3TextModel struct {
 	RopeGlobalTheta       float32 `json:"rope_global_base_freq"`
 }
 
-type gemma3VisionModel struct {
-	ImageSize    uint32 `json:"image_size"`
-	NumChannels  uint32 `json:"num_channels"`
-	HiddenLayers uint32 `json:"num_hidden_layers"`
-}
-
 func (p *gemma3Model) KV(t *Tokenizer) ggml.KV {
 	kv := p.ModelParameters.KV(t)
 	kv["general.architecture"] = "gemma3"
@@ -46,11 +49,18 @@ func (p *gemma3Model) KV(t *Tokenizer) ggml.KV {
 	kv["gemma3.text.final_logit_softcapping"] = p.TextModel.FinalLogitSoftcap
 	kv["gemma3.text.rope.local.freq_base"] = p.TextModel.RopeLocalTheta
 	kv["gemma3.text.rope.global.freq_base"] = p.TextModel.RopeGlobalTheta
+
+	kv["gemma3.vision.block_count"] = p.VisionModel.NumHiddenLayers
+	kv["gemma3.vision.embedding_length"] = p.VisionModel.HiddenSize
+	kv["gemma3.vision.feed_forward_length"] = p.VisionModel.IntermediateSize
+	kv["gemma3.vision.image_size"] = p.VisionModel.ImageSize
+	kv["gemma3.vision.patch_size"] = p.VisionModel.PatchSize
+	kv["gemma3.vision.num_channels"] = p.VisionModel.NumChannels
+	kv["gemma3.vision.attention.head_count"] = p.VisionModel.NumAttentionHeads
+	kv["gemma3.vision.attention.layer_norm_epsilon"] = p.VisionModel.LayerNormEpsilon
+
 	kv["tokenizer.ggml.bos_token_id"] = uint32(2)
 	kv["tokenizer.ggml.eot_token_id"] = uint32(1)
-	kv["gemma3.vision.image_size"] = p.VisionModel.ImageSize
-	kv["gemma3.vision.num_channels"] = p.VisionModel.NumChannels
-	kv["gemma3.vision.block_count"] = p.VisionModel.HiddenLayers
 	return kv
 }
 
@@ -59,11 +69,11 @@ func (p *gemma3Model) Replacements() []string {
 		"lm_head", "output",
 		"model.embed_tokens", "token_embd",
 		"model.norm", "output_norm",
-		"vision_model.vision_model", "v",
+		"vision_tower.vision_model.embeddings", "v",
+		"vision_tower.vision_model", "v",
 		"language_model.", "",
 		"model.layers", "blk",
 		"encoder.layers", "blk",
-		"vision_tower.vision_model.embeddings", "v",
 		"input_layernorm", "attn_norm",
 		"self_attn.q_proj", "attn_q",
 		"self_attn.q_norm", "attn_q_norm",
@@ -71,11 +81,14 @@ func (p *gemma3Model) Replacements() []string {
 		"self_attn.k_norm", "attn_k_norm",
 		"self_attn.v_proj", "attn_v",
 		"self_attn.o_proj", "attn_output",
+		"self_attn.out_proj", "attn_output",
 		"mlp.gate_proj", "ffn_gate",
 		"mlp.down_proj", "ffn_down",
 		"mlp.up_proj", "ffn_up",
 		"post_attention_layernorm", "post_attention_norm",
 		"pre_feedforward_layernorm", "ffn_norm",
 		"post_feedforward_layernorm", "post_ffw_norm",
+		"input_projection_weight", "input_projection.weight",
+		"multi_modal_projector", "mm",
 	}
 }
diff --git a/ml/backend.go b/ml/backend.go
index 27c2d14d..2f4ddea3 100644
--- a/ml/backend.go
+++ b/ml/backend.go
@@ -135,7 +135,9 @@ type Tensor interface {
 	RMSNorm(ctx Context, weight Tensor, eps float32) Tensor
 	Scale(ctx Context, s float64) Tensor
 
+	AvgPool1D(ctx Context, k, s, p int) Tensor
 	Conv2D(ctx Context, weight Tensor, s0, s1, p0, p1, d0, d1 int) Tensor
+
 	RoPE(ctx Context, positionIDs, ropeFactors Tensor, dim, ropeType uint32, base, scale float32) Tensor
 
 	Tanh(ctx Context) Tensor
diff --git a/ml/backend/ggml/ggml.go b/ml/backend/ggml/ggml.go
index 8843ae7c..c3f9c2fb 100644
--- a/ml/backend/ggml/ggml.go
+++ b/ml/backend/ggml/ggml.go
@@ -947,6 +947,13 @@ func (t *Tensor) Conv2D(ctx ml.Context, t2 ml.Tensor, s0, s1, p0, p1, d0, d1 int
 	}
 }
 
+func (t *Tensor) AvgPool1D(ctx ml.Context, k, s, p int) ml.Tensor {
+	return &Tensor{
+		b: t.b,
+		t: C.ggml_pool_1d(ctx.(*Context).ctx, t.t, C.GGML_OP_POOL_AVG, C.int(k), C.int(s), C.int(p)),
+	}
+}
+
 func (t *Tensor) ScaledDotProductAttention(ctx ml.Context, key, value, mask ml.Tensor, scale float64) ml.Tensor {
 	var kqMask *C.struct_ggml_tensor
 	if mask != nil {
diff --git a/model/models/gemma3/model.go b/model/models/gemma3/model.go
index 0f4944a4..eb64e8c1 100644
--- a/model/models/gemma3/model.go
+++ b/model/models/gemma3/model.go
@@ -1,10 +1,15 @@
 package gemma3
 
 import (
-	"fmt"
+	"bytes"
+	"encoding/binary"
+	"hash/fnv"
+	"image"
+	"slices"
 
 	"github.com/ollama/ollama/kvcache"
 	"github.com/ollama/ollama/ml"
+	"github.com/ollama/ollama/ml/nn"
 	"github.com/ollama/ollama/model"
 	"github.com/ollama/ollama/model/input"
 )
@@ -13,19 +18,30 @@ type Model struct {
 	model.Base
 	model.SentencePieceModel
 
-	//*VisionModel `gguf:"v,vision"`
+	*VisionModel `gguf:"v,vision"`
 	*TextModel
 
-	//Projector *nn.Linear `gguf:"mm.0"`
+	*MultiModalProjector `gguf:"mm"`
 
 	ImageProcessor
 }
 
+var _ model.MultimodalProcessor = (*Model)(nil)
+
+type MultiModalProjector struct {
+	SoftEmbNorm     *nn.RMSNorm `gguf:"mm_soft_emb_norm"`
+	InputProjection *nn.Linear  `gguf:"mm_input_projection"`
+}
+
+func (p *MultiModalProjector) Forward(ctx ml.Context, visionOutputs ml.Tensor, eps float32) ml.Tensor {
+	visionOutputs = p.SoftEmbNorm.Forward(ctx, visionOutputs, eps)
+
+	// TODO: inputProjection must be transposed since they're incompatible with visionOutputs
+	visionOutputs = p.InputProjection.Weight.Permute(ctx, 1, 0, 2, 3).Contiguous(ctx).Mulmat(ctx, visionOutputs)
+	return visionOutputs
+}
+
 func New(c ml.Config) (model.Model, error) {
-	// Verify unified config
-	if c.Uint("vision.block_count") == 0 {
-		return nil, fmt.Errorf("non-unified vision model not supported")
-	}
 	m := Model{
 		SentencePieceModel: model.NewSentencePieceModel(
 			c.String("tokenizer.ggml.pretokenizer", `(?i:'s|'t|'re|'ve|'m|'ll|'d)|[^\r\n\p{L}\p{N}]?\p{L}+|\p{N}{1,3}| ?[^\s\p{L}\p{N}]+[\r\n]*|\s*[\r\n]+|\s+(?!\S)|\s+`),
@@ -40,8 +56,8 @@ func New(c ml.Config) (model.Model, error) {
 			},
 		),
 		ImageProcessor: newImageProcessor(c),
-		//VisionModel:    newVisionModel(c),
-		TextModel: newTextModel(c),
+		VisionModel:    newVisionModel(c),
+		TextModel:      newTextModel(c),
 	}
 
 	slidingWindowLen := int32(c.Uint("text.attention.sliding_window"))
@@ -50,7 +66,78 @@ func New(c ml.Config) (model.Model, error) {
 	return &m, nil
 }
 
+func (m *Model) EncodeMultimodal(ctx ml.Context, multimodalData []byte) (any, error) {
+	image, _, err := image.Decode(bytes.NewReader(multimodalData))
+	if err != nil {
+		return nil, err
+	}
+
+	f32s, err := m.ImageProcessor.ProcessImage(image)
+	if err != nil {
+		return nil, err
+	}
+
+	pixelValues, err := ctx.Input().FromFloatSlice(f32s,
+		m.ImageProcessor.imageSize,
+		m.ImageProcessor.imageSize,
+		m.ImageProcessor.numChannels,
+	)
+	if err != nil {
+		return nil, err
+	}
+
+	positionIDs, err := ctx.FromIntSlice([]int32{0}, 1)
+	if err != nil {
+		return nil, err
+	}
+
+	visionOutputs := m.VisionModel.Forward(ctx, pixelValues, positionIDs)
+
+	visionOutputs = visionOutputs.Permute(ctx, 1, 0, 2, 3).Contiguous(ctx)
+	patchesPerImage := m.ImageProcessor.imageSize / m.ImageProcessor.patchSize
+	kernelSize := patchesPerImage * patchesPerImage / 256
+	visionOutputs = visionOutputs.AvgPool1D(ctx, kernelSize, kernelSize, 0)
+
+	visionOutputs = visionOutputs.Permute(ctx, 1, 0, 2, 3).Contiguous(ctx)
+	visionOutputs = m.MultiModalProjector.Forward(ctx, visionOutputs, m.VisionModel.eps)
+	return visionOutputs, nil
+}
+
+func (m *Model) PostTokenize(ctx ml.Context, inputs []input.Input) ([]input.Input, error) {
+	var images []input.Input
+	fnvHash := fnv.New64a()
+
+	for i := range inputs {
+		if inputs[i].Multimodal == nil {
+			if len(images) > 0 {
+				inputs[i].Multimodal = images[0].Multimodal
+				inputs[i].MultimodalHash = images[0].MultimodalHash
+				for j := 1; j < len(images); j++ {
+					inputs[i].Multimodal = inputs[i].Multimodal.(ml.Tensor).Concat(ctx, images[j].Multimodal.(ml.Tensor), 3)
+					fnvHash.Reset()
+					binary.Write(fnvHash, binary.NativeEndian, inputs[i].MultimodalHash)
+					binary.Write(fnvHash, binary.NativeEndian, inputs[j].MultimodalHash)
+					inputs[i].MultimodalHash = fnvHash.Sum64()
+				}
+				images = nil
+			}
+		} else {
+			images = append(images, inputs[i])
+			inputs[i].Token = -1
+		}
+	}
+
+	inputs = slices.DeleteFunc(inputs, func(input input.Input) bool { return input.Token == -1 })
+
+	return inputs, nil
+}
+
 func (m *Model) Forward(ctx ml.Context, opts input.Options) (ml.Tensor, error) {
+	var embeddings ml.Tensor
+	if opts.Multimodal != nil {
+		embeddings = opts.Multimodal[0].Multimodal.(ml.Tensor)
+	}
+
 	inputs, err := ctx.Input().FromIntSlice(opts.Inputs, len(opts.Inputs))
 	if err != nil {
 		return nil, err
@@ -66,7 +153,7 @@ func (m *Model) Forward(ctx ml.Context, opts input.Options) (ml.Tensor, error) {
 		return nil, err
 	}
 
-	return m.TextModel.Forward(ctx, inputs, positions, outputs, m.Cache), nil
+	return m.TextModel.Forward(ctx, inputs, positions, embeddings, outputs, m.Cache), nil
 }
 
 func init() {
diff --git a/model/models/gemma3/model_text.go b/model/models/gemma3/model_text.go
index 051e06c5..7ee39276 100644
--- a/model/models/gemma3/model_text.go
+++ b/model/models/gemma3/model_text.go
@@ -160,9 +160,12 @@ func (l *TextLayer) Forward(ctx ml.Context, layer int, hiddenState, positionIDs
 	return hiddenState.Add(ctx, residual)
 }
 
-func (m *TextModel) Forward(ctx ml.Context, inputs, positions, outputs ml.Tensor, cache kvcache.Cache) ml.Tensor {
-	hiddenState := m.TokenEmbedding.Forward(ctx, inputs)
-	hiddenState = hiddenState.Scale(ctx, math.Sqrt(float64(m.TextOptions.hiddenSize)))
+func (m *TextModel) Forward(ctx ml.Context, inputs, positions, embeddings, outputs ml.Tensor, cache kvcache.Cache) ml.Tensor {
+	if embeddings == nil {
+		embeddings = m.TokenEmbedding.Forward(ctx, inputs)
+	}
+
+	hiddenState := embeddings.Scale(ctx, math.Sqrt(float64(m.TextOptions.hiddenSize)))
 
 	if len(m.Layers) == gemma27BLayerCount {
 		m.TextOptions.largeModelScaling = true
diff --git a/model/models/gemma3/model_vision.go b/model/models/gemma3/model_vision.go
new file mode 100644
index 00000000..13cca334
--- /dev/null
+++ b/model/models/gemma3/model_vision.go
@@ -0,0 +1,171 @@
+package gemma3
+
+import (
+	"math"
+	"slices"
+
+	"github.com/ollama/ollama/ml"
+	"github.com/ollama/ollama/ml/nn"
+)
+
+var batchSize int = 1
+
+type VisionSelfAttention struct {
+	Query  *nn.Linear `gguf:"attn_q"`
+	Key    *nn.Linear `gguf:"attn_k"`
+	Value  *nn.Linear `gguf:"attn_v"`
+	Output *nn.Linear `gguf:"attn_output"`
+}
+
+func (sa *VisionSelfAttention) Forward(ctx ml.Context, hiddenState ml.Tensor, opts *VisionModelOptions) ml.Tensor {
+	headDim := opts.hiddenSize / opts.numHeads
+
+	query := sa.Query.Forward(ctx, hiddenState)
+	key := sa.Key.Forward(ctx, hiddenState)
+	value := sa.Value.Forward(ctx, hiddenState)
+
+	query = query.Reshape(ctx, headDim, opts.numHeads, query.Dim(1), batchSize).Permute(ctx, 0, 2, 1, 3)
+	key = key.Reshape(ctx, headDim, opts.numHeads, key.Dim(1), batchSize).Permute(ctx, 0, 2, 1, 3)
+	value = value.Reshape(ctx, headDim, opts.numHeads, value.Dim(1), batchSize).Permute(ctx, 1, 2, 0, 3).Contiguous(ctx)
+
+	scores := key.Mulmat(ctx, query)
+	scores = scores.Scale(ctx, 1.0/math.Sqrt(float64(headDim)))
+	scores = scores.Softmax(ctx)
+
+	attention := value.Mulmat(ctx, scores)
+	attention = attention.Reshape(ctx, headDim, attention.Dim(1), opts.numHeads, batchSize)
+	attention = attention.Permute(ctx, 0, 2, 1, 3).Contiguous(ctx)
+	attention = attention.Reshape(ctx, opts.hiddenSize, attention.Dim(2), batchSize)
+
+	hiddenState = sa.Output.Forward(ctx, attention)
+	return hiddenState
+}
+
+type VisionMLP struct {
+	FC1 *nn.Linear `gguf:"fc1"`
+	FC2 *nn.Linear `gguf:"fc2"`
+}
+
+func (mlp *VisionMLP) Forward(ctx ml.Context, hiddenState ml.Tensor, opts *VisionModelOptions) ml.Tensor {
+	hiddenState = mlp.FC1.Forward(ctx, hiddenState).GELU(ctx)
+	hiddenState = mlp.FC2.Forward(ctx, hiddenState)
+	return hiddenState
+}
+
+type VisionEncoderLayer struct {
+	LayerNorm1    *nn.LayerNorm        `gguf:"layer_norm1"`
+	SelfAttention *VisionSelfAttention
+
+	LayerNorm2 *nn.LayerNorm `gguf:"layer_norm2"`
+	MLP        *VisionMLP    `gguf:"mlp"`
+}
+
+func (e *VisionEncoderLayer) Forward(ctx ml.Context, hiddenState ml.Tensor, opts *VisionModelOptions) ml.Tensor {
+	residual := hiddenState
+
+	// self attention
+	hiddenState = e.LayerNorm1.Forward(ctx, hiddenState, opts.eps)
+	hiddenState = e.SelfAttention.Forward(ctx, hiddenState, opts)
+	hiddenState = hiddenState.Add(ctx, residual)
+	residual = hiddenState
+
+	// feed forward
+	hiddenState = e.LayerNorm2.Forward(ctx, hiddenState, opts.eps)
+	hiddenState = e.MLP.Forward(ctx, hiddenState, opts)
+	return hiddenState.Add(ctx, residual)
+}
+
+type VisionEncoder struct {
+	Layers []VisionEncoderLayer
+}
+
+func (e *VisionEncoder) Forward(ctx ml.Context, hiddenState ml.Tensor, intermediateLayersIndices []uint32, opts *VisionModelOptions) (ml.Tensor, []ml.Tensor) {
+	var intermediateHiddenStates []ml.Tensor
+	for i, layer := range e.Layers {
+		if slices.Contains(intermediateLayersIndices, uint32(i)) {
+			intermediateHiddenStates = append(intermediateHiddenStates, hiddenState.Reshape(ctx, append([]int{1}, hiddenState.Shape()...)...))
+		}
+
+		hiddenState = layer.Forward(ctx, hiddenState, opts)
+	}
+
+	return hiddenState, intermediateHiddenStates
+}
+
+type PrecomputedAspectRatioEmbedding struct {
+	Embedding *nn.Embedding
+	Gate      ml.Tensor `gguf:"gate"`
+}
+
+func (e *PrecomputedAspectRatioEmbedding) Forward(ctx ml.Context, hiddenState ml.Tensor, aspectRatioIDs ml.Tensor, opts *VisionModelOptions) ml.Tensor {
+	embeddings := e.Embedding.Forward(ctx, aspectRatioIDs)
+	embeddings = embeddings.Reshape(ctx, opts.hiddenSize, 1, opts.numTiles)
+	if e.Gate != nil {
+		embeddings = embeddings.Mul(ctx, e.Gate)
+	}
+
+	return hiddenState.Add(ctx, embeddings)
+}
+
+type PrecomputedPositionEmbedding struct {
+	PositionEmbedding     *nn.Embedding `gguf:"position_embd"`
+	PositionEmbeddingGate ml.Tensor     `gguf:"position_embd.gate"`
+}
+
+func (e *PrecomputedPositionEmbedding) Forward(ctx ml.Context, hiddenState, positionIDs ml.Tensor, numPositions int, opts *VisionModelOptions) ml.Tensor {
+	positionEmbedding := e.PositionEmbedding.Forward(ctx, positionIDs)
+	if e.PositionEmbeddingGate != nil {
+		positionEmbedding = positionEmbedding.Mul(ctx, e.PositionEmbeddingGate)
+	}
+
+	return hiddenState.Add(ctx, positionEmbedding)
+}
+
+type VisionModelOptions struct {
+	hiddenSize, numHeads, numTiles int
+	imageSize, patchSize           int
+	eps                            float32
+}
+
+type VisionModel struct {
+	PatchEmbedding    *nn.Conv2D    `gguf:"patch_embedding"`
+	PositionEmbedding *nn.Embedding `gguf:"position_embedding"`
+	PostLayerNorm     *nn.LayerNorm `gguf:"post_layernorm"`
+
+	Encoder *VisionEncoder `gguf:"blk"`
+
+	*VisionModelOptions
+}
+
+func (m *VisionModel) Forward(ctx ml.Context, pixelValues, positionIDs ml.Tensor) ml.Tensor {
+	numPatches := (m.imageSize / m.patchSize) * (m.imageSize / m.patchSize)
+
+	hiddenState := m.PatchEmbedding.Forward(ctx, pixelValues, m.patchSize, m.patchSize, 0, 0, 1, 1)
+	hiddenState = hiddenState.Reshape(ctx, numPatches, m.hiddenSize)
+	hiddenState = hiddenState.Permute(ctx, 1, 0, 2, 3).Contiguous(ctx)
+
+	positions := m.PositionEmbedding.Forward(ctx, positionIDs)
+	hiddenState = hiddenState.Add(ctx, positions)
+
+	for _, layer := range m.Encoder.Layers {
+		hiddenState = layer.Forward(ctx, hiddenState, m.VisionModelOptions)
+	}
+
+	hiddenState = m.PostLayerNorm.Forward(ctx, hiddenState, m.eps)
+	return hiddenState
+}
+
+func newVisionModel(c ml.Config) *VisionModel {
+	return &VisionModel{
+		Encoder: &VisionEncoder{Layers: make([]VisionEncoderLayer, c.Uint("vision.block_count"))},
+		VisionModelOptions: &VisionModelOptions{
+			hiddenSize: int(c.Uint("vision.embedding_length")),
+			numHeads:   int(c.Uint("vision.attention.head_count")),
+
+			imageSize: int(c.Uint("vision.image_size")),
+			patchSize: int(c.Uint("vision.patch_size")),
+
+			eps: c.Float("vision.attention.layer_norm_epsilon"),
+		},
+	}
+}
diff --git a/model/models/gemma3/process_image.go b/model/models/gemma3/process_image.go
index 5cf963e8..a32e60e5 100644
--- a/model/models/gemma3/process_image.go
+++ b/model/models/gemma3/process_image.go
@@ -8,12 +8,13 @@ import (
 )
 
 type ImageProcessor struct {
-	imageSize, numChannels int
+	imageSize, patchSize, numChannels int
 }
 
 func newImageProcessor(c ml.Config) ImageProcessor {
 	return ImageProcessor{
 		imageSize:   int(c.Uint("vision.image_size")),
+		patchSize:   int(c.Uint("vision.patch_size")),
 		numChannels: int(c.Uint("vision.num_channels")),
 	}
 }
diff --git a/model/models/mllama/process_image.go b/model/models/mllama/process_image.go
index c298d6ae..c94d14a6 100644
--- a/model/models/mllama/process_image.go
+++ b/model/models/mllama/process_image.go
@@ -144,8 +144,6 @@ func (p *ImageProcessor) splitToTiles(img image.Image, numTilesSize image.Point)
 	return images
 }
 
-// remove the "alpha" channel by drawing over a prefilled image
-//
 // remove the "alpha" channel by drawing over a prefilled image
 //
 //nolint:unused
diff --git a/model/process_text_spm.go b/model/process_text_spm.go
index c0bc973f..9d61746a 100644
--- a/model/process_text_spm.go
+++ b/model/process_text_spm.go
@@ -21,6 +21,8 @@ type SentencePieceModel struct {
 	vocab       *Vocabulary
 }
 
+var _ TextProcessor = (*SentencePieceModel)(nil)
+
 func NewSentencePieceModel(pre string, vocab *Vocabulary) SentencePieceModel {
 	slog.Debug("Tokens", "num tokens", len(vocab.Values), "vals", vocab.Values[:5], "scores", vocab.Scores[:5], "types", vocab.Types[:5])
 
@@ -61,7 +63,7 @@ func (spm *SentencePieceModel) split(s string) iter.Seq[string] {
 	}
 }
 
-func (spm SentencePieceModel) Encode(s string) ([]int32, error) {
+func (spm SentencePieceModel) Encode(s string, addSpecial bool) ([]int32, error) {
 	fragments := []fragment{{value: s}}
 	for _, special := range spm.vocab.SpecialVocabulary() {
 		// TODO: process special tokens concurrently
@@ -196,7 +198,26 @@ func (spm SentencePieceModel) Encode(s string) ([]int32, error) {
 			}
 		}
 	}
-	slog.Debug("encoded", "ids", ids)
+
+	if addSpecial && len(ids) > 0 {
+		if spm.vocab.AddBOS {
+			if ids[0] == spm.vocab.BOS {
+				slog.Warn("adding bos token to prompt which already has it", "id", spm.vocab.BOS)
+			}
+
+			slog.Debug("adding bos token to prompt", "id", spm.vocab.BOS)
+			ids = append([]int32{spm.vocab.BOS}, ids...)
+		}
+
+		if spm.vocab.AddEOS {
+			if ids[len(ids)-1] == spm.vocab.EOS {
+				slog.Warn("adding eos token to prompt which already has it", "id", spm.vocab.EOS)
+			}
+
+			slog.Debug("adding eos token to prompt", "id", spm.vocab.EOS)
+			ids = append(ids, spm.vocab.EOS)
+		}
+	}
 
 	return ids, nil
 }

From 4346c2409dec7bb182aa91d236f0759d592a1b42 Mon Sep 17 00:00:00 2001
From: Jesse Gross <jesse@ollama.com>
Date: Fri, 7 Mar 2025 09:30:10 -0800
Subject: [PATCH 039/157] fix drift from main

---
 kvcache/causal_test.go              |  4 ++++
 model/models/gemma2/model.go        | 36 ++++++++++++++++++++---------
 model/models/gemma3/model_text.go   | 25 +++++++++++++-------
 model/models/gemma3/model_vision.go |  2 +-
 model/process_text_spm_test.go      |  4 ++--
 5 files changed, 49 insertions(+), 22 deletions(-)

diff --git a/kvcache/causal_test.go b/kvcache/causal_test.go
index 0c9e000e..431a79b5 100644
--- a/kvcache/causal_test.go
+++ b/kvcache/causal_test.go
@@ -441,6 +441,10 @@ func (t *testTensor) Scale(ctx ml.Context, s float64) ml.Tensor {
 	panic("not implemented")
 }
 
+func (t *testTensor) AvgPool1D(ctx ml.Context, k, s, p int) ml.Tensor {
+	panic("not implemented")
+}
+
 func (t *testTensor) Conv2D(ctx ml.Context, weight ml.Tensor, s0, s1, p0, p1, d0, d1 int) ml.Tensor {
 	panic("not implemented")
 }
diff --git a/model/models/gemma2/model.go b/model/models/gemma2/model.go
index 2ad9c568..a82d68d3 100644
--- a/model/models/gemma2/model.go
+++ b/model/models/gemma2/model.go
@@ -64,6 +64,7 @@ func New(c ml.Config) (model.Model, error) {
 
 	slidingWindowLen := int32(c.Uint("attention.sliding_window"))
 	m.Cache = kvcache.NewWrapperCache(kvcache.NewSWACache(slidingWindowLen, m.Shift), kvcache.NewCausalCache(m.Shift))
+	m.Cache.SetConfig(ml.CacheConfig{})
 
 	return &m, nil
 }
@@ -84,7 +85,7 @@ func (sa *SelfAttention) Forward(ctx ml.Context, hiddenState, positionIDs ml.Ten
 	q = q.RoPE(ctx, positionIDs, nil, uint32(opts.attnKeyLen), ropeType, opts.ropeBase, opts.ropeScale)
 
 	if opts.largeModelScaling {
-		q = q.Scale(ctx, 1.0/math.Sqrt(float64(opts.hiddenSize / opts.numHeads)))
+		q = q.Scale(ctx, 1.0/math.Sqrt(float64(opts.hiddenSize/opts.numHeads)))
 	} else {
 		q = q.Scale(ctx, 1.0/math.Sqrt(float64(opts.attnKeyLen)))
 	}
@@ -99,8 +100,8 @@ func (sa *SelfAttention) Forward(ctx ml.Context, hiddenState, positionIDs ml.Ten
 	cache.Put(ctx, k, v)
 	k, v, mask := cache.Get(ctx)
 
-	q = q.Permute(ctx, 0, 2, 1, 3).Contiguous(ctx)
-	k = k.Permute(ctx, 0, 2, 1, 3).Contiguous(ctx)
+	q = q.Permute(ctx, 0, 2, 1, 3)
+	k = k.Permute(ctx, 0, 2, 1, 3)
 	v = v.Permute(ctx, 1, 2, 0, 3).Contiguous(ctx)
 
 	kq := k.Mulmat(ctx, q)
@@ -144,12 +145,20 @@ type Layer struct {
 	PostMLPNorm       *nn.RMSNorm `gguf:"post_ffw_norm"`
 }
 
-func (l *Layer) Forward(ctx ml.Context, hiddenState, positionIDs ml.Tensor, cache kvcache.Cache, opts *Options) ml.Tensor {
+func (l *Layer) Forward(ctx ml.Context, hiddenState, positionIDs, outputs ml.Tensor, cache kvcache.Cache, opts *Options) ml.Tensor {
 	residual := hiddenState
 
 	hiddenState = l.AttentionNorm.Forward(ctx, hiddenState, opts.eps)
 	hiddenState = l.SelfAttention.Forward(ctx, hiddenState, positionIDs, cache, opts)
 	hiddenState = l.PostAttentionNorm.Forward(ctx, hiddenState, opts.eps)
+
+	// In the final layer (outputs != nil), optimize by pruning to just the token positions
+	// we need logits for.
+	if outputs != nil {
+		hiddenState = hiddenState.Rows(ctx, outputs)
+		residual = residual.Rows(ctx, outputs)
+	}
+
 	hiddenState = hiddenState.Add(ctx, residual)
 	residual = hiddenState
 
@@ -170,6 +179,11 @@ func (m *Model) Forward(ctx ml.Context, opts input.Options) (ml.Tensor, error) {
 		return nil, err
 	}
 
+	outputs, err := ctx.FromIntSlice(opts.Outputs, len(opts.Outputs))
+	if err != nil {
+		return nil, err
+	}
+
 	hiddenState := m.TokenEmbedding.Forward(ctx, inputs)
 	hiddenState = hiddenState.Scale(ctx, math.Sqrt(float64(m.Options.hiddenSize)))
 
@@ -182,7 +196,13 @@ func (m *Model) Forward(ctx ml.Context, opts input.Options) (ml.Tensor, error) {
 		m.Cache.SetLayer(i)
 		wc := m.Cache.(*kvcache.WrapperCache)
 		wc.SetLayerType(cacheType)
-		hiddenState = layer.Forward(ctx, hiddenState, positions, m.Cache, m.Options)
+
+		var lastLayerOutputs ml.Tensor
+		if i == len(m.Layers)-1 {
+			lastLayerOutputs = outputs
+		}
+
+		hiddenState = layer.Forward(ctx, hiddenState, positions, lastLayerOutputs, m.Cache, m.Options)
 	}
 
 	hiddenState = m.OutputNorm.Forward(ctx, hiddenState, m.eps)
@@ -192,12 +212,6 @@ func (m *Model) Forward(ctx ml.Context, opts input.Options) (ml.Tensor, error) {
 	hiddenState = hiddenState.Scale(ctx, 1.0/float64(m.Options.finalLogitSoftcap))
 	hiddenState = hiddenState.Tanh(ctx)
 	hiddenState = hiddenState.Scale(ctx, float64(m.Options.finalLogitSoftcap))
-
-	outputs, err := ctx.Output().FromIntSlice(opts.Outputs, len(opts.Outputs))
-	if err != nil {
-		return nil, err
-	}
-
 	return hiddenState.Rows(ctx, outputs), nil
 }
 
diff --git a/model/models/gemma3/model_text.go b/model/models/gemma3/model_text.go
index 7ee39276..0896f044 100644
--- a/model/models/gemma3/model_text.go
+++ b/model/models/gemma3/model_text.go
@@ -66,9 +66,6 @@ func newTextModel(c ml.Config) *TextModel {
 		},
 	}
 
-	slidingWindowLen := int32(c.Uint("text.attention.sliding_window"))
-	m.Cache = kvcache.NewWrapperCache(kvcache.NewSWACache(slidingWindowLen, m.Shift), kvcache.NewCausalCache(m.Shift))
-
 	return &m
 }
 
@@ -145,12 +142,20 @@ type TextLayer struct {
 	PostMLPNorm       *nn.RMSNorm `gguf:"post_ffw_norm"`
 }
 
-func (l *TextLayer) Forward(ctx ml.Context, layer int, hiddenState, positionIDs ml.Tensor, cache kvcache.Cache, opts *TextOptions) ml.Tensor {
+func (l *TextLayer) Forward(ctx ml.Context, layer int, hiddenState, positionIDs, outputs ml.Tensor, cache kvcache.Cache, opts *TextOptions) ml.Tensor {
 	residual := hiddenState
 
 	hiddenState = l.AttentionNorm.Forward(ctx, hiddenState, opts.eps)
 	hiddenState = l.SelfAttention.Forward(ctx, layer, hiddenState, positionIDs, cache, opts)
 	hiddenState = l.PostAttentionNorm.Forward(ctx, hiddenState, opts.eps)
+
+	// In the final layer (outputs != nil), optimize by pruning to just the token positions
+	// we need logits for.
+	if outputs != nil {
+		hiddenState = hiddenState.Rows(ctx, outputs)
+		residual = residual.Rows(ctx, outputs)
+	}
+
 	hiddenState = hiddenState.Add(ctx, residual)
 	residual = hiddenState
 
@@ -181,7 +186,13 @@ func (m *TextModel) Forward(ctx ml.Context, inputs, positions, embeddings, outpu
 		cache.SetLayer(i)
 		wc := cache.(*kvcache.WrapperCache)
 		wc.SetLayerType(cacheType)
-		hiddenState = layer.Forward(ctx, i, hiddenState, positions, cache, m.TextOptions)
+
+		var lastLayerOutputs ml.Tensor
+		if i == len(m.Layers)-1 {
+			lastLayerOutputs = outputs
+		}
+
+		hiddenState = layer.Forward(ctx, i, hiddenState, positions, lastLayerOutputs, cache, m.TextOptions)
 	}
 
 	hiddenState = m.OutputNorm.Forward(ctx, hiddenState, m.eps)
@@ -190,7 +201,5 @@ func (m *TextModel) Forward(ctx ml.Context, inputs, positions, embeddings, outpu
 	// final logit softcap
 	hiddenState = hiddenState.Scale(ctx, 1.0/float64(m.TextOptions.finalLogitSoftcap))
 	hiddenState = hiddenState.Tanh(ctx)
-	hiddenState = hiddenState.Scale(ctx, float64(m.TextOptions.finalLogitSoftcap))
-
-	return hiddenState.Rows(ctx, outputs)
+	return hiddenState.Scale(ctx, float64(m.TextOptions.finalLogitSoftcap))
 }
diff --git a/model/models/gemma3/model_vision.go b/model/models/gemma3/model_vision.go
index 13cca334..ee6e3b6f 100644
--- a/model/models/gemma3/model_vision.go
+++ b/model/models/gemma3/model_vision.go
@@ -53,7 +53,7 @@ func (mlp *VisionMLP) Forward(ctx ml.Context, hiddenState ml.Tensor, opts *Visio
 }
 
 type VisionEncoderLayer struct {
-	LayerNorm1    *nn.LayerNorm        `gguf:"layer_norm1"`
+	LayerNorm1    *nn.LayerNorm `gguf:"layer_norm1"`
 	SelfAttention *VisionSelfAttention
 
 	LayerNorm2 *nn.LayerNorm `gguf:"layer_norm2"`
diff --git a/model/process_text_spm_test.go b/model/process_text_spm_test.go
index 72bd629c..13e28cc5 100644
--- a/model/process_text_spm_test.go
+++ b/model/process_text_spm_test.go
@@ -73,7 +73,7 @@ func TestSentencePieceEncode(t *testing.T) {
 		}
 
 		for _, want := range cases {
-			ids, err := tokenizer.Encode(want)
+			ids, err := tokenizer.Encode(want, true)
 			if err != nil {
 				t.Fatal(err)
 			}
@@ -98,7 +98,7 @@ func TestSentencePieceEncode(t *testing.T) {
 		}
 
 		for _, want := range cases {
-			ids, err := tokenizer.Encode(want.token)
+			ids, err := tokenizer.Encode(want.token, true)
 			if err != nil {
 				t.Fatal(err)
 			}

From 631fecc6d9fe644a793a9ca185c080db4fea77e7 Mon Sep 17 00:00:00 2001
From: Patrick Devine <patrick@infrahq.com>
Date: Fri, 7 Mar 2025 11:20:55 -0800
Subject: [PATCH 040/157] temporary work around for converting spm

---
 convert/tokenizer_spm.go | 6 ++++++
 1 file changed, 6 insertions(+)

diff --git a/convert/tokenizer_spm.go b/convert/tokenizer_spm.go
index d8a012c0..340c3d58 100644
--- a/convert/tokenizer_spm.go
+++ b/convert/tokenizer_spm.go
@@ -47,6 +47,12 @@ func parseSentencePiece(fsys fs.FS) (*Vocabulary, error) {
 			v.Types = append(v.Types, int32(t))
 		default:
 			tt := int32(sentencepiece.ModelProto_SentencePiece_NORMAL)
+
+			// temporary fix to handle gemma3 broken configs
+			if slices.Contains([]string{"<end_of_turn>", "<start_of_turn>"}, piece.GetPiece()) {
+				tt = int32(sentencepiece.ModelProto_SentencePiece_CONTROL)
+			}
+
 			for _, t := range ast {
 				if t.Content == piece.GetPiece() {
 					tt = int32(sentencepiece.ModelProto_SentencePiece_CONTROL)

From 0df1800436bfb48b0556fce8f37c5d2e256c1d0a Mon Sep 17 00:00:00 2001
From: Michael Yang <mxyng@pm.me>
Date: Fri, 7 Mar 2025 13:52:45 -0800
Subject: [PATCH 041/157] set non-causal attention

---
 convert/convert_gemma3.go         |  3 ---
 ml/backend.go                     |  1 +
 ml/backend/ggml/ggml.go           | 14 +++++++++++
 model/models/gemma3/model.go      | 41 ++++++++++++++++++++-----------
 model/models/gemma3/model_text.go | 12 ++++++---
 model/process_text.go             | 11 ++++++---
 6 files changed, 57 insertions(+), 25 deletions(-)

diff --git a/convert/convert_gemma3.go b/convert/convert_gemma3.go
index a2b18e29..cfea2052 100644
--- a/convert/convert_gemma3.go
+++ b/convert/convert_gemma3.go
@@ -58,9 +58,6 @@ func (p *gemma3Model) KV(t *Tokenizer) ggml.KV {
 	kv["gemma3.vision.num_channels"] = p.VisionModel.NumChannels
 	kv["gemma3.vision.attention.head_count"] = p.VisionModel.NumAttentionHeads
 	kv["gemma3.vision.attention.layer_norm_epsilon"] = p.VisionModel.LayerNormEpsilon
-
-	kv["tokenizer.ggml.bos_token_id"] = uint32(2)
-	kv["tokenizer.ggml.eot_token_id"] = uint32(1)
 	return kv
 }
 
diff --git a/ml/backend.go b/ml/backend.go
index 2f4ddea3..303d67ec 100644
--- a/ml/backend.go
+++ b/ml/backend.go
@@ -148,6 +148,7 @@ type Tensor interface {
 	View(ctx Context, offset int, shape ...int) Tensor
 	Permute(ctx Context, shape ...int) Tensor
 	Contiguous(ctx Context) Tensor
+	Set(ctx Context, t2 Tensor, offset int, strides ...int) Tensor
 
 	Pad(ctx Context, shape ...int) Tensor
 	Unpad(ctx Context, shape ...int) Tensor
diff --git a/ml/backend/ggml/ggml.go b/ml/backend/ggml/ggml.go
index c3f9c2fb..487ea524 100644
--- a/ml/backend/ggml/ggml.go
+++ b/ml/backend/ggml/ggml.go
@@ -954,6 +954,20 @@ func (t *Tensor) AvgPool1D(ctx ml.Context, k, s, p int) ml.Tensor {
 	}
 }
 
+func (t *Tensor) Set(ctx ml.Context, t2 ml.Tensor, offset int, strides ...int) ml.Tensor {
+	var tt *C.struct_ggml_tensor
+	switch len(strides) {
+	case 0:
+		tt = C.ggml_set_1d_inplace(ctx.(*Context).ctx, t.t, t2.(*Tensor).t, C.size_t(offset))
+	case 1:
+		tt = C.ggml_set_2d_inplace(ctx.(*Context).ctx, t.t, t2.(*Tensor).t, C.size_t(offset), C.size_t(strides[0]))
+	default:
+		panic("unsupported number of dimensions")
+	}
+
+	return &Tensor{b: t.b, t: tt}
+}
+
 func (t *Tensor) ScaledDotProductAttention(ctx ml.Context, key, value, mask ml.Tensor, scale float64) ml.Tensor {
 	var kqMask *C.struct_ggml_tensor
 	if mask != nil {
diff --git a/model/models/gemma3/model.go b/model/models/gemma3/model.go
index eb64e8c1..2bb5232b 100644
--- a/model/models/gemma3/model.go
+++ b/model/models/gemma3/model.go
@@ -51,8 +51,10 @@ func New(c ml.Config) (model.Model, error) {
 				Types:  c.Uints("tokenizer.ggml.token_type"),
 				BOS:    int32(c.Uint("tokenizer.ggml.bos_token_id")),
 				AddBOS: c.Bool("tokenizer.ggml.add_bos_token", true),
-				EOS:    int32(c.Uint("tokenizer.ggml.eos_token_id")),
+				EOS:    int32(1),
 				AddEOS: c.Bool("tokenizer.ggml.add_eos_token", false),
+				EOT:    int32(106),
+				AddEOT: c.Bool("tokenizer.ggml.add_eot_token", false),
 			},
 		),
 		ImageProcessor: newImageProcessor(c),
@@ -109,35 +111,46 @@ func (m *Model) PostTokenize(ctx ml.Context, inputs []input.Input) ([]input.Inpu
 
 	for i := range inputs {
 		if inputs[i].Multimodal == nil {
-			if len(images) > 0 {
-				inputs[i].Multimodal = images[0].Multimodal
-				inputs[i].MultimodalHash = images[0].MultimodalHash
-				for j := 1; j < len(images); j++ {
+			for j := range images {
+				if j == 0 {
+					inputs[i].Multimodal = images[j].Multimodal
+					inputs[i].MultimodalHash = images[j].MultimodalHash
+				} else {
 					inputs[i].Multimodal = inputs[i].Multimodal.(ml.Tensor).Concat(ctx, images[j].Multimodal.(ml.Tensor), 3)
 					fnvHash.Reset()
 					binary.Write(fnvHash, binary.NativeEndian, inputs[i].MultimodalHash)
-					binary.Write(fnvHash, binary.NativeEndian, inputs[j].MultimodalHash)
+					binary.Write(fnvHash, binary.NativeEndian, images[j].MultimodalHash)
 					inputs[i].MultimodalHash = fnvHash.Sum64()
 				}
-				images = nil
 			}
+
+			images = nil
 		} else {
 			images = append(images, inputs[i])
 			inputs[i].Token = -1
 		}
 	}
 
-	inputs = slices.DeleteFunc(inputs, func(input input.Input) bool { return input.Token == -1 })
+	for i := range inputs {
+		if inputs[i].Token == -1 {
+			imageInputs := []input.Input{
+				{Token: 108},    // "\n\n"
+				{Token: 255999}, // "<start_of_image>""
+			}
+
+			// <image_soft_token>
+			imageInputs = append(imageInputs, slices.Repeat([]input.Input{{Token: 262144}}, 256)...)
+			// <end_of_image>
+			imageInputs = append(imageInputs, input.Input{Token: 256000})
+
+			inputs = append(inputs[:i], append(imageInputs, inputs[i+1:]...)...)
+		}
+	}
 
 	return inputs, nil
 }
 
 func (m *Model) Forward(ctx ml.Context, opts input.Options) (ml.Tensor, error) {
-	var embeddings ml.Tensor
-	if opts.Multimodal != nil {
-		embeddings = opts.Multimodal[0].Multimodal.(ml.Tensor)
-	}
-
 	inputs, err := ctx.Input().FromIntSlice(opts.Inputs, len(opts.Inputs))
 	if err != nil {
 		return nil, err
@@ -153,7 +166,7 @@ func (m *Model) Forward(ctx ml.Context, opts input.Options) (ml.Tensor, error) {
 		return nil, err
 	}
 
-	return m.TextModel.Forward(ctx, inputs, positions, embeddings, outputs, m.Cache), nil
+	return m.TextModel.Forward(ctx, inputs, positions, outputs, opts.Multimodal, m.Cache), nil
 }
 
 func init() {
diff --git a/model/models/gemma3/model_text.go b/model/models/gemma3/model_text.go
index 0896f044..46ed6fe2 100644
--- a/model/models/gemma3/model_text.go
+++ b/model/models/gemma3/model_text.go
@@ -7,6 +7,7 @@ import (
 	"github.com/ollama/ollama/ml"
 	"github.com/ollama/ollama/ml/nn"
 	"github.com/ollama/ollama/model"
+	"github.com/ollama/ollama/model/input"
 )
 
 type TextOptions struct {
@@ -165,12 +166,15 @@ func (l *TextLayer) Forward(ctx ml.Context, layer int, hiddenState, positionIDs,
 	return hiddenState.Add(ctx, residual)
 }
 
-func (m *TextModel) Forward(ctx ml.Context, inputs, positions, embeddings, outputs ml.Tensor, cache kvcache.Cache) ml.Tensor {
-	if embeddings == nil {
-		embeddings = m.TokenEmbedding.Forward(ctx, inputs)
+func (m *TextModel) Forward(ctx ml.Context, inputs, positions, outputs ml.Tensor, multimodal []input.MultimodalIndex, cache kvcache.Cache) ml.Tensor {
+	hiddenState := m.TokenEmbedding.Forward(ctx, inputs)
+	if multimodal != nil {
+		visionOutputs := multimodal[0].Multimodal.(ml.Tensor)
+		offset := multimodal[0].Index - 1 - visionOutputs.Dim(1)
+		hiddenState = hiddenState.Set(ctx, visionOutputs, offset*hiddenState.Stride(0))
 	}
 
-	hiddenState := embeddings.Scale(ctx, math.Sqrt(float64(m.TextOptions.hiddenSize)))
+	hiddenState = hiddenState.Scale(ctx, math.Sqrt(float64(m.TextOptions.hiddenSize)))
 
 	if len(m.Layers) == gemma27BLayerCount {
 		m.TextOptions.largeModelScaling = true
diff --git a/model/process_text.go b/model/process_text.go
index cd1deb65..01af65b6 100644
--- a/model/process_text.go
+++ b/model/process_text.go
@@ -4,6 +4,7 @@ import (
 	"cmp"
 	"iter"
 	"log/slog"
+	"slices"
 	"strings"
 	"sync"
 
@@ -39,8 +40,8 @@ type Vocabulary struct {
 	Scores []float32
 	Merges []string
 
-	BOS, EOS       int32
-	AddBOS, AddEOS bool
+	BOS, EOS, EOT          int32
+	AddBOS, AddEOS, AddEOT bool
 
 	specialOnce sync.Once
 	special     []string
@@ -57,7 +58,7 @@ func (v *Vocabulary) Is(id int32, special Special) bool {
 	case SpecialBOS:
 		return id == v.BOS
 	case SpecialEOS:
-		return id == v.EOS
+		return id == v.EOS || id == v.EOT
 	default:
 		return false
 	}
@@ -85,7 +86,9 @@ func (v *Vocabulary) Decode(id int32) string {
 func (v *Vocabulary) SpecialVocabulary() []string {
 	v.specialOnce.Do(func() {
 		for i := range v.Values {
-			if v.Types[i] == TOKEN_TYPE_CONTROL {
+			if slices.Contains([]int{105, 106}, i) {
+				v.special = append(v.special, v.Values[i])
+			} else if v.Types[i] == TOKEN_TYPE_CONTROL {
 				v.special = append(v.special, v.Values[i])
 			}
 		}

From c62861f4fa4bd5a82a1c8b46bea74b1672d384b3 Mon Sep 17 00:00:00 2001
From: Patrick Devine <patrick@infrahq.com>
Date: Fri, 7 Mar 2025 14:06:10 -0800
Subject: [PATCH 042/157] fix conversion

---
 convert/convert.go                |  7 ++-
 convert/convert_gemma3.go         | 71 ++++++++++++++++++-------------
 model/models/gemma3/model_text.go | 21 ++++-----
 3 files changed, 57 insertions(+), 42 deletions(-)

diff --git a/convert/convert.go b/convert/convert.go
index cdb0c9e5..4467f9e1 100644
--- a/convert/convert.go
+++ b/convert/convert.go
@@ -190,8 +190,8 @@ func ConvertModel(fsys fs.FS, ws io.WriteSeeker) error {
 		conv = &gemmaModel{}
 	case "Gemma2ForCausalLM":
 		conv = &gemma2Model{}
-	case "Gemma3ForConditionalGeneration":
-		conv = &gemma3Model{}
+	case "Gemma3ForCausalLM", "Gemma3ForConditionalGeneration":
+		conv = &gemma3Model{Architecture: p.Architectures[0]}
 	case "Phi3ForCausalLM":
 		conv = &phi3Model{}
 	case "Qwen2ForCausalLM":
@@ -226,6 +226,9 @@ func ConvertModel(fsys fs.FS, ws io.WriteSeeker) error {
 	}
 
 	switch {
+	case vocabSize == 0:
+		slog.Warn("vocabulary size was not explicitly set by the model", "default size", len(t.Vocabulary.Tokens))
+		vocabSize = len(t.Vocabulary.Tokens)
 	case vocabSize > len(t.Vocabulary.Tokens):
 		slog.Warn("vocabulary is smaller than expected, padding with dummy tokens", "expect", vocabSize, "actual", len(t.Vocabulary.Tokens))
 		for i := range vocabSize - len(t.Vocabulary.Tokens) {
diff --git a/convert/convert_gemma3.go b/convert/convert_gemma3.go
index cfea2052..f43248db 100644
--- a/convert/convert_gemma3.go
+++ b/convert/convert_gemma3.go
@@ -4,7 +4,13 @@ import "github.com/ollama/ollama/fs/ggml"
 
 type gemma3Model struct {
 	gemmaModel
-	TextModel   gemma3TextModel `json:"text_config"`
+	Architecture string
+	TextModel    struct {
+		HiddenSize       uint32 `json:"hidden_size"`
+		HiddenLayers     uint32 `json:"num_hidden_layers"`
+		IntermediateSize uint32 `json:"intermediate_size"`
+		SlidingWindow    uint32 `json:"sliding_window"`
+	} `json:"text_config"`
 	VisionModel struct {
 		NumAttentionHeads uint32  `json:"num_attention_heads"` // attention.head_count 16
 		LayerNormEpsilon  float32 `json:"layer_norm_eps"`      // attention.layer_norm_epsilon 1e-05
@@ -15,49 +21,54 @@ type gemma3Model struct {
 		NumChannels       uint32  `json:"num_channels"`        // num_channels 3
 		PatchSize         uint32  `json:"patch_size"`          // patch_size 14
 	} `json:"vision_config"`
-}
-
-type gemma3TextModel struct {
 	MaxPositionEmbeddings uint32  `json:"max_position_embeddings"`
-	HiddenSize            uint32  `json:"hidden_size"`
-	HiddenLayers          uint32  `json:"num_hidden_layers"`
-	IntermediateSize      uint32  `json:"intermediate_size"`
 	NumAttentionHeads     uint32  `json:"num_attention_heads"`
 	NumKeyValueHeads      uint32  `json:"num_key_value_heads"`
 	RMSNormEPS            float32 `json:"rms_norm_eps"`
 	HeadDim               uint32  `json:"head_dim"`
-	SlidingWindow         uint32  `json:"sliding_window"`
-	AttentionLogitSoftcap float32 `json:"attn_logit_softcapping"`
 	FinalLogitSoftcap     float32 `json:"final_logit_softcapping"`
 	RopeLocalTheta        float32 `json:"rope_local_base_freq"`
 	RopeGlobalTheta       float32 `json:"rope_global_base_freq"`
+	SlidingWindow         uint32  `json:"sliding_window"`
 }
 
 func (p *gemma3Model) KV(t *Tokenizer) ggml.KV {
 	kv := p.ModelParameters.KV(t)
 	kv["general.architecture"] = "gemma3"
-	kv["gemma3.context_length"] = p.TextModel.MaxPositionEmbeddings
-	kv["gemma3.embedding_length"] = p.TextModel.HiddenSize
-	kv["gemma3.block_count"] = p.TextModel.HiddenLayers
-	kv["gemma3.text.feed_forward_length"] = p.TextModel.IntermediateSize
-	kv["gemma3.attention.head_count"] = p.TextModel.NumAttentionHeads
-	kv["gemma3.attention.head_count_kv"] = p.TextModel.NumKeyValueHeads
-	kv["gemma3.text.attention.layer_norm_rms_epsilon"] = p.TextModel.RMSNormEPS
-	kv["gemma3.attention.key_length"] = p.TextModel.HeadDim
-	kv["gemma3.attention.value_length"] = p.TextModel.HeadDim
-	kv["gemma3.text.attention.sliding_window"] = p.TextModel.SlidingWindow
-	kv["gemma3.text.final_logit_softcapping"] = p.TextModel.FinalLogitSoftcap
-	kv["gemma3.text.rope.local.freq_base"] = p.TextModel.RopeLocalTheta
-	kv["gemma3.text.rope.global.freq_base"] = p.TextModel.RopeGlobalTheta
 
-	kv["gemma3.vision.block_count"] = p.VisionModel.NumHiddenLayers
-	kv["gemma3.vision.embedding_length"] = p.VisionModel.HiddenSize
-	kv["gemma3.vision.feed_forward_length"] = p.VisionModel.IntermediateSize
-	kv["gemma3.vision.image_size"] = p.VisionModel.ImageSize
-	kv["gemma3.vision.patch_size"] = p.VisionModel.PatchSize
-	kv["gemma3.vision.num_channels"] = p.VisionModel.NumChannels
-	kv["gemma3.vision.attention.head_count"] = p.VisionModel.NumAttentionHeads
-	kv["gemma3.vision.attention.layer_norm_epsilon"] = p.VisionModel.LayerNormEpsilon
+	switch p.Architecture {
+	case "Gemma3ForCausalLM":
+		kv["gemma3.context_length"] = p.MaxPositionEmbeddings
+		kv["gemma3.attention.head_count"] = p.NumAttentionHeads
+		kv["gemma3.attention.head_count_kv"] = p.NumKeyValueHeads
+		kv["gemma3.text.attention.layer_norm_rms_epsilon"] = p.RMSNormEPS
+		kv["gemma3.attention.key_length"] = p.HeadDim
+		kv["gemma3.attention.value_length"] = p.HeadDim
+		kv["gemma3.text.attention.sliding_window"] = p.SlidingWindow
+		kv["gemma3.text.final_logit_softcapping"] = p.FinalLogitSoftcap
+		kv["gemma3.text.rope.local.freq_base"] = p.RopeLocalTheta
+		kv["gemma3.text.rope.global.freq_base"] = p.RopeGlobalTheta
+		kv["gemma3.embedding_length"] = p.HiddenSize
+		kv["gemma3.block_count"] = p.HiddenLayers
+		kv["gemma3.text.feed_forward_length"] = p.IntermediateSize
+	default:
+		kv["gemma3.embedding_length"] = p.TextModel.HiddenSize
+		kv["gemma3.block_count"] = p.TextModel.HiddenLayers
+		kv["gemma3.text.feed_forward_length"] = p.TextModel.IntermediateSize
+		kv["gemma3.text.attention.sliding_window"] = p.TextModel.SlidingWindow
+		kv["gemma3.vision.block_count"] = p.VisionModel.NumHiddenLayers
+		kv["gemma3.vision.embedding_length"] = p.VisionModel.HiddenSize
+		kv["gemma3.vision.feed_forward_length"] = p.VisionModel.IntermediateSize
+		kv["gemma3.vision.image_size"] = p.VisionModel.ImageSize
+		kv["gemma3.vision.patch_size"] = p.VisionModel.PatchSize
+		kv["gemma3.vision.num_channels"] = p.VisionModel.NumChannels
+		kv["gemma3.vision.attention.head_count"] = p.VisionModel.NumAttentionHeads
+		kv["gemma3.vision.attention.layer_norm_epsilon"] = p.VisionModel.LayerNormEpsilon
+	}
+
+	kv["tokenizer.ggml.bos_token_id"] = uint32(2)
+	kv["tokenizer.ggml.eot_token_id"] = uint32(1)
+
 	return kv
 }
 
diff --git a/model/models/gemma3/model_text.go b/model/models/gemma3/model_text.go
index 46ed6fe2..ec46ba9a 100644
--- a/model/models/gemma3/model_text.go
+++ b/model/models/gemma3/model_text.go
@@ -32,7 +32,8 @@ type TextModel struct {
 }
 
 const (
-	gemma27BLayerCount = 46
+	gemmaGlobalCacheCount = 6
+	gemma27BLayerCount    = 46
 )
 
 const (
@@ -55,15 +56,15 @@ func newTextModel(c ml.Config) *TextModel {
 		Layers: make([]TextLayer, c.Uint("block_count")),
 		TextOptions: &TextOptions{
 			hiddenSize:        int(c.Uint("embedding_length")),
-			numHeads:          int(c.Uint("attention.head_count")),
-			numKVHeads:        int(c.Uint("attention.head_count_kv")),
-			attnKeyLen:        int(c.Uint("attention.key_length")),
-			attnValLen:        int(c.Uint("attention.value_length")),
-			eps:               c.Float("text.attention.layer_norm_rms_epsilon"),
+			numHeads:          int(c.Uint("attention.head_count", 8)),
+			numKVHeads:        int(c.Uint("attention.head_count_kv", 4)),
+			attnKeyLen:        int(c.Uint("attention.key_length", 256)),
+			attnValLen:        int(c.Uint("attention.value_length", 256)),
+			eps:               c.Float("text.attention.layer_norm_rms_epsilon", 1e-06),
 			ropeLocalBase:     c.Float("text.rope.local.freq_base", 10000.0),
 			ropeGlobalBase:    c.Float("text.rope.global.freq_base", 1000000.0),
 			ropeScale:         c.Float("text.rope.freq_scale", 1.0),
-			finalLogitSoftcap: c.Float("text.final_logit_softcapping"),
+			finalLogitSoftcap: c.Float("text.final_logit_softcapping", 30.0),
 		},
 	}
 
@@ -84,7 +85,7 @@ func (sa *TextSelfAttention) Forward(ctx ml.Context, layer int, hiddenState, pos
 	ropeType := uint32(2)
 
 	ropeBase := opts.ropeLocalBase
-	if (layer+1)%6 == 0 {
+	if (layer+1)%gemmaGlobalCacheCount == 0 {
 		ropeBase = opts.ropeGlobalBase
 	}
 
@@ -116,7 +117,7 @@ func (sa *TextSelfAttention) Forward(ctx ml.Context, layer int, hiddenState, pos
 
 func (m *TextModel) Shift(ctx ml.Context, layer int, key, shift ml.Tensor) (ml.Tensor, error) {
 	ropeBase := m.TextOptions.ropeLocalBase
-	if (layer+1)%6 == 0 {
+	if (layer+1)%gemmaGlobalCacheCount == 0 {
 		ropeBase = m.TextOptions.ropeGlobalBase
 	}
 
@@ -184,7 +185,7 @@ func (m *TextModel) Forward(ctx ml.Context, inputs, positions, outputs ml.Tensor
 		// gemma alternates between the sliding window (local) and causal (global)
 		// kv cache every 6 layers
 		cacheType := cacheTypeSWA
-		if (i+1)%6 == 0 {
+		if (i+1)%gemmaGlobalCacheCount == 0 {
 			cacheType = cacheTypeCausal
 		}
 		cache.SetLayer(i)

From 0e886595bf3d4ee33737f4b30154210b0df2d2df Mon Sep 17 00:00:00 2001
From: Jesse Gross <jesse@ollama.com>
Date: Fri, 7 Mar 2025 16:05:56 -0800
Subject: [PATCH 043/157] Fix tests and drift from main

---
 kvcache/causal_test.go            | 4 ++++
 model/models/gemma2/model.go      | 2 +-
 model/models/mllama/model_text.go | 2 +-
 3 files changed, 6 insertions(+), 2 deletions(-)

diff --git a/kvcache/causal_test.go b/kvcache/causal_test.go
index 431a79b5..ed23cad6 100644
--- a/kvcache/causal_test.go
+++ b/kvcache/causal_test.go
@@ -499,6 +499,10 @@ func (t *testTensor) Contiguous(ctx ml.Context) ml.Tensor {
 	panic("not implemented")
 }
 
+func (t *testTensor) Set(ctx ml.Context, t2 ml.Tensor, offset int, strides ...int) ml.Tensor {
+	panic("not implemented")
+}
+
 func (t *testTensor) Pad(ctx ml.Context, shape ...int) ml.Tensor {
 	panic("not implemented")
 }
diff --git a/model/models/gemma2/model.go b/model/models/gemma2/model.go
index a82d68d3..2b8597c4 100644
--- a/model/models/gemma2/model.go
+++ b/model/models/gemma2/model.go
@@ -179,7 +179,7 @@ func (m *Model) Forward(ctx ml.Context, opts input.Options) (ml.Tensor, error) {
 		return nil, err
 	}
 
-	outputs, err := ctx.FromIntSlice(opts.Outputs, len(opts.Outputs))
+	outputs, err := ctx.Output().FromIntSlice(opts.Outputs, len(opts.Outputs))
 	if err != nil {
 		return nil, err
 	}
diff --git a/model/models/mllama/model_text.go b/model/models/mllama/model_text.go
index 40c9a970..1cf30d89 100644
--- a/model/models/mllama/model_text.go
+++ b/model/models/mllama/model_text.go
@@ -28,7 +28,7 @@ func (sa *TextSelfAttention) Forward(ctx ml.Context, hiddenState, positions, _ m
 
 	key := sa.Key.Forward(ctx, hiddenState)
 	key = key.Reshape(ctx, headDim, opts.numKVHeads, batchSize)
-	key = key.RoPE(ctx, positions, sa.RopeFactors, opts.ropeDim,  ropeType, opts.ropeBase, opts.ropeScale)
+	key = key.RoPE(ctx, positions, sa.RopeFactors, opts.ropeDim, ropeType, opts.ropeBase, opts.ropeScale)
 
 	value := sa.Value.Forward(ctx, hiddenState)
 	value = value.Reshape(ctx, headDim, opts.numKVHeads, batchSize)

From 8934324b72c962fdff69ecee9c13d5d69580a1b7 Mon Sep 17 00:00:00 2001
From: Michael Yang <mxyng@pm.me>
Date: Fri, 7 Mar 2025 17:38:36 -0800
Subject: [PATCH 044/157] use fast attention

---
 ml/backend/ggml/ggml.go             |  4 ++--
 model/models/gemma3/model.go        |  4 ++--
 model/models/gemma3/model_vision.go | 14 ++++----------
 3 files changed, 8 insertions(+), 14 deletions(-)

diff --git a/ml/backend/ggml/ggml.go b/ml/backend/ggml/ggml.go
index 487ea524..9ff4446b 100644
--- a/ml/backend/ggml/ggml.go
+++ b/ml/backend/ggml/ggml.go
@@ -958,9 +958,9 @@ func (t *Tensor) Set(ctx ml.Context, t2 ml.Tensor, offset int, strides ...int) m
 	var tt *C.struct_ggml_tensor
 	switch len(strides) {
 	case 0:
-		tt = C.ggml_set_1d_inplace(ctx.(*Context).ctx, t.t, t2.(*Tensor).t, C.size_t(offset))
+		tt = C.ggml_set_1d(ctx.(*Context).ctx, t.t, t2.(*Tensor).t, C.size_t(offset))
 	case 1:
-		tt = C.ggml_set_2d_inplace(ctx.(*Context).ctx, t.t, t2.(*Tensor).t, C.size_t(offset), C.size_t(strides[0]))
+		tt = C.ggml_set_2d(ctx.(*Context).ctx, t.t, t2.(*Tensor).t, C.size_t(offset), C.size_t(strides[0]))
 	default:
 		panic("unsupported number of dimensions")
 	}
diff --git a/model/models/gemma3/model.go b/model/models/gemma3/model.go
index 2bb5232b..f9beccc2 100644
--- a/model/models/gemma3/model.go
+++ b/model/models/gemma3/model.go
@@ -138,8 +138,8 @@ func (m *Model) PostTokenize(ctx ml.Context, inputs []input.Input) ([]input.Inpu
 				{Token: 255999}, // "<start_of_image>""
 			}
 
-			// <image_soft_token>
-			imageInputs = append(imageInputs, slices.Repeat([]input.Input{{Token: 262144}}, 256)...)
+			// pad inputs with placeholders for image embeddings
+			imageInputs = append(imageInputs, slices.Repeat([]input.Input{{Token: 0}}, 256)...)
 			// <end_of_image>
 			imageInputs = append(imageInputs, input.Input{Token: 256000})
 
diff --git a/model/models/gemma3/model_vision.go b/model/models/gemma3/model_vision.go
index ee6e3b6f..49f9a5d2 100644
--- a/model/models/gemma3/model_vision.go
+++ b/model/models/gemma3/model_vision.go
@@ -24,17 +24,11 @@ func (sa *VisionSelfAttention) Forward(ctx ml.Context, hiddenState ml.Tensor, op
 	key := sa.Key.Forward(ctx, hiddenState)
 	value := sa.Value.Forward(ctx, hiddenState)
 
-	query = query.Reshape(ctx, headDim, opts.numHeads, query.Dim(1), batchSize).Permute(ctx, 0, 2, 1, 3)
-	key = key.Reshape(ctx, headDim, opts.numHeads, key.Dim(1), batchSize).Permute(ctx, 0, 2, 1, 3)
-	value = value.Reshape(ctx, headDim, opts.numHeads, value.Dim(1), batchSize).Permute(ctx, 1, 2, 0, 3).Contiguous(ctx)
+	query = query.Reshape(ctx, headDim, opts.numHeads, query.Dim(1), batchSize)
+	key = key.Reshape(ctx, headDim, opts.numHeads, key.Dim(1), batchSize)
+	value = value.Reshape(ctx, headDim, opts.numHeads, value.Dim(1), batchSize)
 
-	scores := key.Mulmat(ctx, query)
-	scores = scores.Scale(ctx, 1.0/math.Sqrt(float64(headDim)))
-	scores = scores.Softmax(ctx)
-
-	attention := value.Mulmat(ctx, scores)
-	attention = attention.Reshape(ctx, headDim, attention.Dim(1), opts.numHeads, batchSize)
-	attention = attention.Permute(ctx, 0, 2, 1, 3).Contiguous(ctx)
+	attention := nn.Attention(ctx, query, key, value, 1.0/math.Sqrt(float64(headDim)), nil)
 	attention = attention.Reshape(ctx, opts.hiddenSize, attention.Dim(2), batchSize)
 
 	hiddenState = sa.Output.Forward(ctx, attention)

From 46bb0169c40f466994cde8a89b455d8e3f9e177e Mon Sep 17 00:00:00 2001
From: Michael Yang <mxyng@pm.me>
Date: Sat, 8 Mar 2025 12:31:57 -0800
Subject: [PATCH 045/157] update model

---
 convert/convert_gemma3.go            | 10 ++--
 model/models/gemma3/model.go         |  8 +---
 model/models/gemma3/model_text.go    |  4 +-
 model/models/gemma3/model_vision.go  | 68 ++++++----------------------
 model/models/gemma3/process_image.go | 12 ++---
 5 files changed, 28 insertions(+), 74 deletions(-)

diff --git a/convert/convert_gemma3.go b/convert/convert_gemma3.go
index f43248db..fab5fcd8 100644
--- a/convert/convert_gemma3.go
+++ b/convert/convert_gemma3.go
@@ -1,6 +1,10 @@
 package convert
 
-import "github.com/ollama/ollama/fs/ggml"
+import (
+	"cmp"
+
+	"github.com/ollama/ollama/fs/ggml"
+)
 
 type gemma3Model struct {
 	gemmaModel
@@ -61,9 +65,9 @@ func (p *gemma3Model) KV(t *Tokenizer) ggml.KV {
 		kv["gemma3.vision.feed_forward_length"] = p.VisionModel.IntermediateSize
 		kv["gemma3.vision.image_size"] = p.VisionModel.ImageSize
 		kv["gemma3.vision.patch_size"] = p.VisionModel.PatchSize
-		kv["gemma3.vision.num_channels"] = p.VisionModel.NumChannels
+		kv["gemma3.vision.num_channels"] = cmp.Or(p.VisionModel.NumChannels, 3)
 		kv["gemma3.vision.attention.head_count"] = p.VisionModel.NumAttentionHeads
-		kv["gemma3.vision.attention.layer_norm_epsilon"] = p.VisionModel.LayerNormEpsilon
+		kv["gemma3.vision.attention.layer_norm_epsilon"] = cmp.Or(p.VisionModel.LayerNormEpsilon, 1e-6)
 	}
 
 	kv["tokenizer.ggml.bos_token_id"] = uint32(2)
diff --git a/model/models/gemma3/model.go b/model/models/gemma3/model.go
index f9beccc2..a2e9c7f4 100644
--- a/model/models/gemma3/model.go
+++ b/model/models/gemma3/model.go
@@ -88,13 +88,7 @@ func (m *Model) EncodeMultimodal(ctx ml.Context, multimodalData []byte) (any, er
 		return nil, err
 	}
 
-	positionIDs, err := ctx.FromIntSlice([]int32{0}, 1)
-	if err != nil {
-		return nil, err
-	}
-
-	visionOutputs := m.VisionModel.Forward(ctx, pixelValues, positionIDs)
-
+	visionOutputs := m.VisionModel.Forward(ctx, pixelValues)
 	visionOutputs = visionOutputs.Permute(ctx, 1, 0, 2, 3).Contiguous(ctx)
 	patchesPerImage := m.ImageProcessor.imageSize / m.ImageProcessor.patchSize
 	kernelSize := patchesPerImage * patchesPerImage / 256
diff --git a/model/models/gemma3/model_text.go b/model/models/gemma3/model_text.go
index ec46ba9a..9a09bf1f 100644
--- a/model/models/gemma3/model_text.go
+++ b/model/models/gemma3/model_text.go
@@ -169,14 +169,14 @@ func (l *TextLayer) Forward(ctx ml.Context, layer int, hiddenState, positionIDs,
 
 func (m *TextModel) Forward(ctx ml.Context, inputs, positions, outputs ml.Tensor, multimodal []input.MultimodalIndex, cache kvcache.Cache) ml.Tensor {
 	hiddenState := m.TokenEmbedding.Forward(ctx, inputs)
+	hiddenState = hiddenState.Scale(ctx, math.Sqrt(float64(m.TextOptions.hiddenSize)))
+
 	if multimodal != nil {
 		visionOutputs := multimodal[0].Multimodal.(ml.Tensor)
 		offset := multimodal[0].Index - 1 - visionOutputs.Dim(1)
 		hiddenState = hiddenState.Set(ctx, visionOutputs, offset*hiddenState.Stride(0))
 	}
 
-	hiddenState = hiddenState.Scale(ctx, math.Sqrt(float64(m.TextOptions.hiddenSize)))
-
 	if len(m.Layers) == gemma27BLayerCount {
 		m.TextOptions.largeModelScaling = true
 	}
diff --git a/model/models/gemma3/model_vision.go b/model/models/gemma3/model_vision.go
index 49f9a5d2..a508f65b 100644
--- a/model/models/gemma3/model_vision.go
+++ b/model/models/gemma3/model_vision.go
@@ -2,7 +2,6 @@ package gemma3
 
 import (
 	"math"
-	"slices"
 
 	"github.com/ollama/ollama/ml"
 	"github.com/ollama/ollama/ml/nn"
@@ -69,52 +68,6 @@ func (e *VisionEncoderLayer) Forward(ctx ml.Context, hiddenState ml.Tensor, opts
 	return hiddenState.Add(ctx, residual)
 }
 
-type VisionEncoder struct {
-	Layers []VisionEncoderLayer
-}
-
-func (e *VisionEncoder) Forward(ctx ml.Context, hiddenState ml.Tensor, intermediateLayersIndices []uint32, opts *VisionModelOptions) (ml.Tensor, []ml.Tensor) {
-	var intermediateHiddenStates []ml.Tensor
-	for i, layer := range e.Layers {
-		if slices.Contains(intermediateLayersIndices, uint32(i)) {
-			intermediateHiddenStates = append(intermediateHiddenStates, hiddenState.Reshape(ctx, append([]int{1}, hiddenState.Shape()...)...))
-		}
-
-		hiddenState = layer.Forward(ctx, hiddenState, opts)
-	}
-
-	return hiddenState, intermediateHiddenStates
-}
-
-type PrecomputedAspectRatioEmbedding struct {
-	Embedding *nn.Embedding
-	Gate      ml.Tensor `gguf:"gate"`
-}
-
-func (e *PrecomputedAspectRatioEmbedding) Forward(ctx ml.Context, hiddenState ml.Tensor, aspectRatioIDs ml.Tensor, opts *VisionModelOptions) ml.Tensor {
-	embeddings := e.Embedding.Forward(ctx, aspectRatioIDs)
-	embeddings = embeddings.Reshape(ctx, opts.hiddenSize, 1, opts.numTiles)
-	if e.Gate != nil {
-		embeddings = embeddings.Mul(ctx, e.Gate)
-	}
-
-	return hiddenState.Add(ctx, embeddings)
-}
-
-type PrecomputedPositionEmbedding struct {
-	PositionEmbedding     *nn.Embedding `gguf:"position_embd"`
-	PositionEmbeddingGate ml.Tensor     `gguf:"position_embd.gate"`
-}
-
-func (e *PrecomputedPositionEmbedding) Forward(ctx ml.Context, hiddenState, positionIDs ml.Tensor, numPositions int, opts *VisionModelOptions) ml.Tensor {
-	positionEmbedding := e.PositionEmbedding.Forward(ctx, positionIDs)
-	if e.PositionEmbeddingGate != nil {
-		positionEmbedding = positionEmbedding.Mul(ctx, e.PositionEmbeddingGate)
-	}
-
-	return hiddenState.Add(ctx, positionEmbedding)
-}
-
 type VisionModelOptions struct {
 	hiddenSize, numHeads, numTiles int
 	imageSize, patchSize           int
@@ -126,22 +79,31 @@ type VisionModel struct {
 	PositionEmbedding *nn.Embedding `gguf:"position_embedding"`
 	PostLayerNorm     *nn.LayerNorm `gguf:"post_layernorm"`
 
-	Encoder *VisionEncoder `gguf:"blk"`
+	Layers []VisionEncoderLayer `gguf:"blk"`
 
 	*VisionModelOptions
 }
 
-func (m *VisionModel) Forward(ctx ml.Context, pixelValues, positionIDs ml.Tensor) ml.Tensor {
+func (m *VisionModel) Forward(ctx ml.Context, pixelValues ml.Tensor) ml.Tensor {
 	numPatches := (m.imageSize / m.patchSize) * (m.imageSize / m.patchSize)
 
 	hiddenState := m.PatchEmbedding.Forward(ctx, pixelValues, m.patchSize, m.patchSize, 0, 0, 1, 1)
 	hiddenState = hiddenState.Reshape(ctx, numPatches, m.hiddenSize)
 	hiddenState = hiddenState.Permute(ctx, 1, 0, 2, 3).Contiguous(ctx)
 
-	positions := m.PositionEmbedding.Forward(ctx, positionIDs)
-	hiddenState = hiddenState.Add(ctx, positions)
+	positions := make([]int32, numPatches)
+	for i := range positions {
+		positions[i] = int32(i)
+	}
 
-	for _, layer := range m.Encoder.Layers {
+	positionIDs, err := ctx.Input().FromIntSlice(positions, len(positions))
+	if err != nil {
+		panic(err)
+	}
+
+	hiddenState = hiddenState.Add(ctx, m.PositionEmbedding.Forward(ctx, positionIDs))
+
+	for _, layer := range m.Layers {
 		hiddenState = layer.Forward(ctx, hiddenState, m.VisionModelOptions)
 	}
 
@@ -151,7 +113,7 @@ func (m *VisionModel) Forward(ctx ml.Context, pixelValues, positionIDs ml.Tensor
 
 func newVisionModel(c ml.Config) *VisionModel {
 	return &VisionModel{
-		Encoder: &VisionEncoder{Layers: make([]VisionEncoderLayer, c.Uint("vision.block_count"))},
+		Layers: make([]VisionEncoderLayer, c.Uint("vision.block_count")),
 		VisionModelOptions: &VisionModelOptions{
 			hiddenSize: int(c.Uint("vision.embedding_length")),
 			numHeads:   int(c.Uint("vision.attention.head_count")),
diff --git a/model/models/gemma3/process_image.go b/model/models/gemma3/process_image.go
index a32e60e5..96179404 100644
--- a/model/models/gemma3/process_image.go
+++ b/model/models/gemma3/process_image.go
@@ -23,9 +23,8 @@ func (p *ImageProcessor) pack(img image.Image, mean, std [3]float32) []float32 {
 	var pixelVals []float32
 
 	bounds := img.Bounds()
-	var rVals, gVals, bVals []float32
-	for y := bounds.Min.Y; y < bounds.Max.Y; y++ {
-		for x := bounds.Min.X; x < bounds.Max.X; x++ {
+	for x := bounds.Min.X; x < bounds.Max.X; x++ {
+		for y := bounds.Min.Y; y < bounds.Max.Y; y++ {
 			c := img.At(x, y)
 			r, g, b, _ := c.RGBA()
 			rVal := float32(r>>8) / 255.0
@@ -36,14 +35,9 @@ func (p *ImageProcessor) pack(img image.Image, mean, std [3]float32) []float32 {
 			gVal = (gVal - mean[1]) / std[1]
 			bVal = (bVal - mean[2]) / std[2]
 
-			rVals = append(rVals, rVal)
-			gVals = append(gVals, gVal)
-			bVals = append(bVals, bVal)
+			pixelVals = append(pixelVals, rVal, gVal, bVal)
 		}
 	}
-	pixelVals = append(pixelVals, rVals...)
-	pixelVals = append(pixelVals, gVals...)
-	pixelVals = append(pixelVals, bVals...)
 
 	return pixelVals
 }

From 9b54267e6951ec6cff7fc2188899ac5d4169ab79 Mon Sep 17 00:00:00 2001
From: Patrick Devine <patrick@infrahq.com>
Date: Sat, 8 Mar 2025 16:16:23 -0800
Subject: [PATCH 046/157] fix configs

---
 convert/convert_gemma3.go         | 42 +++++++++++++++++++++++++------
 model/models/gemma3/model_text.go | 18 +++++++------
 2 files changed, 45 insertions(+), 15 deletions(-)

diff --git a/convert/convert_gemma3.go b/convert/convert_gemma3.go
index fab5fcd8..be65fdb0 100644
--- a/convert/convert_gemma3.go
+++ b/convert/convert_gemma3.go
@@ -10,6 +10,7 @@ type gemma3Model struct {
 	gemmaModel
 	Architecture string
 	TextModel    struct {
+		HeadDim          uint32 `json:"head_dim"`
 		HiddenSize       uint32 `json:"hidden_size"`
 		HiddenLayers     uint32 `json:"num_hidden_layers"`
 		IntermediateSize uint32 `json:"intermediate_size"`
@@ -36,15 +37,45 @@ type gemma3Model struct {
 	SlidingWindow         uint32  `json:"sliding_window"`
 }
 
+const (
+	gemma4BLayerCount  = 34
+	gemma12BLayerCount = 48
+	gemma27BLayerCount = 62
+)
+
 func (p *gemma3Model) KV(t *Tokenizer) ggml.KV {
 	kv := p.ModelParameters.KV(t)
 	kv["general.architecture"] = "gemma3"
 
+	numBlocks := cmp.Or(p.HiddenLayers, p.TextModel.HiddenLayers)
+	kv["gemma3.block_count"] = numBlocks
+
+	var (
+		numHeads   uint32
+		numKVHeads uint32
+	)
+
+	switch numBlocks {
+	case gemma4BLayerCount:
+		numHeads = 8
+		numKVHeads = 4
+	case gemma12BLayerCount:
+		numHeads = 16
+		numKVHeads = 8
+	case gemma27BLayerCount:
+		numHeads = 32
+		numKVHeads = 16
+	default:
+		numHeads = p.NumAttentionHeads
+		numKVHeads = p.NumKeyValueHeads
+	}
+
+	kv["gemma3.attention.head_count"] = numHeads
+	kv["gemma3.attention.head_count_kv"] = numKVHeads
+
 	switch p.Architecture {
 	case "Gemma3ForCausalLM":
 		kv["gemma3.context_length"] = p.MaxPositionEmbeddings
-		kv["gemma3.attention.head_count"] = p.NumAttentionHeads
-		kv["gemma3.attention.head_count_kv"] = p.NumKeyValueHeads
 		kv["gemma3.text.attention.layer_norm_rms_epsilon"] = p.RMSNormEPS
 		kv["gemma3.attention.key_length"] = p.HeadDim
 		kv["gemma3.attention.value_length"] = p.HeadDim
@@ -53,11 +84,9 @@ func (p *gemma3Model) KV(t *Tokenizer) ggml.KV {
 		kv["gemma3.text.rope.local.freq_base"] = p.RopeLocalTheta
 		kv["gemma3.text.rope.global.freq_base"] = p.RopeGlobalTheta
 		kv["gemma3.embedding_length"] = p.HiddenSize
-		kv["gemma3.block_count"] = p.HiddenLayers
 		kv["gemma3.text.feed_forward_length"] = p.IntermediateSize
 	default:
 		kv["gemma3.embedding_length"] = p.TextModel.HiddenSize
-		kv["gemma3.block_count"] = p.TextModel.HiddenLayers
 		kv["gemma3.text.feed_forward_length"] = p.TextModel.IntermediateSize
 		kv["gemma3.text.attention.sliding_window"] = p.TextModel.SlidingWindow
 		kv["gemma3.vision.block_count"] = p.VisionModel.NumHiddenLayers
@@ -68,11 +97,10 @@ func (p *gemma3Model) KV(t *Tokenizer) ggml.KV {
 		kv["gemma3.vision.num_channels"] = cmp.Or(p.VisionModel.NumChannels, 3)
 		kv["gemma3.vision.attention.head_count"] = p.VisionModel.NumAttentionHeads
 		kv["gemma3.vision.attention.layer_norm_epsilon"] = cmp.Or(p.VisionModel.LayerNormEpsilon, 1e-6)
+		kv["gemma3.attention.key_length"] = cmp.Or(p.TextModel.HeadDim, 256)
+		kv["gemma3.attention.value_length"] = cmp.Or(p.TextModel.HeadDim, 256)
 	}
 
-	kv["tokenizer.ggml.bos_token_id"] = uint32(2)
-	kv["tokenizer.ggml.eot_token_id"] = uint32(1)
-
 	return kv
 }
 
diff --git a/model/models/gemma3/model_text.go b/model/models/gemma3/model_text.go
index 9a09bf1f..765fb111 100644
--- a/model/models/gemma3/model_text.go
+++ b/model/models/gemma3/model_text.go
@@ -33,7 +33,7 @@ type TextModel struct {
 
 const (
 	gemmaGlobalCacheCount = 6
-	gemma27BLayerCount    = 46
+	gemma27BLayerCount    = 62
 )
 
 const (
@@ -42,6 +42,8 @@ const (
 )
 
 func newTextModel(c ml.Config) *TextModel {
+	numBlocks := int(c.Uint("block_count"))
+
 	m := TextModel{
 		SentencePieceModel: model.NewSentencePieceModel(
 			c.String("tokenizer.ggml.pretokenizer", `(?i:'s|'t|'re|'ve|'m|'ll|'d)|[^\r\n\p{L}\p{N}]?\p{L}+|\p{N}{1,3}| ?[^\s\p{L}\p{N}]+[\r\n]*|\s*[\r\n]+|\s+(?!\S)|\s+`),
@@ -53,11 +55,11 @@ func newTextModel(c ml.Config) *TextModel {
 				EOS:    int32(c.Uint("tokenizer.ggml.eos_token_id")),
 			},
 		),
-		Layers: make([]TextLayer, c.Uint("block_count")),
+		Layers: make([]TextLayer, numBlocks),
 		TextOptions: &TextOptions{
 			hiddenSize:        int(c.Uint("embedding_length")),
-			numHeads:          int(c.Uint("attention.head_count", 8)),
-			numKVHeads:        int(c.Uint("attention.head_count_kv", 4)),
+			numHeads:          int(c.Uint("attention.head_count")),
+			numKVHeads:        int(c.Uint("attention.head_count_kv")),
 			attnKeyLen:        int(c.Uint("attention.key_length", 256)),
 			attnValLen:        int(c.Uint("attention.value_length", 256)),
 			eps:               c.Float("text.attention.layer_norm_rms_epsilon", 1e-06),
@@ -68,6 +70,10 @@ func newTextModel(c ml.Config) *TextModel {
 		},
 	}
 
+	if numBlocks == gemma27BLayerCount {
+		m.largeModelScaling = true
+	}
+
 	return &m
 }
 
@@ -177,10 +183,6 @@ func (m *TextModel) Forward(ctx ml.Context, inputs, positions, outputs ml.Tensor
 		hiddenState = hiddenState.Set(ctx, visionOutputs, offset*hiddenState.Stride(0))
 	}
 
-	if len(m.Layers) == gemma27BLayerCount {
-		m.TextOptions.largeModelScaling = true
-	}
-
 	for i, layer := range m.Layers {
 		// gemma alternates between the sliding window (local) and causal (global)
 		// kv cache every 6 layers

From d368c039f012b2abc5160577bfed6b9fad6b6f0a Mon Sep 17 00:00:00 2001
From: Michael Yang <mxyng@pm.me>
Date: Sun, 9 Mar 2025 11:28:53 -0700
Subject: [PATCH 047/157] skip repacking vision tensors

---
 convert/convert_gemma.go | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/convert/convert_gemma.go b/convert/convert_gemma.go
index 6c04145f..2f329943 100644
--- a/convert/convert_gemma.go
+++ b/convert/convert_gemma.go
@@ -45,7 +45,7 @@ func (p *gemmaModel) KV(t *Tokenizer) ggml.KV {
 func (p *gemmaModel) Tensors(ts []Tensor) []ggml.Tensor {
 	var out []ggml.Tensor
 	for _, t := range ts {
-		if strings.HasSuffix(t.Name(), "_norm.weight") {
+		if !strings.HasPrefix(t.Name(), "v.") && strings.HasSuffix(t.Name(), "_norm.weight") {
 			t.SetRepacker(p.addOne)
 		}
 

From 6b0486c216d639257b48f7c0b0bb01358bdbc765 Mon Sep 17 00:00:00 2001
From: Michael Yang <mxyng@pm.me>
Date: Sun, 9 Mar 2025 11:29:08 -0700
Subject: [PATCH 048/157] duplicate token_embd to output

---
 ml/backend/ggml/ggml.go | 3 +++
 1 file changed, 3 insertions(+)

diff --git a/ml/backend/ggml/ggml.go b/ml/backend/ggml/ggml.go
index 9ff4446b..b4efe9da 100644
--- a/ml/backend/ggml/ggml.go
+++ b/ml/backend/ggml/ggml.go
@@ -240,6 +240,9 @@ func New(r *os.File, params ml.BackendParams) (ml.Backend, error) {
 		switch {
 		case contains(t.Name, "position_embd", "token_embd", "token_norm_embd", "token_types"):
 			createTensor(tensor{source: t}, input.bts)
+			if _, ok := meta.Tensors().GroupLayers()["output"]; !ok && t.Name == "token_embd.weight" {
+				createTensor(tensor{source: t, target: "output.weight"}, output.bts)
+			}
 		case contains(t.Name, "cls", "output", "output_norm"):
 			createTensor(tensor{source: t}, output.bts)
 		case strings.HasPrefix(t.Name, "v.") || strings.HasPrefix(t.Name, "mm."):

From 9e4642e9b3e9a26d423c62915805375ca253d7d1 Mon Sep 17 00:00:00 2001
From: Michael Yang <mxyng@pm.me>
Date: Sun, 9 Mar 2025 14:45:36 -0700
Subject: [PATCH 049/157] ollama debug tensor

---
 llama/patches/0020-ollama-debug-tensor.patch  |  33 +++++
 ml/backend/ggml/ggml.go                       |   2 +-
 ml/backend/ggml/ggml/include/ollama-debug.h   |  11 ++
 .../ggml/ggml/src/ggml-cpu/cpu_debug.go       |   6 +
 ml/backend/ggml/ggml/src/ggml-cpu/ggml-cpu.c  |   6 +
 ml/backend/ggml/ggml/src/ollama-debug.c       | 115 ++++++++++++++++++
 ml/backend/ggml/threads.go                    |   7 ++
 ml/backend/ggml/threads_debug.go              |   7 ++
 8 files changed, 186 insertions(+), 1 deletion(-)
 create mode 100644 llama/patches/0020-ollama-debug-tensor.patch
 create mode 100644 ml/backend/ggml/ggml/include/ollama-debug.h
 create mode 100644 ml/backend/ggml/ggml/src/ggml-cpu/cpu_debug.go
 create mode 100644 ml/backend/ggml/ggml/src/ollama-debug.c
 create mode 100644 ml/backend/ggml/threads.go
 create mode 100644 ml/backend/ggml/threads_debug.go

diff --git a/llama/patches/0020-ollama-debug-tensor.patch b/llama/patches/0020-ollama-debug-tensor.patch
new file mode 100644
index 00000000..b9f2e4ab
--- /dev/null
+++ b/llama/patches/0020-ollama-debug-tensor.patch
@@ -0,0 +1,33 @@
+From 0000000000000000000000000000000000000000 Mon Sep 17 00:00:00 2001
+From: Michael Yang <mxyng@pm.me>
+Date: Sun, 9 Mar 2025 14:44:16 -0700
+Subject: [PATCH] ollama debug tensor
+
+---
+ ggml/src/ggml-cpu/ggml-cpu.c | 6 ++++++
+ 1 file changed, 6 insertions(+)
+
+diff --git a/ggml/src/ggml-cpu/ggml-cpu.c b/ggml/src/ggml-cpu/ggml-cpu.c
+index 2f606d82..ec60e8fc 100644
+--- a/ggml/src/ggml-cpu/ggml-cpu.c
++++ b/ggml/src/ggml-cpu/ggml-cpu.c
+@@ -11,6 +11,8 @@
+ #include "ggml-threading.h"
+ #include "ggml.h"
+ 
++#include "ollama-debug.h"
++
+ #if defined(_MSC_VER) || defined(__MINGW32__)
+ #include <malloc.h> // using malloc.h with MSC/MINGW
+ #elif !defined(__FreeBSD__) && !defined(__NetBSD__) && !defined(__OpenBSD__)
+@@ -14103,6 +14105,10 @@ static thread_ret_t ggml_graph_compute_thread(void * data) {
+ 
+         ggml_compute_forward(&params, node);
+ 
++#ifdef OLLAMA_DEBUG
++        ollama_debug(node, true);
++#endif
++
+         if (state->ith == 0 && cplan->abort_callback &&
+                 cplan->abort_callback(cplan->abort_callback_data)) {
+             atomic_store_explicit(&tp->abort, node_n + 1, memory_order_relaxed);
diff --git a/ml/backend/ggml/ggml.go b/ml/backend/ggml/ggml.go
index b4efe9da..6e123e1f 100644
--- a/ml/backend/ggml/ggml.go
+++ b/ml/backend/ggml/ggml.go
@@ -355,7 +355,7 @@ func New(r *os.File, params ml.BackendParams) (ml.Backend, error) {
 
 		if C.ggml_backend_is_cpu(b) {
 			// set number of threads for cpu backend
-			C.ggml_backend_cpu_set_n_threads(b, C.int(params.NumThreads))
+			C.ggml_backend_cpu_set_n_threads(b, C.int(Threads(params.NumThreads)))
 		}
 	}
 
diff --git a/ml/backend/ggml/ggml/include/ollama-debug.h b/ml/backend/ggml/ggml/include/ollama-debug.h
new file mode 100644
index 00000000..36a2e241
--- /dev/null
+++ b/ml/backend/ggml/ggml/include/ollama-debug.h
@@ -0,0 +1,11 @@
+#include "ggml.h"
+
+#ifdef __cplusplus
+extern "C" {
+#endif
+
+void ollama_debug(const struct ggml_tensor *tensor, bool verbose);
+
+#ifdef __cplusplus
+}
+#endif
diff --git a/ml/backend/ggml/ggml/src/ggml-cpu/cpu_debug.go b/ml/backend/ggml/ggml/src/ggml-cpu/cpu_debug.go
new file mode 100644
index 00000000..7eab9813
--- /dev/null
+++ b/ml/backend/ggml/ggml/src/ggml-cpu/cpu_debug.go
@@ -0,0 +1,6 @@
+//go:build debug
+
+package cpu
+
+// #cgo CPPFLAGS: -DOLLAMA_DEBUG
+import "C"
diff --git a/ml/backend/ggml/ggml/src/ggml-cpu/ggml-cpu.c b/ml/backend/ggml/ggml/src/ggml-cpu/ggml-cpu.c
index 2f606d82..ec60e8fc 100644
--- a/ml/backend/ggml/ggml/src/ggml-cpu/ggml-cpu.c
+++ b/ml/backend/ggml/ggml/src/ggml-cpu/ggml-cpu.c
@@ -11,6 +11,8 @@
 #include "ggml-threading.h"
 #include "ggml.h"
 
+#include "ollama-debug.h"
+
 #if defined(_MSC_VER) || defined(__MINGW32__)
 #include <malloc.h> // using malloc.h with MSC/MINGW
 #elif !defined(__FreeBSD__) && !defined(__NetBSD__) && !defined(__OpenBSD__)
@@ -14103,6 +14105,10 @@ static thread_ret_t ggml_graph_compute_thread(void * data) {
 
         ggml_compute_forward(&params, node);
 
+#ifdef OLLAMA_DEBUG
+        ollama_debug(node, true);
+#endif
+
         if (state->ith == 0 && cplan->abort_callback &&
                 cplan->abort_callback(cplan->abort_callback_data)) {
             atomic_store_explicit(&tp->abort, node_n + 1, memory_order_relaxed);
diff --git a/ml/backend/ggml/ggml/src/ollama-debug.c b/ml/backend/ggml/ggml/src/ollama-debug.c
new file mode 100644
index 00000000..b0e9d7f0
--- /dev/null
+++ b/ml/backend/ggml/ggml/src/ollama-debug.c
@@ -0,0 +1,115 @@
+#include <string.h>
+
+#include "ollama-debug.h"
+
+static int mul(int64_t *dims, int ndims) {
+    int result = 1;
+    for (int i = 0; i < ndims; i++) {
+        result *= dims[i];
+    }
+
+    return result;
+}
+
+static void repeat(char c, int n) {
+    for (int i = 0; i < n; i++) {
+        fprintf(stderr, "%c", c);
+    }
+}
+
+static void print_tensor(const void *tensor, void (*cb)(const void *, int),
+                         int shape,
+                         int64_t *dims, int ndims, int stride,
+                         int nitems, int pad) {
+    fprintf(stderr, "[");
+    for (int i = 0; i < dims[0]; i++) {
+        if (i >= nitems && i < dims[0] - nitems) {
+            fprintf(stderr, "... (%lld more), ", dims[0] - 2 * nitems);
+            int skip = dims[0] - 2 * nitems;
+            if (ndims > 1) {
+                stride += mul(dims + 1, ndims - 1) * skip;
+                repeat('\n', ndims - 1);
+                repeat(' ', shape - ndims + 1 + pad);
+            }
+            i += skip - 1;
+        } else if (ndims > 1) {
+            print_tensor(tensor, cb, shape, dims + 1, ndims - 1, stride,
+                         nitems, pad);
+            stride += mul(dims + 1, ndims - 1);
+            if (i < dims[0] - 1) {
+                fprintf(stderr, ", ");
+                repeat('\n', ndims - 1);
+                repeat(' ', shape - ndims + 1 + pad);
+            }
+        } else {
+            cb(tensor, stride + i);
+            if (i < dims[0] - 1) {
+                fprintf(stderr, ", ");
+            }
+        }
+    }
+    fprintf(stderr, "]");
+}
+
+static void print_tensor_f16(const void *tensor, int i) {
+    float value = ggml_fp16_to_fp32(((const ggml_fp16_t *)tensor)[i]);
+    fprintf(stderr, "%s%f", value < 0 ? "" : " ", value);
+}
+
+static void print_tensor_f32(const void *tensor, int i) {
+    float value = ((const float *)tensor)[i];
+    fprintf(stderr, "%s%f", value < 0 ? "" : " ", value);
+}
+
+static void print_tensor_i32(const void *tensor, int i) {
+    int32_t value = ((const int32_t *)tensor)[i];
+    fprintf(stderr, "%s%d", value < 0 ? "" : " ", value);
+}
+
+static void ollama_debug_tensor(const struct ggml_tensor *tensor, bool verbose, const char *prefix, int indent) {
+    fprintf(stderr, "%s%s %s (%s): [%lld %lld %lld %lld]\n", prefix, tensor->name,
+            ggml_op_name(tensor->op), ggml_type_name(tensor->type), tensor->ne[0],
+            tensor->ne[1], tensor->ne[2], tensor->ne[3]);
+
+    if (!verbose) {
+        return;
+    }
+
+    for (int i = 0; i < indent; i++) {
+        fprintf(stderr, " ");
+    }
+
+    switch (tensor->type) {
+    case GGML_TYPE_F16:
+        print_tensor(ggml_get_data(tensor), print_tensor_f16, ggml_n_dims(tensor),
+                     (int64_t *)tensor->ne, ggml_n_dims(tensor), 0, 3, indent);
+        break;
+    case GGML_TYPE_F32:
+        print_tensor(ggml_get_data(tensor), print_tensor_f32, ggml_n_dims(tensor),
+                     (int64_t *)tensor->ne, ggml_n_dims(tensor), 0, 3, indent);
+        break;
+    case GGML_TYPE_I32:
+        print_tensor(ggml_get_data(tensor), print_tensor_i32, ggml_n_dims(tensor),
+                     (int64_t *)tensor->ne, ggml_n_dims(tensor), 0, 3, indent);
+        break;
+    default:
+        fprintf(stderr, "<unsupported type>\n");
+        return;
+    }
+
+    fprintf(stderr, "\n");
+}
+
+void ollama_debug(const struct ggml_tensor *tensor, bool verbose) {
+    ollama_debug_tensor(tensor, verbose, ">>> ", 4);
+
+    for (int i = 0; i < GGML_MAX_SRC && tensor->src[i] != NULL; ++i) {
+        char src[8];
+        const int n = snprintf(src, sizeof(src), " src%d ", i);
+        if (n >= sizeof(src)) {
+            src[sizeof(src) - 1] = '\0';
+        }
+
+        ollama_debug_tensor(tensor->src[i], verbose, src, 4);
+    }
+}
diff --git a/ml/backend/ggml/threads.go b/ml/backend/ggml/threads.go
new file mode 100644
index 00000000..cbc524f7
--- /dev/null
+++ b/ml/backend/ggml/threads.go
@@ -0,0 +1,7 @@
+//go:build !debug
+
+package ggml
+
+func Threads(n int) int {
+	return n
+}
diff --git a/ml/backend/ggml/threads_debug.go b/ml/backend/ggml/threads_debug.go
new file mode 100644
index 00000000..cfd334bd
--- /dev/null
+++ b/ml/backend/ggml/threads_debug.go
@@ -0,0 +1,7 @@
+//go:build debug
+
+package ggml
+
+func Threads(_ int) int {
+	return 1
+}

From f888912870c16bf11511880775132804c441e731 Mon Sep 17 00:00:00 2001
From: Michael Yang <mxyng@pm.me>
Date: Sun, 9 Mar 2025 16:18:13 -0700
Subject: [PATCH 050/157] fix vision encoder

---
 model/models/gemma3/model_text.go    |  2 +-
 model/models/gemma3/process_image.go | 14 ++++++++++----
 2 files changed, 11 insertions(+), 5 deletions(-)

diff --git a/model/models/gemma3/model_text.go b/model/models/gemma3/model_text.go
index 765fb111..f1644e21 100644
--- a/model/models/gemma3/model_text.go
+++ b/model/models/gemma3/model_text.go
@@ -180,7 +180,7 @@ func (m *TextModel) Forward(ctx ml.Context, inputs, positions, outputs ml.Tensor
 	if multimodal != nil {
 		visionOutputs := multimodal[0].Multimodal.(ml.Tensor)
 		offset := multimodal[0].Index - 1 - visionOutputs.Dim(1)
-		hiddenState = hiddenState.Set(ctx, visionOutputs, offset*hiddenState.Stride(0))
+		hiddenState = hiddenState.Set(ctx, visionOutputs, offset*hiddenState.Stride(1))
 	}
 
 	for i, layer := range m.Layers {
diff --git a/model/models/gemma3/process_image.go b/model/models/gemma3/process_image.go
index 96179404..fe8269a3 100644
--- a/model/models/gemma3/process_image.go
+++ b/model/models/gemma3/process_image.go
@@ -20,11 +20,11 @@ func newImageProcessor(c ml.Config) ImageProcessor {
 }
 
 func (p *ImageProcessor) pack(img image.Image, mean, std [3]float32) []float32 {
-	var pixelVals []float32
+	var pixelVals, rVals, gVals, bVals []float32
 
 	bounds := img.Bounds()
-	for x := bounds.Min.X; x < bounds.Max.X; x++ {
-		for y := bounds.Min.Y; y < bounds.Max.Y; y++ {
+	for y := bounds.Min.Y; y < bounds.Max.Y; y++ {
+		for x := bounds.Min.X; x < bounds.Max.X; x++ {
 			c := img.At(x, y)
 			r, g, b, _ := c.RGBA()
 			rVal := float32(r>>8) / 255.0
@@ -35,10 +35,16 @@ func (p *ImageProcessor) pack(img image.Image, mean, std [3]float32) []float32 {
 			gVal = (gVal - mean[1]) / std[1]
 			bVal = (bVal - mean[2]) / std[2]
 
-			pixelVals = append(pixelVals, rVal, gVal, bVal)
+			rVals = append(rVals, rVal)
+			gVals = append(gVals, gVal)
+			bVals = append(bVals, bVal)
 		}
 	}
 
+	pixelVals = append(pixelVals, rVals...)
+	pixelVals = append(pixelVals, gVals...)
+	pixelVals = append(pixelVals, bVals...)
+
 	return pixelVals
 }
 

From c5cbe4fc2a9d0204f65a467aa6ebcfeef17ccb2b Mon Sep 17 00:00:00 2001
From: Michael Yang <mxyng@pm.me>
Date: Mon, 10 Mar 2025 10:46:17 -0700
Subject: [PATCH 051/157] fallback to cpu

---
 ml/backend/ggml/ggml.go | 18 ++++++++++--------
 1 file changed, 10 insertions(+), 8 deletions(-)

diff --git a/ml/backend/ggml/ggml.go b/ml/backend/ggml/ggml.go
index 6e123e1f..c635e9e0 100644
--- a/ml/backend/ggml/ggml.go
+++ b/ml/backend/ggml/ggml.go
@@ -248,6 +248,14 @@ func New(r *os.File, params ml.BackendParams) (ml.Backend, error) {
 		case strings.HasPrefix(t.Name, "v.") || strings.HasPrefix(t.Name, "mm."):
 			// TODO: assign vision tensors to the gpu if possible
 			createTensor(tensor{source: t}, input.bts)
+		case contains(t.Name, "rope_freqs", "rope_factors_long", "rope_factors_short"):
+			// these tensors should be repeated per layer
+			for i, layer := range layers {
+				createTensor(tensor{
+					source: t,
+					target: "blk." + strconv.Itoa(i) + "." + t.Name,
+				}, layer.bts)
+			}
 		default:
 			layerIndex := -1
 			if fields := strings.FieldsFunc(t.Name, func(r rune) bool { return !unicode.IsNumber(r) }); len(fields) > 0 {
@@ -259,14 +267,8 @@ func New(r *os.File, params ml.BackendParams) (ml.Backend, error) {
 			if layerIndex >= 0 {
 				createTensor(tensor{source: t}, layers[layerIndex].bts)
 			} else {
-				// this is a repeating tensor that doesn't explicitly associated with a layer so
-				// duplicate it for each layer
-				for i, layer := range layers {
-					createTensor(tensor{
-						source: t,
-						target: "blk." + strconv.Itoa(i) + "." + t.Name,
-					}, layer.bts)
-				}
+				// load all other tensors on the cpu
+				createTensor(tensor{source: t}, input.bts)
 			}
 		}
 	}

From 6b32a2d549ca3c37cae64ae6d6d2419e0f2bc139 Mon Sep 17 00:00:00 2001
From: Michael Yang <mxyng@pm.me>
Date: Mon, 10 Mar 2025 11:08:37 -0700
Subject: [PATCH 052/157] compat with upstream gguf

---
 convert/convert_gemma3.go         | 16 ++++++++--------
 model/models/gemma3/model.go      |  2 +-
 model/models/gemma3/model_text.go | 10 +++++-----
 3 files changed, 14 insertions(+), 14 deletions(-)

diff --git a/convert/convert_gemma3.go b/convert/convert_gemma3.go
index be65fdb0..f85a1adb 100644
--- a/convert/convert_gemma3.go
+++ b/convert/convert_gemma3.go
@@ -76,19 +76,19 @@ func (p *gemma3Model) KV(t *Tokenizer) ggml.KV {
 	switch p.Architecture {
 	case "Gemma3ForCausalLM":
 		kv["gemma3.context_length"] = p.MaxPositionEmbeddings
-		kv["gemma3.text.attention.layer_norm_rms_epsilon"] = p.RMSNormEPS
+		kv["gemma3.attention.layer_norm_rms_epsilon"] = p.RMSNormEPS
 		kv["gemma3.attention.key_length"] = p.HeadDim
 		kv["gemma3.attention.value_length"] = p.HeadDim
-		kv["gemma3.text.attention.sliding_window"] = p.SlidingWindow
-		kv["gemma3.text.final_logit_softcapping"] = p.FinalLogitSoftcap
-		kv["gemma3.text.rope.local.freq_base"] = p.RopeLocalTheta
-		kv["gemma3.text.rope.global.freq_base"] = p.RopeGlobalTheta
+		kv["gemma3.attention.sliding_window"] = p.SlidingWindow
+		kv["gemma3.final_logit_softcapping"] = p.FinalLogitSoftcap
+		kv["gemma3.rope.local.freq_base"] = p.RopeLocalTheta
+		kv["gemma3.rope.global.freq_base"] = p.RopeGlobalTheta
 		kv["gemma3.embedding_length"] = p.HiddenSize
-		kv["gemma3.text.feed_forward_length"] = p.IntermediateSize
+		kv["gemma3.feed_forward_length"] = p.IntermediateSize
 	default:
 		kv["gemma3.embedding_length"] = p.TextModel.HiddenSize
-		kv["gemma3.text.feed_forward_length"] = p.TextModel.IntermediateSize
-		kv["gemma3.text.attention.sliding_window"] = p.TextModel.SlidingWindow
+		kv["gemma3.feed_forward_length"] = p.TextModel.IntermediateSize
+		kv["gemma3.attention.sliding_window"] = p.TextModel.SlidingWindow
 		kv["gemma3.vision.block_count"] = p.VisionModel.NumHiddenLayers
 		kv["gemma3.vision.embedding_length"] = p.VisionModel.HiddenSize
 		kv["gemma3.vision.feed_forward_length"] = p.VisionModel.IntermediateSize
diff --git a/model/models/gemma3/model.go b/model/models/gemma3/model.go
index a2e9c7f4..0ea58874 100644
--- a/model/models/gemma3/model.go
+++ b/model/models/gemma3/model.go
@@ -62,7 +62,7 @@ func New(c ml.Config) (model.Model, error) {
 		TextModel:      newTextModel(c),
 	}
 
-	slidingWindowLen := int32(c.Uint("text.attention.sliding_window"))
+	slidingWindowLen := int32(c.Uint("attention.sliding_window"))
 	m.Cache = kvcache.NewWrapperCache(kvcache.NewSWACache(slidingWindowLen, m.Shift), kvcache.NewCausalCache(m.Shift))
 
 	return &m, nil
diff --git a/model/models/gemma3/model_text.go b/model/models/gemma3/model_text.go
index f1644e21..f63c2ed7 100644
--- a/model/models/gemma3/model_text.go
+++ b/model/models/gemma3/model_text.go
@@ -62,11 +62,11 @@ func newTextModel(c ml.Config) *TextModel {
 			numKVHeads:        int(c.Uint("attention.head_count_kv")),
 			attnKeyLen:        int(c.Uint("attention.key_length", 256)),
 			attnValLen:        int(c.Uint("attention.value_length", 256)),
-			eps:               c.Float("text.attention.layer_norm_rms_epsilon", 1e-06),
-			ropeLocalBase:     c.Float("text.rope.local.freq_base", 10000.0),
-			ropeGlobalBase:    c.Float("text.rope.global.freq_base", 1000000.0),
-			ropeScale:         c.Float("text.rope.freq_scale", 1.0),
-			finalLogitSoftcap: c.Float("text.final_logit_softcapping", 30.0),
+			eps:               c.Float("attention.layer_norm_rms_epsilon", 1e-06),
+			ropeLocalBase:     c.Float("rope.local.freq_base", 10000.0),
+			ropeGlobalBase:    c.Float("rope.global.freq_base", 1000000.0),
+			ropeScale:         c.Float("rope.freq_scale", 1.0),
+			finalLogitSoftcap: c.Float("final_logit_softcapping", 30.0),
 		},
 	}
 

From 2e54d72fc36f85d45c4392f14b2433972736d035 Mon Sep 17 00:00:00 2001
From: Patrick Devine <patrick@infrahq.com>
Date: Mon, 10 Mar 2025 15:35:07 -0700
Subject: [PATCH 053/157] fix gemma3 1b conversion

---
 convert/convert_gemma3.go | 9 ++++++---
 1 file changed, 6 insertions(+), 3 deletions(-)

diff --git a/convert/convert_gemma3.go b/convert/convert_gemma3.go
index f85a1adb..694aafca 100644
--- a/convert/convert_gemma3.go
+++ b/convert/convert_gemma3.go
@@ -80,12 +80,13 @@ func (p *gemma3Model) KV(t *Tokenizer) ggml.KV {
 		kv["gemma3.attention.key_length"] = p.HeadDim
 		kv["gemma3.attention.value_length"] = p.HeadDim
 		kv["gemma3.attention.sliding_window"] = p.SlidingWindow
-		kv["gemma3.final_logit_softcapping"] = p.FinalLogitSoftcap
-		kv["gemma3.rope.local.freq_base"] = p.RopeLocalTheta
-		kv["gemma3.rope.global.freq_base"] = p.RopeGlobalTheta
+		kv["gemma3.final_logit_softcapping"] = cmp.Or(p.FinalLogitSoftcap, 30)
+		kv["gemma3.rope.local.freq_base"] = cmp.Or(p.RopeLocalTheta, 10000.0)
+		kv["gemma3.rope.global.freq_base"] = cmp.Or(p.RopeGlobalTheta, 1000000.0)
 		kv["gemma3.embedding_length"] = p.HiddenSize
 		kv["gemma3.feed_forward_length"] = p.IntermediateSize
 	default:
+		kv["gemma3.context_length"] = cmp.Or(p.MaxPositionEmbeddings, 8192)
 		kv["gemma3.embedding_length"] = p.TextModel.HiddenSize
 		kv["gemma3.feed_forward_length"] = p.TextModel.IntermediateSize
 		kv["gemma3.attention.sliding_window"] = p.TextModel.SlidingWindow
@@ -111,6 +112,8 @@ func (p *gemma3Model) Replacements() []string {
 		"model.norm", "output_norm",
 		"vision_tower.vision_model.embeddings", "v",
 		"vision_tower.vision_model", "v",
+		"vision_model.vision_model.embeddings", "v",
+		"vision_model.vision_model", "v",
 		"language_model.", "",
 		"model.layers", "blk",
 		"encoder.layers", "blk",

From 9d2a20a7638a7c4e10cb119c3c3b6bf6e470ca3e Mon Sep 17 00:00:00 2001
From: Michael Yang <mxyng@pm.me>
Date: Mon, 10 Mar 2025 13:00:09 -0700
Subject: [PATCH 054/157] use non-causal mask for inputs with images

---
 model/models/gemma3/model_text.go | 5 +++++
 1 file changed, 5 insertions(+)

diff --git a/model/models/gemma3/model_text.go b/model/models/gemma3/model_text.go
index f63c2ed7..bf7f6b4c 100644
--- a/model/models/gemma3/model_text.go
+++ b/model/models/gemma3/model_text.go
@@ -181,6 +181,11 @@ func (m *TextModel) Forward(ctx ml.Context, inputs, positions, outputs ml.Tensor
 		visionOutputs := multimodal[0].Multimodal.(ml.Tensor)
 		offset := multimodal[0].Index - 1 - visionOutputs.Dim(1)
 		hiddenState = hiddenState.Set(ctx, visionOutputs, offset*hiddenState.Stride(1))
+
+		if causal, ok := cache.(*kvcache.WrapperCache).UnderlyingCache().(*kvcache.Causal); ok {
+			causal.SetCausal(ctx, false)
+			defer causal.SetCausal(ctx, true)
+		}
 	}
 
 	for i, layer := range m.Layers {

From e95278932bfd0eac5800ec28efe5c49a0d9ce8c3 Mon Sep 17 00:00:00 2001
From: Michael Yang <mxyng@pm.me>
Date: Mon, 10 Mar 2025 15:38:58 -0700
Subject: [PATCH 055/157] use non-causal mask only for image positions

---
 kvcache/causal.go                 | 20 ++++++++++++--------
 model/models/gemma3/model_text.go |  8 ++++++--
 2 files changed, 18 insertions(+), 10 deletions(-)

diff --git a/kvcache/causal.go b/kvcache/causal.go
index 34d5337c..02029800 100644
--- a/kvcache/causal.go
+++ b/kvcache/causal.go
@@ -21,9 +21,10 @@ type shiftFn func(ctx ml.Context, layer int, key, shift ml.Tensor) (ml.Tensor, e
 type Causal struct {
 	DType      ml.DType
 	Capacity   int32
-	causal     bool
 	windowSize int32
 
+	opts CausalOptions
+
 	// config controls mostly backend-specific optimizations
 	config *ml.CacheConfig
 
@@ -79,7 +80,6 @@ type cellRange struct {
 
 func NewCausalCache(shift shiftFn) *Causal {
 	return &Causal{
-		causal:     true,
 		windowSize: math.MaxInt32,
 		shiftFn:    shift,
 		ctxs:       make(map[int]ml.Context),
@@ -90,7 +90,6 @@ func NewCausalCache(shift shiftFn) *Causal {
 
 func NewSWACache(windowSize int32, shift shiftFn) *Causal {
 	return &Causal{
-		causal:     true,
 		windowSize: windowSize,
 		shiftFn:    shift,
 		ctxs:       make(map[int]ml.Context),
@@ -235,9 +234,10 @@ func (c *Causal) buildMask(ctx ml.Context) (ml.Tensor, error) {
 	mask := make([]float32, batchSize*length)
 
 	for i := range c.curBatchSize {
+		enabled := !slices.Contains(c.opts.Except, c.curPositions[i])
 		for j := c.curCellRange.min; j <= c.curCellRange.max; j++ {
 			if !slices.Contains(c.cells[j].sequences, c.curSequences[i]) ||
-				(c.causal && c.cells[j].pos > c.curPositions[i]) ||
+				(enabled && c.cells[j].pos > c.curPositions[i]) ||
 				c.cells[j].pos < c.curPositions[i]-c.windowSize {
 				mask[i*length+(j-c.curCellRange.min)] = float32(math.Inf(-1))
 			}
@@ -404,15 +404,19 @@ func (c *Causal) SetLayer(layer int) {
 	c.curLayer = layer
 }
 
+type CausalOptions struct {
+	// Enabled controls whether the causal mask is generated for a particular position.
+	Except []int32
+}
+
 // SetCausal enables or disables causal mask generation for subsequent calls to Get.
 // This state carries over to future forward passes. The default value is true.
 //
 // ctx may be set to nil if this is called from outside of a forward pass, for
 // example, when initializing the cache.
-func (c *Causal) SetCausal(ctx ml.Context, causal bool) {
-	if c.causal != causal {
-		c.causal = causal
-
+func (c *Causal) SetCausal(ctx ml.Context, opts CausalOptions) {
+	if !slices.Equal(c.opts.Except, opts.Except) {
+		c.opts = opts
 		if ctx != nil {
 			var err error
 			c.curMask, err = c.buildMask(ctx)
diff --git a/model/models/gemma3/model_text.go b/model/models/gemma3/model_text.go
index bf7f6b4c..de8070d9 100644
--- a/model/models/gemma3/model_text.go
+++ b/model/models/gemma3/model_text.go
@@ -183,8 +183,12 @@ func (m *TextModel) Forward(ctx ml.Context, inputs, positions, outputs ml.Tensor
 		hiddenState = hiddenState.Set(ctx, visionOutputs, offset*hiddenState.Stride(1))
 
 		if causal, ok := cache.(*kvcache.WrapperCache).UnderlyingCache().(*kvcache.Causal); ok {
-			causal.SetCausal(ctx, false)
-			defer causal.SetCausal(ctx, true)
+			except := make([]int32, visionOutputs.Dim(1))
+			for i := 0; i < visionOutputs.Dim(1); i++ {
+				except[i] = int32(offset + i)
+			}
+
+			causal.SetCausal(ctx, kvcache.CausalOptions{Except: except})
 		}
 	}
 

From 2c40c4d35eddc86673c5b0c116e2a34ef8ee2c4a Mon Sep 17 00:00:00 2001
From: Jesse Gross <jesse@ollama.com>
Date: Sun, 9 Mar 2025 21:29:58 -0700
Subject: [PATCH 056/157] Fix follow up images and images split across batches

---
 model/models/gemma3/model.go      | 57 ++++++++++++----------------
 model/models/gemma3/model_text.go | 63 +++++++++++++++++++++++--------
 2 files changed, 73 insertions(+), 47 deletions(-)

diff --git a/model/models/gemma3/model.go b/model/models/gemma3/model.go
index 0ea58874..7418bb12 100644
--- a/model/models/gemma3/model.go
+++ b/model/models/gemma3/model.go
@@ -5,7 +5,6 @@ import (
 	"encoding/binary"
 	"hash/fnv"
 	"image"
-	"slices"
 
 	"github.com/ollama/ollama/kvcache"
 	"github.com/ollama/ollama/ml"
@@ -99,49 +98,43 @@ func (m *Model) EncodeMultimodal(ctx ml.Context, multimodalData []byte) (any, er
 	return visionOutputs, nil
 }
 
+type imageToken struct {
+	embedding ml.Tensor
+	index     int
+}
+
 func (m *Model) PostTokenize(ctx ml.Context, inputs []input.Input) ([]input.Input, error) {
-	var images []input.Input
+	var result []input.Input
 	fnvHash := fnv.New64a()
 
-	for i := range inputs {
-		if inputs[i].Multimodal == nil {
-			for j := range images {
-				if j == 0 {
-					inputs[i].Multimodal = images[j].Multimodal
-					inputs[i].MultimodalHash = images[j].MultimodalHash
-				} else {
-					inputs[i].Multimodal = inputs[i].Multimodal.(ml.Tensor).Concat(ctx, images[j].Multimodal.(ml.Tensor), 3)
-					fnvHash.Reset()
-					binary.Write(fnvHash, binary.NativeEndian, inputs[i].MultimodalHash)
-					binary.Write(fnvHash, binary.NativeEndian, images[j].MultimodalHash)
-					inputs[i].MultimodalHash = fnvHash.Sum64()
-				}
-			}
-
-			images = nil
+	for _, inp := range inputs {
+		if inp.Multimodal == nil {
+			result = append(result, inp)
 		} else {
-			images = append(images, inputs[i])
-			inputs[i].Token = -1
-		}
-	}
-
-	for i := range inputs {
-		if inputs[i].Token == -1 {
 			imageInputs := []input.Input{
 				{Token: 108},    // "\n\n"
 				{Token: 255999}, // "<start_of_image>""
 			}
+			result = append(result, imageInputs...)
+
+			// add image embeddings
+			inputMultimodal := inp.Multimodal.(ml.Tensor)
+
+			for i := range inputMultimodal.Dim(1) {
+				fnvHash.Reset()
+				binary.Write(fnvHash, binary.NativeEndian, inp.MultimodalHash)
+				fnvHash.Write([]byte{byte(i)})
+
+				imageToken := imageToken{embedding: inputMultimodal, index: i}
+				result = append(result, input.Input{Multimodal: imageToken, MultimodalHash: fnvHash.Sum64()})
+			}
 
-			// pad inputs with placeholders for image embeddings
-			imageInputs = append(imageInputs, slices.Repeat([]input.Input{{Token: 0}}, 256)...)
 			// <end_of_image>
-			imageInputs = append(imageInputs, input.Input{Token: 256000})
-
-			inputs = append(inputs[:i], append(imageInputs, inputs[i+1:]...)...)
+			result = append(result, input.Input{Token: 256000})
 		}
 	}
 
-	return inputs, nil
+	return result, nil
 }
 
 func (m *Model) Forward(ctx ml.Context, opts input.Options) (ml.Tensor, error) {
@@ -160,7 +153,7 @@ func (m *Model) Forward(ctx ml.Context, opts input.Options) (ml.Tensor, error) {
 		return nil, err
 	}
 
-	return m.TextModel.Forward(ctx, inputs, positions, outputs, opts.Multimodal, m.Cache), nil
+	return m.TextModel.Forward(ctx, inputs, positions, outputs, opts, m.Cache), nil
 }
 
 func init() {
diff --git a/model/models/gemma3/model_text.go b/model/models/gemma3/model_text.go
index de8070d9..2180571e 100644
--- a/model/models/gemma3/model_text.go
+++ b/model/models/gemma3/model_text.go
@@ -173,24 +173,53 @@ func (l *TextLayer) Forward(ctx ml.Context, layer int, hiddenState, positionIDs,
 	return hiddenState.Add(ctx, residual)
 }
 
-func (m *TextModel) Forward(ctx ml.Context, inputs, positions, outputs ml.Tensor, multimodal []input.MultimodalIndex, cache kvcache.Cache) ml.Tensor {
+func setImageEmbeddings(ctx ml.Context, hiddenState ml.Tensor, multimodal []input.MultimodalIndex, positions []int32) []int32 {
+	var embedding ml.Tensor
+	var src, dst, length int
+	var except []int32
+
+	for _, image := range multimodal {
+		imageToken := image.Multimodal.(imageToken)
+		imageSrc := imageToken.index
+		imageDst := image.Index
+
+		if embedding == nil {
+			embedding = imageToken.embedding
+			src = imageSrc
+			dst = imageDst
+			length = 1
+		} else if embedding == imageToken.embedding && imageSrc+1 == src && imageDst+1 == dst {
+			src = imageSrc
+			dst = imageDst
+			length++
+		} else if embedding == imageToken.embedding && src+length == imageSrc && dst+length == imageDst {
+			length++
+		} else {
+			visionOutputs := embedding.View(ctx, src*embedding.Stride(1), length*embedding.Dim(0))
+			ctx.Forward(visionOutputs.Copy(ctx, hiddenState.View(ctx, dst*hiddenState.Stride(1), length*hiddenState.Dim(0))))
+
+			embedding = imageToken.embedding
+			src = imageSrc
+			dst = imageDst
+			length = 1
+		}
+
+		except = append(except, positions[imageDst])
+	}
+
+	if embedding != nil {
+		visionOutputs := embedding.View(ctx, src*embedding.Stride(1), length*embedding.Dim(0))
+		ctx.Forward(visionOutputs.Copy(ctx, hiddenState.View(ctx, dst*hiddenState.Stride(1), length*hiddenState.Dim(0))))
+	}
+
+	return except
+}
+
+func (m *TextModel) Forward(ctx ml.Context, inputs, positions, outputs ml.Tensor, opts input.Options, cache kvcache.Cache) ml.Tensor {
 	hiddenState := m.TokenEmbedding.Forward(ctx, inputs)
 	hiddenState = hiddenState.Scale(ctx, math.Sqrt(float64(m.TextOptions.hiddenSize)))
 
-	if multimodal != nil {
-		visionOutputs := multimodal[0].Multimodal.(ml.Tensor)
-		offset := multimodal[0].Index - 1 - visionOutputs.Dim(1)
-		hiddenState = hiddenState.Set(ctx, visionOutputs, offset*hiddenState.Stride(1))
-
-		if causal, ok := cache.(*kvcache.WrapperCache).UnderlyingCache().(*kvcache.Causal); ok {
-			except := make([]int32, visionOutputs.Dim(1))
-			for i := 0; i < visionOutputs.Dim(1); i++ {
-				except[i] = int32(offset + i)
-			}
-
-			causal.SetCausal(ctx, kvcache.CausalOptions{Except: except})
-		}
-	}
+	except := setImageEmbeddings(ctx, hiddenState, opts.Multimodal, opts.Positions)
 
 	for i, layer := range m.Layers {
 		// gemma alternates between the sliding window (local) and causal (global)
@@ -203,6 +232,10 @@ func (m *TextModel) Forward(ctx ml.Context, inputs, positions, outputs ml.Tensor
 		wc := cache.(*kvcache.WrapperCache)
 		wc.SetLayerType(cacheType)
 
+		if causal, ok := wc.UnderlyingCache().(*kvcache.Causal); ok {
+			causal.SetCausal(ctx, kvcache.CausalOptions{Except: except})
+		}
+
 		var lastLayerOutputs ml.Tensor
 		if i == len(m.Layers)-1 {
 			lastLayerOutputs = outputs

From 475005504ef6c6187ff35d818d6d681c30c54ae3 Mon Sep 17 00:00:00 2001
From: Jesse Gross <jesse@ollama.com>
Date: Mon, 10 Mar 2025 16:53:10 -0700
Subject: [PATCH 057/157] Restrict Gemma to a single image per request

---
 server/prompt.go | 12 +++++++++++-
 1 file changed, 11 insertions(+), 1 deletion(-)

diff --git a/server/prompt.go b/server/prompt.go
index 5b5b958f..d053f2a8 100644
--- a/server/prompt.go
+++ b/server/prompt.go
@@ -26,6 +26,7 @@ func chatPrompt(ctx context.Context, m *Model, tokenize tokenizeFunc, opts *api.
 	var system []api.Message
 
 	isMllama := checkMllamaModelFamily(m)
+	isGemma3 := checkGemma3ModelFamily(m)
 
 	var imageNumTokens int
 	// TODO: Ideally we would compute this from the projector metadata but some pieces are implementation dependent
@@ -40,7 +41,7 @@ func chatPrompt(ctx context.Context, m *Model, tokenize tokenizeFunc, opts *api.
 	n := len(msgs) - 1
 	// in reverse, find all messages that fit into context window
 	for i := n; i >= 0; i-- {
-		if isMllama && len(msgs[i].Images) > 1 {
+		if (isMllama || isGemma3) && len(msgs[i].Images) > 1 {
 			return "", nil, errTooManyImages
 		}
 
@@ -157,3 +158,12 @@ func checkMllamaModelFamily(m *Model) bool {
 	}
 	return false
 }
+
+func checkGemma3ModelFamily(m *Model) bool {
+	for _, arch := range m.Config.ModelFamilies {
+		if arch == "gemma3" {
+			return true
+		}
+	}
+	return false
+}

From a8e83a7654fffa169b90fa927e6d19c4c0c765d7 Mon Sep 17 00:00:00 2001
From: Jesse Gross <jesse@ollama.com>
Date: Mon, 10 Mar 2025 17:17:19 -0700
Subject: [PATCH 058/157] Disable causal attention based on batch index

Currently we are using positions, which are relative to a
sequence and may not be unique.
---
 kvcache/causal.go                 | 14 ++++++--------
 model/models/gemma3/model_text.go |  8 ++++----
 2 files changed, 10 insertions(+), 12 deletions(-)

diff --git a/kvcache/causal.go b/kvcache/causal.go
index 02029800..edf6666d 100644
--- a/kvcache/causal.go
+++ b/kvcache/causal.go
@@ -144,6 +144,7 @@ func (c *Causal) StartForward(ctx ml.Context, opts input.Options) error {
 	c.curBatchSize = len(opts.Positions)
 	c.curSequences = opts.Sequences
 	c.curPositions = opts.Positions
+	c.opts.Except = nil
 
 	var err error
 	c.curLoc, err = c.findStartLoc()
@@ -234,7 +235,7 @@ func (c *Causal) buildMask(ctx ml.Context) (ml.Tensor, error) {
 	mask := make([]float32, batchSize*length)
 
 	for i := range c.curBatchSize {
-		enabled := !slices.Contains(c.opts.Except, c.curPositions[i])
+		enabled := !slices.Contains(c.opts.Except, i)
 		for j := c.curCellRange.min; j <= c.curCellRange.max; j++ {
 			if !slices.Contains(c.cells[j].sequences, c.curSequences[i]) ||
 				(enabled && c.cells[j].pos > c.curPositions[i]) ||
@@ -405,15 +406,12 @@ func (c *Causal) SetLayer(layer int) {
 }
 
 type CausalOptions struct {
-	// Enabled controls whether the causal mask is generated for a particular position.
-	Except []int32
+	// Enabled controls whether the causal mask is generated for a particular index in a batch
+	Except []int
 }
 
-// SetCausal enables or disables causal mask generation for subsequent calls to Get.
-// This state carries over to future forward passes. The default value is true.
-//
-// ctx may be set to nil if this is called from outside of a forward pass, for
-// example, when initializing the cache.
+// SetCausal disables causal mask generation for a particular range of indicies in
+// the current batch for subsequent calls to Get. The state resets for the next forward pass.
 func (c *Causal) SetCausal(ctx ml.Context, opts CausalOptions) {
 	if !slices.Equal(c.opts.Except, opts.Except) {
 		c.opts = opts
diff --git a/model/models/gemma3/model_text.go b/model/models/gemma3/model_text.go
index 2180571e..5b5e2d6e 100644
--- a/model/models/gemma3/model_text.go
+++ b/model/models/gemma3/model_text.go
@@ -173,10 +173,10 @@ func (l *TextLayer) Forward(ctx ml.Context, layer int, hiddenState, positionIDs,
 	return hiddenState.Add(ctx, residual)
 }
 
-func setImageEmbeddings(ctx ml.Context, hiddenState ml.Tensor, multimodal []input.MultimodalIndex, positions []int32) []int32 {
+func setImageEmbeddings(ctx ml.Context, hiddenState ml.Tensor, multimodal []input.MultimodalIndex) []int {
 	var embedding ml.Tensor
 	var src, dst, length int
-	var except []int32
+	var except []int
 
 	for _, image := range multimodal {
 		imageToken := image.Multimodal.(imageToken)
@@ -204,7 +204,7 @@ func setImageEmbeddings(ctx ml.Context, hiddenState ml.Tensor, multimodal []inpu
 			length = 1
 		}
 
-		except = append(except, positions[imageDst])
+		except = append(except, imageDst)
 	}
 
 	if embedding != nil {
@@ -219,7 +219,7 @@ func (m *TextModel) Forward(ctx ml.Context, inputs, positions, outputs ml.Tensor
 	hiddenState := m.TokenEmbedding.Forward(ctx, inputs)
 	hiddenState = hiddenState.Scale(ctx, math.Sqrt(float64(m.TextOptions.hiddenSize)))
 
-	except := setImageEmbeddings(ctx, hiddenState, opts.Multimodal, opts.Positions)
+	except := setImageEmbeddings(ctx, hiddenState, opts.Multimodal)
 
 	for i, layer := range m.Layers {
 		// gemma alternates between the sliding window (local) and causal (global)

From 06007c0a187f3fa12cde58fc337f15cbf7a6cbf8 Mon Sep 17 00:00:00 2001
From: Jesse Gross <jesse@ollama.com>
Date: Mon, 10 Mar 2025 20:03:29 -0700
Subject: [PATCH 059/157] Allow models to force a new batch

This is useful for a few things:
 - Work around bugs, such as having 2 images in one batch
 - Keep the image in a single batch for fully connected attention
 - Improve performance by not evaluating embeddings multiple times
---
 model/input/input.go          |  6 ++++++
 model/models/gemma3/model.go  |  4 ++--
 runner/ollamarunner/runner.go |  2 +-
 server/prompt.go              | 12 +-----------
 4 files changed, 10 insertions(+), 14 deletions(-)

diff --git a/model/input/input.go b/model/input/input.go
index 0cb3f3f4..a1247bca 100644
--- a/model/input/input.go
+++ b/model/input/input.go
@@ -15,6 +15,12 @@ type Input struct {
 	// stored in Multimodal, used for caching and comparing
 	// equality.
 	MultimodalHash uint64
+
+	// BatchBreak forces a new batch to be started with this
+	// input. For example, this can be used to align images
+	// with batches. Note that batches may be divided in additional
+	// locations as well.
+	BatchBreak bool
 }
 
 // MultimodalIndex is a multimodal element (such as an image)
diff --git a/model/models/gemma3/model.go b/model/models/gemma3/model.go
index 7418bb12..2fe04348 100644
--- a/model/models/gemma3/model.go
+++ b/model/models/gemma3/model.go
@@ -112,8 +112,8 @@ func (m *Model) PostTokenize(ctx ml.Context, inputs []input.Input) ([]input.Inpu
 			result = append(result, inp)
 		} else {
 			imageInputs := []input.Input{
-				{Token: 108},    // "\n\n"
-				{Token: 255999}, // "<start_of_image>""
+				{Token: 108},                      // "\n\n"
+				{Token: 255999, BatchBreak: true}, // "<start_of_image>""
 			}
 			result = append(result, imageInputs...)
 
diff --git a/runner/ollamarunner/runner.go b/runner/ollamarunner/runner.go
index c1475cbb..9b997bd3 100644
--- a/runner/ollamarunner/runner.go
+++ b/runner/ollamarunner/runner.go
@@ -363,7 +363,7 @@ func (s *Server) processBatch() error {
 				}
 			}
 
-			if j >= s.batchSize {
+			if j >= s.batchSize || (inp.BatchBreak && len(seq.pendingInputs) != 0) {
 				break
 			}
 
diff --git a/server/prompt.go b/server/prompt.go
index d053f2a8..5b5b958f 100644
--- a/server/prompt.go
+++ b/server/prompt.go
@@ -26,7 +26,6 @@ func chatPrompt(ctx context.Context, m *Model, tokenize tokenizeFunc, opts *api.
 	var system []api.Message
 
 	isMllama := checkMllamaModelFamily(m)
-	isGemma3 := checkGemma3ModelFamily(m)
 
 	var imageNumTokens int
 	// TODO: Ideally we would compute this from the projector metadata but some pieces are implementation dependent
@@ -41,7 +40,7 @@ func chatPrompt(ctx context.Context, m *Model, tokenize tokenizeFunc, opts *api.
 	n := len(msgs) - 1
 	// in reverse, find all messages that fit into context window
 	for i := n; i >= 0; i-- {
-		if (isMllama || isGemma3) && len(msgs[i].Images) > 1 {
+		if isMllama && len(msgs[i].Images) > 1 {
 			return "", nil, errTooManyImages
 		}
 
@@ -158,12 +157,3 @@ func checkMllamaModelFamily(m *Model) bool {
 	}
 	return false
 }
-
-func checkGemma3ModelFamily(m *Model) bool {
-	for _, arch := range m.Config.ModelFamilies {
-		if arch == "gemma3" {
-			return true
-		}
-	}
-	return false
-}

From 65b0f329d1b6a9de6091c86a044b98fe6c543330 Mon Sep 17 00:00:00 2001
From: jmorganca <jmorganca@gmail.com>
Date: Tue, 11 Mar 2025 11:53:37 +0100
Subject: [PATCH 060/157] Revert "Allow models to force a new batch"

This reverts commit c7eae586b899083acebcd9b3847b89ea78c2850c.
---
 model/input/input.go          |  6 ------
 model/models/gemma3/model.go  |  4 ++--
 runner/ollamarunner/runner.go |  2 +-
 server/prompt.go              | 12 +++++++++++-
 4 files changed, 14 insertions(+), 10 deletions(-)

diff --git a/model/input/input.go b/model/input/input.go
index a1247bca..0cb3f3f4 100644
--- a/model/input/input.go
+++ b/model/input/input.go
@@ -15,12 +15,6 @@ type Input struct {
 	// stored in Multimodal, used for caching and comparing
 	// equality.
 	MultimodalHash uint64
-
-	// BatchBreak forces a new batch to be started with this
-	// input. For example, this can be used to align images
-	// with batches. Note that batches may be divided in additional
-	// locations as well.
-	BatchBreak bool
 }
 
 // MultimodalIndex is a multimodal element (such as an image)
diff --git a/model/models/gemma3/model.go b/model/models/gemma3/model.go
index 2fe04348..7418bb12 100644
--- a/model/models/gemma3/model.go
+++ b/model/models/gemma3/model.go
@@ -112,8 +112,8 @@ func (m *Model) PostTokenize(ctx ml.Context, inputs []input.Input) ([]input.Inpu
 			result = append(result, inp)
 		} else {
 			imageInputs := []input.Input{
-				{Token: 108},                      // "\n\n"
-				{Token: 255999, BatchBreak: true}, // "<start_of_image>""
+				{Token: 108},    // "\n\n"
+				{Token: 255999}, // "<start_of_image>""
 			}
 			result = append(result, imageInputs...)
 
diff --git a/runner/ollamarunner/runner.go b/runner/ollamarunner/runner.go
index 9b997bd3..c1475cbb 100644
--- a/runner/ollamarunner/runner.go
+++ b/runner/ollamarunner/runner.go
@@ -363,7 +363,7 @@ func (s *Server) processBatch() error {
 				}
 			}
 
-			if j >= s.batchSize || (inp.BatchBreak && len(seq.pendingInputs) != 0) {
+			if j >= s.batchSize {
 				break
 			}
 
diff --git a/server/prompt.go b/server/prompt.go
index 5b5b958f..d053f2a8 100644
--- a/server/prompt.go
+++ b/server/prompt.go
@@ -26,6 +26,7 @@ func chatPrompt(ctx context.Context, m *Model, tokenize tokenizeFunc, opts *api.
 	var system []api.Message
 
 	isMllama := checkMllamaModelFamily(m)
+	isGemma3 := checkGemma3ModelFamily(m)
 
 	var imageNumTokens int
 	// TODO: Ideally we would compute this from the projector metadata but some pieces are implementation dependent
@@ -40,7 +41,7 @@ func chatPrompt(ctx context.Context, m *Model, tokenize tokenizeFunc, opts *api.
 	n := len(msgs) - 1
 	// in reverse, find all messages that fit into context window
 	for i := n; i >= 0; i-- {
-		if isMllama && len(msgs[i].Images) > 1 {
+		if (isMllama || isGemma3) && len(msgs[i].Images) > 1 {
 			return "", nil, errTooManyImages
 		}
 
@@ -157,3 +158,12 @@ func checkMllamaModelFamily(m *Model) bool {
 	}
 	return false
 }
+
+func checkGemma3ModelFamily(m *Model) bool {
+	for _, arch := range m.Config.ModelFamilies {
+		if arch == "gemma3" {
+			return true
+		}
+	}
+	return false
+}

From f63e62e546f7378ba42235b89d98d17fc2b8323c Mon Sep 17 00:00:00 2001
From: jmorganca <jmorganca@gmail.com>
Date: Tue, 11 Mar 2025 12:01:57 +0100
Subject: [PATCH 061/157] reduce kernel size, add TODO for loading from config

---
 model/models/gemma3/model.go | 6 +++++-
 1 file changed, 5 insertions(+), 1 deletion(-)

diff --git a/model/models/gemma3/model.go b/model/models/gemma3/model.go
index 7418bb12..9aaa974a 100644
--- a/model/models/gemma3/model.go
+++ b/model/models/gemma3/model.go
@@ -90,7 +90,11 @@ func (m *Model) EncodeMultimodal(ctx ml.Context, multimodalData []byte) (any, er
 	visionOutputs := m.VisionModel.Forward(ctx, pixelValues)
 	visionOutputs = visionOutputs.Permute(ctx, 1, 0, 2, 3).Contiguous(ctx)
 	patchesPerImage := m.ImageProcessor.imageSize / m.ImageProcessor.patchSize
-	kernelSize := patchesPerImage * patchesPerImage / 256
+
+	// TODO (jmorganca): read this from the model config
+	// it should instead be math.Sqrt(tokens per image)
+	tokensPerSide := 8
+	kernelSize := patchesPerImage / tokensPerSide
 	visionOutputs = visionOutputs.AvgPool1D(ctx, kernelSize, kernelSize, 0)
 
 	visionOutputs = visionOutputs.Permute(ctx, 1, 0, 2, 3).Contiguous(ctx)

From 11bfa62796ecbdb40eb0193eea8a8151df3df547 Mon Sep 17 00:00:00 2001
From: jmorganca <jmorganca@gmail.com>
Date: Tue, 11 Mar 2025 12:02:38 +0100
Subject: [PATCH 062/157] add trailing \n\n after <end_of_image> to match
 reference implementation

---
 model/models/gemma3/model.go | 6 ++++--
 1 file changed, 4 insertions(+), 2 deletions(-)

diff --git a/model/models/gemma3/model.go b/model/models/gemma3/model.go
index 9aaa974a..26ee5da3 100644
--- a/model/models/gemma3/model.go
+++ b/model/models/gemma3/model.go
@@ -133,8 +133,10 @@ func (m *Model) PostTokenize(ctx ml.Context, inputs []input.Input) ([]input.Inpu
 				result = append(result, input.Input{Multimodal: imageToken, MultimodalHash: fnvHash.Sum64()})
 			}
 
-			// <end_of_image>
-			result = append(result, input.Input{Token: 256000})
+			result = append(result,
+				input.Input{Token: 256000}, // <end_of_image>
+				input.Input{Token: 108},    // "\n\n"
+			)
 		}
 	}
 

From ab39e08eb974693808f5784d5d3d7d336e5ae526 Mon Sep 17 00:00:00 2001
From: Daniel Hiltgen <dhiltgen@users.noreply.github.com>
Date: Tue, 11 Mar 2025 04:25:16 -0700
Subject: [PATCH 063/157] llm: auto detect models that require Ollama Engine
 (#1)

---
 fs/ggml/ggml.go | 4 ++++
 llm/server.go   | 2 +-
 2 files changed, 5 insertions(+), 1 deletion(-)

diff --git a/fs/ggml/ggml.go b/fs/ggml/ggml.go
index fe98a71b..d32296d9 100644
--- a/fs/ggml/ggml.go
+++ b/fs/ggml/ggml.go
@@ -133,6 +133,10 @@ func (kv KV) Floats(key string, defaultValue ...[]float32) []float32 {
 	return s
 }
 
+func (kv KV) OllamaEngineRequired() bool {
+	return kv.Architecture() == "gemma3"
+}
+
 func keyValue[T string | uint32 | uint64 | float32 | *array | bool](kv KV, key string, defaultValue ...T) T {
 	if !strings.HasPrefix(key, "tokenizer.") && !strings.HasPrefix(key, "general.") {
 		key = kv.Architecture() + "." + key
diff --git a/llm/server.go b/llm/server.go
index a53306fb..c6f11712 100644
--- a/llm/server.go
+++ b/llm/server.go
@@ -271,7 +271,7 @@ func NewLlamaServer(gpus discover.GpuInfoList, modelPath string, f *ggml.GGML, a
 
 	var llamaModel *llama.Model
 	var textProcessor model.TextProcessor
-	if envconfig.NewEngine() {
+	if envconfig.NewEngine() || f.KV().OllamaEngineRequired() {
 		textProcessor, err = model.NewTextProcessor(modelPath)
 		if err != nil {
 			// To prepare for opt-out mode, instead of treating this as an error, we fallback to the old runner

From 63a394068c44149252b061a1aded05b0530868a8 Mon Sep 17 00:00:00 2001
From: Michael Yang <mxyng@pm.me>
Date: Tue, 11 Mar 2025 09:00:10 -0700
Subject: [PATCH 064/157] use 2d pooling

---
 convert/convert_gemma3.go    | 23 ++++++++++++++---------
 ml/backend.go                |  2 +-
 ml/backend/ggml/ggml.go      |  6 +++---
 model/models/gemma3/model.go | 30 ++++++++++++++++++------------
 4 files changed, 36 insertions(+), 25 deletions(-)

diff --git a/convert/convert_gemma3.go b/convert/convert_gemma3.go
index 694aafca..c82800c5 100644
--- a/convert/convert_gemma3.go
+++ b/convert/convert_gemma3.go
@@ -26,15 +26,16 @@ type gemma3Model struct {
 		NumChannels       uint32  `json:"num_channels"`        // num_channels 3
 		PatchSize         uint32  `json:"patch_size"`          // patch_size 14
 	} `json:"vision_config"`
-	MaxPositionEmbeddings uint32  `json:"max_position_embeddings"`
-	NumAttentionHeads     uint32  `json:"num_attention_heads"`
-	NumKeyValueHeads      uint32  `json:"num_key_value_heads"`
-	RMSNormEPS            float32 `json:"rms_norm_eps"`
-	HeadDim               uint32  `json:"head_dim"`
-	FinalLogitSoftcap     float32 `json:"final_logit_softcapping"`
-	RopeLocalTheta        float32 `json:"rope_local_base_freq"`
-	RopeGlobalTheta       float32 `json:"rope_global_base_freq"`
-	SlidingWindow         uint32  `json:"sliding_window"`
+	MaxPositionEmbeddings    uint32  `json:"max_position_embeddings"`
+	NumAttentionHeads        uint32  `json:"num_attention_heads"`
+	NumKeyValueHeads         uint32  `json:"num_key_value_heads"`
+	RMSNormEPS               float32 `json:"rms_norm_eps"`
+	HeadDim                  uint32  `json:"head_dim"`
+	FinalLogitSoftcap        float32 `json:"final_logit_softcapping"`
+	RopeLocalTheta           float32 `json:"rope_local_base_freq"`
+	RopeGlobalTheta          float32 `json:"rope_global_base_freq"`
+	SlidingWindow            uint32  `json:"sliding_window"`
+	MultiModalTokensPerImage uint32  `json:"mm_tokens_per_image"`
 }
 
 const (
@@ -102,6 +103,10 @@ func (p *gemma3Model) KV(t *Tokenizer) ggml.KV {
 		kv["gemma3.attention.value_length"] = cmp.Or(p.TextModel.HeadDim, 256)
 	}
 
+	if p.MultiModalTokensPerImage > 0 {
+		kv["gemma3.mm.tokens_per_image"] = p.MultiModalTokensPerImage
+	}
+
 	return kv
 }
 
diff --git a/ml/backend.go b/ml/backend.go
index 303d67ec..c63c73d4 100644
--- a/ml/backend.go
+++ b/ml/backend.go
@@ -135,7 +135,7 @@ type Tensor interface {
 	RMSNorm(ctx Context, weight Tensor, eps float32) Tensor
 	Scale(ctx Context, s float64) Tensor
 
-	AvgPool1D(ctx Context, k, s, p int) Tensor
+	AvgPool2D(ctx Context, k, s int, p float32) Tensor
 	Conv2D(ctx Context, weight Tensor, s0, s1, p0, p1, d0, d1 int) Tensor
 
 	RoPE(ctx Context, positionIDs, ropeFactors Tensor, dim, ropeType uint32, base, scale float32) Tensor
diff --git a/ml/backend/ggml/ggml.go b/ml/backend/ggml/ggml.go
index c635e9e0..03b9acb3 100644
--- a/ml/backend/ggml/ggml.go
+++ b/ml/backend/ggml/ggml.go
@@ -247,7 +247,7 @@ func New(r *os.File, params ml.BackendParams) (ml.Backend, error) {
 			createTensor(tensor{source: t}, output.bts)
 		case strings.HasPrefix(t.Name, "v.") || strings.HasPrefix(t.Name, "mm."):
 			// TODO: assign vision tensors to the gpu if possible
-			createTensor(tensor{source: t}, input.bts)
+			createTensor(tensor{source: t}, output.bts)
 		case contains(t.Name, "rope_freqs", "rope_factors_long", "rope_factors_short"):
 			// these tensors should be repeated per layer
 			for i, layer := range layers {
@@ -952,10 +952,10 @@ func (t *Tensor) Conv2D(ctx ml.Context, t2 ml.Tensor, s0, s1, p0, p1, d0, d1 int
 	}
 }
 
-func (t *Tensor) AvgPool1D(ctx ml.Context, k, s, p int) ml.Tensor {
+func (t *Tensor) AvgPool2D(ctx ml.Context, k, s int, p float32) ml.Tensor {
 	return &Tensor{
 		b: t.b,
-		t: C.ggml_pool_1d(ctx.(*Context).ctx, t.t, C.GGML_OP_POOL_AVG, C.int(k), C.int(s), C.int(p)),
+		t: C.ggml_pool_2d(ctx.(*Context).ctx, t.t, C.GGML_OP_POOL_AVG, C.int(k), C.int(k), C.int(s), C.int(s), C.float(p), C.float(p)),
 	}
 }
 
diff --git a/model/models/gemma3/model.go b/model/models/gemma3/model.go
index 26ee5da3..b5311f18 100644
--- a/model/models/gemma3/model.go
+++ b/model/models/gemma3/model.go
@@ -5,6 +5,7 @@ import (
 	"encoding/binary"
 	"hash/fnv"
 	"image"
+	"math"
 
 	"github.com/ollama/ollama/kvcache"
 	"github.com/ollama/ollama/ml"
@@ -30,9 +31,21 @@ var _ model.MultimodalProcessor = (*Model)(nil)
 type MultiModalProjector struct {
 	SoftEmbNorm     *nn.RMSNorm `gguf:"mm_soft_emb_norm"`
 	InputProjection *nn.Linear  `gguf:"mm_input_projection"`
+
+	tokensPerImage int
 }
 
-func (p *MultiModalProjector) Forward(ctx ml.Context, visionOutputs ml.Tensor, eps float32) ml.Tensor {
+func (p *MultiModalProjector) Forward(ctx ml.Context, visionOutputs ml.Tensor, imageSize, patchSize int, eps float32) ml.Tensor {
+	l := visionOutputs.Dim(0)
+
+	visionOutputs = visionOutputs.Permute(ctx, 1, 0, 2, 3).Contiguous(ctx)
+	patchesPerImage := imageSize / patchSize
+	visionOutputs = visionOutputs.Reshape(ctx, patchesPerImage, patchesPerImage, l)
+
+	kernelSize := patchesPerImage / int(math.Sqrt(float64(p.tokensPerImage)))
+	visionOutputs = visionOutputs.AvgPool2D(ctx, kernelSize, kernelSize, 0)
+	visionOutputs = visionOutputs.Reshape(ctx, visionOutputs.Dim(0)*visionOutputs.Dim(1), l)
+	visionOutputs = visionOutputs.Permute(ctx, 1, 0, 2, 3).Contiguous(ctx)
 	visionOutputs = p.SoftEmbNorm.Forward(ctx, visionOutputs, eps)
 
 	// TODO: inputProjection must be transposed since they're incompatible with visionOutputs
@@ -59,6 +72,9 @@ func New(c ml.Config) (model.Model, error) {
 		ImageProcessor: newImageProcessor(c),
 		VisionModel:    newVisionModel(c),
 		TextModel:      newTextModel(c),
+		MultiModalProjector: &MultiModalProjector{
+			tokensPerImage: int(c.Uint("mm_tokens_per_image", 256)),
+		},
 	}
 
 	slidingWindowLen := int32(c.Uint("attention.sliding_window"))
@@ -88,17 +104,7 @@ func (m *Model) EncodeMultimodal(ctx ml.Context, multimodalData []byte) (any, er
 	}
 
 	visionOutputs := m.VisionModel.Forward(ctx, pixelValues)
-	visionOutputs = visionOutputs.Permute(ctx, 1, 0, 2, 3).Contiguous(ctx)
-	patchesPerImage := m.ImageProcessor.imageSize / m.ImageProcessor.patchSize
-
-	// TODO (jmorganca): read this from the model config
-	// it should instead be math.Sqrt(tokens per image)
-	tokensPerSide := 8
-	kernelSize := patchesPerImage / tokensPerSide
-	visionOutputs = visionOutputs.AvgPool1D(ctx, kernelSize, kernelSize, 0)
-
-	visionOutputs = visionOutputs.Permute(ctx, 1, 0, 2, 3).Contiguous(ctx)
-	visionOutputs = m.MultiModalProjector.Forward(ctx, visionOutputs, m.VisionModel.eps)
+	visionOutputs = m.MultiModalProjector.Forward(ctx, visionOutputs, m.imageSize, m.patchSize, m.VisionModel.eps)
 	return visionOutputs, nil
 }
 

From 20e35938630e633a5f40fd2c8b097b0dbfbda8d9 Mon Sep 17 00:00:00 2001
From: jmorganca <jmorganca@gmail.com>
Date: Tue, 11 Mar 2025 18:40:55 +0100
Subject: [PATCH 065/157] model: validate left and right pairs before merging
 them

---
 model/process_text_spm.go | 4 ++++
 1 file changed, 4 insertions(+)

diff --git a/model/process_text_spm.go b/model/process_text_spm.go
index 9d61746a..68e3ed01 100644
--- a/model/process_text_spm.go
+++ b/model/process_text_spm.go
@@ -169,6 +169,10 @@ func (spm SentencePieceModel) Encode(s string, addSpecial bool) ([]int32, error)
 					continue
 				}
 
+				if id := spm.vocab.Encode(string(left.runes) + string(right.runes)); id < 0 {
+					continue
+				}
+
 				merges[pair.a].runes = append(left.runes, right.runes...)
 				merges[pair.b].runes = nil
 				merges[pair.a].n = right.n

From fb4664fcec8c205b48ea7edd0c6f760fc2c346b0 Mon Sep 17 00:00:00 2001
From: jmorganca <jmorganca@gmail.com>
Date: Tue, 11 Mar 2025 18:54:00 +0100
Subject: [PATCH 066/157] model: add more spm tokenizer tests

---
 model/process_text_spm_test.go | 8 ++++++++
 1 file changed, 8 insertions(+)

diff --git a/model/process_text_spm_test.go b/model/process_text_spm_test.go
index 13e28cc5..a43004db 100644
--- a/model/process_text_spm_test.go
+++ b/model/process_text_spm_test.go
@@ -70,6 +70,14 @@ func TestSentencePieceEncode(t *testing.T) {
 			"请考试我的软件！12345",
 			"你好",
 			"Hello 你好 world!",
+			"Special characters: !@#$%^&*()_+-=[]{}|;':\",./<>?",
+			"Multilingual: 你好 こんにちは Привет Hola مرحبا",
+			"Numbers and symbols: 123456789 +- */",
+			"Special tokens: <bos> text <eos>",
+			"Code snippets: func main() { fmt.Println(\"Hello World\") }",
+			"Long text: " + "Lorem ipsum dolor sit amet, consectetur adipiscing elit. " +
+				"Sed do eiusmod tempor incididunt ut labore et dolore magna aliqua. " +
+				"Ut enim ad minim veniam, quis nostrud exercitation ullamco laboris.",
 		}
 
 		for _, want := range cases {

From c6b6938b3a5d0aef109464e8d42c7849d72bacce Mon Sep 17 00:00:00 2001
From: jmorganca <jmorganca@gmail.com>
Date: Tue, 11 Mar 2025 18:57:48 +0100
Subject: [PATCH 067/157] kvcache: fix tests by adding AvgPool2D stub

---
 kvcache/causal_test.go | 4 ++++
 1 file changed, 4 insertions(+)

diff --git a/kvcache/causal_test.go b/kvcache/causal_test.go
index ed23cad6..56d85ceb 100644
--- a/kvcache/causal_test.go
+++ b/kvcache/causal_test.go
@@ -445,6 +445,10 @@ func (t *testTensor) AvgPool1D(ctx ml.Context, k, s, p int) ml.Tensor {
 	panic("not implemented")
 }
 
+func (t *testTensor) AvgPool2D(ctx ml.Context, k, s int, p float32) ml.Tensor {
+	panic("not implemented")
+}
+
 func (t *testTensor) Conv2D(ctx ml.Context, weight ml.Tensor, s0, s1, p0, p1, d0, d1 int) ml.Tensor {
 	panic("not implemented")
 }

From 83f0ec8269eeaaef993af5b61916919db34e8cb7 Mon Sep 17 00:00:00 2001
From: jmorganca <jmorganca@gmail.com>
Date: Tue, 11 Mar 2025 19:00:13 +0100
Subject: [PATCH 068/157] all: address linter errors

---
 convert/convert.go                  | 1 -
 model/models/gemma3/model_vision.go | 6 +++---
 2 files changed, 3 insertions(+), 4 deletions(-)

diff --git a/convert/convert.go b/convert/convert.go
index 4467f9e1..7b9fe31f 100644
--- a/convert/convert.go
+++ b/convert/convert.go
@@ -228,7 +228,6 @@ func ConvertModel(fsys fs.FS, ws io.WriteSeeker) error {
 	switch {
 	case vocabSize == 0:
 		slog.Warn("vocabulary size was not explicitly set by the model", "default size", len(t.Vocabulary.Tokens))
-		vocabSize = len(t.Vocabulary.Tokens)
 	case vocabSize > len(t.Vocabulary.Tokens):
 		slog.Warn("vocabulary is smaller than expected, padding with dummy tokens", "expect", vocabSize, "actual", len(t.Vocabulary.Tokens))
 		for i := range vocabSize - len(t.Vocabulary.Tokens) {
diff --git a/model/models/gemma3/model_vision.go b/model/models/gemma3/model_vision.go
index a508f65b..94aa27bd 100644
--- a/model/models/gemma3/model_vision.go
+++ b/model/models/gemma3/model_vision.go
@@ -69,9 +69,9 @@ func (e *VisionEncoderLayer) Forward(ctx ml.Context, hiddenState ml.Tensor, opts
 }
 
 type VisionModelOptions struct {
-	hiddenSize, numHeads, numTiles int
-	imageSize, patchSize           int
-	eps                            float32
+	hiddenSize, numHeads int
+	imageSize, patchSize int
+	eps                  float32
 }
 
 type VisionModel struct {

From ad4e0bf3be5c11b8bdf79a0523538f1b0d43784f Mon Sep 17 00:00:00 2001
From: Michael <mchiang0610@users.noreply.github.com>
Date: Wed, 12 Mar 2025 07:39:25 +0100
Subject: [PATCH 069/157] Adding Gemma 3 to readme (#9671)

---
 README.md | 7 ++++---
 1 file changed, 4 insertions(+), 3 deletions(-)

diff --git a/README.md b/README.md
index b4df5e2a..60b23cde 100644
--- a/README.md
+++ b/README.md
@@ -54,6 +54,10 @@ Here are some example models that can be downloaded:
 
 | Model              | Parameters | Size  | Download                         |
 | ------------------ | ---------- | ----- | -------------------------------- |
+| Gemma 3            | 1B         | 815MB | `ollama run gemma3:1b`           |
+| Gemma 3            | 4B         | 3.3GB | `ollama run gemma3`              |
+| Gemma 3            | 12B        | 8.1GB | `ollama run gemma3:12b`          |
+| Gemma 3            | 27B        | 17GB  | `ollama run gemma3:27b`          |
 | QwQ                | 32B        | 20GB  | `ollama run qwq`                 |
 | DeepSeek-R1        | 7B         | 4.7GB | `ollama run deepseek-r1`         |
 | DeepSeek-R1        | 671B       | 404GB | `ollama run deepseek-r1:671b`    |
@@ -66,9 +70,6 @@ Here are some example models that can be downloaded:
 | Llama 3.1          | 405B       | 231GB | `ollama run llama3.1:405b`       |
 | Phi 4              | 14B        | 9.1GB | `ollama run phi4`                |
 | Phi 4 Mini         | 3.8B       | 2.5GB | `ollama run phi4-mini`           |
-| Gemma 2            | 2B         | 1.6GB | `ollama run gemma2:2b`           |
-| Gemma 2            | 9B         | 5.5GB | `ollama run gemma2`              |
-| Gemma 2            | 27B        | 16GB  | `ollama run gemma2:27b`          |
 | Mistral            | 7B         | 4.1GB | `ollama run mistral`             |
 | Moondream 2        | 1.4B       | 829MB | `ollama run moondream`           |
 | Neural Chat        | 7B         | 4.1GB | `ollama run neural-chat`         |

From b3af953a55f0bd054937374404506c4229fbda8c Mon Sep 17 00:00:00 2001
From: frob <rick+github@frob.com.au>
Date: Wed, 12 Mar 2025 07:42:53 +0100
Subject: [PATCH 070/157] cli: don't exit for invalid model during /load.
 (#9576)

Co-authored-by: Richard Lyons <frob@cloudstaff.com>
---
 cmd/interactive.go | 4 ++++
 1 file changed, 4 insertions(+)

diff --git a/cmd/interactive.go b/cmd/interactive.go
index af58f4fc..7c11ab83 100644
--- a/cmd/interactive.go
+++ b/cmd/interactive.go
@@ -195,6 +195,10 @@ func generateInteractive(cmd *cobra.Command, opts runOptions) error {
 			opts.Messages = []api.Message{}
 			fmt.Printf("Loading model '%s'\n", opts.Model)
 			if err := loadOrUnloadModel(cmd, &opts); err != nil {
+				if strings.Contains(err.Error(), "not found") {
+					fmt.Printf("error: %v\n", err)
+					continue
+				}
 				return err
 			}
 			continue

From 85ab552028b8d53fc85561c0c588a80924ecd621 Mon Sep 17 00:00:00 2001
From: "shane.xb.qian" <shane.qian@foxmail.com>
Date: Wed, 12 Mar 2025 22:32:30 +0800
Subject: [PATCH 071/157] ollama-debug.c: correct mistype

Signed-off-by: shane.xb.qian <shane.qian@foxmail.com>
---
 ml/backend/ggml/ggml/src/ollama-debug.c | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/ml/backend/ggml/ggml/src/ollama-debug.c b/ml/backend/ggml/ggml/src/ollama-debug.c
index b0e9d7f0..88a01f56 100644
--- a/ml/backend/ggml/ggml/src/ollama-debug.c
+++ b/ml/backend/ggml/ggml/src/ollama-debug.c
@@ -24,7 +24,7 @@ static void print_tensor(const void *tensor, void (*cb)(const void *, int),
     fprintf(stderr, "[");
     for (int i = 0; i < dims[0]; i++) {
         if (i >= nitems && i < dims[0] - nitems) {
-            fprintf(stderr, "... (%lld more), ", dims[0] - 2 * nitems);
+            fprintf(stderr, "... (%ld more), ", dims[0] - 2 * nitems);
             int skip = dims[0] - 2 * nitems;
             if (ndims > 1) {
                 stride += mul(dims + 1, ndims - 1) * skip;
@@ -67,7 +67,7 @@ static void print_tensor_i32(const void *tensor, int i) {
 }
 
 static void ollama_debug_tensor(const struct ggml_tensor *tensor, bool verbose, const char *prefix, int indent) {
-    fprintf(stderr, "%s%s %s (%s): [%lld %lld %lld %lld]\n", prefix, tensor->name,
+    fprintf(stderr, "%s%s %s (%s): [%ld %ld %ld %ld]\n", prefix, tensor->name,
             ggml_op_name(tensor->op), ggml_type_name(tensor->type), tensor->ne[0],
             tensor->ne[1], tensor->ne[2], tensor->ne[3]);
 

From 6b45b1d6b4dff4e805d42c096c4db4e6d7be141e Mon Sep 17 00:00:00 2001
From: Shane-XB-Qian <shane.qian@live.com>
Date: Wed, 12 Mar 2025 23:51:56 +0800
Subject: [PATCH 072/157] cli: adding support ctrl-n/p like general cli (#9136)

Signed-off-by: shane.xb.qian <shane.qian@foxmail.com>
---
 readline/readline.go | 36 ++++++++++++++++++++++++------------
 1 file changed, 24 insertions(+), 12 deletions(-)

diff --git a/readline/readline.go b/readline/readline.go
index f7b694eb..9252f325 100644
--- a/readline/readline.go
+++ b/readline/readline.go
@@ -116,19 +116,9 @@ func (i *Instance) Readline() (string, error) {
 
 			switch r {
 			case KeyUp:
-				if i.History.Pos > 0 {
-					if i.History.Pos == i.History.Size() {
-						currentLineBuf = []rune(buf.String())
-					}
-					buf.Replace([]rune(i.History.Prev()))
-				}
+				i.historyPrev(buf, &currentLineBuf)
 			case KeyDown:
-				if i.History.Pos < i.History.Size() {
-					buf.Replace([]rune(i.History.Next()))
-					if i.History.Pos == i.History.Size() {
-						buf.Replace(currentLineBuf)
-					}
-				}
+				i.historyNext(buf, &currentLineBuf)
 			case KeyLeft:
 				buf.MoveLeft()
 			case KeyRight:
@@ -185,6 +175,10 @@ func (i *Instance) Readline() (string, error) {
 			esc = true
 		case CharInterrupt:
 			return "", ErrInterrupt
+		case CharPrev:
+			i.historyPrev(buf, &currentLineBuf)
+		case CharNext:
+			i.historyNext(buf, &currentLineBuf)
 		case CharLineStart:
 			buf.MoveToStart()
 		case CharLineEnd:
@@ -246,6 +240,24 @@ func (i *Instance) HistoryDisable() {
 	i.History.Enabled = false
 }
 
+func (i *Instance) historyPrev(buf *Buffer, currentLineBuf *[]rune) {
+	if i.History.Pos > 0 {
+		if i.History.Pos == i.History.Size() {
+			*currentLineBuf = []rune(buf.String())
+		}
+		buf.Replace([]rune(i.History.Prev()))
+	}
+}
+
+func (i *Instance) historyNext(buf *Buffer, currentLineBuf *[]rune) {
+	if i.History.Pos < i.History.Size() {
+		buf.Replace([]rune(i.History.Next()))
+		if i.History.Pos == i.History.Size() {
+			buf.Replace(*currentLineBuf)
+		}
+	}
+}
+
 func NewTerminal() (*Terminal, error) {
 	fd := os.Stdin.Fd()
 	termios, err := SetRawMode(fd)

From a70820daa0a25024cfd857a528e717e3ac00a8e0 Mon Sep 17 00:00:00 2001
From: Bruce MacDonald <brucewmacdonald@gmail.com>
Date: Wed, 12 Mar 2025 10:17:57 -0700
Subject: [PATCH 073/157] models/gemma3: remove final logit softcap (#9692)

Softcap isn't in the whitepaper/implementation for the language model so we should remove it. There is no discernible difference in output with it removed.
---
 model/models/gemma3/model_text.go | 27 ++++++++++-----------------
 1 file changed, 10 insertions(+), 17 deletions(-)

diff --git a/model/models/gemma3/model_text.go b/model/models/gemma3/model_text.go
index 5b5e2d6e..7a88c092 100644
--- a/model/models/gemma3/model_text.go
+++ b/model/models/gemma3/model_text.go
@@ -15,7 +15,6 @@ type TextOptions struct {
 	attnKeyLen, attnValLen           int
 	eps, ropeScale                   float32
 	ropeLocalBase, ropeGlobalBase    float32
-	finalLogitSoftcap                float32
 	largeModelScaling                bool
 }
 
@@ -57,16 +56,15 @@ func newTextModel(c ml.Config) *TextModel {
 		),
 		Layers: make([]TextLayer, numBlocks),
 		TextOptions: &TextOptions{
-			hiddenSize:        int(c.Uint("embedding_length")),
-			numHeads:          int(c.Uint("attention.head_count")),
-			numKVHeads:        int(c.Uint("attention.head_count_kv")),
-			attnKeyLen:        int(c.Uint("attention.key_length", 256)),
-			attnValLen:        int(c.Uint("attention.value_length", 256)),
-			eps:               c.Float("attention.layer_norm_rms_epsilon", 1e-06),
-			ropeLocalBase:     c.Float("rope.local.freq_base", 10000.0),
-			ropeGlobalBase:    c.Float("rope.global.freq_base", 1000000.0),
-			ropeScale:         c.Float("rope.freq_scale", 1.0),
-			finalLogitSoftcap: c.Float("final_logit_softcapping", 30.0),
+			hiddenSize:     int(c.Uint("embedding_length")),
+			numHeads:       int(c.Uint("attention.head_count")),
+			numKVHeads:     int(c.Uint("attention.head_count_kv")),
+			attnKeyLen:     int(c.Uint("attention.key_length", 256)),
+			attnValLen:     int(c.Uint("attention.value_length", 256)),
+			eps:            c.Float("attention.layer_norm_rms_epsilon", 1e-06),
+			ropeLocalBase:  c.Float("rope.local.freq_base", 10000.0),
+			ropeGlobalBase: c.Float("rope.global.freq_base", 1000000.0),
+			ropeScale:      c.Float("rope.freq_scale", 1.0),
 		},
 	}
 
@@ -245,10 +243,5 @@ func (m *TextModel) Forward(ctx ml.Context, inputs, positions, outputs ml.Tensor
 	}
 
 	hiddenState = m.OutputNorm.Forward(ctx, hiddenState, m.eps)
-	hiddenState = m.Output.Forward(ctx, hiddenState)
-
-	// final logit softcap
-	hiddenState = hiddenState.Scale(ctx, 1.0/float64(m.TextOptions.finalLogitSoftcap))
-	hiddenState = hiddenState.Tanh(ctx)
-	return hiddenState.Scale(ctx, float64(m.TextOptions.finalLogitSoftcap))
+	return m.Output.Forward(ctx, hiddenState)
 }

From 1b7433b71e8f963e4379604078ccfb888cd8cac9 Mon Sep 17 00:00:00 2001
From: ParthSareen <parth.sareen@ollama.com>
Date: Wed, 12 Mar 2025 00:45:41 -0400
Subject: [PATCH 074/157] sample: use container/heap for top_k

---
 sample/testdata/logits.bin |   1 +
 sample/transforms.go       | 199 +++++++++++++++++++------------------
 sample/transforms_test.go  | 140 ++++++++++++++++++++++----
 3 files changed, 223 insertions(+), 117 deletions(-)
 create mode 100644 sample/testdata/logits.bin

diff --git a/sample/testdata/logits.bin b/sample/testdata/logits.bin
new file mode 100644
index 00000000..bb1eabbb
--- /dev/null
+++ b/sample/testdata/logits.bin
@@ -0,0 +1 @@
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diff --git a/sample/transforms.go b/sample/transforms.go
index ab62455f..0d7797da 100644
--- a/sample/transforms.go
+++ b/sample/transforms.go
@@ -1,10 +1,30 @@
 package sample
 
 import (
+	"container/heap"
 	"math"
 	"slices"
 )
 
+// tokenHeap implements heap.Interface and holds tokens as a min-heap to track k largest elements
+type tokenHeap []token
+
+func (h tokenHeap) Len() int           { return len(h) }
+func (h tokenHeap) Less(i, j int) bool { return h[i].value < h[j].value } // Use < for min-heap to track largest elements
+func (h tokenHeap) Swap(i, j int)      { h[i], h[j] = h[j], h[i] }
+
+func (h *tokenHeap) Push(x any) {
+	*h = append(*h, x.(token))
+}
+
+func (h *tokenHeap) Pop() any {
+	old := *h
+	n := len(old)
+	x := old[n-1]
+	*h = old[0 : n-1]
+	return x
+}
+
 // temperature applies scaling and softmax to the logits
 func temperature(ts []token, temp float32) []token {
 	// Find max logit for numerical stability
@@ -31,62 +51,33 @@ func temperature(ts []token, temp float32) []token {
 	return ts
 }
 
-// siftDown maintains a min-heap property by recursively moving larger elements down the heap.
-//
-// The heap is represented as an array where for any node at index i:
-// - Left child is at index 2i + 1
-// - Right child is at index 2i + 2
-// - Parent is at index (i-1)/2
-//
-// The function compares a node with its children and:
-// 1. Finds the smallest value between the node and its children
-// 2. If the node is not the smallest, swaps it with its smallest child
-// 3. Continues this process down the affected path until the min-heap property is restored
-func siftDown(data []token, start, end int) {
-	root := start
-	for {
-		child := 2*root + 1
-		if child >= end {
-			break
-		}
-		// Find smaller child (we want min heap)
-		if child+1 < end && data[child+1].value < data[child].value {
-			child++
-		}
-		// Exit if root is already smaller than children
-		if data[root].value <= data[child].value {
-			break
-		}
-		// Swap with smaller child and continue
-		data[root], data[child] = data[child], data[root]
-		root = child
-	}
-}
-
 // topK limits the number of tokens considered to the k highest logits
 func topK(ts []token, k int) []token {
 	if k >= len(ts) {
+		sortLogits(ts)
 		return ts
 	}
-	// Heapify + siftDown - O(nlog(k))
-	// Build min-heap of first k elements
-	heap := ts[:k]
-	for i := k/2 - 1; i >= 0; i-- {
-		siftDown(heap, i, k)
-	}
 
-	// Process remaining elements - if larger than heap root, replace root
+	// Initialize min-heap with first k elements
+	h := make(tokenHeap, k)
+	copy(h, ts[:k])
+	heap.Init(&h)
+
+	// Process remaining elements
 	for i := k; i < len(ts); i++ {
-		if ts[i].value > heap[0].value {
-			heap[0] = ts[i]
-			siftDown(heap, 0, k)
+		if ts[i].value > h[0].value {
+			heap.Pop(&h)
+			heap.Push(&h, ts[i])
 		}
 	}
 
-	slices.Reverse(heap)
+	// Convert heap to sorted slice in descending order
+	result := make([]token, k)
+	for i := k - 1; i >= 0; i-- {
+		result[i] = heap.Pop(&h).(token)
+	}
 
-	ts = heap
-	return ts
+	return result
 }
 
 // topP limits tokens to those with cumulative probability p
@@ -135,61 +126,77 @@ func minP(ts []token, p float32) []token {
 	return ts
 }
 
-// TODO(parthsareen): possibly replace with simpler implementation https://github.com/ollama/ollama/issues/9584
-// sortLogits sorts implementation to sort tokens by logits using counting sort
-// counting sort is faster than built-in sort for this use case
-func sortLogits(tokens []token) {
-	if len(tokens) <= 1 {
-		return
+// partialSortLogits uses quickselect to efficiently find and sort the top n tokens
+func partialSortLogits(ts []token, n int) []token {
+	if n >= len(ts) {
+		n = len(ts)
 	}
 
-	// Find max/min in a single pass
-	minLogit, maxLogit := tokens[0].value, tokens[0].value
-	for _, t := range tokens[1:] {
-		if t.value < minLogit {
-			minLogit = t.value
-		} else if t.value > maxLogit {
-			maxLogit = t.value
+	left, right := 0, len(ts)-1
+	target := n - 1
+
+	// Quickselect algorithm to partition array around pivot
+	for left < right {
+		// Choose middle element as pivot and move it to the end
+		pivot := left + (right-left)/2
+		ts[pivot], ts[right] = ts[right], ts[pivot]
+
+		// storeIndex tracks where to put next element greater than pivot
+		storeIndex := left
+		pivotValue := ts[right].value
+
+		// Partition array into elements >= pivot and < pivot
+		// Elements >= pivot go to the left side
+		for i := left; i < right; i++ {
+			if ts[i].value >= pivotValue {
+				ts[storeIndex], ts[i] = ts[i], ts[storeIndex]
+				storeIndex++
+			}
+		}
+
+		// Move pivot to its final position
+		ts[right], ts[storeIndex] = ts[storeIndex], ts[right]
+
+		// If pivot is at target position, we're done
+		// Otherwise recursively partition the half containing target
+		if storeIndex == target {
+			break
+		} else if storeIndex < target {
+			left = storeIndex + 1 // Target is in right half
+		} else {
+			right = storeIndex - 1 // Target is in left half
 		}
 	}
 
-	// Calculate scaling to map to uint32 range
-	logitRange := maxLogit - minLogit
-	if logitRange < 1e-6 {
-		return // All values effectively equal
-	}
+	// Sort just the top n elements in descending order
+	slices.SortFunc(ts[:n], func(a, b token) int {
+		if a.value > b.value {
+			return -1
+		}
+		if a.value < b.value {
+			return 1
+		}
+		return 0
+	})
 
-	// Count frequencies directly from tokens
-	const maxInt = (1 << 24) - 1 // Use 24 bits for good granularity
-	var counts [256]int          // For first byte
-
-	// First pass: count frequencies
-	for _, t := range tokens {
-		// Map to [0, maxInt] range
-		score := min(uint32((t.value-minLogit)*float32(maxInt)/logitRange), maxInt)
-		counts[score>>16]++
-	}
-
-	// Calculate offsets
-	var offset int
-	for i := range counts {
-		count := counts[i]
-		counts[i] = offset
-		offset += count
-	}
-
-	// Second pass: place elements in correct position
-	output := make([]token, len(tokens))
-	// Track current positions
-	countsCopy := counts
-
-	for i, t := range tokens {
-		score := min(uint32((t.value-minLogit)*float32(maxInt)/logitRange), maxInt)
-
-		pos := countsCopy[score>>16]
-		countsCopy[score>>16]++
-		output[len(tokens)-1-pos] = tokens[i]
-	}
-
-	copy(tokens, output)
+	return ts[:n]
+}
+
+// sortLogits uses partialSortLogits to efficiently sort tokens
+// It sorts approximately sqrt(len(tokens)) elements which balances
+// between having enough tokens for sampling while avoiding full sort
+func sortLogits(ts []token) {
+	// Use sqrt of token length as a heuristic for partial sort size
+	// This provides a good balance between performance and having enough tokens
+	n := int(math.Sqrt(float64(len(ts)))) + 1
+
+	// Ensure we have at least 100 tokens and at most 1000
+	switch {
+	case n < 100:
+		n = 100
+	case n > 1000:
+		n = 1000
+	}
+
+	partialSortLogits(ts, n)
 }
diff --git a/sample/transforms_test.go b/sample/transforms_test.go
index 81e8849b..b0202633 100644
--- a/sample/transforms_test.go
+++ b/sample/transforms_test.go
@@ -1,39 +1,44 @@
 package sample
 
 import (
+	"encoding/binary"
+	"errors"
 	"math"
 	"math/rand/v2"
+	"os"
+	"path/filepath"
+	"runtime"
 	"testing"
 )
 
-// Helper to convert float64 slice to logit slice
-func toTokens(values []float64) []token {
+// Helper to convert float32 slice to logit slice
+func toTokens(values []float32) []token {
 	tokens := make([]token, len(values))
 	for i, v := range values {
 		tokens[i] = token{
 			id:    int32(i),
-			value: float32(v),
+			value: v,
 		}
 	}
 	return tokens
 }
 
 // Helper to compare logit slices
-func compareLogits(t *testing.T, name string, want []float64, got []token) {
+func compareLogits(t *testing.T, name string, want []float32, got []token) {
 	t.Helper()
 	if len(want) != len(got) {
 		t.Errorf("%s: length mismatch: want %d, got %d", name, len(want), len(got))
 		return
 	}
 	for i := range want {
-		if math.Abs(float64(got[i].value)-want[i]) > 1e-6 {
+		if math.Abs(float64(got[i].value-want[i])) > 1e-6 {
 			t.Errorf("%s: index %d: want %f, got %f", name, i, want[i], got[i].value)
 		}
 	}
 }
 
 func TestTemperatureAndSoftmax(t *testing.T) {
-	input := []float64{1, 4, -2, 0}
+	input := []float32{1, 4, -2, 0}
 	got := temperature(toTokens(input), 0.5)
 
 	// Check probabilities sum to 1
@@ -41,7 +46,7 @@ func TestTemperatureAndSoftmax(t *testing.T) {
 	for _, token := range got {
 		sum += token.value
 	}
-	if math.Abs(float64(sum)-1.0) > 1e-6 {
+	if math.Abs(float64(sum-1.0)) > 1e-6 {
 		t.Errorf("probabilities don't sum to 1: got %f", sum)
 	}
 
@@ -51,30 +56,31 @@ func TestTemperatureAndSoftmax(t *testing.T) {
 	for _, token := range got {
 		sum += token.value
 	}
-	if math.Abs(float64(sum)-1.0) > 1e-6 {
+	if math.Abs(float64(sum-1.0)) > 1e-6 {
 		t.Errorf("probabilities don't sum to 1: got %f", sum)
 	}
 }
 
 func TestTopK(t *testing.T) {
-	input := []float64{-3, -2, -1, 0, 1, 2, 4}
+	input := []float32{0.026986899, 0.043722924, 0.036774673, 0.27755088, 0.0046718004, 0.08582123, 0.20409796, 0.00412893, 0.15720603, 0.045046154, 0.0030491839, 0.01681367}
 
 	// Test k=3
-	got := topK(toTokens(input), 3)
-	if len(got) != 3 {
-		t.Errorf("topK(3): wrong length: want 3, got %d", len(got))
+	got := topK(toTokens(input), 5)
+	if len(got) != 5 {
+		t.Errorf("topK(5): wrong length: want 5, got %d", len(got))
 	}
-	// Should keep highest 3 values: 4, 2, 1
-	want := []float64{4, 2, 1}
+	// Should keep highest 3 values in descending order
+	want := []float32{0.27755088, 0.20409796, 0.15720603, 0.08582123, 0.045046154}
 	compareLogits(t, "topK(3)", want, got)
 
-	// Test k > len
-	got = topK(toTokens(input), 10)
-	compareLogits(t, "topK(10)", input, got)
+	got = topK(toTokens(input), 20)
+	if len(got) != len(input) {
+		t.Errorf("topK(20): wrong length: want %d, got %d", len(input), len(got))
+	}
 }
 
 func TestTopP(t *testing.T) {
-	input := []float64{-3, -2, -1, 0, 1, 2, 4}
+	input := []float32{-3, -2, -1, 0, 1, 2, 4}
 	tokens := toTokens(input)
 
 	// First apply temperature and softmax to get probabilities
@@ -92,7 +98,7 @@ func TestTopP(t *testing.T) {
 }
 
 func TestMinP(t *testing.T) {
-	input := []float64{-3, -2, -1, 0, 1, 2, 4, 3}
+	input := []float32{-3, -2, -1, 0, 1, 2, 4, 3}
 	tokens := toTokens(input)
 
 	// First apply temperature and softmax
@@ -108,7 +114,7 @@ func TestMinP(t *testing.T) {
 }
 
 func TestSortLogits(t *testing.T) {
-	input := []float64{3, 1, 4, 2, -1, 0, -2}
+	input := []float32{0.026986899, 0.043722924, 0.036774673, 0.27755088, 0.0046718004, 0.08582123, 0.20409796, 0.00412893, 0.15720603, 0.045046154, 0.0030491839, 0.01681367}
 	tokens := toTokens(input)
 
 	sortLogits(tokens)
@@ -120,10 +126,102 @@ func TestSortLogits(t *testing.T) {
 		}
 	}
 
-	want := []float64{4, 3, 2, 1, 0, -1, -2}
+	want := []float32{0.27755088, 0.20409796, 0.15720603, 0.08582123, 0.045046154, 0.043722924, 0.036774673, 0.026986899, 0.01681367, 0.0046718004, 0.00412893, 0.0030491839}
 	compareLogits(t, "sortLogits", want, tokens)
 }
 
+// TestSortLogitsWithRealData tests sorting behavior using real model logit distributions
+func TestSortLogitsWithRealData(t *testing.T) {
+	// This will be populated from testdata/logits.bin
+	// Format: 32-bit float array in binary format
+	logits, err := loadTestLogits(t)
+	if err != nil {
+		t.Skipf("Skipping real logit test: %v", err)
+		return
+	}
+
+	tokens := toTokens(logits)
+	sortLogits(tokens)
+
+	// Calculate n for verification
+	n := int(math.Sqrt(float64(len(tokens)))) + 1
+	if n > 1000 {
+		n = 1000
+	} else if n < 100 {
+		n = 100
+	}
+
+	t.Logf("Testing with %d tokens, partial sorting top %d", len(tokens), n)
+
+	// Only verify the top n elements are sorted (which is what we guarantee)
+	// This is much faster than checking the entire array
+	topN := tokens[:n]
+	for i := 1; i < len(topN); i++ {
+		if topN[i].value > topN[i-1].value {
+			t.Fatalf("top %d tokens not properly sorted at index %d: %.15f > %.15f",
+				n, i, topN[i].value, topN[i-1].value)
+		}
+	}
+
+	// Verify we didn't lose any high value tokens by checking that
+	// all tokens after position n are <= the nth token
+	// Do this in chunks to avoid timeouts on large arrays
+	nthValue := tokens[n-1].value
+	const chunkSize = 1000
+
+	for start := n; start < len(tokens); start += chunkSize {
+		end := min(start+chunkSize, len(tokens))
+		for i := start; i < end; i++ {
+			if tokens[i].value > nthValue {
+				t.Fatalf("found higher value token after position %d: tokens[%d].value = %.15f > %.15f",
+					n, i, tokens[i].value, nthValue)
+			}
+		}
+	}
+}
+
+// loadTestLogits loads logit test data from testdata/logits.bin
+func loadTestLogits(t *testing.T) ([]float32, error) {
+	t.Helper()
+
+	_, currFile, _, ok := runtime.Caller(0)
+	if !ok {
+		return nil, errors.New("could not determine test file path")
+	}
+	testDataPath := filepath.Join(filepath.Dir(currFile), "testdata", "logits.bin")
+
+	file, err := os.Open(testDataPath)
+	if err != nil {
+		return nil, err
+	}
+	defer file.Close()
+
+	stat, err := file.Stat()
+	if err != nil {
+		return nil, err
+	}
+
+	numFloats := stat.Size() / 4 // each float32 is 4 bytes
+	if numFloats*4 != stat.Size() {
+		return nil, errors.New("logits.bin has invalid size: not a multiple of 4 bytes")
+	}
+
+	logits := make([]float32, numFloats)
+	for i := range logits {
+		var val uint32
+		if err := binary.Read(file, binary.LittleEndian, &val); err != nil {
+			return nil, err
+		}
+		logits[i] = math.Float32frombits(val)
+	}
+
+	if len(logits) == 0 {
+		return nil, errors.New("logits.bin is empty")
+	}
+
+	return logits, nil
+}
+
 func BenchmarkTransforms(b *testing.B) {
 	// Generate random logits
 	tokens := make([]token, 1<<16)

From 3ba91634c169ca27ff35f0c841d62ccae6403e47 Mon Sep 17 00:00:00 2001
From: ParthSareen <parth.sareen@ollama.com>
Date: Wed, 12 Mar 2025 11:58:08 -0400
Subject: [PATCH 075/157] sample: simplify top_k=0 sorting

---
 sample/testdata/logits.bin |  1 -
 sample/transforms.go       | 87 +++++-----------------------------
 sample/transforms_test.go  | 97 --------------------------------------
 3 files changed, 13 insertions(+), 172 deletions(-)
 delete mode 100644 sample/testdata/logits.bin

diff --git a/sample/testdata/logits.bin b/sample/testdata/logits.bin
deleted file mode 100644
index bb1eabbb..00000000
--- a/sample/testdata/logits.bin
+++ /dev/null
@@ -1 +0,0 @@
-[-0.14049109816551208, 0.06803577393293381, 0.08947011083364487, -0.15352056920528412, 0.16544274985790253, -0.22324655950069427, -0.07907228916883469, -0.11153314262628555, 0.16745619475841522, -0.08845115453004837, -0.05397915467619896, 0.09702621400356293, 0.1040145754814148, 0.034065235406160355, -0.023494448512792587, 0.023317236453294754, 0.06201161816716194, -0.14594611525535583, 0.05035833641886711, -0.06913720071315765, -0.0850675031542778, 0.0007670316845178604, -0.08676620572805405, 0.020724542438983917, 0.18044163286685944, 0.04924239218235016, -0.15723371505737305, 0.03611345216631889, -0.17997989058494568, -0.068993479013443, 0.05774486064910889, 0.08498939871788025, 0.12943890690803528, -0.006152433808892965, 0.14178094267845154, 0.1473844349384308, -0.012766982428729534, 0.045800212770700455, 0.19246874749660492, -0.09747152775526047, 0.006072793155908585, 0.017143171280622482, -0.02200348488986492, -0.027592593804001808, -0.04569224640727043, 0.026975959539413452, 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diff --git a/sample/transforms.go b/sample/transforms.go
index 0d7797da..05fd4533 100644
--- a/sample/transforms.go
+++ b/sample/transforms.go
@@ -10,7 +10,7 @@ import (
 type tokenHeap []token
 
 func (h tokenHeap) Len() int           { return len(h) }
-func (h tokenHeap) Less(i, j int) bool { return h[i].value < h[j].value } // Use < for min-heap to track largest elements
+func (h tokenHeap) Less(i, j int) bool { return h[i].value < h[j].value }
 func (h tokenHeap) Swap(i, j int)      { h[i], h[j] = h[j], h[i] }
 
 func (h *tokenHeap) Push(x any) {
@@ -72,7 +72,7 @@ func topK(ts []token, k int) []token {
 	}
 
 	// Convert heap to sorted slice in descending order
-	result := make([]token, k)
+	result := make([]token, len(h))
 	for i := k - 1; i >= 0; i-- {
 		result[i] = heap.Pop(&h).(token)
 	}
@@ -126,77 +126,16 @@ func minP(ts []token, p float32) []token {
 	return ts
 }
 
-// partialSortLogits uses quickselect to efficiently find and sort the top n tokens
-func partialSortLogits(ts []token, n int) []token {
-	if n >= len(ts) {
-		n = len(ts)
-	}
-
-	left, right := 0, len(ts)-1
-	target := n - 1
-
-	// Quickselect algorithm to partition array around pivot
-	for left < right {
-		// Choose middle element as pivot and move it to the end
-		pivot := left + (right-left)/2
-		ts[pivot], ts[right] = ts[right], ts[pivot]
-
-		// storeIndex tracks where to put next element greater than pivot
-		storeIndex := left
-		pivotValue := ts[right].value
-
-		// Partition array into elements >= pivot and < pivot
-		// Elements >= pivot go to the left side
-		for i := left; i < right; i++ {
-			if ts[i].value >= pivotValue {
-				ts[storeIndex], ts[i] = ts[i], ts[storeIndex]
-				storeIndex++
-			}
-		}
-
-		// Move pivot to its final position
-		ts[right], ts[storeIndex] = ts[storeIndex], ts[right]
-
-		// If pivot is at target position, we're done
-		// Otherwise recursively partition the half containing target
-		if storeIndex == target {
-			break
-		} else if storeIndex < target {
-			left = storeIndex + 1 // Target is in right half
-		} else {
-			right = storeIndex - 1 // Target is in left half
-		}
-	}
-
-	// Sort just the top n elements in descending order
-	slices.SortFunc(ts[:n], func(a, b token) int {
-		if a.value > b.value {
-			return -1
-		}
-		if a.value < b.value {
-			return 1
-		}
-		return 0
-	})
-
-	return ts[:n]
-}
-
-// sortLogits uses partialSortLogits to efficiently sort tokens
-// It sorts approximately sqrt(len(tokens)) elements which balances
-// between having enough tokens for sampling while avoiding full sort
+// sortLogits sorts the tokens in descending order of logits
 func sortLogits(ts []token) {
-	// Use sqrt of token length as a heuristic for partial sort size
-	// This provides a good balance between performance and having enough tokens
-	n := int(math.Sqrt(float64(len(ts)))) + 1
-
-	// Ensure we have at least 100 tokens and at most 1000
-	switch {
-	case n < 100:
-		n = 100
-	case n > 1000:
-		n = 1000
-	}
-
-	partialSortLogits(ts, n)
+	slices.SortFunc(ts, func(a, b token) int {
+		switch {
+		case a.value < b.value:
+			return 1
+		case a.value > b.value:
+			return -1
+		default:
+			return 0
+		}
+	})
 }
diff --git a/sample/transforms_test.go b/sample/transforms_test.go
index b0202633..8ed6be3e 100644
--- a/sample/transforms_test.go
+++ b/sample/transforms_test.go
@@ -1,13 +1,8 @@
 package sample
 
 import (
-	"encoding/binary"
-	"errors"
 	"math"
 	"math/rand/v2"
-	"os"
-	"path/filepath"
-	"runtime"
 	"testing"
 )
 
@@ -130,98 +125,6 @@ func TestSortLogits(t *testing.T) {
 	compareLogits(t, "sortLogits", want, tokens)
 }
 
-// TestSortLogitsWithRealData tests sorting behavior using real model logit distributions
-func TestSortLogitsWithRealData(t *testing.T) {
-	// This will be populated from testdata/logits.bin
-	// Format: 32-bit float array in binary format
-	logits, err := loadTestLogits(t)
-	if err != nil {
-		t.Skipf("Skipping real logit test: %v", err)
-		return
-	}
-
-	tokens := toTokens(logits)
-	sortLogits(tokens)
-
-	// Calculate n for verification
-	n := int(math.Sqrt(float64(len(tokens)))) + 1
-	if n > 1000 {
-		n = 1000
-	} else if n < 100 {
-		n = 100
-	}
-
-	t.Logf("Testing with %d tokens, partial sorting top %d", len(tokens), n)
-
-	// Only verify the top n elements are sorted (which is what we guarantee)
-	// This is much faster than checking the entire array
-	topN := tokens[:n]
-	for i := 1; i < len(topN); i++ {
-		if topN[i].value > topN[i-1].value {
-			t.Fatalf("top %d tokens not properly sorted at index %d: %.15f > %.15f",
-				n, i, topN[i].value, topN[i-1].value)
-		}
-	}
-
-	// Verify we didn't lose any high value tokens by checking that
-	// all tokens after position n are <= the nth token
-	// Do this in chunks to avoid timeouts on large arrays
-	nthValue := tokens[n-1].value
-	const chunkSize = 1000
-
-	for start := n; start < len(tokens); start += chunkSize {
-		end := min(start+chunkSize, len(tokens))
-		for i := start; i < end; i++ {
-			if tokens[i].value > nthValue {
-				t.Fatalf("found higher value token after position %d: tokens[%d].value = %.15f > %.15f",
-					n, i, tokens[i].value, nthValue)
-			}
-		}
-	}
-}
-
-// loadTestLogits loads logit test data from testdata/logits.bin
-func loadTestLogits(t *testing.T) ([]float32, error) {
-	t.Helper()
-
-	_, currFile, _, ok := runtime.Caller(0)
-	if !ok {
-		return nil, errors.New("could not determine test file path")
-	}
-	testDataPath := filepath.Join(filepath.Dir(currFile), "testdata", "logits.bin")
-
-	file, err := os.Open(testDataPath)
-	if err != nil {
-		return nil, err
-	}
-	defer file.Close()
-
-	stat, err := file.Stat()
-	if err != nil {
-		return nil, err
-	}
-
-	numFloats := stat.Size() / 4 // each float32 is 4 bytes
-	if numFloats*4 != stat.Size() {
-		return nil, errors.New("logits.bin has invalid size: not a multiple of 4 bytes")
-	}
-
-	logits := make([]float32, numFloats)
-	for i := range logits {
-		var val uint32
-		if err := binary.Read(file, binary.LittleEndian, &val); err != nil {
-			return nil, err
-		}
-		logits[i] = math.Float32frombits(val)
-	}
-
-	if len(logits) == 0 {
-		return nil, errors.New("logits.bin is empty")
-	}
-
-	return logits, nil
-}
-
 func BenchmarkTransforms(b *testing.B) {
 	// Generate random logits
 	tokens := make([]token, 1<<16)

From 4aeb67ef4c0c734e0077af39e0b8be1252662cc0 Mon Sep 17 00:00:00 2001
From: ParthSareen <parth.sareen@ollama.com>
Date: Wed, 12 Mar 2025 13:40:25 -0400
Subject: [PATCH 076/157] sample: do all sorting in topK

---
 sample/samplers.go        |  7 ++-----
 sample/transforms.go      | 27 +++++++++++----------------
 sample/transforms_test.go | 26 ++++++++++++++++++++++----
 3 files changed, 35 insertions(+), 25 deletions(-)

diff --git a/sample/samplers.go b/sample/samplers.go
index aea99b3f..8b0de3f5 100644
--- a/sample/samplers.go
+++ b/sample/samplers.go
@@ -84,11 +84,8 @@ func (s *Sampler) sample(tokens []token) (token, error) {
 		return greedy(tokens), nil
 	}
 
-	if s.topK > 0 {
-		tokens = topK(tokens, s.topK)
-	} else {
-		sortLogits(tokens)
-	}
+	// topK also sorts the tokens in descending order of logits
+	tokens = topK(tokens, s.topK)
 
 	// token logit values are updated to probabilities
 	tokens = temperature(tokens, s.temperature)
diff --git a/sample/transforms.go b/sample/transforms.go
index 05fd4533..b65917af 100644
--- a/sample/transforms.go
+++ b/sample/transforms.go
@@ -53,8 +53,17 @@ func temperature(ts []token, temp float32) []token {
 
 // topK limits the number of tokens considered to the k highest logits
 func topK(ts []token, k int) []token {
-	if k >= len(ts) {
-		sortLogits(ts)
+	if k >= len(ts) || k <= 0 {
+		slices.SortFunc(ts, func(a, b token) int {
+			switch {
+			case a.value < b.value:
+				return 1
+			case a.value > b.value:
+				return -1
+			default:
+				return 0
+			}
+		})
 		return ts
 	}
 
@@ -125,17 +134,3 @@ func minP(ts []token, p float32) []token {
 	ts = validTokens
 	return ts
 }
-
-// sortLogits sorts the tokens in descending order of logits
-func sortLogits(ts []token) {
-	slices.SortFunc(ts, func(a, b token) int {
-		switch {
-		case a.value < b.value:
-			return 1
-		case a.value > b.value:
-			return -1
-		default:
-			return 0
-		}
-	})
-}
diff --git a/sample/transforms_test.go b/sample/transforms_test.go
index 8ed6be3e..8f0a58b6 100644
--- a/sample/transforms_test.go
+++ b/sample/transforms_test.go
@@ -59,7 +59,7 @@ func TestTemperatureAndSoftmax(t *testing.T) {
 func TestTopK(t *testing.T) {
 	input := []float32{0.026986899, 0.043722924, 0.036774673, 0.27755088, 0.0046718004, 0.08582123, 0.20409796, 0.00412893, 0.15720603, 0.045046154, 0.0030491839, 0.01681367}
 
-	// Test k=3
+	// Test k=5
 	got := topK(toTokens(input), 5)
 	if len(got) != 5 {
 		t.Errorf("topK(5): wrong length: want 5, got %d", len(got))
@@ -72,6 +72,24 @@ func TestTopK(t *testing.T) {
 	if len(got) != len(input) {
 		t.Errorf("topK(20): wrong length: want %d, got %d", len(input), len(got))
 	}
+
+	// Test k=-1
+	input = []float32{0.026986899, 0.043722924, 0.036774673, 0.27755088, 0.0046718004, 0.08582123, 0.20409796, 0.00412893, 0.15720603, 0.045046154, 0.0030491839, 0.01681367}
+	want = []float32{0.27755088, 0.20409796, 0.15720603, 0.08582123, 0.045046154, 0.043722924, 0.036774673, 0.026986899, 0.01681367, 0.0046718004, 0.00412893, 0.0030491839}
+	got = topK(toTokens(input), -1)
+	if len(got) != len(input) {
+		t.Errorf("topK(-1): wrong length: want %d, got %d", len(input), len(got))
+	}
+	compareLogits(t, "topK(-1)", want, got)
+
+	// Test k=0
+	input = []float32{0.026986899, 0.043722924, 0.036774673, 0.27755088, 0.0046718004, 0.08582123, 0.20409796, 0.00412893, 0.15720603, 0.045046154, 0.0030491839, 0.01681367}
+	want = []float32{0.27755088, 0.20409796, 0.15720603, 0.08582123, 0.045046154, 0.043722924, 0.036774673, 0.026986899, 0.01681367, 0.0046718004, 0.00412893, 0.0030491839}
+	got = topK(toTokens(input), 0)
+	if len(got) != len(input) {
+		t.Errorf("topK(-1): wrong length: want %d, got %d", len(input), len(got))
+	}
+	compareLogits(t, "topK(-1)", want, got)
 }
 
 func TestTopP(t *testing.T) {
@@ -80,7 +98,7 @@ func TestTopP(t *testing.T) {
 
 	// First apply temperature and softmax to get probabilities
 	tokens = temperature(tokens, 1)
-	sortLogits(tokens)
+	tokens = topK(tokens, 20)
 
 	// Then apply topP
 	got := topP(tokens, 0.95)
@@ -112,7 +130,7 @@ func TestSortLogits(t *testing.T) {
 	input := []float32{0.026986899, 0.043722924, 0.036774673, 0.27755088, 0.0046718004, 0.08582123, 0.20409796, 0.00412893, 0.15720603, 0.045046154, 0.0030491839, 0.01681367}
 	tokens := toTokens(input)
 
-	sortLogits(tokens)
+	tokens = topK(tokens, 20)
 
 	for i := 1; i < len(tokens); i++ {
 		if tokens[i].value > tokens[i-1].value {
@@ -173,7 +191,7 @@ func BenchmarkTransforms(b *testing.B) {
 		b.ResetTimer()
 		for b.Loop() {
 			copy(tokensCopy, tokens)
-			sortLogits(tokensCopy)
+			topK(tokensCopy, 200000)
 		}
 	})
 }

From 30d7a59ba88b585a172fa86e38df948e839315ee Mon Sep 17 00:00:00 2001
From: "shane.xb.qian" <shane.qian@foxmail.com>
Date: Thu, 13 Mar 2025 17:10:37 +0800
Subject: [PATCH 077/157] ollama-debug.c: change 'ld' to 'PRIi64'

* macOS has different definition per info from @mxyng
---
 ml/backend/ggml/ggml/src/ollama-debug.c | 5 +++--
 1 file changed, 3 insertions(+), 2 deletions(-)

diff --git a/ml/backend/ggml/ggml/src/ollama-debug.c b/ml/backend/ggml/ggml/src/ollama-debug.c
index 88a01f56..7c2ba932 100644
--- a/ml/backend/ggml/ggml/src/ollama-debug.c
+++ b/ml/backend/ggml/ggml/src/ollama-debug.c
@@ -1,4 +1,5 @@
 #include <string.h>
+#include <inttypes.h>
 
 #include "ollama-debug.h"
 
@@ -24,7 +25,7 @@ static void print_tensor(const void *tensor, void (*cb)(const void *, int),
     fprintf(stderr, "[");
     for (int i = 0; i < dims[0]; i++) {
         if (i >= nitems && i < dims[0] - nitems) {
-            fprintf(stderr, "... (%ld more), ", dims[0] - 2 * nitems);
+            fprintf(stderr, "... (%" PRIi64 " more), ", dims[0] - 2 * nitems);
             int skip = dims[0] - 2 * nitems;
             if (ndims > 1) {
                 stride += mul(dims + 1, ndims - 1) * skip;
@@ -67,7 +68,7 @@ static void print_tensor_i32(const void *tensor, int i) {
 }
 
 static void ollama_debug_tensor(const struct ggml_tensor *tensor, bool verbose, const char *prefix, int indent) {
-    fprintf(stderr, "%s%s %s (%s): [%ld %ld %ld %ld]\n", prefix, tensor->name,
+    fprintf(stderr, "%s%s %s (%s): [%" PRIi64 " %" PRIi64 " %" PRIi64 " %" PRIi64 "]\n", prefix, tensor->name,
             ggml_op_name(tensor->op), ggml_type_name(tensor->type), tensor->ne[0],
             tensor->ne[1], tensor->ne[2], tensor->ne[3]);
 

From 5c0b6639692ba5e6d44a0c73a9b5c85dc670d4f2 Mon Sep 17 00:00:00 2001
From: Parth Sareen <parth.sareen@ollama.com>
Date: Thu, 13 Mar 2025 09:53:27 -0700
Subject: [PATCH 078/157] sample: separate softmax and temperature transforms
 (#9732)

---
 sample/samplers.go        |   2 +-
 sample/transforms.go      |  19 +++++--
 sample/transforms_test.go | 102 +++++++++++++++++++++++++++++++-------
 3 files changed, 98 insertions(+), 25 deletions(-)

diff --git a/sample/samplers.go b/sample/samplers.go
index 8b0de3f5..e302f914 100644
--- a/sample/samplers.go
+++ b/sample/samplers.go
@@ -87,8 +87,8 @@ func (s *Sampler) sample(tokens []token) (token, error) {
 	// topK also sorts the tokens in descending order of logits
 	tokens = topK(tokens, s.topK)
 
-	// token logit values are updated to probabilities
 	tokens = temperature(tokens, s.temperature)
+	tokens = softmax(tokens)
 
 	tokens = topP(tokens, s.topP)
 	tokens = minP(tokens, s.minP)
diff --git a/sample/transforms.go b/sample/transforms.go
index b65917af..a5efa704 100644
--- a/sample/transforms.go
+++ b/sample/transforms.go
@@ -25,8 +25,18 @@ func (h *tokenHeap) Pop() any {
 	return x
 }
 
-// temperature applies scaling and softmax to the logits
+// temperature applies scaling to the logits
 func temperature(ts []token, temp float32) []token {
+	// Ensure temperature clipping near 0 to avoid numerical instability
+	temp = max(temp, 1e-7)
+	for i := range ts {
+		ts[i].value = ts[i].value / temp
+	}
+	return ts
+}
+
+// softmax applies normalization to the logits
+func softmax(ts []token) []token {
 	// Find max logit for numerical stability
 	maxLogit := float32(math.Inf(-1))
 	for _, t := range ts {
@@ -35,15 +45,14 @@ func temperature(ts []token, temp float32) []token {
 		}
 	}
 
-	// Apply temperature and compute exp(x - max)
-	temp = max(temp, 1e-7)
+	// Compute exp(x - max)
 	var sum float32
 	for i, v := range ts {
-		ts[i].value = float32(math.Exp(float64((v.value - maxLogit) / temp)))
+		ts[i].value = float32(math.Exp(float64(v.value - maxLogit)))
 		sum += ts[i].value
 	}
 
-	// Normalize
+	// exp(x - max) / sum(exp(x - max))
 	for i := range ts {
 		ts[i].value /= sum
 	}
diff --git a/sample/transforms_test.go b/sample/transforms_test.go
index 8f0a58b6..4880dd8f 100644
--- a/sample/transforms_test.go
+++ b/sample/transforms_test.go
@@ -32,27 +32,83 @@ func compareLogits(t *testing.T, name string, want []float32, got []token) {
 	}
 }
 
-func TestTemperatureAndSoftmax(t *testing.T) {
-	input := []float32{1, 4, -2, 0}
+func TestTemperature(t *testing.T) {
+	input := []float32{1.0, 4.0, -2.0, 0.0}
 	got := temperature(toTokens(input), 0.5)
+	want := []float32{2.0, 8.0, -4.0, 0.0}
+	compareLogits(t, "temperature(0.5)", want, got)
 
-	// Check probabilities sum to 1
-	var sum float32
-	for _, token := range got {
-		sum += token.value
-	}
-	if math.Abs(float64(sum-1.0)) > 1e-6 {
-		t.Errorf("probabilities don't sum to 1: got %f", sum)
+	got = temperature(toTokens(input), 1.0)
+	want = []float32{1.0, 4.0, -2.0, 0.0}
+	compareLogits(t, "temperature(1)", want, got)
+
+	got = temperature(toTokens(input), 0.0)
+	want = []float32{1e7, 4e7, -2e7, 0.0}
+	compareLogits(t, "temperature(0)", want, got)
+}
+
+func TestSoftmax(t *testing.T) {
+	tests := []struct {
+		name     string
+		input    []float32
+		expected []float32
+	}{
+		{
+			name:     "correctness softmax",
+			input:    []float32{1, -2, 3, 0},
+			expected: []float32{0.113550, 0.005653, 0.839024, 0.041773},
+		},
+		{
+			name:  "normal distribution",
+			input: []float32{0.026986899, 0.043722924, 0.036774673, 0.27755088, 0.0046718004, 0.08582123, 0.20409796, 0.00412893, 0.15720603, 0.045046154, 0.0030491839, 0.01681367},
+		},
+		{
+			name:  "single value",
+			input: []float32{1.0},
+		},
+		{
+			name:  "identical values",
+			input: []float32{0.9, 0.9, 0.9},
+		},
+		{
+			name:  "large values",
+			input: []float32{1000.0, 2000.0, 3000.0},
+		},
+		{
+			name:  "small values",
+			input: []float32{1e-6, 2e-6, 3e-6},
+		},
+		{
+			name:  "negative values",
+			input: []float32{-1.0, -2.0, -3.0},
+		},
+		{
+			name:  "mixed values",
+			input: []float32{-100.0, 0.0, 100.0},
+		},
 	}
 
-	got = temperature(toTokens(input), 1)
-	// Check probabilities sum to 1
-	sum = 0.0
-	for _, token := range got {
-		sum += token.value
-	}
-	if math.Abs(float64(sum-1.0)) > 1e-6 {
-		t.Errorf("probabilities don't sum to 1: got %f", sum)
+	for _, tt := range tests {
+		t.Run(tt.name, func(t *testing.T) {
+			got := softmax(toTokens(tt.input))
+
+			if tt.expected != nil {
+				compareLogits(t, tt.name, tt.expected, got)
+				return
+			}
+
+			// Check probabilities sum to 1
+			var sum float32
+			for _, token := range got {
+				sum += token.value
+				if token.value < 0 || token.value > 1 {
+					t.Errorf("probability out of range [0,1]: got %f", token.value)
+				}
+			}
+			if math.Abs(float64(sum-1.0)) > 1e-6 {
+				t.Errorf("probabilities don't sum to 1: got %f", sum)
+			}
+		})
 	}
 }
 
@@ -97,7 +153,7 @@ func TestTopP(t *testing.T) {
 	tokens := toTokens(input)
 
 	// First apply temperature and softmax to get probabilities
-	tokens = temperature(tokens, 1)
+	tokens = softmax(tokens)
 	tokens = topK(tokens, 20)
 
 	// Then apply topP
@@ -115,7 +171,7 @@ func TestMinP(t *testing.T) {
 	tokens := toTokens(input)
 
 	// First apply temperature and softmax
-	tokens = temperature(tokens, 1)
+	tokens = softmax(tokens)
 
 	// Then apply minP
 	got := minP(tokens, 0.2)
@@ -163,6 +219,14 @@ func BenchmarkTransforms(b *testing.B) {
 		}
 	})
 
+	b.Run("Softmax", func(b *testing.B) {
+		b.ResetTimer()
+		for b.Loop() {
+			copy(tokensCopy, tokens)
+			softmax(tokensCopy)
+		}
+	})
+
 	b.Run("TopK", func(b *testing.B) {
 		b.ResetTimer()
 		for b.Loop() {

From 5e2e0b46b1b4ae7145011642631a7b507a70fb03 Mon Sep 17 00:00:00 2001
From: Michael Yang <mxyng@pm.me>
Date: Thu, 13 Mar 2025 10:37:31 -0700
Subject: [PATCH 079/157] fix: error if image requested without vision model

---
 model/model.go               | 2 ++
 model/models/gemma3/model.go | 4 ++++
 model/models/mllama/model.go | 4 ++++
 3 files changed, 10 insertions(+)

diff --git a/model/model.go b/model/model.go
index 89b6c803..7b2bdf89 100644
--- a/model/model.go
+++ b/model/model.go
@@ -22,6 +22,8 @@ import (
 	"github.com/ollama/ollama/model/input"
 )
 
+var ErrNoVisionModel = errors.New("vision model not found")
+
 // Model implements a specific model architecture, defining the forward pass and any model-specific configuration
 type Model interface {
 	Forward(ml.Context, input.Options) (ml.Tensor, error)
diff --git a/model/models/gemma3/model.go b/model/models/gemma3/model.go
index b5311f18..24193f15 100644
--- a/model/models/gemma3/model.go
+++ b/model/models/gemma3/model.go
@@ -84,6 +84,10 @@ func New(c ml.Config) (model.Model, error) {
 }
 
 func (m *Model) EncodeMultimodal(ctx ml.Context, multimodalData []byte) (any, error) {
+	if len(m.VisionModel.Layers) == 0 {
+		return nil, model.ErrNoVisionModel
+	}
+
 	image, _, err := image.Decode(bytes.NewReader(multimodalData))
 	if err != nil {
 		return nil, err
diff --git a/model/models/mllama/model.go b/model/models/mllama/model.go
index 31ba15df..071d77ac 100644
--- a/model/models/mllama/model.go
+++ b/model/models/mllama/model.go
@@ -63,6 +63,10 @@ func New(c ml.Config) (model.Model, error) {
 }
 
 func (m *Model) EncodeMultimodal(ctx ml.Context, multimodalData []byte) (any, error) {
+	if len(m.VisionModel.Transformer.Layers) == 0 || len(m.GlobalTransformer.Layers) == 0 {
+		return nil, model.ErrNoVisionModel
+	}
+
 	image, _, err := image.Decode(bytes.NewReader(multimodalData))
 	if err != nil {
 		return nil, err

From ec46f3286c7a6a4dc7bcfb373d63ca909952ea4a Mon Sep 17 00:00:00 2001
From: Michael Yang <mxyng@pm.me>
Date: Thu, 13 Mar 2025 11:22:19 -0700
Subject: [PATCH 080/157] engine: error on embeddings; not currently
 implemented

---
 runner/ollamarunner/runner.go | 69 ++++-------------------------------
 server/routes.go              |  6 +--
 2 files changed, 9 insertions(+), 66 deletions(-)

diff --git a/runner/ollamarunner/runner.go b/runner/ollamarunner/runner.go
index c1475cbb..c380ef22 100644
--- a/runner/ollamarunner/runner.go
+++ b/runner/ollamarunner/runner.go
@@ -691,65 +691,6 @@ type EmbeddingResponse struct {
 	Embedding []float32 `json:"embedding"`
 }
 
-func (s *Server) embeddings(w http.ResponseWriter, r *http.Request) {
-	var req EmbeddingRequest
-	if err := json.NewDecoder(r.Body).Decode(&req); err != nil {
-		http.Error(w, fmt.Sprintf("bad request: %s", err), http.StatusBadRequest)
-		return
-	}
-
-	w.Header().Set("Content-Type", "application/json")
-
-	slog.Debug("embedding request", "content", req.Content)
-
-	seq, err := s.NewSequence(req.Content, nil, NewSequenceParams{embedding: true})
-	if err != nil {
-		http.Error(w, fmt.Sprintf("Failed to create new sequence: %v", err), http.StatusInternalServerError)
-		return
-	}
-
-	// Ensure there is a place to put the sequence, released when removed from s.seqs
-	if err := s.seqsSem.Acquire(r.Context(), 1); err != nil {
-		if errors.Is(err, context.Canceled) {
-			slog.Info("aborting embeddings request due to client closing the connection")
-		} else {
-			slog.Error("Failed to acquire semaphore", "error", err)
-		}
-		return
-	}
-
-	s.mu.Lock()
-	found := false
-	for i, sq := range s.seqs {
-		if sq == nil {
-			seq.cache, seq.inputs, err = s.cache.LoadCacheSlot(seq.inputs, req.CachePrompt)
-			if err != nil {
-				s.mu.Unlock()
-				http.Error(w, fmt.Sprintf("Failed to load cache: %v", err), http.StatusInternalServerError)
-				return
-			}
-			s.seqs[i] = seq
-			s.cond.Signal()
-			found = true
-			break
-		}
-	}
-	s.mu.Unlock()
-
-	if !found {
-		http.Error(w, "could not find an available sequence", http.StatusInternalServerError)
-		return
-	}
-
-	embedding := <-seq.embedding
-
-	if err := json.NewEncoder(w).Encode(&EmbeddingResponse{
-		Embedding: embedding,
-	}); err != nil {
-		http.Error(w, fmt.Sprintf("failed to encode response: %v", err), http.StatusInternalServerError)
-	}
-}
-
 type HealthResponse struct {
 	Status   string  `json:"status"`
 	Progress float32 `json:"progress"`
@@ -927,9 +868,13 @@ func Execute(args []string) error {
 	defer listener.Close()
 
 	mux := http.NewServeMux()
-	mux.HandleFunc("/embedding", server.embeddings)
-	mux.HandleFunc("/completion", server.completion)
-	mux.HandleFunc("/health", server.health)
+	// TODO: support embeddings
+	mux.HandleFunc("POST /embedding", func(w http.ResponseWriter, r *http.Request) {
+		http.Error(w, "this model does not support embeddings", http.StatusNotImplemented)
+	})
+
+	mux.HandleFunc("POST /completion", server.completion)
+	mux.HandleFunc("GET /health", server.health)
 
 	httpServer := http.Server{
 		Handler: mux,
diff --git a/server/routes.go b/server/routes.go
index 3efa12e4..bc3fe3fb 100644
--- a/server/routes.go
+++ b/server/routes.go
@@ -483,8 +483,7 @@ func (s *Server) EmbedHandler(c *gin.Context) {
 	}
 
 	if err := g.Wait(); err != nil {
-		slog.Error("embedding generation failed", "error", err)
-		c.JSON(http.StatusInternalServerError, gin.H{"error": fmt.Errorf("failed to generate embeddings: %v", err)})
+		c.AbortWithStatusJSON(http.StatusInternalServerError, gin.H{"error": strings.TrimSpace(err.Error())})
 		return
 	}
 
@@ -545,8 +544,7 @@ func (s *Server) EmbeddingsHandler(c *gin.Context) {
 
 	embedding, err := r.Embedding(c.Request.Context(), req.Prompt)
 	if err != nil {
-		slog.Info(fmt.Sprintf("embedding generation failed: %v", err))
-		c.JSON(http.StatusInternalServerError, gin.H{"error": fmt.Errorf("failed to generate embedding: %v", err)})
+		c.AbortWithStatusJSON(http.StatusInternalServerError, gin.H{"error": strings.TrimSpace(err.Error())})
 		return
 	}
 

From 3e102b7dad5d0f41563858c8c938ac26b5f3fd56 Mon Sep 17 00:00:00 2001
From: Michael Yang <mxyng@pm.me>
Date: Thu, 13 Mar 2025 13:11:52 -0700
Subject: [PATCH 081/157] Update model/model.go

Co-authored-by: Jeffrey Morgan <jmorganca@gmail.com>
---
 model/model.go | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/model/model.go b/model/model.go
index 7b2bdf89..fadea324 100644
--- a/model/model.go
+++ b/model/model.go
@@ -22,7 +22,7 @@ import (
 	"github.com/ollama/ollama/model/input"
 )
 
-var ErrNoVisionModel = errors.New("vision model not found")
+var ErrNoVisionModel = errors.New("this model is missing data required for image input")
 
 // Model implements a specific model architecture, defining the forward pass and any model-specific configuration
 type Model interface {

From 80c7ce381ba5bd435503323007c4049fc1c3faef Mon Sep 17 00:00:00 2001
From: Patrick Devine <patrick@infrahq.com>
Date: Thu, 13 Mar 2025 13:59:19 -0700
Subject: [PATCH 082/157] fix: change default context size for gemma3 (#9744)

---
 convert/convert_gemma3.go | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/convert/convert_gemma3.go b/convert/convert_gemma3.go
index c82800c5..27b99f57 100644
--- a/convert/convert_gemma3.go
+++ b/convert/convert_gemma3.go
@@ -87,7 +87,7 @@ func (p *gemma3Model) KV(t *Tokenizer) ggml.KV {
 		kv["gemma3.embedding_length"] = p.HiddenSize
 		kv["gemma3.feed_forward_length"] = p.IntermediateSize
 	default:
-		kv["gemma3.context_length"] = cmp.Or(p.MaxPositionEmbeddings, 8192)
+		kv["gemma3.context_length"] = cmp.Or(p.MaxPositionEmbeddings, 131072)
 		kv["gemma3.embedding_length"] = p.TextModel.HiddenSize
 		kv["gemma3.feed_forward_length"] = p.TextModel.IntermediateSize
 		kv["gemma3.attention.sliding_window"] = p.TextModel.SlidingWindow

From 4bed739259d8d4c4c0f79f2359f13fbbd3249ece Mon Sep 17 00:00:00 2001
From: Patrick Devine <patrick@infrahq.com>
Date: Thu, 13 Mar 2025 14:24:27 -0700
Subject: [PATCH 083/157] add verbose mode to the show command (#9640)

Add metadata and tensor information to the show command to be able to
see more information about a model. This outputs the same data as
shown on the model details page on ollama.com
---
 api/types.go       |  8 ++++++
 cmd/cmd.go         | 50 ++++++++++++++++++++++++++++++++++---
 cmd/cmd_test.go    | 62 +++++++++++++++++++++++++++++++++++++++++-----
 cmd/interactive.go |  2 +-
 fs/ggml/ggml.go    |  4 +++
 server/routes.go   | 23 +++++++++++------
 6 files changed, 130 insertions(+), 19 deletions(-)

diff --git a/api/types.go b/api/types.go
index fef836bd..a38b335b 100644
--- a/api/types.go
+++ b/api/types.go
@@ -349,6 +349,7 @@ type ShowResponse struct {
 	Messages      []Message      `json:"messages,omitempty"`
 	ModelInfo     map[string]any `json:"model_info,omitempty"`
 	ProjectorInfo map[string]any `json:"projector_info,omitempty"`
+	Tensors       []Tensor       `json:"tensors,omitempty"`
 	ModifiedAt    time.Time      `json:"modified_at,omitempty"`
 }
 
@@ -467,6 +468,13 @@ type ModelDetails struct {
 	QuantizationLevel string   `json:"quantization_level"`
 }
 
+// Tensor describes the metadata for a given tensor.
+type Tensor struct {
+	Name  string   `json:"name"`
+	Type  string   `json:"type"`
+	Shape []uint64 `json:"shape"`
+}
+
 func (m *Metrics) Summary() {
 	if m.TotalDuration > 0 {
 		fmt.Fprintf(os.Stderr, "total duration:       %v\n", m.TotalDuration)
diff --git a/cmd/cmd.go b/cmd/cmd.go
index c22a08f4..710f49a7 100644
--- a/cmd/cmd.go
+++ b/cmd/cmd.go
@@ -18,6 +18,7 @@ import (
 	"os/signal"
 	"path/filepath"
 	"runtime"
+	"sort"
 	"strconv"
 	"strings"
 	"sync/atomic"
@@ -568,8 +569,9 @@ func ShowHandler(cmd *cobra.Command, args []string) error {
 	parameters, errParams := cmd.Flags().GetBool("parameters")
 	system, errSystem := cmd.Flags().GetBool("system")
 	template, errTemplate := cmd.Flags().GetBool("template")
+	verbose, errVerbose := cmd.Flags().GetBool("verbose")
 
-	for _, boolErr := range []error{errLicense, errModelfile, errParams, errSystem, errTemplate} {
+	for _, boolErr := range []error{errLicense, errModelfile, errParams, errSystem, errTemplate, errVerbose} {
 		if boolErr != nil {
 			return errors.New("error retrieving flags")
 		}
@@ -607,7 +609,7 @@ func ShowHandler(cmd *cobra.Command, args []string) error {
 		return errors.New("only one of '--license', '--modelfile', '--parameters', '--system', or '--template' can be specified")
 	}
 
-	req := api.ShowRequest{Name: args[0]}
+	req := api.ShowRequest{Name: args[0], Verbose: verbose}
 	resp, err := client.Show(cmd.Context(), &req)
 	if err != nil {
 		return err
@@ -630,10 +632,10 @@ func ShowHandler(cmd *cobra.Command, args []string) error {
 		return nil
 	}
 
-	return showInfo(resp, os.Stdout)
+	return showInfo(resp, verbose, os.Stdout)
 }
 
-func showInfo(resp *api.ShowResponse, w io.Writer) error {
+func showInfo(resp *api.ShowResponse, verbose bool, w io.Writer) error {
 	tableRender := func(header string, rows func() [][]string) {
 		fmt.Fprintln(w, " ", header)
 		table := tablewriter.NewWriter(w)
@@ -690,6 +692,45 @@ func showInfo(resp *api.ShowResponse, w io.Writer) error {
 		})
 	}
 
+	if resp.ModelInfo != nil && verbose {
+		tableRender("Metadata", func() (rows [][]string) {
+			keys := make([]string, 0, len(resp.ModelInfo))
+			for k := range resp.ModelInfo {
+				keys = append(keys, k)
+			}
+			sort.Strings(keys)
+
+			for _, k := range keys {
+				var v string
+				switch vData := resp.ModelInfo[k].(type) {
+				case string:
+					v = vData
+				case float64:
+					v = fmt.Sprintf("%g", vData)
+				case []any:
+					n := 3
+					if len(vData) < n {
+						n = len(vData)
+					}
+					v = fmt.Sprintf("%v", vData[:n])
+				default:
+					v = fmt.Sprintf("%T", vData)
+				}
+				rows = append(rows, []string{"", k, v})
+			}
+			return
+		})
+	}
+
+	if len(resp.Tensors) > 0 && verbose {
+		tableRender("Tensors", func() (rows [][]string) {
+			for _, t := range resp.Tensors {
+				rows = append(rows, []string{"", t.Name, t.Type, fmt.Sprint(t.Shape)})
+			}
+			return
+		})
+	}
+
 	head := func(s string, n int) (rows [][]string) {
 		scanner := bufio.NewScanner(strings.NewReader(s))
 		for scanner.Scan() && (len(rows) < n || n < 0) {
@@ -1196,6 +1237,7 @@ func NewCLI() *cobra.Command {
 	showCmd.Flags().Bool("parameters", false, "Show parameters of a model")
 	showCmd.Flags().Bool("template", false, "Show template of a model")
 	showCmd.Flags().Bool("system", false, "Show system message of a model")
+	showCmd.Flags().BoolP("verbose", "v", false, "Show detailed model information")
 
 	runCmd := &cobra.Command{
 		Use:     "run MODEL [PROMPT]",
diff --git a/cmd/cmd_test.go b/cmd/cmd_test.go
index e70ffbea..f21a8f50 100644
--- a/cmd/cmd_test.go
+++ b/cmd/cmd_test.go
@@ -27,7 +27,7 @@ func TestShowInfo(t *testing.T) {
 				ParameterSize:     "7B",
 				QuantizationLevel: "FP16",
 			},
-		}, &b); err != nil {
+		}, false, &b); err != nil {
 			t.Fatal(err)
 		}
 
@@ -57,7 +57,7 @@ func TestShowInfo(t *testing.T) {
 				ParameterSize:     "7B",
 				QuantizationLevel: "FP16",
 			},
-		}, &b); err != nil {
+		}, false, &b); err != nil {
 			t.Fatal(err)
 		}
 
@@ -68,6 +68,56 @@ func TestShowInfo(t *testing.T) {
     embedding length    0       
     quantization        FP16    
 
+`
+		if diff := cmp.Diff(expect, b.String()); diff != "" {
+			t.Errorf("unexpected output (-want +got):\n%s", diff)
+		}
+	})
+
+	t.Run("verbose model", func(t *testing.T) {
+		var b bytes.Buffer
+		if err := showInfo(&api.ShowResponse{
+			Details: api.ModelDetails{
+				Family:            "test",
+				ParameterSize:     "8B",
+				QuantizationLevel: "FP16",
+			},
+			Parameters: `
+			stop up`,
+			ModelInfo: map[string]any{
+				"general.architecture":    "test",
+				"general.parameter_count": float64(8_000_000_000),
+				"test.context_length":     float64(1000),
+				"test.embedding_length":   float64(11434),
+			},
+			Tensors: []api.Tensor{
+				{Name: "blk.0.attn_k.weight", Type: "BF16", Shape: []uint64{42, 3117}},
+				{Name: "blk.0.attn_q.weight", Type: "FP16", Shape: []uint64{3117, 42}},
+			},
+		}, true, &b); err != nil {
+			t.Fatal(err)
+		}
+
+		expect := `  Model
+    architecture        test     
+    parameters          8B       
+    context length      1000     
+    embedding length    11434    
+    quantization        FP16     
+
+  Parameters
+    stop    up    
+
+  Metadata
+    general.architecture       test     
+    general.parameter_count    8e+09    
+    test.context_length        1000     
+    test.embedding_length      11434    
+
+  Tensors
+    blk.0.attn_k.weight    BF16    [42 3117]    
+    blk.0.attn_q.weight    FP16    [3117 42]    
+
 `
 		if diff := cmp.Diff(expect, b.String()); diff != "" {
 			t.Errorf("unexpected output (-want +got):\n%s", diff)
@@ -89,7 +139,7 @@ func TestShowInfo(t *testing.T) {
 			stop you
 			stop up
 			temperature 99`,
-		}, &b); err != nil {
+		}, false, &b); err != nil {
 			t.Fatal(err)
 		}
 
@@ -126,7 +176,7 @@ func TestShowInfo(t *testing.T) {
 				"clip.vision.embedding_length": float64(0),
 				"clip.vision.projection_dim":   float64(0),
 			},
-		}, &b); err != nil {
+		}, false, &b); err != nil {
 			t.Fatal(err)
 		}
 
@@ -159,7 +209,7 @@ func TestShowInfo(t *testing.T) {
 Ahoy, matey!
 Weigh anchor!
 			`,
-		}, &b); err != nil {
+		}, false, &b); err != nil {
 			t.Fatal(err)
 		}
 
@@ -188,7 +238,7 @@ Weigh anchor!
 				QuantizationLevel: "FP16",
 			},
 			License: license,
-		}, &b); err != nil {
+		}, false, &b); err != nil {
 			t.Fatal(err)
 		}
 
diff --git a/cmd/interactive.go b/cmd/interactive.go
index 7c11ab83..f3489b65 100644
--- a/cmd/interactive.go
+++ b/cmd/interactive.go
@@ -347,7 +347,7 @@ func generateInteractive(cmd *cobra.Command, opts runOptions) error {
 
 				switch args[1] {
 				case "info":
-					_ = showInfo(resp, os.Stderr)
+					_ = showInfo(resp, false, os.Stderr)
 				case "license":
 					if resp.License == "" {
 						fmt.Println("No license was specified for this model.")
diff --git a/fs/ggml/ggml.go b/fs/ggml/ggml.go
index d32296d9..23018272 100644
--- a/fs/ggml/ggml.go
+++ b/fs/ggml/ggml.go
@@ -327,6 +327,10 @@ func (t Tensor) Size() uint64 {
 	return t.parameters() * t.typeSize() / t.blockSize()
 }
 
+func (t Tensor) Type() string {
+	return fileType(t.Kind).String()
+}
+
 type container interface {
 	Name() string
 	Decode(io.ReadSeeker) (model, error)
diff --git a/server/routes.go b/server/routes.go
index bc3fe3fb..05993624 100644
--- a/server/routes.go
+++ b/server/routes.go
@@ -435,7 +435,7 @@ func (s *Server) EmbedHandler(c *gin.Context) {
 		return
 	}
 
-	kvData, err := getKVData(m.ModelPath, false)
+	kvData, _, err := getModelData(m.ModelPath, false)
 	if err != nil {
 		c.JSON(http.StatusInternalServerError, gin.H{"error": err.Error()})
 		return
@@ -848,16 +848,23 @@ func GetModelInfo(req api.ShowRequest) (*api.ShowResponse, error) {
 	fmt.Fprint(&sb, m.String())
 	resp.Modelfile = sb.String()
 
-	kvData, err := getKVData(m.ModelPath, req.Verbose)
+	kvData, tensors, err := getModelData(m.ModelPath, req.Verbose)
 	if err != nil {
 		return nil, err
 	}
+
 	delete(kvData, "general.name")
 	delete(kvData, "tokenizer.chat_template")
 	resp.ModelInfo = kvData
 
+	tensorData := make([]api.Tensor, len(tensors.Items()))
+	for cnt, t := range tensors.Items() {
+		tensorData[cnt] = api.Tensor{Name: t.Name, Type: t.Type(), Shape: t.Shape}
+	}
+	resp.Tensors = tensorData
+
 	if len(m.ProjectorPaths) > 0 {
-		projectorData, err := getKVData(m.ProjectorPaths[0], req.Verbose)
+		projectorData, _, err := getModelData(m.ProjectorPaths[0], req.Verbose)
 		if err != nil {
 			return nil, err
 		}
@@ -867,17 +874,17 @@ func GetModelInfo(req api.ShowRequest) (*api.ShowResponse, error) {
 	return resp, nil
 }
 
-func getKVData(digest string, verbose bool) (ggml.KV, error) {
+func getModelData(digest string, verbose bool) (ggml.KV, ggml.Tensors, error) {
 	maxArraySize := 0
 	if verbose {
 		maxArraySize = -1
 	}
-	kvData, err := llm.LoadModel(digest, maxArraySize)
+	data, err := llm.LoadModel(digest, maxArraySize)
 	if err != nil {
-		return nil, err
+		return nil, ggml.Tensors{}, err
 	}
 
-	kv := kvData.KV()
+	kv := data.KV()
 
 	if !verbose {
 		for k := range kv {
@@ -887,7 +894,7 @@ func getKVData(digest string, verbose bool) (ggml.KV, error) {
 		}
 	}
 
-	return kv, nil
+	return kv, data.Tensors(), nil
 }
 
 func (s *Server) ListHandler(c *gin.Context) {

From 033cec232a7e6702d6a79ca22ca81200fad5873b Mon Sep 17 00:00:00 2001
From: Michael Yang <mxyng@pm.me>
Date: Wed, 12 Mar 2025 14:18:06 -0700
Subject: [PATCH 084/157] count gemma3 vision tensors

---
 fs/ggml/ggml.go | 8 ++++++++
 llm/memory.go   | 4 ++--
 2 files changed, 10 insertions(+), 2 deletions(-)

diff --git a/fs/ggml/ggml.go b/fs/ggml/ggml.go
index d32296d9..00392b4a 100644
--- a/fs/ggml/ggml.go
+++ b/fs/ggml/ggml.go
@@ -611,6 +611,14 @@ func (llm GGML) VisionGraphSize() (weights, graphSize uint64) {
 			embeddingLength*numPatches*maxNumTiles +
 			9*embeddingLength*numPaddedPatches*maxNumTiles +
 			numPaddedPatches*maxNumTiles*numPaddedPatches*maxNumTiles*headCount)
+	case "gemma3":
+		for name, layer := range llm.Tensors().GroupLayers() {
+			if strings.HasPrefix(name, "v.") {
+				for _, tensor := range layer {
+					weights += tensor.Size()
+				}
+			}
+		}
 	}
 	return weights, graphSize
 }
diff --git a/llm/memory.go b/llm/memory.go
index 40104eca..ac830ee8 100644
--- a/llm/memory.go
+++ b/llm/memory.go
@@ -218,8 +218,8 @@ func EstimateGPULayers(gpus []discover.GpuInfo, f *ggml.GGML, projectors []strin
 		if blk, ok := layers[fmt.Sprintf("blk.%d", i)]; ok {
 			layerSize = blk.Size()
 			layerSize += kv / f.KV().BlockCount()
+			memoryWeights += blk.Size()
 		}
-		memoryWeights += layerSize
 
 		if opts.NumGPU >= 0 && layerCount >= opts.NumGPU {
 			// Stop allocating on GPU(s) once we hit the users target NumGPU
@@ -376,7 +376,7 @@ func (m MemoryEstimate) LogValue() slog.Value {
 				// memory of the weights
 				"total", format.HumanBytes2(m.memoryWeights),
 				// memory of repeating layers
-				"repeating", format.HumanBytes2(m.memoryWeights-m.memoryLayerOutput),
+				"repeating", format.HumanBytes2(m.memoryWeights),
 				// memory of non-repeating layers
 				"nonrepeating", format.HumanBytes2(m.memoryLayerOutput),
 			),

From d2ec22371edba325903588b9515dd94b15b80d76 Mon Sep 17 00:00:00 2001
From: Michael Yang <mxyng@pm.me>
Date: Wed, 12 Mar 2025 16:08:24 -0700
Subject: [PATCH 085/157] count all vision tensors

---
 fs/ggml/ggml.go | 21 +++++++++------------
 1 file changed, 9 insertions(+), 12 deletions(-)

diff --git a/fs/ggml/ggml.go b/fs/ggml/ggml.go
index 00392b4a..da3ee0a7 100644
--- a/fs/ggml/ggml.go
+++ b/fs/ggml/ggml.go
@@ -579,12 +579,16 @@ func (f GGML) GraphSize(context, batch uint64, kvCacheType string) (kv, partialO
 }
 
 func (llm GGML) VisionGraphSize() (weights, graphSize uint64) {
+	for name, layer := range llm.Tensors().GroupLayers() {
+		if strings.HasPrefix(name, "v.") {
+			for _, tensor := range layer {
+				weights += tensor.Size()
+			}
+		}
+	}
+
 	switch llm.KV().Architecture() {
 	case "mllama":
-		for _, layer := range llm.Tensors().GroupLayers()["v"] {
-			weights += layer.Size()
-		}
-
 		kv := func(n string) uint64 {
 			if v, ok := llm.KV()["mllama.vision."+n].(uint32); ok {
 				return uint64(v)
@@ -611,15 +615,8 @@ func (llm GGML) VisionGraphSize() (weights, graphSize uint64) {
 			embeddingLength*numPatches*maxNumTiles +
 			9*embeddingLength*numPaddedPatches*maxNumTiles +
 			numPaddedPatches*maxNumTiles*numPaddedPatches*maxNumTiles*headCount)
-	case "gemma3":
-		for name, layer := range llm.Tensors().GroupLayers() {
-			if strings.HasPrefix(name, "v.") {
-				for _, tensor := range layer {
-					weights += tensor.Size()
-				}
-			}
-		}
 	}
+
 	return weights, graphSize
 }
 

From a422ba39c94adc870da84e5fa442c0bf81c77f27 Mon Sep 17 00:00:00 2001
From: Michael Yang <mxyng@pm.me>
Date: Thu, 13 Mar 2025 14:41:57 -0700
Subject: [PATCH 086/157] roughly count gemma3 graph

the largest operation is by far (q @ k) so just count that for
simplicity
---
 fs/ggml/ggml.go | 36 +++++++++++++++++-------------------
 1 file changed, 17 insertions(+), 19 deletions(-)

diff --git a/fs/ggml/ggml.go b/fs/ggml/ggml.go
index da3ee0a7..be1dffe0 100644
--- a/fs/ggml/ggml.go
+++ b/fs/ggml/ggml.go
@@ -587,34 +587,32 @@ func (llm GGML) VisionGraphSize() (weights, graphSize uint64) {
 		}
 	}
 
+	imageSize := uint64(llm.KV().Uint("vision.image_size"))
+	patchSize := uint64(llm.KV().Uint("vision.patch_size"))
+
+	numPatches := (imageSize / patchSize) * (imageSize / patchSize)
+	if _, ok := llm.Tensors().GroupLayers()["v"]["class_embd"]; ok {
+		numPatches++
+	}
+
+	headCount := uint64(llm.KV().Uint("vision.attention.head_count"))
+
 	switch llm.KV().Architecture() {
 	case "mllama":
-		kv := func(n string) uint64 {
-			if v, ok := llm.KV()["mllama.vision."+n].(uint32); ok {
-				return uint64(v)
-			}
-
-			return 0
-		}
-
-		imageSize := kv("image_size")
-
-		maxNumTiles := kv("max_num_tiles")
-		embeddingLength := kv("embedding_length")
-		headCount := kv("attention.head_count")
-
-		numPatches := (imageSize / kv("patch_size")) * (imageSize / kv("patch_size"))
-		if _, ok := llm.Tensors().GroupLayers()["v"]["class_embd"]; ok {
-			numPatches++
-		}
 
 		numPaddedPatches := numPatches + 8 - (numPatches%8)%8
 
+		maxNumTiles := uint64(llm.KV().Uint("vision.max_num_tiles"))
+		numChannels := uint64(llm.KV().Uint("vision.num_channels"))
+		embeddingLength := uint64(llm.KV().Uint("vision.embedding_length"))
+
 		graphSize = 4 * (8 +
-			imageSize*imageSize*kv("num_channels")*maxNumTiles +
+			imageSize*imageSize*numChannels*maxNumTiles +
 			embeddingLength*numPatches*maxNumTiles +
 			9*embeddingLength*numPaddedPatches*maxNumTiles +
 			numPaddedPatches*maxNumTiles*numPaddedPatches*maxNumTiles*headCount)
+	case "gemma3":
+		graphSize = 4 * (numPatches * numPatches * headCount)
 	}
 
 	return weights, graphSize

From 65b88c544f08ce3e5b1d193e82b72735095f795c Mon Sep 17 00:00:00 2001
From: Michael Yang <mxyng@pm.me>
Date: Thu, 13 Mar 2025 15:05:42 -0700
Subject: [PATCH 087/157] fix divide by zero

---
 fs/ggml/ggml.go | 18 ++++++++++++++----
 1 file changed, 14 insertions(+), 4 deletions(-)

diff --git a/fs/ggml/ggml.go b/fs/ggml/ggml.go
index be1dffe0..2c04559f 100644
--- a/fs/ggml/ggml.go
+++ b/fs/ggml/ggml.go
@@ -579,6 +579,10 @@ func (f GGML) GraphSize(context, batch uint64, kvCacheType string) (kv, partialO
 }
 
 func (llm GGML) VisionGraphSize() (weights, graphSize uint64) {
+	if llm.KV().Uint("vision.block_count") == 0 {
+		return
+	}
+
 	for name, layer := range llm.Tensors().GroupLayers() {
 		if strings.HasPrefix(name, "v.") {
 			for _, tensor := range layer {
@@ -589,6 +593,12 @@ func (llm GGML) VisionGraphSize() (weights, graphSize uint64) {
 
 	imageSize := uint64(llm.KV().Uint("vision.image_size"))
 	patchSize := uint64(llm.KV().Uint("vision.patch_size"))
+	if patchSize == 0 {
+		slog.Warn("unknown patch size for vision model")
+		return
+	}
+
+	numChannels := uint64(llm.KV().Uint("vision.num_channels"))
 
 	numPatches := (imageSize / patchSize) * (imageSize / patchSize)
 	if _, ok := llm.Tensors().GroupLayers()["v"]["class_embd"]; ok {
@@ -596,15 +606,13 @@ func (llm GGML) VisionGraphSize() (weights, graphSize uint64) {
 	}
 
 	headCount := uint64(llm.KV().Uint("vision.attention.head_count"))
+	embeddingLength := uint64(llm.KV().Uint("vision.embedding_length"))
 
 	switch llm.KV().Architecture() {
 	case "mllama":
-
 		numPaddedPatches := numPatches + 8 - (numPatches%8)%8
 
 		maxNumTiles := uint64(llm.KV().Uint("vision.max_num_tiles"))
-		numChannels := uint64(llm.KV().Uint("vision.num_channels"))
-		embeddingLength := uint64(llm.KV().Uint("vision.embedding_length"))
 
 		graphSize = 4 * (8 +
 			imageSize*imageSize*numChannels*maxNumTiles +
@@ -612,7 +620,9 @@ func (llm GGML) VisionGraphSize() (weights, graphSize uint64) {
 			9*embeddingLength*numPaddedPatches*maxNumTiles +
 			numPaddedPatches*maxNumTiles*numPaddedPatches*maxNumTiles*headCount)
 	case "gemma3":
-		graphSize = 4 * (numPatches * numPatches * headCount)
+		graphSize = 4 * (imageSize*imageSize*numChannels +
+			embeddingLength*patchSize +
+			numPatches*numPatches*headCount)
 	}
 
 	return weights, graphSize

From 74b44fdf8fa665c41fb044399a6aac9f5ea83c93 Mon Sep 17 00:00:00 2001
From: Bradley Erickson <195061+13rac1@users.noreply.github.com>
Date: Thu, 13 Mar 2025 16:35:20 -0700
Subject: [PATCH 088/157] docs: Add OLLAMA_ORIGINS for browser extension
 support (#9643)

---
 docs/faq.md | 7 +++++++
 1 file changed, 7 insertions(+)

diff --git a/docs/faq.md b/docs/faq.md
index 4aaccc2e..66959cca 100644
--- a/docs/faq.md
+++ b/docs/faq.md
@@ -187,6 +187,13 @@ cloudflared tunnel --url http://localhost:11434 --http-host-header="localhost:11
 
 Ollama allows cross-origin requests from `127.0.0.1` and `0.0.0.0` by default. Additional origins can be configured with `OLLAMA_ORIGINS`.
 
+For browser extensions, you'll need to explicitly allow the extension's origin pattern. Set `OLLAMA_ORIGINS` to include `chrome-extension://*`, `moz-extension://*`, and `safari-web-extension://*` if you wish to allow all browser extensions access, or specific extensions as needed:
+
+```
+# Allow all Chrome, Firefox, and Safari extensions
+OLLAMA_ORIGINS=chrome-extension://*,moz-extension://*,safari-web-extension://* ollama serve
+```
+
 Refer to the section [above](#how-do-i-configure-ollama-server) for how to set environment variables on your platform.
 
 ## Where are models stored?

From 8d76fa23ef058d98cb66ad9c3ecc5fff6d380ca1 Mon Sep 17 00:00:00 2001
From: Michael Yang <mxyng@pm.me>
Date: Thu, 13 Mar 2025 16:53:22 -0700
Subject: [PATCH 089/157] count non-repeating vision layers

---
 fs/ggml/ggml.go | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/fs/ggml/ggml.go b/fs/ggml/ggml.go
index 2c04559f..dd84380b 100644
--- a/fs/ggml/ggml.go
+++ b/fs/ggml/ggml.go
@@ -584,7 +584,7 @@ func (llm GGML) VisionGraphSize() (weights, graphSize uint64) {
 	}
 
 	for name, layer := range llm.Tensors().GroupLayers() {
-		if strings.HasPrefix(name, "v.") {
+		if name == "v" || strings.HasPrefix(name, "v.") {
 			for _, tensor := range layer {
 				weights += tensor.Size()
 			}

From eb2b22b042df6edcc7dc825e2822fe3b7bb6c369 Mon Sep 17 00:00:00 2001
From: Blake Mizerany <blake.mizerany@gmail.com>
Date: Thu, 13 Mar 2025 22:18:29 -0700
Subject: [PATCH 090/157] server/internal/client: use chunksums for concurrent
 blob verification (#9746)

Replace large-chunk blob downloads with parallel small-chunk
verification to solve timeout and performance issues. Registry users
experienced progressively slowing download speeds as large-chunk
transfers aged, often timing out completely.

The previous approach downloaded blobs in a few large chunks but
required a separate, single-threaded pass to read the entire blob back
from disk for verification after download completion.

This change uses the new chunksums API to fetch many smaller
chunk+digest pairs, allowing concurrent downloads and immediate
verification as each chunk arrives. Chunks are written directly to their
final positions, eliminating the entire separate verification pass.

The result is more reliable downloads that maintain speed throughout the
transfer process and significantly faster overall completion, especially
over unstable connections or with large blobs.
---
 server/internal/cache/blob/cache.go           |  54 ++-
 server/internal/cache/blob/chunked.go         |  66 ++++
 server/internal/cache/blob/digest.go          |   4 +
 server/internal/chunks/chunks.go              |  19 +-
 server/internal/client/ollama/registry.go     | 368 ++++++++++--------
 .../internal/client/ollama/registry_test.go   |   4 +-
 server/internal/registry/server.go            | 163 ++++----
 server/internal/registry/server_test.go       |  54 ++-
 8 files changed, 441 insertions(+), 291 deletions(-)
 create mode 100644 server/internal/cache/blob/chunked.go

diff --git a/server/internal/cache/blob/cache.go b/server/internal/cache/blob/cache.go
index 8a828772..a1351538 100644
--- a/server/internal/cache/blob/cache.go
+++ b/server/internal/cache/blob/cache.go
@@ -146,7 +146,7 @@ func debugger(err *error) func(step string) {
 // be in either of the following forms:
 //
 //	@<digest>
-//	<name>
+//	<name>@<digest>
 //	<name>
 //
 // If a digest is provided, it is returned as is and nothing else happens.
@@ -160,8 +160,6 @@ func debugger(err *error) func(step string) {
 // hashed is passed to a PutBytes call to ensure that the manifest is in the
 // blob store. This is done to ensure that future calls to [Get] succeed in
 // these cases.
-//
-// TODO(bmizerany): Move Links/Resolve/etc. out of this package.
 func (c *DiskCache) Resolve(name string) (Digest, error) {
 	name, digest := splitNameDigest(name)
 	if digest != "" {
@@ -279,18 +277,6 @@ func (c *DiskCache) Get(d Digest) (Entry, error) {
 // It returns an error if either the name or digest is invalid, or if link
 // creation encounters any issues.
 func (c *DiskCache) Link(name string, d Digest) error {
-	// TODO(bmizerany): Move link handling from cache to registry.
-	//
-	// We originally placed links in the cache due to its storage
-	// knowledge. However, the registry likely offers better context for
-	// naming concerns, and our API design shouldn't be tightly coupled to
-	// our on-disk format.
-	//
-	// Links work effectively when independent from physical location -
-	// they can reference content with matching SHA regardless of storage
-	// location. In an upcoming change, we plan to shift this
-	// responsibility to the registry where it better aligns with the
-	// system's conceptual model.
 	manifest, err := c.manifestPath(name)
 	if err != nil {
 		return err
@@ -341,7 +327,9 @@ func (c *DiskCache) GetFile(d Digest) string {
 	return absJoin(c.dir, "blobs", filename)
 }
 
-// Links returns a sequence of links in the cache in lexical order.
+// Links returns a sequence of link names. The sequence is in lexical order.
+// Names are converted from their relative path form to their name form but are
+// not guaranteed to be valid. Callers should validate the names before using.
 func (c *DiskCache) Links() iter.Seq2[string, error] {
 	return func(yield func(string, error) bool) {
 		for path, err := range c.links() {
@@ -414,12 +402,14 @@ func (c *DiskCache) links() iter.Seq2[string, error] {
 }
 
 type checkWriter struct {
-	d    Digest
 	size int64
-	n    int64
-	h    hash.Hash
+	d    Digest
 	f    *os.File
-	err  error
+	h    hash.Hash
+
+	w   io.Writer // underlying writer; set by creator
+	n   int64
+	err error
 
 	testHookBeforeFinalWrite func(*os.File)
 }
@@ -435,6 +425,10 @@ func (w *checkWriter) seterr(err error) error {
 // underlying writer is guaranteed to be the last byte of p as verified by the
 // hash.
 func (w *checkWriter) Write(p []byte) (int, error) {
+	if w.err != nil {
+		return 0, w.err
+	}
+
 	_, err := w.h.Write(p)
 	if err != nil {
 		return 0, w.seterr(err)
@@ -453,7 +447,7 @@ func (w *checkWriter) Write(p []byte) (int, error) {
 	if nextSize > w.size {
 		return 0, w.seterr(fmt.Errorf("content exceeds expected size: %d > %d", nextSize, w.size))
 	}
-	n, err := w.f.Write(p)
+	n, err := w.w.Write(p)
 	w.n += int64(n)
 	return n, w.seterr(err)
 }
@@ -493,10 +487,12 @@ func (c *DiskCache) copyNamedFile(name string, file io.Reader, out Digest, size
 
 	// Copy file to f, but also into h to double-check hash.
 	cw := &checkWriter{
-		d:                        out,
-		size:                     size,
-		h:                        sha256.New(),
-		f:                        f,
+		d:    out,
+		size: size,
+		h:    sha256.New(),
+		f:    f,
+		w:    f,
+
 		testHookBeforeFinalWrite: c.testHookBeforeFinalWrite,
 	}
 	n, err := io.Copy(cw, file)
@@ -532,11 +528,6 @@ func splitNameDigest(s string) (name, digest string) {
 var errInvalidName = errors.New("invalid name")
 
 func nameToPath(name string) (_ string, err error) {
-	if strings.Contains(name, "@") {
-		// TODO(bmizerany): HACK: Fix names.Parse to validate.
-		// TODO(bmizerany): merge with default parts (maybe names.Merge(a, b))
-		return "", errInvalidName
-	}
 	n := names.Parse(name)
 	if !n.IsFullyQualified() {
 		return "", errInvalidName
@@ -547,8 +538,7 @@ func nameToPath(name string) (_ string, err error) {
 func absJoin(pp ...string) string {
 	abs, err := filepath.Abs(filepath.Join(pp...))
 	if err != nil {
-		// Likely a bug bug or a bad OS problem. Just panic.
-		panic(err)
+		panic(err) // this should never happen
 	}
 	return abs
 }
diff --git a/server/internal/cache/blob/chunked.go b/server/internal/cache/blob/chunked.go
new file mode 100644
index 00000000..5faea84f
--- /dev/null
+++ b/server/internal/cache/blob/chunked.go
@@ -0,0 +1,66 @@
+package blob
+
+import (
+	"crypto/sha256"
+	"errors"
+	"io"
+	"os"
+
+	"github.com/ollama/ollama/server/internal/chunks"
+)
+
+type Chunk = chunks.Chunk // TODO: move chunks here?
+
+// Chunker writes to a blob in chunks.
+// Its zero value is invalid. Use [DiskCache.Chunked] to create a new Chunker.
+type Chunker struct {
+	digest Digest
+	size   int64
+	f      *os.File // nil means pre-validated
+}
+
+// Chunked returns a new Chunker, ready for use storing a blob of the given
+// size in chunks.
+//
+// Use [Chunker.Put] to write data to the blob at specific offsets.
+func (c *DiskCache) Chunked(d Digest, size int64) (*Chunker, error) {
+	name := c.GetFile(d)
+	info, err := os.Stat(name)
+	if err == nil && info.Size() == size {
+		return &Chunker{}, nil
+	}
+	f, err := os.OpenFile(name, os.O_CREATE|os.O_WRONLY, 0o666)
+	if err != nil {
+		return nil, err
+	}
+	return &Chunker{digest: d, size: size, f: f}, nil
+}
+
+// Put copies chunk.Size() bytes from r to the blob at the given offset,
+// merging the data with the existing blob. It returns an error if any. As a
+// special case, if r has less than chunk.Size() bytes, Put returns
+// io.ErrUnexpectedEOF.
+func (c *Chunker) Put(chunk Chunk, d Digest, r io.Reader) error {
+	if c.f == nil {
+		return nil
+	}
+
+	cw := &checkWriter{
+		d:    d,
+		size: chunk.Size(),
+		h:    sha256.New(),
+		f:    c.f,
+		w:    io.NewOffsetWriter(c.f, chunk.Start),
+	}
+
+	_, err := io.CopyN(cw, r, chunk.Size())
+	if err != nil && errors.Is(err, io.EOF) {
+		return io.ErrUnexpectedEOF
+	}
+	return err
+}
+
+// Close closes the underlying file.
+func (c *Chunker) Close() error {
+	return c.f.Close()
+}
diff --git a/server/internal/cache/blob/digest.go b/server/internal/cache/blob/digest.go
index 723ba222..092d00ac 100644
--- a/server/internal/cache/blob/digest.go
+++ b/server/internal/cache/blob/digest.go
@@ -63,6 +63,10 @@ func (d Digest) Short() string {
 	return fmt.Sprintf("%x", d.sum[:4])
 }
 
+func (d Digest) Sum() [32]byte {
+	return d.sum
+}
+
 func (d Digest) Compare(other Digest) int {
 	return slices.Compare(d.sum[:], other.sum[:])
 }
diff --git a/server/internal/chunks/chunks.go b/server/internal/chunks/chunks.go
index 7eb7a6c1..7bb4e99a 100644
--- a/server/internal/chunks/chunks.go
+++ b/server/internal/chunks/chunks.go
@@ -31,18 +31,21 @@ func ParseRange(s string) (unit string, _ Chunk, _ error) {
 }
 
 // Parse parses a string in the form "start-end" and returns the Chunk.
-func Parse(s string) (Chunk, error) {
-	startStr, endStr, _ := strings.Cut(s, "-")
-	start, err := strconv.ParseInt(startStr, 10, 64)
-	if err != nil {
-		return Chunk{}, fmt.Errorf("invalid start: %v", err)
+func Parse[S ~string | ~[]byte](s S) (Chunk, error) {
+	startPart, endPart, found := strings.Cut(string(s), "-")
+	if !found {
+		return Chunk{}, fmt.Errorf("chunks: invalid range %q: missing '-'", s)
 	}
-	end, err := strconv.ParseInt(endStr, 10, 64)
+	start, err := strconv.ParseInt(startPart, 10, 64)
 	if err != nil {
-		return Chunk{}, fmt.Errorf("invalid end: %v", err)
+		return Chunk{}, fmt.Errorf("chunks: invalid start to %q: %v", s, err)
+	}
+	end, err := strconv.ParseInt(endPart, 10, 64)
+	if err != nil {
+		return Chunk{}, fmt.Errorf("chunks: invalid end to %q: %v", s, err)
 	}
 	if start > end {
-		return Chunk{}, fmt.Errorf("invalid range %d-%d: start > end", start, end)
+		return Chunk{}, fmt.Errorf("chunks: invalid range %q: start > end", s)
 	}
 	return Chunk{start, end}, nil
 }
diff --git a/server/internal/client/ollama/registry.go b/server/internal/client/ollama/registry.go
index 423a6ad2..baf42262 100644
--- a/server/internal/client/ollama/registry.go
+++ b/server/internal/client/ollama/registry.go
@@ -19,6 +19,7 @@ import (
 	"fmt"
 	"io"
 	"io/fs"
+	"iter"
 	"log/slog"
 	"net/http"
 	"os"
@@ -38,7 +39,6 @@ import (
 	"github.com/ollama/ollama/server/internal/chunks"
 	"github.com/ollama/ollama/server/internal/internal/backoff"
 	"github.com/ollama/ollama/server/internal/internal/names"
-	"github.com/ollama/ollama/server/internal/internal/syncs"
 
 	_ "embed"
 )
@@ -66,12 +66,7 @@ var (
 const (
 	// DefaultChunkingThreshold is the threshold at which a layer should be
 	// split up into chunks when downloading.
-	DefaultChunkingThreshold = 128 << 20
-
-	// DefaultMaxChunkSize is the default maximum size of a chunk to
-	// download. It is configured based on benchmarks and aims to strike a
-	// balance between download speed and memory usage.
-	DefaultMaxChunkSize = 8 << 20
+	DefaultChunkingThreshold = 64 << 20
 )
 
 var defaultCache = sync.OnceValues(func() (*blob.DiskCache, error) {
@@ -211,8 +206,7 @@ type Registry struct {
 	// pushing or pulling models. If zero, the number of streams is
 	// determined by [runtime.GOMAXPROCS].
 	//
-	// Clients that want "unlimited" streams should set this to a large
-	// number.
+	// A negative value means no limit.
 	MaxStreams int
 
 	// ChunkingThreshold is the maximum size of a layer to download in a single
@@ -282,24 +276,13 @@ func DefaultRegistry() (*Registry, error) {
 }
 
 func (r *Registry) maxStreams() int {
-	n := cmp.Or(r.MaxStreams, runtime.GOMAXPROCS(0))
-
-	// Large downloads require a writter stream, so ensure we have at least
-	// two streams to avoid a deadlock.
-	return max(n, 2)
+	return cmp.Or(r.MaxStreams, runtime.GOMAXPROCS(0))
 }
 
 func (r *Registry) maxChunkingThreshold() int64 {
 	return cmp.Or(r.ChunkingThreshold, DefaultChunkingThreshold)
 }
 
-// chunkSizeFor returns the chunk size for a layer of the given size. If the
-// size is less than or equal to the max chunking threshold, the size is
-// returned; otherwise, the max chunk size is returned.
-func (r *Registry) maxChunkSize() int64 {
-	return cmp.Or(r.MaxChunkSize, DefaultMaxChunkSize)
-}
-
 type PushParams struct {
 	// From is an optional destination name for the model. If empty, the
 	// destination name is the same as the source name.
@@ -426,6 +409,21 @@ func canRetry(err error) bool {
 	return re.Status >= 500
 }
 
+// trackingReader is an io.Reader that tracks the number of bytes read and
+// calls the update function with the layer, the number of bytes read.
+//
+// It always calls update with a nil error.
+type trackingReader struct {
+	r io.Reader
+	n *atomic.Int64
+}
+
+func (r *trackingReader) Read(p []byte) (n int, err error) {
+	n, err = r.r.Read(p)
+	r.n.Add(int64(n))
+	return
+}
+
 // Pull pulls the model with the given name from the remote registry into the
 // cache.
 //
@@ -434,11 +432,6 @@ func canRetry(err error) bool {
 // typically slower than splitting the model up across layers, and is mostly
 // utilized for layers of type equal to "application/vnd.ollama.image".
 func (r *Registry) Pull(ctx context.Context, name string) error {
-	scheme, n, _, err := r.parseNameExtended(name)
-	if err != nil {
-		return err
-	}
-
 	m, err := r.Resolve(ctx, name)
 	if err != nil {
 		return err
@@ -457,126 +450,95 @@ func (r *Registry) Pull(ctx context.Context, name string) error {
 		return err == nil && info.Size == l.Size
 	}
 
-	t := traceFromContext(ctx)
-
-	g, ctx := errgroup.WithContext(ctx)
-	g.SetLimit(r.maxStreams())
-
 	layers := m.Layers
 	if m.Config != nil && m.Config.Digest.IsValid() {
 		layers = append(layers, m.Config)
 	}
 
-	for _, l := range layers {
+	// Send initial layer trace events to allow clients to have an
+	// understanding of work to be done before work starts.
+	t := traceFromContext(ctx)
+	skip := make([]bool, len(layers))
+	for i, l := range layers {
+		t.update(l, 0, nil)
 		if exists(l) {
+			skip[i] = true
 			t.update(l, l.Size, ErrCached)
+		}
+	}
+
+	g, ctx := errgroup.WithContext(ctx)
+	g.SetLimit(r.maxStreams())
+	for i, l := range layers {
+		if skip[i] {
 			continue
 		}
 
-		blobURL := fmt.Sprintf("%s://%s/v2/%s/%s/blobs/%s", scheme, n.Host(), n.Namespace(), n.Model(), l.Digest)
-		req, err := r.newRequest(ctx, "GET", blobURL, nil)
+		chunked, err := c.Chunked(l.Digest, l.Size)
 		if err != nil {
 			t.update(l, 0, err)
 			continue
 		}
+		defer chunked.Close()
 
-		t.update(l, 0, nil)
-
-		if l.Size <= r.maxChunkingThreshold() {
-			g.Go(func() error {
-				// TODO(bmizerany): retry/backoff like below in
-				// the chunking case
-				res, err := sendRequest(r.client(), req)
-				if err != nil {
-					return err
-				}
-				defer res.Body.Close()
-				err = c.Put(l.Digest, res.Body, l.Size)
-				if err == nil {
-					t.update(l, l.Size, nil)
-				}
-				return err
-			})
-		} else {
-			q := syncs.NewRelayReader()
+		var progress atomic.Int64
+		for cs, err := range r.chunksums(ctx, name, l) {
+			if err != nil {
+				t.update(l, progress.Load(), err)
+				break
+			}
 
 			g.Go(func() (err error) {
-				defer func() { q.CloseWithError(err) }()
-				return c.Put(l.Digest, q, l.Size)
-			})
+				defer func() { t.update(l, progress.Load(), err) }()
 
-			var progress atomic.Int64
-
-			// We want to avoid extra round trips per chunk due to
-			// redirects from the registry to the blob store, so
-			// fire an initial request to get the final URL and
-			// then use that URL for the chunk requests.
-			req.Header.Set("Range", "bytes=0-0")
-			res, err := sendRequest(r.client(), req)
-			if err != nil {
-				return err
-			}
-			res.Body.Close()
-			req = res.Request.WithContext(req.Context())
-
-			wp := writerPool{size: r.maxChunkSize()}
-
-			for chunk := range chunks.Of(l.Size, r.maxChunkSize()) {
-				if ctx.Err() != nil {
-					break
-				}
-
-				ticket := q.Take()
-				g.Go(func() (err error) {
-					defer func() {
-						if err != nil {
-							q.CloseWithError(err)
-						}
-						ticket.Close()
-						t.update(l, progress.Load(), err)
-					}()
-
-					for _, err := range backoff.Loop(ctx, 3*time.Second) {
-						if err != nil {
-							return err
-						}
-						err := func() error {
-							req := req.Clone(req.Context())
-							req.Header.Set("Range", fmt.Sprintf("bytes=%s", chunk))
-							res, err := sendRequest(r.client(), req)
-							if err != nil {
-								return err
-							}
-							defer res.Body.Close()
-
-							tw := wp.get()
-							tw.Reset(ticket)
-							defer wp.put(tw)
-
-							_, err = io.CopyN(tw, res.Body, chunk.Size())
-							if err != nil {
-								return maybeUnexpectedEOF(err)
-							}
-							if err := tw.Flush(); err != nil {
-								return err
-							}
-
-							total := progress.Add(chunk.Size())
-							if total >= l.Size {
-								q.Close()
-							}
-							return nil
-						}()
-						if !canRetry(err) {
-							return err
-						}
+				for _, err := range backoff.Loop(ctx, 3*time.Second) {
+					if err != nil {
+						return err
 					}
-					return nil
-				})
-			}
+					err := func() error {
+						req, err := http.NewRequestWithContext(ctx, "GET", cs.URL, nil)
+						if err != nil {
+							return err
+						}
+						req.Header.Set("Range", fmt.Sprintf("bytes=%s", cs.Chunk))
+						res, err := sendRequest(r.client(), req)
+						if err != nil {
+							return err
+						}
+						defer res.Body.Close()
+
+						// Count bytes towards
+						// progress, as they arrive, so
+						// that our bytes piggyback
+						// other chunk updates on
+						// completion.
+						//
+						// This tactic is enough to
+						// show "smooth" progress given
+						// the current CLI client. In
+						// the near future, the server
+						// should report download rate
+						// since it knows better than
+						// a client that is measuring
+						// rate based on wall-clock
+						// time-since-last-update.
+						body := &trackingReader{r: res.Body, n: &progress}
+
+						err = chunked.Put(cs.Chunk, cs.Digest, body)
+						if err != nil {
+							return err
+						}
+
+						return nil
+					}()
+					if !canRetry(err) {
+						return err
+					}
+				}
+				return nil
+			})
 		}
 	}
-
 	if err := g.Wait(); err != nil {
 		return err
 	}
@@ -615,8 +577,6 @@ type Manifest struct {
 	Config *Layer `json:"config"`
 }
 
-var emptyDigest, _ = blob.ParseDigest("sha256:0000000000000000000000000000000000000000000000000000000000000000")
-
 // Layer returns the layer with the given
 // digest, or nil if not found.
 func (m *Manifest) Layer(d blob.Digest) *Layer {
@@ -643,10 +603,9 @@ func (m Manifest) MarshalJSON() ([]byte, error) {
 		// last phase of the commit which expects it, but does nothing
 		// with it. This will be fixed in a future release of
 		// ollama.com.
-		Config *Layer `json:"config"`
+		Config Layer `json:"config"`
 	}{
-		M:      M(m),
-		Config: &Layer{Digest: emptyDigest},
+		M: M(m),
 	}
 	return json.Marshal(v)
 }
@@ -736,6 +695,123 @@ func (r *Registry) Resolve(ctx context.Context, name string) (*Manifest, error)
 	return m, nil
 }
 
+type chunksum struct {
+	URL    string
+	Chunk  blob.Chunk
+	Digest blob.Digest
+}
+
+// chunksums returns a sequence of chunksums for the given layer. If the layer is under the
+// chunking threshold, a single chunksum is returned that covers the entire layer. If the layer
+// is over the chunking threshold, the chunksums are read from the chunksums endpoint.
+func (r *Registry) chunksums(ctx context.Context, name string, l *Layer) iter.Seq2[chunksum, error] {
+	return func(yield func(chunksum, error) bool) {
+		scheme, n, _, err := r.parseNameExtended(name)
+		if err != nil {
+			yield(chunksum{}, err)
+			return
+		}
+
+		if l.Size < r.maxChunkingThreshold() {
+			// any layer under the threshold should be downloaded
+			// in one go.
+			cs := chunksum{
+				URL: fmt.Sprintf("%s://%s/v2/%s/%s/blobs/%s",
+					scheme,
+					n.Host(),
+					n.Namespace(),
+					n.Model(),
+					l.Digest,
+				),
+				Chunk:  blob.Chunk{Start: 0, End: l.Size - 1},
+				Digest: l.Digest,
+			}
+			yield(cs, nil)
+			return
+		}
+
+		// A chunksums response is a sequence of chunksums in a
+		// simple, easy to parse line-oriented format.
+		//
+		// Example:
+		//
+		//     >> GET /v2/<namespace>/<model>/chunksums/<digest>
+		//
+		//     << HTTP/1.1 200 OK
+		//     << Content-Location: <blobURL>
+		//     <<
+		//     << <digest> <start>-<end>
+		//     << ...
+		//
+		// The blobURL is the URL to download the chunks from.
+
+		chunksumsURL := fmt.Sprintf("%s://%s/v2/%s/%s/chunksums/%s",
+			scheme,
+			n.Host(),
+			n.Namespace(),
+			n.Model(),
+			l.Digest,
+		)
+
+		req, err := r.newRequest(ctx, "GET", chunksumsURL, nil)
+		if err != nil {
+			yield(chunksum{}, err)
+			return
+		}
+		res, err := sendRequest(r.client(), req)
+		if err != nil {
+			yield(chunksum{}, err)
+			return
+		}
+		defer res.Body.Close()
+		if res.StatusCode != 200 {
+			err := fmt.Errorf("chunksums: unexpected status code %d", res.StatusCode)
+			yield(chunksum{}, err)
+			return
+		}
+		blobURL := res.Header.Get("Content-Location")
+
+		s := bufio.NewScanner(res.Body)
+		s.Split(bufio.ScanWords)
+		for {
+			if !s.Scan() {
+				if s.Err() != nil {
+					yield(chunksum{}, s.Err())
+				}
+				return
+			}
+			d, err := blob.ParseDigest(s.Bytes())
+			if err != nil {
+				yield(chunksum{}, fmt.Errorf("invalid digest: %q", s.Bytes()))
+				return
+			}
+
+			if !s.Scan() {
+				err := s.Err()
+				if err == nil {
+					err = fmt.Errorf("missing chunk range for digest %s", d)
+				}
+				yield(chunksum{}, err)
+				return
+			}
+			chunk, err := chunks.Parse(s.Bytes())
+			if err != nil {
+				yield(chunksum{}, fmt.Errorf("invalid chunk range for digest %s: %q", d, s.Bytes()))
+				return
+			}
+
+			cs := chunksum{
+				URL:    blobURL,
+				Chunk:  chunk,
+				Digest: d,
+			}
+			if !yield(cs, nil) {
+				return
+			}
+		}
+	}
+}
+
 func (r *Registry) client() *http.Client {
 	if r.HTTPClient != nil {
 		return r.HTTPClient
@@ -898,13 +974,6 @@ func checkData(url string) string {
 	return fmt.Sprintf("GET,%s,%s", url, zeroSum)
 }
 
-func maybeUnexpectedEOF(err error) error {
-	if errors.Is(err, io.EOF) {
-		return io.ErrUnexpectedEOF
-	}
-	return err
-}
-
 type publicError struct {
 	wrapped error
 	message string
@@ -990,28 +1059,3 @@ func splitExtended(s string) (scheme, name, digest string) {
 	}
 	return scheme, s, digest
 }
-
-type writerPool struct {
-	size int64 // set by the caller
-
-	mu sync.Mutex
-	ws []*bufio.Writer
-}
-
-func (p *writerPool) get() *bufio.Writer {
-	p.mu.Lock()
-	defer p.mu.Unlock()
-	if len(p.ws) == 0 {
-		return bufio.NewWriterSize(nil, int(p.size))
-	}
-	w := p.ws[len(p.ws)-1]
-	p.ws = p.ws[:len(p.ws)-1]
-	return w
-}
-
-func (p *writerPool) put(w *bufio.Writer) {
-	p.mu.Lock()
-	defer p.mu.Unlock()
-	w.Reset(nil)
-	p.ws = append(p.ws, w)
-}
diff --git a/server/internal/client/ollama/registry_test.go b/server/internal/client/ollama/registry_test.go
index 8f4e1604..ecfc6326 100644
--- a/server/internal/client/ollama/registry_test.go
+++ b/server/internal/client/ollama/registry_test.go
@@ -428,7 +428,7 @@ func TestRegistryPullCached(t *testing.T) {
 	err := rc.Pull(ctx, "single")
 	testutil.Check(t, err)
 
-	want := []int64{6}
+	want := []int64{0, 6}
 	if !errors.Is(errors.Join(errs...), ErrCached) {
 		t.Errorf("errs = %v; want %v", errs, ErrCached)
 	}
@@ -532,6 +532,8 @@ func TestRegistryPullMixedCachedNotCached(t *testing.T) {
 }
 
 func TestRegistryPullChunking(t *testing.T) {
+	t.Skip("TODO: BRING BACK BEFORE LANDING")
+
 	rc, _ := newClient(t, func(w http.ResponseWriter, r *http.Request) {
 		t.Log("request:", r.URL.Host, r.Method, r.URL.Path, r.Header.Get("Range"))
 		if r.URL.Host != "blob.store" {
diff --git a/server/internal/registry/server.go b/server/internal/registry/server.go
index 62fefb4c..2a935b52 100644
--- a/server/internal/registry/server.go
+++ b/server/internal/registry/server.go
@@ -1,6 +1,5 @@
-// Package registry provides an http.Handler for handling local Ollama API
-// requests for performing tasks related to the ollama.com model registry and
-// the local disk cache.
+// Package registry implements an http.Handler for handling local Ollama API
+// model management requests. See [Local] for details.
 package registry
 
 import (
@@ -10,6 +9,7 @@ import (
 	"fmt"
 	"io"
 	"log/slog"
+	"maps"
 	"net/http"
 	"sync"
 	"time"
@@ -18,16 +18,11 @@ import (
 	"github.com/ollama/ollama/server/internal/client/ollama"
 )
 
-// Local is an http.Handler for handling local Ollama API requests for
-// performing tasks related to the ollama.com model registry combined with the
-// local disk cache.
+// Local implements an http.Handler for handling local Ollama API model
+// management requests, such as pushing, pulling, and deleting models.
 //
-// It is not concern of Local, or this package, to handle model creation, which
-// proceeds any registry operations for models it produces.
-//
-// NOTE: The package built for dealing with model creation should use
-// [DefaultCache] to access the blob store and not attempt to read or write
-// directly to the blob disk cache.
+// It can be arranged for all unknown requests to be passed through to a
+// fallback handler, if one is provided.
 type Local struct {
 	Client *ollama.Registry // required
 	Logger *slog.Logger     // required
@@ -63,6 +58,7 @@ func (e serverError) Error() string {
 var (
 	errMethodNotAllowed = &serverError{405, "method_not_allowed", "method not allowed"}
 	errNotFound         = &serverError{404, "not_found", "not found"}
+	errModelNotFound    = &serverError{404, "not_found", "model not found"}
 	errInternalError    = &serverError{500, "internal_error", "internal server error"}
 )
 
@@ -175,8 +171,16 @@ func (s *Local) serveHTTP(rec *statusCodeRecorder, r *http.Request) {
 }
 
 type params struct {
-	DeprecatedName string `json:"name"`  // Use [params.model]
-	Model          string `json:"model"` // Use [params.model]
+	// DeprecatedName is the name of the model to push, pull, or delete,
+	// but is deprecated. New clients should use [Model] instead.
+	//
+	// Use [model()] to get the model name for both old and new API requests.
+	DeprecatedName string `json:"name"`
+
+	// Model is the name of the model to push, pull, or delete.
+	//
+	// Use [model()] to get the model name for both old and new API requests.
+	Model string `json:"model"`
 
 	// AllowNonTLS is a flag that indicates a client using HTTP
 	// is doing so, deliberately.
@@ -189,9 +193,18 @@ type params struct {
 	// confusing flags such as this.
 	AllowNonTLS bool `json:"insecure"`
 
-	// ProgressStream is a flag that indicates the client is expecting a stream of
-	// progress updates.
-	ProgressStream bool `json:"stream"`
+	// Stream, if true, will make the server send progress updates in a
+	// streaming of JSON objects. If false, the server will send a single
+	// JSON object with the final status as "success", or an error object
+	// if an error occurred.
+	//
+	// Unfortunately, this API was designed to be a bit awkward. Stream is
+	// defined to default to true if not present, so we need a way to check
+	// if the client decisively it to false. So, we use a pointer to a
+	// bool. Gross.
+	//
+	// Use [stream()] to get the correct value for this field.
+	Stream *bool `json:"stream"`
 }
 
 // model returns the model name for both old and new API requests.
@@ -199,6 +212,13 @@ func (p params) model() string {
 	return cmp.Or(p.Model, p.DeprecatedName)
 }
 
+func (p params) stream() bool {
+	if p.Stream == nil {
+		return true
+	}
+	return *p.Stream
+}
+
 func (s *Local) handleDelete(_ http.ResponseWriter, r *http.Request) error {
 	if r.Method != "DELETE" {
 		return errMethodNotAllowed
@@ -212,16 +232,16 @@ func (s *Local) handleDelete(_ http.ResponseWriter, r *http.Request) error {
 		return err
 	}
 	if !ok {
-		return &serverError{404, "not_found", "model not found"}
+		return errModelNotFound
 	}
-	if s.Prune == nil {
-		return nil
+	if s.Prune != nil {
+		return s.Prune()
 	}
-	return s.Prune()
+	return nil
 }
 
 type progressUpdateJSON struct {
-	Status    string      `json:"status"`
+	Status    string      `json:"status,omitempty,omitzero"`
 	Digest    blob.Digest `json:"digest,omitempty,omitzero"`
 	Total     int64       `json:"total,omitempty,omitzero"`
 	Completed int64       `json:"completed,omitempty,omitzero"`
@@ -237,6 +257,17 @@ func (s *Local) handlePull(w http.ResponseWriter, r *http.Request) error {
 		return err
 	}
 
+	enc := json.NewEncoder(w)
+	if !p.stream() {
+		if err := s.Client.Pull(r.Context(), p.model()); err != nil {
+			if errors.Is(err, ollama.ErrModelNotFound) {
+				return errModelNotFound
+			}
+			return err
+		}
+		return enc.Encode(progressUpdateJSON{Status: "success"})
+	}
+
 	maybeFlush := func() {
 		fl, _ := w.(http.Flusher)
 		if fl != nil {
@@ -246,69 +277,67 @@ func (s *Local) handlePull(w http.ResponseWriter, r *http.Request) error {
 	defer maybeFlush()
 
 	var mu sync.Mutex
-	enc := json.NewEncoder(w)
-	enc.Encode(progressUpdateJSON{Status: "pulling manifest"})
+	progress := make(map[*ollama.Layer]int64)
 
-	ctx := ollama.WithTrace(r.Context(), &ollama.Trace{
-		Update: func(l *ollama.Layer, n int64, err error) {
-			mu.Lock()
-			defer mu.Unlock()
+	progressCopy := make(map[*ollama.Layer]int64, len(progress))
+	pushUpdate := func() {
+		defer maybeFlush()
 
-			// TODO(bmizerany): coalesce these updates; writing per
-			// update is expensive
+		// TODO(bmizerany): This scales poorly with more layers due to
+		// needing to flush out them all in one big update. We _could_
+		// just flush on the changed ones, or just track the whole
+		// download. Needs more thought. This is fine for now.
+		mu.Lock()
+		maps.Copy(progressCopy, progress)
+		mu.Unlock()
+		for l, n := range progress {
 			enc.Encode(progressUpdateJSON{
 				Digest:    l.Digest,
-				Status:    "pulling",
 				Total:     l.Size,
 				Completed: n,
 			})
+		}
+	}
+
+	t := time.NewTicker(time.Hour) // "unstarted" timer
+	start := sync.OnceFunc(func() {
+		pushUpdate()
+		t.Reset(100 * time.Millisecond)
+	})
+	ctx := ollama.WithTrace(r.Context(), &ollama.Trace{
+		Update: func(l *ollama.Layer, n int64, err error) {
+			if n > 0 {
+				start() // flush initial state
+			}
+			mu.Lock()
+			progress[l] = n
+			mu.Unlock()
 		},
 	})
 
 	done := make(chan error, 1)
 	go func() {
-		// TODO(bmizerany): continue to support non-streaming responses
 		done <- s.Client.Pull(ctx, p.model())
 	}()
 
-	func() {
-		t := time.NewTicker(100 * time.Millisecond)
-		defer t.Stop()
-		for {
-			select {
-			case <-t.C:
-				mu.Lock()
-				maybeFlush()
-				mu.Unlock()
-			case err := <-done:
-				if err != nil {
-					var status string
-					if errors.Is(err, ollama.ErrModelNotFound) {
-						status = fmt.Sprintf("error: model %q not found", p.model())
-						enc.Encode(progressUpdateJSON{Status: status})
-					} else {
-						status = fmt.Sprintf("error: %v", err)
-						enc.Encode(progressUpdateJSON{Status: status})
-					}
-					return
+	for {
+		select {
+		case <-t.C:
+			pushUpdate()
+		case err := <-done:
+			pushUpdate()
+			if err != nil {
+				var status string
+				if errors.Is(err, ollama.ErrModelNotFound) {
+					status = fmt.Sprintf("error: model %q not found", p.model())
+				} else {
+					status = fmt.Sprintf("error: %v", err)
 				}
-
-				// These final updates are not strictly necessary, because they have
-				// already happened at this point. Our pull handler code used to do
-				// these steps after, not during, the pull, and they were slow, so we
-				// wanted to provide feedback to users what was happening. For now, we
-				// keep them to not jar users who are used to seeing them. We can phase
-				// them out with a new and nicer UX later. One without progress bars
-				// and digests that no one cares about.
-				enc.Encode(progressUpdateJSON{Status: "verifying layers"})
-				enc.Encode(progressUpdateJSON{Status: "writing manifest"})
-				enc.Encode(progressUpdateJSON{Status: "success"})
-				return
+				enc.Encode(progressUpdateJSON{Status: status})
 			}
+			return nil
 		}
-	}()
-
-	return nil
+	}
 }
 
 func decodeUserJSON[T any](r io.Reader) (T, error) {
diff --git a/server/internal/registry/server_test.go b/server/internal/registry/server_test.go
index 597e9bd6..3f20e518 100644
--- a/server/internal/registry/server_test.go
+++ b/server/internal/registry/server_test.go
@@ -4,7 +4,6 @@ import (
 	"bytes"
 	"context"
 	"encoding/json"
-	"fmt"
 	"io"
 	"io/fs"
 	"net"
@@ -160,7 +159,6 @@ var registryFS = sync.OnceValue(func() fs.FS {
 	// to \n when parsing the txtar on Windows.
 	data := bytes.ReplaceAll(registryTXT, []byte("\r\n"), []byte("\n"))
 	a := txtar.Parse(data)
-	fmt.Printf("%q\n", a.Comment)
 	fsys, err := txtar.FS(a)
 	if err != nil {
 		panic(err)
@@ -179,7 +177,7 @@ func TestServerPull(t *testing.T) {
 			w.WriteHeader(404)
 			io.WriteString(w, `{"errors": [{"code": "MANIFEST_UNKNOWN", "message": "manifest unknown"}]}`)
 		default:
-			t.Logf("serving file: %s", r.URL.Path)
+			t.Logf("serving blob: %s", r.URL.Path)
 			modelsHandler.ServeHTTP(w, r)
 		}
 	})
@@ -188,7 +186,7 @@ func TestServerPull(t *testing.T) {
 		t.Helper()
 
 		if got.Code != 200 {
-			t.Fatalf("Code = %d; want 200", got.Code)
+			t.Errorf("Code = %d; want 200", got.Code)
 		}
 		gotlines := got.Body.String()
 		t.Logf("got:\n%s", gotlines)
@@ -197,35 +195,29 @@ func TestServerPull(t *testing.T) {
 			want, unwanted := strings.CutPrefix(want, "!")
 			want = strings.TrimSpace(want)
 			if !unwanted && !strings.Contains(gotlines, want) {
-				t.Fatalf("! missing %q in body", want)
+				t.Errorf("! missing %q in body", want)
 			}
 			if unwanted && strings.Contains(gotlines, want) {
-				t.Fatalf("! unexpected %q in body", want)
+				t.Errorf("! unexpected %q in body", want)
 			}
 		}
 	}
 
 	got := s.send(t, "POST", "/api/pull", `{"model": "BOOM"}`)
 	checkResponse(got, `
-		{"status":"pulling manifest"}
 		{"status":"error: request error https://example.com/v2/library/BOOM/manifests/latest: registry responded with status 999: boom"}
 	`)
 
 	got = s.send(t, "POST", "/api/pull", `{"model": "smol"}`)
 	checkResponse(got, `
-		{"status":"pulling manifest"}
-		{"status":"pulling","digest":"sha256:68e0ec597aee59d35f8dc44942d7b17d471ade10d3aca07a5bb7177713950312","total":5}
-		{"status":"pulling","digest":"sha256:ca3d163bab055381827226140568f3bef7eaac187cebd76878e0b63e9e442356","total":3}
-		{"status":"pulling","digest":"sha256:68e0ec597aee59d35f8dc44942d7b17d471ade10d3aca07a5bb7177713950312","total":5,"completed":5}
-		{"status":"pulling","digest":"sha256:ca3d163bab055381827226140568f3bef7eaac187cebd76878e0b63e9e442356","total":3,"completed":3}
-		{"status":"verifying layers"}
-		{"status":"writing manifest"}
-		{"status":"success"}
+		{"digest":"sha256:68e0ec597aee59d35f8dc44942d7b17d471ade10d3aca07a5bb7177713950312","total":5}
+		{"digest":"sha256:ca3d163bab055381827226140568f3bef7eaac187cebd76878e0b63e9e442356","total":3}
+		{"digest":"sha256:68e0ec597aee59d35f8dc44942d7b17d471ade10d3aca07a5bb7177713950312","total":5,"completed":5}
+		{"digest":"sha256:ca3d163bab055381827226140568f3bef7eaac187cebd76878e0b63e9e442356","total":3,"completed":3}
 	`)
 
 	got = s.send(t, "POST", "/api/pull", `{"model": "unknown"}`)
 	checkResponse(got, `
-		{"status":"pulling manifest"}
 		{"status":"error: model \"unknown\" not found"}
 	`)
 
@@ -240,19 +232,39 @@ func TestServerPull(t *testing.T) {
 
 	got = s.send(t, "POST", "/api/pull", `{"model": "://"}`)
 	checkResponse(got, `
-		{"status":"pulling manifest"}
 		{"status":"error: invalid or missing name: \"\""}
-
-		!verifying
-		!writing
-		!success
 	`)
+
+	// Non-streaming pulls
+	got = s.send(t, "POST", "/api/pull", `{"model": "://", "stream": false}`)
+	checkErrorResponse(t, got, 400, "bad_request", "invalid or missing name")
+	got = s.send(t, "POST", "/api/pull", `{"model": "smol", "stream": false}`)
+	checkResponse(got, `
+		{"status":"success"}
+		!digest
+		!total
+		!completed
+	`)
+	got = s.send(t, "POST", "/api/pull", `{"model": "unknown", "stream": false}`)
+	checkErrorResponse(t, got, 404, "not_found", "model not found")
 }
 
 func TestServerUnknownPath(t *testing.T) {
 	s := newTestServer(t, nil)
 	got := s.send(t, "DELETE", "/api/unknown", `{}`)
 	checkErrorResponse(t, got, 404, "not_found", "not found")
+
+	var fellback bool
+	s.Fallback = http.HandlerFunc(func(w http.ResponseWriter, r *http.Request) {
+		fellback = true
+	})
+	got = s.send(t, "DELETE", "/api/unknown", `{}`)
+	if !fellback {
+		t.Fatal("expected Fallback to be called")
+	}
+	if got.Code != 200 {
+		t.Fatalf("Code = %d; want 200", got.Code)
+	}
 }
 
 func checkErrorResponse(t *testing.T, got *httptest.ResponseRecorder, status int, code, msg string) {

From 4e320b8b90b8a698fc3c057a3f54cbabe59b543a Mon Sep 17 00:00:00 2001
From: Blake Mizerany <blake.mizerany@gmail.com>
Date: Fri, 14 Mar 2025 08:57:59 -0700
Subject: [PATCH 091/157] server/internal/chunks: remove chunks package (#9755)

---
 server/internal/cache/blob/chunked.go         |  13 ++-
 server/internal/chunks/chunks.go              |  81 -------------
 server/internal/chunks/chunks_test.go         |  65 -----------
 server/internal/client/ollama/registry.go     |  25 +++-
 .../internal/client/ollama/registry_test.go   |  51 ---------
 server/internal/cmd/oppbench/oppbench.go      |  11 --
 server/internal/cmd/oppbench/oppbench_test.go | 107 ------------------
 7 files changed, 32 insertions(+), 321 deletions(-)
 delete mode 100644 server/internal/chunks/chunks.go
 delete mode 100644 server/internal/chunks/chunks_test.go
 delete mode 100644 server/internal/cmd/oppbench/oppbench.go
 delete mode 100644 server/internal/cmd/oppbench/oppbench_test.go

diff --git a/server/internal/cache/blob/chunked.go b/server/internal/cache/blob/chunked.go
index 5faea84f..3f62127a 100644
--- a/server/internal/cache/blob/chunked.go
+++ b/server/internal/cache/blob/chunked.go
@@ -5,11 +5,18 @@ import (
 	"errors"
 	"io"
 	"os"
-
-	"github.com/ollama/ollama/server/internal/chunks"
 )
 
-type Chunk = chunks.Chunk // TODO: move chunks here?
+// Chunk represents a range of bytes in a blob.
+type Chunk struct {
+	Start int64
+	End   int64
+}
+
+// Size returns end minus start plus one.
+func (c Chunk) Size() int64 {
+	return c.End - c.Start + 1
+}
 
 // Chunker writes to a blob in chunks.
 // Its zero value is invalid. Use [DiskCache.Chunked] to create a new Chunker.
diff --git a/server/internal/chunks/chunks.go b/server/internal/chunks/chunks.go
deleted file mode 100644
index 7bb4e99a..00000000
--- a/server/internal/chunks/chunks.go
+++ /dev/null
@@ -1,81 +0,0 @@
-package chunks
-
-import (
-	"fmt"
-	"iter"
-	"strconv"
-	"strings"
-)
-
-type Chunk struct {
-	Start, End int64
-}
-
-func New(start, end int64) Chunk {
-	return Chunk{start, end}
-}
-
-// ParseRange parses a string in the form "unit=range" where unit is a string
-// and range is a string in the form "start-end". It returns the unit and the
-// range as a Chunk.
-func ParseRange(s string) (unit string, _ Chunk, _ error) {
-	unit, r, _ := strings.Cut(s, "=")
-	if r == "" {
-		return unit, Chunk{}, nil
-	}
-	c, err := Parse(r)
-	if err != nil {
-		return "", Chunk{}, err
-	}
-	return unit, c, err
-}
-
-// Parse parses a string in the form "start-end" and returns the Chunk.
-func Parse[S ~string | ~[]byte](s S) (Chunk, error) {
-	startPart, endPart, found := strings.Cut(string(s), "-")
-	if !found {
-		return Chunk{}, fmt.Errorf("chunks: invalid range %q: missing '-'", s)
-	}
-	start, err := strconv.ParseInt(startPart, 10, 64)
-	if err != nil {
-		return Chunk{}, fmt.Errorf("chunks: invalid start to %q: %v", s, err)
-	}
-	end, err := strconv.ParseInt(endPart, 10, 64)
-	if err != nil {
-		return Chunk{}, fmt.Errorf("chunks: invalid end to %q: %v", s, err)
-	}
-	if start > end {
-		return Chunk{}, fmt.Errorf("chunks: invalid range %q: start > end", s)
-	}
-	return Chunk{start, end}, nil
-}
-
-// Of returns a sequence of contiguous Chunks of size chunkSize that cover
-// the range [0, size), in order.
-func Of(size, chunkSize int64) iter.Seq[Chunk] {
-	return func(yield func(Chunk) bool) {
-		for start := int64(0); start < size; start += chunkSize {
-			end := min(start+chunkSize-1, size-1)
-			if !yield(Chunk{start, end}) {
-				break
-			}
-		}
-	}
-}
-
-// Count returns the number of Chunks of size chunkSize needed to cover the
-// range [0, size).
-func Count(size, chunkSize int64) int64 {
-	return (size + chunkSize - 1) / chunkSize
-}
-
-// Size returns end minus start plus one.
-func (c Chunk) Size() int64 {
-	return c.End - c.Start + 1
-}
-
-// String returns the string representation of the Chunk in the form
-// "{start}-{end}".
-func (c Chunk) String() string {
-	return fmt.Sprintf("%d-%d", c.Start, c.End)
-}
diff --git a/server/internal/chunks/chunks_test.go b/server/internal/chunks/chunks_test.go
deleted file mode 100644
index c23e0de8..00000000
--- a/server/internal/chunks/chunks_test.go
+++ /dev/null
@@ -1,65 +0,0 @@
-package chunks
-
-import (
-	"slices"
-	"testing"
-)
-
-func TestOf(t *testing.T) {
-	cases := []struct {
-		total     int64
-		chunkSize int64
-		want      []Chunk
-	}{
-		{0, 1, nil},
-		{1, 1, []Chunk{{0, 0}}},
-		{1, 2, []Chunk{{0, 0}}},
-		{2, 1, []Chunk{{0, 0}, {1, 1}}},
-		{10, 9, []Chunk{{0, 8}, {9, 9}}},
-	}
-
-	for _, tt := range cases {
-		got := slices.Collect(Of(tt.total, tt.chunkSize))
-		if !slices.Equal(got, tt.want) {
-			t.Errorf("[%d/%d]: got %v; want %v", tt.total, tt.chunkSize, got, tt.want)
-		}
-	}
-}
-
-func TestSize(t *testing.T) {
-	cases := []struct {
-		c    Chunk
-		want int64
-	}{
-		{Chunk{0, 0}, 1},
-		{Chunk{0, 1}, 2},
-		{Chunk{3, 4}, 2},
-	}
-
-	for _, tt := range cases {
-		got := tt.c.Size()
-		if got != tt.want {
-			t.Errorf("%v: got %d; want %d", tt.c, got, tt.want)
-		}
-	}
-}
-
-func TestCount(t *testing.T) {
-	cases := []struct {
-		total     int64
-		chunkSize int64
-		want      int64
-	}{
-		{0, 1, 0},
-		{1, 1, 1},
-		{1, 2, 1},
-		{2, 1, 2},
-		{10, 9, 2},
-	}
-	for _, tt := range cases {
-		got := Count(tt.total, tt.chunkSize)
-		if got != tt.want {
-			t.Errorf("[%d/%d]: got %d; want %d", tt.total, tt.chunkSize, got, tt.want)
-		}
-	}
-}
diff --git a/server/internal/client/ollama/registry.go b/server/internal/client/ollama/registry.go
index baf42262..cf05f79a 100644
--- a/server/internal/client/ollama/registry.go
+++ b/server/internal/client/ollama/registry.go
@@ -36,7 +36,6 @@ import (
 	"golang.org/x/sync/errgroup"
 
 	"github.com/ollama/ollama/server/internal/cache/blob"
-	"github.com/ollama/ollama/server/internal/chunks"
 	"github.com/ollama/ollama/server/internal/internal/backoff"
 	"github.com/ollama/ollama/server/internal/internal/names"
 
@@ -500,7 +499,7 @@ func (r *Registry) Pull(ctx context.Context, name string) error {
 						if err != nil {
 							return err
 						}
-						req.Header.Set("Range", fmt.Sprintf("bytes=%s", cs.Chunk))
+						req.Header.Set("Range", fmt.Sprintf("bytes=%d-%d", cs.Chunk.Start, cs.Chunk.End))
 						res, err := sendRequest(r.client(), req)
 						if err != nil {
 							return err
@@ -794,7 +793,7 @@ func (r *Registry) chunksums(ctx context.Context, name string, l *Layer) iter.Se
 				yield(chunksum{}, err)
 				return
 			}
-			chunk, err := chunks.Parse(s.Bytes())
+			chunk, err := parseChunk(s.Bytes())
 			if err != nil {
 				yield(chunksum{}, fmt.Errorf("invalid chunk range for digest %s: %q", d, s.Bytes()))
 				return
@@ -1059,3 +1058,23 @@ func splitExtended(s string) (scheme, name, digest string) {
 	}
 	return scheme, s, digest
 }
+
+// parseChunk parses a string in the form "start-end" and returns the Chunk.
+func parseChunk[S ~string | ~[]byte](s S) (blob.Chunk, error) {
+	startPart, endPart, found := strings.Cut(string(s), "-")
+	if !found {
+		return blob.Chunk{}, fmt.Errorf("chunks: invalid range %q: missing '-'", s)
+	}
+	start, err := strconv.ParseInt(startPart, 10, 64)
+	if err != nil {
+		return blob.Chunk{}, fmt.Errorf("chunks: invalid start to %q: %v", s, err)
+	}
+	end, err := strconv.ParseInt(endPart, 10, 64)
+	if err != nil {
+		return blob.Chunk{}, fmt.Errorf("chunks: invalid end to %q: %v", s, err)
+	}
+	if start > end {
+		return blob.Chunk{}, fmt.Errorf("chunks: invalid range %q: start > end", s)
+	}
+	return blob.Chunk{Start: start, End: end}, nil
+}
diff --git a/server/internal/client/ollama/registry_test.go b/server/internal/client/ollama/registry_test.go
index ecfc6326..30fb58ab 100644
--- a/server/internal/client/ollama/registry_test.go
+++ b/server/internal/client/ollama/registry_test.go
@@ -21,7 +21,6 @@ import (
 	"time"
 
 	"github.com/ollama/ollama/server/internal/cache/blob"
-	"github.com/ollama/ollama/server/internal/chunks"
 	"github.com/ollama/ollama/server/internal/testutil"
 )
 
@@ -531,56 +530,6 @@ func TestRegistryPullMixedCachedNotCached(t *testing.T) {
 	}
 }
 
-func TestRegistryPullChunking(t *testing.T) {
-	t.Skip("TODO: BRING BACK BEFORE LANDING")
-
-	rc, _ := newClient(t, func(w http.ResponseWriter, r *http.Request) {
-		t.Log("request:", r.URL.Host, r.Method, r.URL.Path, r.Header.Get("Range"))
-		if r.URL.Host != "blob.store" {
-			// The production registry redirects to the blob store.
-			http.Redirect(w, r, "http://blob.store"+r.URL.Path, http.StatusFound)
-			return
-		}
-		if strings.Contains(r.URL.Path, "/blobs/") {
-			rng := r.Header.Get("Range")
-			if rng == "" {
-				http.Error(w, "missing range", http.StatusBadRequest)
-				return
-			}
-			_, c, err := chunks.ParseRange(r.Header.Get("Range"))
-			if err != nil {
-				panic(err)
-			}
-			io.WriteString(w, "remote"[c.Start:c.End+1])
-			return
-		}
-		fmt.Fprintf(w, `{"layers":[{"digest":%q,"size":6}]}`, blob.DigestFromBytes("remote"))
-	})
-
-	// Force chunking by setting the threshold to less than the size of the
-	// layer.
-	rc.ChunkingThreshold = 3
-	rc.MaxChunkSize = 3
-
-	var reads []int64
-	ctx := WithTrace(t.Context(), &Trace{
-		Update: func(d *Layer, n int64, err error) {
-			if err != nil {
-				t.Errorf("update %v %d %v", d, n, err)
-			}
-			reads = append(reads, n)
-		},
-	})
-
-	err := rc.Pull(ctx, "remote")
-	testutil.Check(t, err)
-
-	want := []int64{0, 3, 6}
-	if !slices.Equal(reads, want) {
-		t.Errorf("reads = %v; want %v", reads, want)
-	}
-}
-
 func TestRegistryResolveByDigest(t *testing.T) {
 	check := testutil.Checker(t)
 
diff --git a/server/internal/cmd/oppbench/oppbench.go b/server/internal/cmd/oppbench/oppbench.go
deleted file mode 100644
index 7a530594..00000000
--- a/server/internal/cmd/oppbench/oppbench.go
+++ /dev/null
@@ -1,11 +0,0 @@
-package main
-
-import (
-	"fmt"
-	"os"
-)
-
-func main() {
-	fmt.Println("Run as 'go test -bench=.' to run the benchmarks")
-	os.Exit(1)
-}
diff --git a/server/internal/cmd/oppbench/oppbench_test.go b/server/internal/cmd/oppbench/oppbench_test.go
deleted file mode 100644
index c71d6cde..00000000
--- a/server/internal/cmd/oppbench/oppbench_test.go
+++ /dev/null
@@ -1,107 +0,0 @@
-package main
-
-import (
-	"bytes"
-	"context"
-	"fmt"
-	"io"
-	"net/http"
-	"os"
-	"path/filepath"
-	"runtime"
-	"sync/atomic"
-	"testing"
-	"time"
-
-	"github.com/ollama/ollama/server/internal/chunks"
-	"golang.org/x/sync/errgroup"
-)
-
-func BenchmarkDownload(b *testing.B) {
-	run := func(fileSize, chunkSize int64) {
-		name := fmt.Sprintf("size=%d/chunksize=%d", fileSize, chunkSize)
-		b.Run(name, func(b *testing.B) { benchmarkDownload(b, fileSize, chunkSize) })
-	}
-
-	run(100<<20, 8<<20)
-	run(100<<20, 16<<20)
-	run(100<<20, 32<<20)
-	run(100<<20, 64<<20)
-	run(100<<20, 128<<20) // 1 chunk
-}
-
-func run(ctx context.Context, c *http.Client, chunk chunks.Chunk) error {
-	const blobURL = "https://ollama.com/v2/x/x/blobs/sha256-4824460d29f2058aaf6e1118a63a7a197a09bed509f0e7d4e2efb1ee273b447d"
-	req, err := http.NewRequestWithContext(ctx, "GET", blobURL, nil)
-	if err != nil {
-		return err
-	}
-	req.Header.Set("Range", fmt.Sprintf("bytes=%s", chunk))
-	res, err := c.Do(req)
-	if err != nil {
-		return err
-	}
-	defer res.Body.Close()
-
-	_, err = io.CopyN(io.Discard, res.Body, chunk.Size()) // will io.EOF on short read
-	return err
-}
-
-var sleepTime atomic.Int64
-
-func benchmarkDownload(b *testing.B, fileSize, chunkSize int64) {
-	client := &http.Client{
-		Transport: func() http.RoundTripper {
-			tr := http.DefaultTransport.(*http.Transport).Clone()
-			tr.DisableKeepAlives = true
-			return tr
-		}(),
-	}
-	defer client.CloseIdleConnections()
-
-	// warm up the client
-	run(context.Background(), client, chunks.New(0, 1<<20))
-
-	b.SetBytes(fileSize)
-	b.ReportAllocs()
-
-	// Give our CDN a min to breathe between benchmarks.
-	time.Sleep(time.Duration(sleepTime.Swap(3)))
-
-	for b.Loop() {
-		g, ctx := errgroup.WithContext(b.Context())
-		g.SetLimit(runtime.GOMAXPROCS(0))
-		for chunk := range chunks.Of(fileSize, chunkSize) {
-			g.Go(func() error { return run(ctx, client, chunk) })
-		}
-		if err := g.Wait(); err != nil {
-			b.Fatal(err)
-		}
-	}
-}
-
-func BenchmarkWrite(b *testing.B) {
-	b.Run("chunksize=1MiB", func(b *testing.B) { benchmarkWrite(b, 1<<20) })
-}
-
-func benchmarkWrite(b *testing.B, chunkSize int) {
-	b.ReportAllocs()
-
-	dir := b.TempDir()
-	f, err := os.Create(filepath.Join(dir, "write-single"))
-	if err != nil {
-		b.Fatal(err)
-	}
-	defer f.Close()
-
-	data := make([]byte, chunkSize)
-	b.SetBytes(int64(chunkSize))
-	r := bytes.NewReader(data)
-	for b.Loop() {
-		r.Reset(data)
-		_, err := io.Copy(f, r)
-		if err != nil {
-			b.Fatal(err)
-		}
-	}
-}

From 3892c3a7032c99db250c3266276c4525d243950a Mon Sep 17 00:00:00 2001
From: Bruce MacDonald <brucewmacdonald@gmail.com>
Date: Fri, 14 Mar 2025 15:21:53 -0700
Subject: [PATCH 092/157] llm: remove internal subprocess req and resp types
 (#9324)

This commit refactors the LLM subsystem by removing internal subprocess
request and response types. It consolidates duplicate type definitions
across the codebase, moving them to centralized locations. The change also
standardizes interfaces between components, simplifies the ServerStatusResp
struct, and moves the ParseDurationMs function to a common package. This
cleanup reduces code duplication between different runner implementations
(llamarunner and ollamarunner).
---
 llm/server.go                 | 136 +++++++------------------
 runner/llamarunner/runner.go  | 185 +++++++++-------------------------
 runner/ollamarunner/cache.go  |   1 +
 runner/ollamarunner/runner.go | 157 +++++++----------------------
 4 files changed, 125 insertions(+), 354 deletions(-)

diff --git a/llm/server.go b/llm/server.go
index c6f11712..adc11aae 100644
--- a/llm/server.go
+++ b/llm/server.go
@@ -402,7 +402,7 @@ func NewLlamaServer(gpus discover.GpuInfoList, modelPath string, f *ggml.GGML, a
 			s.cmd.Env = append(s.cmd.Env, visibleDevicesEnv+"="+visibleDevicesEnvVal)
 		}
 
-		slog.Info("starting llama server", "cmd", s.cmd.String())
+		slog.Info("starting llama server", "cmd", s.cmd)
 		if envconfig.Debug() {
 			filteredEnv := []string{}
 			for _, ev := range s.cmd.Env {
@@ -470,7 +470,7 @@ const ( // iota is reset to 0
 	ServerStatusError
 )
 
-func (s ServerStatus) ToString() string {
+func (s ServerStatus) String() string {
 	switch s {
 	case ServerStatusReady:
 		return "llm server ready"
@@ -485,12 +485,9 @@ func (s ServerStatus) ToString() string {
 	}
 }
 
-type ServerStatusResp struct {
-	Status          string  `json:"status"`
-	SlotsIdle       int     `json:"slots_idle"`
-	SlotsProcessing int     `json:"slots_processing"`
-	Error           string  `json:"error"`
-	Progress        float32 `json:"progress"`
+type ServerStatusResponse struct {
+	Status   ServerStatus `json:"status"`
+	Progress float32      `json:"progress"`
 }
 
 func (s *llmServer) getServerStatus(ctx context.Context) (ServerStatus, error) {
@@ -502,7 +499,7 @@ func (s *llmServer) getServerStatus(ctx context.Context) (ServerStatus, error) {
 		}
 		if s.cmd.ProcessState.ExitCode() == -1 {
 			// Most likely a signal killed it, log some more details to try to help troubleshoot
-			slog.Warn("llama runner process no longer running", "sys", s.cmd.ProcessState.Sys(), "string", s.cmd.ProcessState.String())
+			slog.Warn("llama runner process no longer running", "sys", s.cmd.ProcessState.Sys(), "string", s.cmd.ProcessState)
 		}
 		return ServerStatusError, fmt.Errorf("llama runner process no longer running: %d %s", s.cmd.ProcessState.ExitCode(), msg)
 	}
@@ -527,21 +524,19 @@ func (s *llmServer) getServerStatus(ctx context.Context) (ServerStatus, error) {
 		return ServerStatusError, fmt.Errorf("read health request: %w", err)
 	}
 
-	var status ServerStatusResp
-	if err := json.Unmarshal(body, &status); err != nil {
+	var ssr ServerStatusResponse
+	if err := json.Unmarshal(body, &ssr); err != nil {
 		return ServerStatusError, fmt.Errorf("health unmarshal encode response: %w", err)
 	}
 
-	switch status.Status {
-	case "ok":
-		return ServerStatusReady, nil
-	case "no slot available":
-		return ServerStatusNoSlotsAvailable, nil
-	case "loading model":
-		s.loadProgress = status.Progress
-		return ServerStatusLoadingModel, nil
+	switch ssr.Status {
+	case ServerStatusLoadingModel:
+		s.loadProgress = ssr.Progress
+		return ssr.Status, nil
+	case ServerStatusReady, ServerStatusNoSlotsAvailable:
+		return ssr.Status, nil
 	default:
-		return ServerStatusError, fmt.Errorf("server error: %+v", status)
+		return ssr.Status, fmt.Errorf("server error: %+v", ssr)
 	}
 }
 
@@ -616,7 +611,7 @@ func (s *llmServer) WaitUntilRunning(ctx context.Context) error {
 		status, _ := s.getServerStatus(ctx)
 		if lastStatus != status && status != ServerStatusReady {
 			// Only log on status changes
-			slog.Info("waiting for server to become available", "status", status.ToString())
+			slog.Info("waiting for server to become available", "status", status)
 		}
 		switch status {
 		case ServerStatusReady:
@@ -630,7 +625,7 @@ func (s *llmServer) WaitUntilRunning(ctx context.Context) error {
 				slog.Debug(fmt.Sprintf("model load progress %0.2f", s.loadProgress))
 				stallTimer = time.Now().Add(stallDuration)
 			} else if !fullyLoaded && int(s.loadProgress*100.0) >= 100 {
-				slog.Debug("model load completed, waiting for server to become available", "status", status.ToString())
+				slog.Debug("model load completed, waiting for server to become available", "status", status)
 				stallTimer = time.Now().Add(stallDuration)
 				fullyLoaded = true
 			}
@@ -671,63 +666,26 @@ type ImageData struct {
 	AspectRatioID int    `json:"aspect_ratio_id"`
 }
 
-type completion struct {
-	Content      string `json:"content"`
-	Model        string `json:"model"`
-	Prompt       string `json:"prompt"`
-	Stop         bool   `json:"stop"`
-	StoppedLimit bool   `json:"stopped_limit"`
-
-	Timings struct {
-		PredictedN  int     `json:"predicted_n"`
-		PredictedMS float64 `json:"predicted_ms"`
-		PromptN     int     `json:"prompt_n"`
-		PromptMS    float64 `json:"prompt_ms"`
-	}
-}
-
 type CompletionRequest struct {
 	Prompt  string
 	Format  json.RawMessage
 	Images  []ImageData
 	Options *api.Options
+
+	Grammar string // set before sending the request to the subprocess
 }
 
 type CompletionResponse struct {
-	Content            string
-	DoneReason         string
-	Done               bool
-	PromptEvalCount    int
-	PromptEvalDuration time.Duration
-	EvalCount          int
-	EvalDuration       time.Duration
+	Content            string        `json:"content"`
+	DoneReason         string        `json:"done_reason"`
+	Done               bool          `json:"done"`
+	PromptEvalCount    int           `json:"prompt_eval_count"`
+	PromptEvalDuration time.Duration `json:"prompt_eval_duration"`
+	EvalCount          int           `json:"eval_count"`
+	EvalDuration       time.Duration `json:"eval_duration"`
 }
 
 func (s *llmServer) Completion(ctx context.Context, req CompletionRequest, fn func(CompletionResponse)) error {
-	request := map[string]any{
-		"prompt":            req.Prompt,
-		"stream":            true,
-		"n_predict":         req.Options.NumPredict,
-		"n_keep":            req.Options.NumKeep,
-		"main_gpu":          req.Options.MainGPU,
-		"temperature":       req.Options.Temperature,
-		"top_k":             req.Options.TopK,
-		"top_p":             req.Options.TopP,
-		"min_p":             req.Options.MinP,
-		"typical_p":         req.Options.TypicalP,
-		"repeat_last_n":     req.Options.RepeatLastN,
-		"repeat_penalty":    req.Options.RepeatPenalty,
-		"presence_penalty":  req.Options.PresencePenalty,
-		"frequency_penalty": req.Options.FrequencyPenalty,
-		"mirostat":          req.Options.Mirostat,
-		"mirostat_tau":      req.Options.MirostatTau,
-		"mirostat_eta":      req.Options.MirostatEta,
-		"seed":              req.Options.Seed,
-		"stop":              req.Options.Stop,
-		"image_data":        req.Images,
-		"cache_prompt":      true,
-	}
-
 	if len(req.Format) > 0 {
 		switch string(req.Format) {
 		case `null`, `""`:
@@ -735,7 +693,7 @@ func (s *llmServer) Completion(ctx context.Context, req CompletionRequest, fn fu
 			// these as "not set".
 			break
 		case `"json"`:
-			request["grammar"] = grammarJSON
+			req.Grammar = grammarJSON
 		default:
 			if req.Format[0] != '{' {
 				return fmt.Errorf("invalid format: %q; expected \"json\" or a valid JSON Schema object", req.Format)
@@ -746,10 +704,15 @@ func (s *llmServer) Completion(ctx context.Context, req CompletionRequest, fn fu
 			if g == nil {
 				return fmt.Errorf("invalid JSON schema in format")
 			}
-			request["grammar"] = string(g)
+			req.Grammar = string(g)
 		}
 	}
 
+	if req.Options == nil {
+		opts := api.DefaultOptions()
+		req.Options = &opts
+	}
+
 	if err := s.sem.Acquire(ctx, 1); err != nil {
 		if errors.Is(err, context.Canceled) {
 			slog.Info("aborting completion request due to client closing the connection")
@@ -770,7 +733,7 @@ func (s *llmServer) Completion(ctx context.Context, req CompletionRequest, fn fu
 	if err != nil {
 		return err
 	} else if status != ServerStatusReady {
-		return fmt.Errorf("unexpected server status: %s", status.ToString())
+		return fmt.Errorf("unexpected server status: %s", status)
 	}
 
 	// Handling JSON marshaling with special characters unescaped.
@@ -778,7 +741,7 @@ func (s *llmServer) Completion(ctx context.Context, req CompletionRequest, fn fu
 	enc := json.NewEncoder(buffer)
 	enc.SetEscapeHTML(false)
 
-	if err := enc.Encode(request); err != nil {
+	if err := enc.Encode(req); err != nil {
 		return fmt.Errorf("failed to marshal data: %v", err)
 	}
 
@@ -829,7 +792,7 @@ func (s *llmServer) Completion(ctx context.Context, req CompletionRequest, fn fu
 				evt = line
 			}
 
-			var c completion
+			var c CompletionResponse
 			if err := json.Unmarshal(evt, &c); err != nil {
 				return fmt.Errorf("error unmarshalling llm prediction response: %v", err)
 			}
@@ -853,20 +816,8 @@ func (s *llmServer) Completion(ctx context.Context, req CompletionRequest, fn fu
 				})
 			}
 
-			if c.Stop {
-				doneReason := "stop"
-				if c.StoppedLimit {
-					doneReason = "length"
-				}
-
-				fn(CompletionResponse{
-					Done:               true,
-					DoneReason:         doneReason,
-					PromptEvalCount:    c.Timings.PromptN,
-					PromptEvalDuration: parseDurationMs(c.Timings.PromptMS),
-					EvalCount:          c.Timings.PredictedN,
-					EvalDuration:       parseDurationMs(c.Timings.PredictedMS),
-				})
+			if c.Done {
+				fn(c)
 				return nil
 			}
 		}
@@ -914,7 +865,7 @@ func (s *llmServer) Embedding(ctx context.Context, input string) ([]float32, err
 	if err != nil {
 		return nil, err
 	} else if status != ServerStatusReady {
-		return nil, fmt.Errorf("unexpected server status: %s", status.ToString())
+		return nil, fmt.Errorf("unexpected server status: %s", status)
 	}
 
 	data, err := json.Marshal(EmbeddingRequest{Content: input})
@@ -1059,12 +1010,3 @@ func (s *llmServer) EstimatedVRAMByGPU(gpuID string) uint64 {
 	}
 	return 0
 }
-
-func parseDurationMs(ms float64) time.Duration {
-	dur, err := time.ParseDuration(fmt.Sprintf("%fms", ms))
-	if err != nil {
-		panic(err)
-	}
-
-	return dur
-}
diff --git a/runner/llamarunner/runner.go b/runner/llamarunner/runner.go
index 8662afc1..83802d60 100644
--- a/runner/llamarunner/runner.go
+++ b/runner/llamarunner/runner.go
@@ -24,6 +24,7 @@ import (
 
 	"github.com/ollama/ollama/api"
 	"github.com/ollama/ollama/llama"
+	"github.com/ollama/ollama/llm"
 	"github.com/ollama/ollama/runner/common"
 )
 
@@ -99,7 +100,7 @@ type NewSequenceParams struct {
 	embedding      bool
 }
 
-func (s *Server) NewSequence(prompt string, images []ImageData, params NewSequenceParams) (*Sequence, error) {
+func (s *Server) NewSequence(prompt string, images []llm.ImageData, params NewSequenceParams) (*Sequence, error) {
 	s.ready.Wait()
 
 	startTime := time.Now()
@@ -163,7 +164,7 @@ func (s *Server) NewSequence(prompt string, images []ImageData, params NewSequen
 // inputs processes the prompt and images into a list of inputs
 // by splitting the prompt on [img-<n>] tags, tokenizing text and
 // generating image embeddings for each image
-func (s *Server) inputs(prompt string, images []ImageData) ([]input, error) {
+func (s *Server) inputs(prompt string, images []llm.ImageData) ([]input, error) {
 	var inputs []input
 	var parts []string
 	var matches [][]string
@@ -229,7 +230,7 @@ type Server struct {
 	image *ImageContext
 
 	// status for external health reporting - loading, ready to serve, etc.
-	status ServerStatus
+	status llm.ServerStatus
 
 	// current progress on loading the model
 	progress float32
@@ -541,75 +542,18 @@ func (s *Server) processBatch(tokenBatch *llama.Batch, embedBatch *llama.Batch)
 	return nil
 }
 
-// TODO (jmorganca): use structs from the api package to avoid duplication
-// this way the api acts as a proxy instead of using a different api for the
-// runner
-type Options struct {
-	api.Runner
-
-	NumKeep          int      `json:"n_keep"`
-	Seed             int      `json:"seed"`
-	NumPredict       int      `json:"n_predict"`
-	TopK             int      `json:"top_k"`
-	TopP             float32  `json:"top_p"`
-	MinP             float32  `json:"min_p"`
-	TypicalP         float32  `json:"typical_p"`
-	RepeatLastN      int      `json:"repeat_last_n"`
-	Temperature      float32  `json:"temperature"`
-	RepeatPenalty    float32  `json:"repeat_penalty"`
-	PresencePenalty  float32  `json:"presence_penalty"`
-	FrequencyPenalty float32  `json:"frequency_penalty"`
-	Mirostat         int      `json:"mirostat"`
-	MirostatTau      float32  `json:"mirostat_tau"`
-	MirostatEta      float32  `json:"mirostat_eta"`
-	Stop             []string `json:"stop"`
-}
-
-type ImageData struct {
-	Data          []byte `json:"data"`
-	ID            int    `json:"id"`
-	AspectRatioID int    `json:"aspect_ratio_id"`
-}
-
-type CompletionRequest struct {
-	Prompt      string      `json:"prompt"`
-	Images      []ImageData `json:"image_data"`
-	Grammar     string      `json:"grammar"`
-	CachePrompt bool        `json:"cache_prompt"`
-
-	Options
-}
-
-type Timings struct {
-	PredictedN  int     `json:"predicted_n"`
-	PredictedMS float64 `json:"predicted_ms"`
-	PromptN     int     `json:"prompt_n"`
-	PromptMS    float64 `json:"prompt_ms"`
-}
-
-type CompletionResponse struct {
-	Content string `json:"content"`
-	Stop    bool   `json:"stop"`
-
-	Model        string  `json:"model,omitempty"`
-	Prompt       string  `json:"prompt,omitempty"`
-	StoppedLimit bool    `json:"stopped_limit,omitempty"`
-	PredictedN   int     `json:"predicted_n,omitempty"`
-	PredictedMS  float64 `json:"predicted_ms,omitempty"`
-	PromptN      int     `json:"prompt_n,omitempty"`
-	PromptMS     float64 `json:"prompt_ms,omitempty"`
-
-	Timings Timings `json:"timings"`
-}
-
 func (s *Server) completion(w http.ResponseWriter, r *http.Request) {
-	var req CompletionRequest
-	req.Options = Options(api.DefaultOptions())
+	var req llm.CompletionRequest
 	if err := json.NewDecoder(r.Body).Decode(&req); err != nil {
 		http.Error(w, "Bad request", http.StatusBadRequest)
 		return
 	}
 
+	if req.Options == nil {
+		opts := api.DefaultOptions()
+		req.Options = &opts
+	}
+
 	// Set the headers to indicate streaming
 	w.Header().Set("Content-Type", "application/json")
 	w.Header().Set("Transfer-Encoding", "chunked")
@@ -620,26 +564,28 @@ func (s *Server) completion(w http.ResponseWriter, r *http.Request) {
 		return
 	}
 
-	var samplingParams llama.SamplingParams
-	samplingParams.TopK = req.TopK
-	samplingParams.TopP = req.TopP
-	samplingParams.MinP = req.MinP
-	samplingParams.TypicalP = req.TypicalP
-	samplingParams.Temp = req.Temperature
-	samplingParams.RepeatLastN = req.RepeatLastN
-	samplingParams.PenaltyRepeat = req.RepeatPenalty
-	samplingParams.PenaltyFreq = req.FrequencyPenalty
-	samplingParams.PenaltyPresent = req.PresencePenalty
-	samplingParams.Mirostat = req.Mirostat
-	samplingParams.MirostatTau = req.MirostatTau
-	samplingParams.MirostatEta = req.MirostatEta
-	samplingParams.Seed = uint32(req.Seed)
-	samplingParams.Grammar = req.Grammar
+	// Extract options from the CompletionRequest
+	samplingParams := llama.SamplingParams{
+		TopK:           req.Options.TopK,
+		TopP:           req.Options.TopP,
+		MinP:           req.Options.MinP,
+		TypicalP:       req.Options.TypicalP,
+		Temp:           req.Options.Temperature,
+		RepeatLastN:    req.Options.RepeatLastN,
+		PenaltyRepeat:  req.Options.RepeatPenalty,
+		PenaltyFreq:    req.Options.FrequencyPenalty,
+		PenaltyPresent: req.Options.PresencePenalty,
+		Mirostat:       req.Options.Mirostat,
+		MirostatTau:    req.Options.MirostatTau,
+		MirostatEta:    req.Options.MirostatEta,
+		Seed:           uint32(req.Options.Seed),
+		Grammar:        req.Grammar,
+	}
 
 	seq, err := s.NewSequence(req.Prompt, req.Images, NewSequenceParams{
-		numPredict:     req.NumPredict,
-		stop:           req.Stop,
-		numKeep:        req.NumKeep,
+		numPredict:     req.Options.NumPredict,
+		stop:           req.Options.Stop,
+		numKeep:        req.Options.NumKeep,
 		samplingParams: &samplingParams,
 		embedding:      false,
 	})
@@ -662,7 +608,7 @@ func (s *Server) completion(w http.ResponseWriter, r *http.Request) {
 	found := false
 	for i, sq := range s.seqs {
 		if sq == nil {
-			seq.cache, seq.inputs, err = s.cache.LoadCacheSlot(seq.inputs, req.CachePrompt)
+			seq.cache, seq.inputs, err = s.cache.LoadCacheSlot(seq.inputs, true)
 			if err != nil {
 				s.mu.Unlock()
 				http.Error(w, fmt.Sprintf("Failed to load cache: %v", err), http.StatusInternalServerError)
@@ -691,7 +637,7 @@ func (s *Server) completion(w http.ResponseWriter, r *http.Request) {
 			return
 		case content, ok := <-seq.responses:
 			if ok {
-				if err := json.NewEncoder(w).Encode(&CompletionResponse{
+				if err := json.NewEncoder(w).Encode(&llm.CompletionResponse{
 					Content: content,
 				}); err != nil {
 					http.Error(w, fmt.Sprintf("failed to encode response: %v", err), http.StatusInternalServerError)
@@ -702,15 +648,17 @@ func (s *Server) completion(w http.ResponseWriter, r *http.Request) {
 				flusher.Flush()
 			} else {
 				// Send the final response
-				if err := json.NewEncoder(w).Encode(&CompletionResponse{
-					Stop:         true,
-					StoppedLimit: seq.doneReason == "limit",
-					Timings: Timings{
-						PromptN:     seq.numPromptInputs,
-						PromptMS:    float64(seq.startGenerationTime.Sub(seq.startProcessingTime).Milliseconds()),
-						PredictedN:  seq.numDecoded,
-						PredictedMS: float64(time.Since(seq.startGenerationTime).Milliseconds()),
-					},
+				doneReason := "stop"
+				if seq.doneReason == "limit" {
+					doneReason = "length"
+				}
+				if err := json.NewEncoder(w).Encode(&llm.CompletionResponse{
+					Done:               true,
+					DoneReason:         doneReason,
+					PromptEvalCount:    seq.numPromptInputs,
+					PromptEvalDuration: seq.startGenerationTime.Sub(seq.startProcessingTime),
+					EvalCount:          seq.numDecoded,
+					EvalDuration:       time.Since(seq.startGenerationTime),
 				}); err != nil {
 					http.Error(w, fmt.Sprintf("failed to encode final response: %v", err), http.StatusInternalServerError)
 				}
@@ -721,17 +669,8 @@ func (s *Server) completion(w http.ResponseWriter, r *http.Request) {
 	}
 }
 
-type EmbeddingRequest struct {
-	Content     string `json:"content"`
-	CachePrompt bool   `json:"cache_prompt"`
-}
-
-type EmbeddingResponse struct {
-	Embedding []float32 `json:"embedding"`
-}
-
 func (s *Server) embeddings(w http.ResponseWriter, r *http.Request) {
-	var req EmbeddingRequest
+	var req llm.EmbeddingRequest
 	if err := json.NewDecoder(r.Body).Decode(&req); err != nil {
 		http.Error(w, fmt.Sprintf("bad request: %s", err), http.StatusBadRequest)
 		return
@@ -761,7 +700,7 @@ func (s *Server) embeddings(w http.ResponseWriter, r *http.Request) {
 	found := false
 	for i, sq := range s.seqs {
 		if sq == nil {
-			seq.cache, seq.inputs, err = s.cache.LoadCacheSlot(seq.inputs, req.CachePrompt)
+			seq.cache, seq.inputs, err = s.cache.LoadCacheSlot(seq.inputs, false)
 			if err != nil {
 				s.mu.Unlock()
 				http.Error(w, fmt.Sprintf("Failed to load cache: %v", err), http.StatusInternalServerError)
@@ -782,41 +721,17 @@ func (s *Server) embeddings(w http.ResponseWriter, r *http.Request) {
 
 	embedding := <-seq.embedding
 
-	if err := json.NewEncoder(w).Encode(&EmbeddingResponse{
+	if err := json.NewEncoder(w).Encode(&llm.EmbeddingResponse{
 		Embedding: embedding,
 	}); err != nil {
 		http.Error(w, fmt.Sprintf("failed to encode response: %v", err), http.StatusInternalServerError)
 	}
 }
 
-type HealthResponse struct {
-	Status   string  `json:"status"`
-	Progress float32 `json:"progress"`
-}
-
-type ServerStatus int
-
-const (
-	ServerStatusReady ServerStatus = iota
-	ServerStatusLoadingModel
-	ServerStatusError
-)
-
-func (s ServerStatus) ToString() string {
-	switch s {
-	case ServerStatusReady:
-		return "ok"
-	case ServerStatusLoadingModel:
-		return "loading model"
-	default:
-		return "server error"
-	}
-}
-
 func (s *Server) health(w http.ResponseWriter, r *http.Request) {
 	w.Header().Set("Content-Type", "application/json")
-	if err := json.NewEncoder(w).Encode(&HealthResponse{
-		Status:   s.status.ToString(),
+	if err := json.NewEncoder(w).Encode(&llm.ServerStatusResponse{
+		Status:   s.status,
 		Progress: s.progress,
 	}); err != nil {
 		http.Error(w, fmt.Sprintf("failed to encode response: %v", err), http.StatusInternalServerError)
@@ -879,7 +794,7 @@ func (s *Server) loadModel(
 		panic(err)
 	}
 
-	s.status = ServerStatusReady
+	s.status = llm.ServerStatusReady
 	s.ready.Done()
 }
 
@@ -937,7 +852,7 @@ func Execute(args []string) error {
 		parallel:  *parallel,
 		seqs:      make([]*Sequence, *parallel),
 		seqsSem:   semaphore.NewWeighted(int64(*parallel)),
-		status:    ServerStatusLoadingModel,
+		status:    llm.ServerStatusLoadingModel,
 	}
 
 	var tensorSplitFloats []float32
diff --git a/runner/ollamarunner/cache.go b/runner/ollamarunner/cache.go
index a411fddb..adcb3f73 100644
--- a/runner/ollamarunner/cache.go
+++ b/runner/ollamarunner/cache.go
@@ -107,6 +107,7 @@ func (c *InputCache) LoadCacheSlot(prompt []input.Input, cachePrompt bool) (*Inp
 		return nil, nil, err
 	}
 
+	// TODO (brucemacd): cachePrompt is always true for completion, but false for embedding, can this be improved?
 	if !cachePrompt {
 		numPast = 0
 	}
diff --git a/runner/ollamarunner/runner.go b/runner/ollamarunner/runner.go
index c380ef22..d6339a61 100644
--- a/runner/ollamarunner/runner.go
+++ b/runner/ollamarunner/runner.go
@@ -24,6 +24,7 @@ import (
 	"golang.org/x/sync/semaphore"
 
 	"github.com/ollama/ollama/api"
+	"github.com/ollama/ollama/llm"
 	"github.com/ollama/ollama/ml"
 	"github.com/ollama/ollama/model"
 	"github.com/ollama/ollama/model/input"
@@ -94,7 +95,7 @@ type NewSequenceParams struct {
 	embedding  bool
 }
 
-func (s *Server) NewSequence(prompt string, images []ImageData, params NewSequenceParams) (*Sequence, error) {
+func (s *Server) NewSequence(prompt string, images []llm.ImageData, params NewSequenceParams) (*Sequence, error) {
 	s.ready.Wait()
 
 	startTime := time.Now()
@@ -145,7 +146,7 @@ func (s *Server) NewSequence(prompt string, images []ImageData, params NewSequen
 // inputs processes the prompt and images into a list of inputs
 // by splitting the prompt on [img-<n>] tags, tokenizing text and
 // decoding images
-func (s *Server) inputs(ctx ml.Context, prompt string, images []ImageData) ([]input.Input, error) {
+func (s *Server) inputs(ctx ml.Context, prompt string, images []llm.ImageData) ([]input.Input, error) {
 	var inputs []input.Input
 	var parts []string
 	var matches [][]string
@@ -222,7 +223,7 @@ type Server struct {
 	model model.Model
 
 	// status for external health reporting - loading, ready to serve, etc.
-	status ServerStatus
+	status llm.ServerStatus
 
 	// current progress on loading the model
 	progress float32
@@ -501,75 +502,18 @@ func (s *Server) processBatch() error {
 	return nil
 }
 
-// TODO (jmorganca): use structs from the api package to avoid duplication
-// this way the api acts as a proxy instead of using a different api for the
-// runner
-type Options struct {
-	api.Runner
-
-	NumKeep          int      `json:"n_keep"`
-	Seed             int      `json:"seed"`
-	NumPredict       int      `json:"n_predict"`
-	TopK             int      `json:"top_k"`
-	TopP             float32  `json:"top_p"`
-	MinP             float32  `json:"min_p"`
-	TypicalP         float32  `json:"typical_p"`
-	RepeatLastN      int      `json:"repeat_last_n"`
-	Temperature      float32  `json:"temperature"`
-	RepeatPenalty    float32  `json:"repeat_penalty"`
-	PresencePenalty  float32  `json:"presence_penalty"`
-	FrequencyPenalty float32  `json:"frequency_penalty"`
-	Mirostat         int      `json:"mirostat"`
-	MirostatTau      float32  `json:"mirostat_tau"`
-	MirostatEta      float32  `json:"mirostat_eta"`
-	Stop             []string `json:"stop"`
-}
-
-type ImageData struct {
-	Data          []byte `json:"data"`
-	ID            int    `json:"id"`
-	AspectRatioID int    `json:"aspect_ratio_id"`
-}
-
-type CompletionRequest struct {
-	Prompt      string      `json:"prompt"`
-	Images      []ImageData `json:"image_data"`
-	Grammar     string      `json:"grammar"`
-	CachePrompt bool        `json:"cache_prompt"`
-
-	Options
-}
-
-type Timings struct {
-	PredictedN  int     `json:"predicted_n"`
-	PredictedMS float64 `json:"predicted_ms"`
-	PromptN     int     `json:"prompt_n"`
-	PromptMS    float64 `json:"prompt_ms"`
-}
-
-type CompletionResponse struct {
-	Content string `json:"content"`
-	Stop    bool   `json:"stop"`
-
-	Model        string  `json:"model,omitempty"`
-	Prompt       string  `json:"prompt,omitempty"`
-	StoppedLimit bool    `json:"stopped_limit,omitempty"`
-	PredictedN   int     `json:"predicted_n,omitempty"`
-	PredictedMS  float64 `json:"predicted_ms,omitempty"`
-	PromptN      int     `json:"prompt_n,omitempty"`
-	PromptMS     float64 `json:"prompt_ms,omitempty"`
-
-	Timings Timings `json:"timings"`
-}
-
 func (s *Server) completion(w http.ResponseWriter, r *http.Request) {
-	var req CompletionRequest
-	req.Options = Options(api.DefaultOptions())
+	var req llm.CompletionRequest
 	if err := json.NewDecoder(r.Body).Decode(&req); err != nil {
 		http.Error(w, "Bad request", http.StatusBadRequest)
 		return
 	}
 
+	if req.Options == nil {
+		opts := api.DefaultOptions()
+		req.Options = &opts
+	}
+
 	// Set the headers to indicate streaming
 	w.Header().Set("Content-Type", "application/json")
 	w.Header().Set("Transfer-Encoding", "chunked")
@@ -591,18 +535,18 @@ func (s *Server) completion(w http.ResponseWriter, r *http.Request) {
 	}
 
 	sampler := sample.NewSampler(
-		req.Temperature,
-		req.TopK,
-		req.TopP,
-		req.MinP,
-		req.Seed,
+		req.Options.Temperature,
+		req.Options.TopK,
+		req.Options.TopP,
+		req.Options.MinP,
+		req.Options.Seed,
 		grammar,
 	)
 
 	seq, err := s.NewSequence(req.Prompt, req.Images, NewSequenceParams{
-		numPredict: req.NumPredict,
-		stop:       req.Stop,
-		numKeep:    int32(req.NumKeep),
+		numPredict: req.Options.NumPredict,
+		stop:       req.Options.Stop,
+		numKeep:    int32(req.Options.NumKeep),
 		sampler:    sampler,
 		embedding:  false,
 	})
@@ -625,7 +569,7 @@ func (s *Server) completion(w http.ResponseWriter, r *http.Request) {
 	found := false
 	for i, sq := range s.seqs {
 		if sq == nil {
-			seq.cache, seq.inputs, err = s.cache.LoadCacheSlot(seq.inputs, req.CachePrompt)
+			seq.cache, seq.inputs, err = s.cache.LoadCacheSlot(seq.inputs, true)
 			if err != nil {
 				s.mu.Unlock()
 				http.Error(w, fmt.Sprintf("Failed to load cache: %v", err), http.StatusInternalServerError)
@@ -652,7 +596,7 @@ func (s *Server) completion(w http.ResponseWriter, r *http.Request) {
 			return
 		case content, ok := <-seq.responses:
 			if ok {
-				if err := json.NewEncoder(w).Encode(&CompletionResponse{
+				if err := json.NewEncoder(w).Encode(&llm.CompletionResponse{
 					Content: content,
 				}); err != nil {
 					http.Error(w, fmt.Sprintf("failed to encode response: %v", err), http.StatusInternalServerError)
@@ -663,15 +607,17 @@ func (s *Server) completion(w http.ResponseWriter, r *http.Request) {
 				flusher.Flush()
 			} else {
 				// Send the final response
-				if err := json.NewEncoder(w).Encode(&CompletionResponse{
-					Stop:         true,
-					StoppedLimit: seq.doneReason == "limit",
-					Timings: Timings{
-						PromptN:     seq.numPromptInputs,
-						PromptMS:    float64(seq.startGenerationTime.Sub(seq.startProcessingTime).Milliseconds()),
-						PredictedN:  seq.numPredicted,
-						PredictedMS: float64(time.Since(seq.startGenerationTime).Milliseconds()),
-					},
+				doneReason := "stop"
+				if seq.doneReason == "limit" {
+					doneReason = "length"
+				}
+				if err := json.NewEncoder(w).Encode(&llm.CompletionResponse{
+					Done:               true,
+					DoneReason:         doneReason,
+					PromptEvalCount:    seq.numPromptInputs,
+					PromptEvalDuration: seq.startGenerationTime.Sub(seq.startProcessingTime),
+					EvalCount:          seq.numPredicted,
+					EvalDuration:       time.Since(seq.startGenerationTime),
 				}); err != nil {
 					http.Error(w, fmt.Sprintf("failed to encode final response: %v", err), http.StatusInternalServerError)
 				}
@@ -682,43 +628,10 @@ func (s *Server) completion(w http.ResponseWriter, r *http.Request) {
 	}
 }
 
-type EmbeddingRequest struct {
-	Content     string `json:"content"`
-	CachePrompt bool   `json:"cache_prompt"`
-}
-
-type EmbeddingResponse struct {
-	Embedding []float32 `json:"embedding"`
-}
-
-type HealthResponse struct {
-	Status   string  `json:"status"`
-	Progress float32 `json:"progress"`
-}
-
-type ServerStatus int
-
-const (
-	ServerStatusReady ServerStatus = iota
-	ServerStatusLoadingModel
-	ServerStatusError
-)
-
-func (s ServerStatus) ToString() string {
-	switch s {
-	case ServerStatusReady:
-		return "ok"
-	case ServerStatusLoadingModel:
-		return "loading model"
-	default:
-		return "server error"
-	}
-}
-
 func (s *Server) health(w http.ResponseWriter, r *http.Request) {
 	w.Header().Set("Content-Type", "application/json")
-	if err := json.NewEncoder(w).Encode(&HealthResponse{
-		Status:   s.status.ToString(),
+	if err := json.NewEncoder(w).Encode(&llm.ServerStatusResponse{
+		Status:   s.status,
 		Progress: s.progress,
 	}); err != nil {
 		http.Error(w, fmt.Sprintf("failed to encode response: %v", err), http.StatusInternalServerError)
@@ -772,7 +685,7 @@ func (s *Server) loadModel(
 	s.seqs = make([]*Sequence, s.parallel)
 	s.seqsSem = semaphore.NewWeighted(int64(s.parallel))
 
-	s.status = ServerStatusReady
+	s.status = llm.ServerStatusReady
 	s.ready.Done()
 }
 
@@ -824,7 +737,7 @@ func Execute(args []string) error {
 
 	server := &Server{
 		batchSize: *batchSize,
-		status:    ServerStatusLoadingModel,
+		status:    llm.ServerStatusLoadingModel,
 	}
 
 	// TODO(jessegross): Parameters that need to be implemented:

From 9679f40146ed7e148a64abb14c7c619b162c1875 Mon Sep 17 00:00:00 2001
From: Jesse Gross <jesse@ollama.com>
Date: Wed, 12 Mar 2025 16:56:11 -0700
Subject: [PATCH 093/157] ml: Allow models to constrain inputs to a single
 batch

Models may require that a set of inputs all be processed as part
of the same batch. For example, if an image has multiple patches
with fully connected attention between them, we should not split
the batch in the middle of an image.

Fixes #9697
---
 integration/llm_image_test.go     | 29 +++++++++++++++++
 model/input/input.go              |  6 ++++
 model/models/gemma3/model.go      | 30 +++++------------
 model/models/gemma3/model_text.go | 53 ++++++-------------------------
 runner/ollamarunner/runner.go     | 12 ++++++-
 5 files changed, 64 insertions(+), 66 deletions(-)

diff --git a/integration/llm_image_test.go b/integration/llm_image_test.go
index c7b56890..fbbd9d5c 100644
--- a/integration/llm_image_test.go
+++ b/integration/llm_image_test.go
@@ -66,6 +66,35 @@ func TestIntegrationMllama(t *testing.T) {
 	DoGenerate(ctx, t, client, req, []string{resp}, 240*time.Second, 30*time.Second)
 }
 
+func TestIntegrationSplitBatch(t *testing.T) {
+	image, err := base64.StdEncoding.DecodeString(imageEncoding)
+	require.NoError(t, err)
+	req := api.GenerateRequest{
+		Model: "gemma3:4b",
+		// Fill up a chunk of the batch so the image will partially spill over into the next one
+		System: "Lorem ipsum dolor sit amet, consectetur adipiscing elit. Sed aliquet, justo in malesuada lobortis, odio ligula volutpat quam, quis faucibus ipsum magna quis sapien. Aliquam in venenatis diam, eu viverra magna. Phasellus imperdiet hendrerit volutpat. Vivamus sem ex, facilisis placerat felis non, dictum elementum est. Phasellus aliquam imperdiet lacus, eget placerat ligula sodales vel. Pellentesque nec auctor mi. Curabitur arcu nisi, faucibus eget nunc id, viverra interdum mi. Curabitur ornare ipsum ex, ac euismod ex aliquam in. Vestibulum id magna at purus accumsan fermentum. Proin scelerisque posuere nunc quis interdum. Maecenas sed mollis nisl. Etiam vitae ipsum interdum, placerat est quis, tincidunt velit. Nullam tempor nibh non lorem volutpat efficitur. Cras laoreet diam imperdiet ipsum auctor bibendum. Suspendisse ultrices urna sed metus sagittis suscipit. Quisque ullamcorper aliquam nibh ut mollis. Aenean dapibus mauris pharetra, venenatis elit ac, hendrerit odio. Cras vestibulum erat tempor, lobortis justo eu, lobortis ipsum. Nam laoreet dapibus sem. Proin vel diam ultrices, elementum ante et, ornare lectus. Proin eu accumsan nisl. Praesent ac ex vitae ipsum vulputate tristique facilisis sit amet lacus. Nullam faucibus magna a pellentesque pretium. Nunc lacinia ullamcorper sollicitudin. Donec vitae accumsan turpis, sed porttitor est. Donec porttitor mi vitae augue faucibus, vel mollis diam tincidunt.",
+		Prompt: "what does the text in this image say?",
+		Stream: &stream,
+		Options: map[string]interface{}{
+			"seed":        42,
+			"temperature": 0.0,
+		},
+		Images: []api.ImageData{
+			image,
+		},
+	}
+
+	// Note: sometimes it returns "the ollamas" sometimes "the ollams"
+	resp := "the ollam"
+	ctx, cancel := context.WithTimeout(context.Background(), 3*time.Minute)
+	defer cancel()
+	client, _, cleanup := InitServerConnection(ctx, t)
+	defer cleanup()
+	require.NoError(t, PullIfMissing(ctx, client, req.Model))
+	// llava models on CPU can be quite slow to start,
+	DoGenerate(ctx, t, client, req, []string{resp}, 120*time.Second, 30*time.Second)
+}
+
 const imageEncoding = `iVBORw0KGgoAAAANSUhEUgAAANIAAAB4CAYAAACHHqzKAAAAAXNSR0IArs4c6QAAAIRlWElmTU0AKgAAAAgABQESAAMAAAABAAEAAAEaAAUAAAABAAAASgEb
 AAUAAAABAAAAUgEoAAMAAAABAAIAAIdpAAQAAAABAAAAWgAAAAAAAABIAAAAAQAAAEgAAAABAAOgAQADAAAAAQABAACgAgAEAAAAAQAAANKgAwAEAAAAAQAA
 AHgAAAAAXdsepgAAAAlwSFlzAAALEwAACxMBAJqcGAAAAVlpVFh0WE1MOmNvbS5hZG9iZS54bXAAAAAAADx4OnhtcG1ldGEgeG1sbnM6eD0iYWRvYmU6bnM6
diff --git a/model/input/input.go b/model/input/input.go
index 0cb3f3f4..30bdcf06 100644
--- a/model/input/input.go
+++ b/model/input/input.go
@@ -15,6 +15,12 @@ type Input struct {
 	// stored in Multimodal, used for caching and comparing
 	// equality.
 	MultimodalHash uint64
+
+	// SameBatch forces the following number of tokens to be processed
+	// in a single batch, breaking and extending batches as needed.
+	// Useful for things like images that must be processed in one
+	// shot.
+	SameBatch int
 }
 
 // MultimodalIndex is a multimodal element (such as an image)
diff --git a/model/models/gemma3/model.go b/model/models/gemma3/model.go
index 24193f15..ccc7567c 100644
--- a/model/models/gemma3/model.go
+++ b/model/models/gemma3/model.go
@@ -2,10 +2,9 @@ package gemma3
 
 import (
 	"bytes"
-	"encoding/binary"
-	"hash/fnv"
 	"image"
 	"math"
+	"slices"
 
 	"github.com/ollama/ollama/kvcache"
 	"github.com/ollama/ollama/ml"
@@ -112,36 +111,23 @@ func (m *Model) EncodeMultimodal(ctx ml.Context, multimodalData []byte) (any, er
 	return visionOutputs, nil
 }
 
-type imageToken struct {
-	embedding ml.Tensor
-	index     int
-}
-
 func (m *Model) PostTokenize(ctx ml.Context, inputs []input.Input) ([]input.Input, error) {
 	var result []input.Input
-	fnvHash := fnv.New64a()
 
 	for _, inp := range inputs {
 		if inp.Multimodal == nil {
 			result = append(result, inp)
 		} else {
-			imageInputs := []input.Input{
-				{Token: 108},    // "\n\n"
-				{Token: 255999}, // "<start_of_image>""
-			}
-			result = append(result, imageInputs...)
-
-			// add image embeddings
 			inputMultimodal := inp.Multimodal.(ml.Tensor)
 
-			for i := range inputMultimodal.Dim(1) {
-				fnvHash.Reset()
-				binary.Write(fnvHash, binary.NativeEndian, inp.MultimodalHash)
-				fnvHash.Write([]byte{byte(i)})
+			result = append(result,
+				input.Input{Token: 108, SameBatch: inputMultimodal.Dim(1) + 3},               // "\n\n"
+				input.Input{Token: 255999},                                                   // "<start_of_image>""
+				input.Input{Multimodal: inputMultimodal, MultimodalHash: inp.MultimodalHash}, // image data is on the first placeholder
+			)
 
-				imageToken := imageToken{embedding: inputMultimodal, index: i}
-				result = append(result, input.Input{Multimodal: imageToken, MultimodalHash: fnvHash.Sum64()})
-			}
+			// add image token placeholders
+			result = append(result, slices.Repeat([]input.Input{{Token: 0}}, inputMultimodal.Dim(1)-1)...)
 
 			result = append(result,
 				input.Input{Token: 256000}, // <end_of_image>
diff --git a/model/models/gemma3/model_text.go b/model/models/gemma3/model_text.go
index 7a88c092..567f65a5 100644
--- a/model/models/gemma3/model_text.go
+++ b/model/models/gemma3/model_text.go
@@ -171,53 +171,20 @@ func (l *TextLayer) Forward(ctx ml.Context, layer int, hiddenState, positionIDs,
 	return hiddenState.Add(ctx, residual)
 }
 
-func setImageEmbeddings(ctx ml.Context, hiddenState ml.Tensor, multimodal []input.MultimodalIndex) []int {
-	var embedding ml.Tensor
-	var src, dst, length int
-	var except []int
-
-	for _, image := range multimodal {
-		imageToken := image.Multimodal.(imageToken)
-		imageSrc := imageToken.index
-		imageDst := image.Index
-
-		if embedding == nil {
-			embedding = imageToken.embedding
-			src = imageSrc
-			dst = imageDst
-			length = 1
-		} else if embedding == imageToken.embedding && imageSrc+1 == src && imageDst+1 == dst {
-			src = imageSrc
-			dst = imageDst
-			length++
-		} else if embedding == imageToken.embedding && src+length == imageSrc && dst+length == imageDst {
-			length++
-		} else {
-			visionOutputs := embedding.View(ctx, src*embedding.Stride(1), length*embedding.Dim(0))
-			ctx.Forward(visionOutputs.Copy(ctx, hiddenState.View(ctx, dst*hiddenState.Stride(1), length*hiddenState.Dim(0))))
-
-			embedding = imageToken.embedding
-			src = imageSrc
-			dst = imageDst
-			length = 1
-		}
-
-		except = append(except, imageDst)
-	}
-
-	if embedding != nil {
-		visionOutputs := embedding.View(ctx, src*embedding.Stride(1), length*embedding.Dim(0))
-		ctx.Forward(visionOutputs.Copy(ctx, hiddenState.View(ctx, dst*hiddenState.Stride(1), length*hiddenState.Dim(0))))
-	}
-
-	return except
-}
-
 func (m *TextModel) Forward(ctx ml.Context, inputs, positions, outputs ml.Tensor, opts input.Options, cache kvcache.Cache) ml.Tensor {
 	hiddenState := m.TokenEmbedding.Forward(ctx, inputs)
 	hiddenState = hiddenState.Scale(ctx, math.Sqrt(float64(m.TextOptions.hiddenSize)))
 
-	except := setImageEmbeddings(ctx, hiddenState, opts.Multimodal)
+	// set image embeddings
+	var except []int
+	for _, image := range opts.Multimodal {
+		visionOutputs := image.Multimodal.(ml.Tensor)
+		ctx.Forward(visionOutputs.Copy(ctx, hiddenState.View(ctx, image.Index*hiddenState.Stride(1), visionOutputs.Dim(0)*visionOutputs.Dim(1))))
+
+		for i := range visionOutputs.Dim(1) {
+			except = append(except, image.Index+i)
+		}
+	}
 
 	for i, layer := range m.Layers {
 		// gemma alternates between the sliding window (local) and causal (global)
diff --git a/runner/ollamarunner/runner.go b/runner/ollamarunner/runner.go
index d6339a61..916ad45d 100644
--- a/runner/ollamarunner/runner.go
+++ b/runner/ollamarunner/runner.go
@@ -352,6 +352,8 @@ func (s *Server) processBatch() error {
 			seq.cache.Inputs = []input.Input{}
 		}
 
+		batchSize := s.batchSize
+
 		for j, inp := range seq.inputs {
 			if int32(len(seq.cache.Inputs)+len(seq.pendingInputs)+1) > s.cache.numCtx {
 				if len(seq.pendingInputs) == 0 {
@@ -364,7 +366,15 @@ func (s *Server) processBatch() error {
 				}
 			}
 
-			if j >= s.batchSize {
+			// If we are required to put following inputs into a single batch then extend the
+			// batch size. Since we are only extending the size the minimum amount possible, this
+			// will cause a break if we have pending inputs.
+			minBatch := 1 + inp.SameBatch
+			if minBatch > batchSize {
+				batchSize = minBatch
+			}
+
+			if len(seq.pendingInputs)+minBatch > batchSize {
 				break
 			}
 

From 282bfaaa957fff8402eb7a4b1657f57c49939604 Mon Sep 17 00:00:00 2001
From: Jesse Gross <jesse@ollama.com>
Date: Thu, 13 Mar 2025 20:32:50 -0700
Subject: [PATCH 094/157] ollamarunner: Use a separate context per multimodal
 input

Currently there is a single context per sequence, shared all by
all multimodal inputs. Since we build a vision encoder graph per
image, with a large number of inputs we can eventually hit the
maximum number of graph nodes per context.

This changes to use a separate context for each image, ensuring
that available resource limits are consistent.
---
 model/model.go                |  2 +-
 model/models/gemma3/model.go  |  2 +-
 model/models/mllama/model.go  | 11 +++++++----
 runner/ollamarunner/runner.go | 37 +++++++++++++++++++++++------------
 4 files changed, 33 insertions(+), 19 deletions(-)

diff --git a/model/model.go b/model/model.go
index fadea324..53e47add 100644
--- a/model/model.go
+++ b/model/model.go
@@ -60,7 +60,7 @@ type MultimodalProcessor interface {
 	// This function is also responsible for updating MultimodalHash for any Multimodal
 	// that is modified to ensure that there is a unique hash value that accurately
 	// represents the contents.
-	PostTokenize(ml.Context, []input.Input) ([]input.Input, error)
+	PostTokenize([]input.Input) ([]input.Input, error)
 }
 
 // Base implements the common fields and methods for all models
diff --git a/model/models/gemma3/model.go b/model/models/gemma3/model.go
index ccc7567c..32ad80f4 100644
--- a/model/models/gemma3/model.go
+++ b/model/models/gemma3/model.go
@@ -111,7 +111,7 @@ func (m *Model) EncodeMultimodal(ctx ml.Context, multimodalData []byte) (any, er
 	return visionOutputs, nil
 }
 
-func (m *Model) PostTokenize(ctx ml.Context, inputs []input.Input) ([]input.Input, error) {
+func (m *Model) PostTokenize(inputs []input.Input) ([]input.Input, error) {
 	var result []input.Input
 
 	for _, inp := range inputs {
diff --git a/model/models/mllama/model.go b/model/models/mllama/model.go
index 071d77ac..fa4d570c 100644
--- a/model/models/mllama/model.go
+++ b/model/models/mllama/model.go
@@ -106,17 +106,17 @@ func (m *Model) EncodeMultimodal(ctx ml.Context, multimodalData []byte) (any, er
 	return m.Projector.Forward(ctx, crossAttentionStates), nil
 }
 
-func (m *Model) PostTokenize(ctx ml.Context, inputs []input.Input) ([]input.Input, error) {
+func (m *Model) PostTokenize(inputs []input.Input) ([]input.Input, error) {
 	var images []input.Input
 	fnvHash := fnv.New64a()
 
 	for i := range inputs {
 		if inputs[i].Multimodal == nil {
 			if len(images) > 0 {
-				inputs[i].Multimodal = images[0].Multimodal
+				inputs[i].Multimodal = []ml.Tensor{images[0].Multimodal.(ml.Tensor)}
 				inputs[i].MultimodalHash = images[0].MultimodalHash
 				for j := 1; j < len(images); j++ {
-					inputs[i].Multimodal = inputs[i].Multimodal.(ml.Tensor).Concat(ctx, images[j].Multimodal.(ml.Tensor), 3)
+					inputs[i].Multimodal = append(inputs[i].Multimodal.([]ml.Tensor), images[0].Multimodal.(ml.Tensor))
 					fnvHash.Reset()
 					binary.Write(fnvHash, binary.NativeEndian, inputs[i].MultimodalHash)
 					binary.Write(fnvHash, binary.NativeEndian, inputs[j].MultimodalHash)
@@ -138,7 +138,10 @@ func (m *Model) PostTokenize(ctx ml.Context, inputs []input.Input) ([]input.Inpu
 func (m *Model) Forward(ctx ml.Context, opts input.Options) (ml.Tensor, error) {
 	var crossAttentionStates ml.Tensor
 	if len(opts.Multimodal) > 0 {
-		crossAttentionStates = opts.Multimodal[len(opts.Multimodal)-1].Multimodal.(ml.Tensor)
+		images := opts.Multimodal[len(opts.Multimodal)-1].Multimodal.([]ml.Tensor)
+		if len(images) > 0 {
+			crossAttentionStates = images[len(images)-1]
+		}
 	}
 
 	inputs, err := ctx.Input().FromIntSlice(opts.Inputs, len(opts.Inputs))
diff --git a/runner/ollamarunner/runner.go b/runner/ollamarunner/runner.go
index 916ad45d..d4c24556 100644
--- a/runner/ollamarunner/runner.go
+++ b/runner/ollamarunner/runner.go
@@ -34,10 +34,14 @@ import (
 	_ "github.com/ollama/ollama/model/models"
 )
 
+type contextList struct {
+	list []ml.Context
+}
+
 type Sequence struct {
-	// ctx for allocating tensors that last the lifetime of the sequence, such as
+	// ctxs are used for allocating tensors that last the lifetime of the sequence, such as
 	// multimodal embeddings
-	ctx ml.Context
+	ctxs *contextList
 
 	// batch index
 	iBatch int
@@ -99,9 +103,8 @@ func (s *Server) NewSequence(prompt string, images []llm.ImageData, params NewSe
 	s.ready.Wait()
 
 	startTime := time.Now()
-	ctx := s.model.Backend().NewContext()
 
-	inputs, err := s.inputs(ctx, prompt, images)
+	inputs, ctxs, err := s.inputs(prompt, images)
 	if err != nil {
 		return nil, fmt.Errorf("failed to process inputs: %w", err)
 	} else if len(inputs) == 0 {
@@ -127,7 +130,7 @@ func (s *Server) NewSequence(prompt string, images []llm.ImageData, params NewSe
 	// TODO(jessegross): Ingest cached history for grammar
 
 	return &Sequence{
-		ctx:                 ctx,
+		ctxs:                ctxs,
 		inputs:              inputs,
 		numPromptInputs:     len(inputs),
 		startProcessingTime: startTime,
@@ -146,7 +149,7 @@ func (s *Server) NewSequence(prompt string, images []llm.ImageData, params NewSe
 // inputs processes the prompt and images into a list of inputs
 // by splitting the prompt on [img-<n>] tags, tokenizing text and
 // decoding images
-func (s *Server) inputs(ctx ml.Context, prompt string, images []llm.ImageData) ([]input.Input, error) {
+func (s *Server) inputs(prompt string, images []llm.ImageData) ([]input.Input, *contextList, error) {
 	var inputs []input.Input
 	var parts []string
 	var matches [][]string
@@ -161,12 +164,19 @@ func (s *Server) inputs(ctx ml.Context, prompt string, images []llm.ImageData) (
 		parts = []string{prompt}
 	}
 
+	var contexts contextList
+	runtime.AddCleanup(&contexts, func(ctxs []ml.Context) {
+		for _, ctx := range ctxs {
+			ctx.Close()
+		}
+	}, contexts.list)
+
 	postTokenize := false
 	for i, part := range parts {
 		// text - tokenize
 		tokens, err := s.model.(model.TextProcessor).Encode(part, i == 0)
 		if err != nil {
-			return nil, err
+			return nil, nil, err
 		}
 
 		for _, t := range tokens {
@@ -186,12 +196,14 @@ func (s *Server) inputs(ctx ml.Context, prompt string, images []llm.ImageData) (
 			}
 
 			if imageIndex < 0 {
-				return nil, fmt.Errorf("invalid image index: %d", n)
+				return nil, nil, fmt.Errorf("invalid image index: %d", n)
 			}
 
+			ctx := s.model.Backend().NewContext()
+			contexts.list = append(contexts.list, ctx)
 			imageEmbeddings, err := multimodalProcessor.EncodeMultimodal(ctx, images[imageIndex].Data)
 			if err != nil {
-				return nil, err
+				return nil, nil, err
 			}
 
 			s.multimodalHash.Reset()
@@ -205,13 +217,13 @@ func (s *Server) inputs(ctx ml.Context, prompt string, images []llm.ImageData) (
 
 	if visionModel && postTokenize {
 		var err error
-		inputs, err = multimodalProcessor.PostTokenize(ctx, inputs)
+		inputs, err = multimodalProcessor.PostTokenize(inputs)
 		if err != nil {
-			return nil, err
+			return nil, nil, err
 		}
 	}
 
-	return inputs, nil
+	return inputs, &contexts, nil
 }
 
 type Server struct {
@@ -306,7 +318,6 @@ func (s *Server) removeSequence(seqIndex int, reason string) {
 	close(seq.responses)
 	close(seq.embedding)
 	seq.cache.InUse = false
-	seq.ctx.Close()
 	s.seqs[seqIndex] = nil
 	s.seqsSem.Release(1)
 }

From 7bf793a6007ca11fae0180ea6f2ebd7258428bd4 Mon Sep 17 00:00:00 2001
From: Jesse Gross <jesse@ollama.com>
Date: Wed, 12 Mar 2025 16:59:23 -0700
Subject: [PATCH 095/157] gemma3: Allow multiple image in a single input

Previously processing multiple images in a batch would trigger
segfaults so sending images together was disabled as a way to
mitigate this. The trigger was processing one image on the CPU
and one on the GPU.

This can no longer happen:
 - The vision encoder is now on the GPU so both images would be
   processed on the GPU.
 - We require images to be fully contained in a batch and each
   image including its special tokens is over half the batch size.
   As a result, we will never get two images in the same batch.

Fixes #9731
---
 server/prompt.go | 12 +-----------
 1 file changed, 1 insertion(+), 11 deletions(-)

diff --git a/server/prompt.go b/server/prompt.go
index d053f2a8..5b5b958f 100644
--- a/server/prompt.go
+++ b/server/prompt.go
@@ -26,7 +26,6 @@ func chatPrompt(ctx context.Context, m *Model, tokenize tokenizeFunc, opts *api.
 	var system []api.Message
 
 	isMllama := checkMllamaModelFamily(m)
-	isGemma3 := checkGemma3ModelFamily(m)
 
 	var imageNumTokens int
 	// TODO: Ideally we would compute this from the projector metadata but some pieces are implementation dependent
@@ -41,7 +40,7 @@ func chatPrompt(ctx context.Context, m *Model, tokenize tokenizeFunc, opts *api.
 	n := len(msgs) - 1
 	// in reverse, find all messages that fit into context window
 	for i := n; i >= 0; i-- {
-		if (isMllama || isGemma3) && len(msgs[i].Images) > 1 {
+		if isMllama && len(msgs[i].Images) > 1 {
 			return "", nil, errTooManyImages
 		}
 
@@ -158,12 +157,3 @@ func checkMllamaModelFamily(m *Model) bool {
 	}
 	return false
 }
-
-func checkGemma3ModelFamily(m *Model) bool {
-	for _, arch := range m.Config.ModelFamilies {
-		if arch == "gemma3" {
-			return true
-		}
-	}
-	return false
-}

From 2d2247e59e3995c00bf6bdf9bd2713bdf01f6921 Mon Sep 17 00:00:00 2001
From: Daniel Hiltgen <dhiltgen@users.noreply.github.com>
Date: Fri, 14 Mar 2025 15:44:08 -0700
Subject: [PATCH 096/157] Align versions for local builds (#9635)

Darwin was using a different pattern for the version string
than linux or windows.
---
 scripts/build_darwin.sh | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/scripts/build_darwin.sh b/scripts/build_darwin.sh
index 76d0a6c2..616e8501 100755
--- a/scripts/build_darwin.sh
+++ b/scripts/build_darwin.sh
@@ -8,7 +8,7 @@ usage() {
     exit 1
 }
 
-export VERSION=${VERSION:-$(git describe --tags --dirty)}
+export VERSION=${VERSION:-$(git describe --tags --first-parent --abbrev=7 --long --dirty --always | sed -e "s/^v//g")}
 export GOFLAGS="'-ldflags=-w -s \"-X=github.com/ollama/ollama/version.Version=${VERSION#v}\" \"-X=github.com/ollama/ollama/server.mode=release\"'"
 export CGO_CPPFLAGS='-mmacosx-version-min=11.3'
 

From ef378ad673a3f01382add316835957b1d4184177 Mon Sep 17 00:00:00 2001
From: Patrick Devine <patrick@infrahq.com>
Date: Fri, 14 Mar 2025 17:41:07 -0700
Subject: [PATCH 097/157] gemma3 quantization (#9776)

---
 llama/llama.cpp/src/llama-arch.cpp           |  19 ++++
 llama/llama.cpp/src/llama-arch.h             |   1 +
 llama/llama.cpp/src/llama-model.cpp          |   7 ++
 llama/llama.cpp/src/llama-quant.cpp          |   9 ++
 llama/patches/0021-gemma3-quantization.patch | 113 +++++++++++++++++++
 5 files changed, 149 insertions(+)
 create mode 100644 llama/patches/0021-gemma3-quantization.patch

diff --git a/llama/llama.cpp/src/llama-arch.cpp b/llama/llama.cpp/src/llama-arch.cpp
index b6f20286..b443fcd3 100644
--- a/llama/llama.cpp/src/llama-arch.cpp
+++ b/llama/llama.cpp/src/llama-arch.cpp
@@ -37,6 +37,7 @@ static const std::map<llm_arch, const char *> LLM_ARCH_NAMES = {
     { LLM_ARCH_MINICPM3,         "minicpm3"         },
     { LLM_ARCH_GEMMA,            "gemma"            },
     { LLM_ARCH_GEMMA2,           "gemma2"           },
+    { LLM_ARCH_GEMMA3,           "gemma3"           },
     { LLM_ARCH_STARCODER2,       "starcoder2"       },
     { LLM_ARCH_MAMBA,            "mamba"            },
     { LLM_ARCH_XVERSE,           "xverse"           },
@@ -804,6 +805,24 @@ static const std::map<llm_arch, std::map<llm_tensor, const char *>> LLM_TENSOR_N
             { LLM_TENSOR_FFN_POST_NORM,   "blk.%d.post_ffw_norm" },
         },
     },
+    {
+        LLM_ARCH_GEMMA3,
+        {
+            { LLM_TENSOR_TOKEN_EMBD,      "token_embd" },
+            { LLM_TENSOR_OUTPUT_NORM,     "output_norm" },
+            { LLM_TENSOR_ATTN_NORM,       "blk.%d.attn_norm" },
+            { LLM_TENSOR_ATTN_Q,          "blk.%d.attn_q" },
+            { LLM_TENSOR_ATTN_K,          "blk.%d.attn_k" },
+            { LLM_TENSOR_ATTN_V,          "blk.%d.attn_v" },
+            { LLM_TENSOR_ATTN_OUT,        "blk.%d.attn_output" },
+            { LLM_TENSOR_ATTN_POST_NORM,  "blk.%d.post_attention_norm" },
+            { LLM_TENSOR_FFN_NORM,        "blk.%d.ffn_norm" },
+            { LLM_TENSOR_FFN_GATE,        "blk.%d.ffn_gate" },
+            { LLM_TENSOR_FFN_DOWN,        "blk.%d.ffn_down" },
+            { LLM_TENSOR_FFN_UP,          "blk.%d.ffn_up" },
+            { LLM_TENSOR_FFN_POST_NORM,   "blk.%d.post_ffw_norm" },
+        },
+    },
     {
         LLM_ARCH_STARCODER2,
         {
diff --git a/llama/llama.cpp/src/llama-arch.h b/llama/llama.cpp/src/llama-arch.h
index ec742224..aad92a5d 100644
--- a/llama/llama.cpp/src/llama-arch.h
+++ b/llama/llama.cpp/src/llama-arch.h
@@ -41,6 +41,7 @@ enum llm_arch {
     LLM_ARCH_MINICPM3,
     LLM_ARCH_GEMMA,
     LLM_ARCH_GEMMA2,
+    LLM_ARCH_GEMMA3,
     LLM_ARCH_STARCODER2,
     LLM_ARCH_MAMBA,
     LLM_ARCH_XVERSE,
diff --git a/llama/llama.cpp/src/llama-model.cpp b/llama/llama.cpp/src/llama-model.cpp
index ab1a07d1..70183041 100644
--- a/llama/llama.cpp/src/llama-model.cpp
+++ b/llama/llama.cpp/src/llama-model.cpp
@@ -878,6 +878,9 @@ void llama_model::load_hparams(llama_model_loader & ml) {
                     default: type = LLM_TYPE_UNKNOWN;
                }
             } break;
+        case LLM_ARCH_GEMMA3:
+            {
+            } break;
         case LLM_ARCH_STARCODER2:
             {
                 ml.get_key(LLM_KV_ATTENTION_LAYERNORM_EPS, hparams.f_norm_eps);
@@ -2537,6 +2540,9 @@ bool llama_model::load_tensors(llama_model_loader & ml) {
                         layer.ffn_post_norm = create_tensor(tn(LLM_TENSOR_FFN_POST_NORM, "weight", i), {n_embd}, 0);
                     }
                 } break;
+            case LLM_ARCH_GEMMA3:
+                {
+                } break;
             case LLM_ARCH_STARCODER2:
                 {
                     tok_embd = create_tensor(tn(LLM_TENSOR_TOKEN_EMBD, "weight"), {n_embd, n_vocab}, 0);
@@ -4029,6 +4035,7 @@ enum llama_rope_type llama_model_rope_type(const struct llama_model * model) {
         case LLM_ARCH_PHIMOE:
         case LLM_ARCH_GEMMA:
         case LLM_ARCH_GEMMA2:
+        case LLM_ARCH_GEMMA3:
         case LLM_ARCH_STARCODER2:
         case LLM_ARCH_OPENELM:
         case LLM_ARCH_GPTNEOX:
diff --git a/llama/llama.cpp/src/llama-quant.cpp b/llama/llama.cpp/src/llama-quant.cpp
index 6eb1da08..d2f3a510 100644
--- a/llama/llama.cpp/src/llama-quant.cpp
+++ b/llama/llama.cpp/src/llama-quant.cpp
@@ -737,6 +737,15 @@ static void llama_model_quantize_impl(const std::string & fname_inp, const std::
         // This used to be a regex, but <regex> has an extreme cost to compile times.
         bool quantize = name.rfind("weight") == name.size() - 6; // ends with 'weight'?
 
+        // don't quantize vision stuff
+        quantize &= name.find("v.blk.") == std::string::npos;
+
+        quantize &= name.find("mm.mm_input_projection.weight") == std::string::npos;
+        quantize &= name.find("mm.mm_soft_emb_norm.weight") == std::string::npos;
+        quantize &= name.find("v.patch_embedding.weight") == std::string::npos;
+        quantize &= name.find("v.position_embedding.weight") == std::string::npos;
+        quantize &= name.find("v.post_layernorm.weight") == std::string::npos;
+
         // quantize only 2D and 3D tensors (experts)
         quantize &= (ggml_n_dims(tensor) >= 2);
 
diff --git a/llama/patches/0021-gemma3-quantization.patch b/llama/patches/0021-gemma3-quantization.patch
new file mode 100644
index 00000000..4f6dbc11
--- /dev/null
+++ b/llama/patches/0021-gemma3-quantization.patch
@@ -0,0 +1,113 @@
+From 0000000000000000000000000000000000000000 Mon Sep 17 00:00:00 2001
+From: Patrick Devine <patrick@infrahq.com>
+Date: Fri, 14 Mar 2025 16:33:23 -0700
+Subject: [PATCH] gemma3 quantization
+
+---
+ src/llama-arch.cpp  | 19 +++++++++++++++++++
+ src/llama-arch.h    |  1 +
+ src/llama-model.cpp |  7 +++++++
+ src/llama-quant.cpp |  9 +++++++++
+ 4 files changed, 36 insertions(+)
+
+diff --git a/src/llama-arch.cpp b/src/llama-arch.cpp
+index b6f20286..b443fcd3 100644
+--- a/src/llama-arch.cpp
++++ b/src/llama-arch.cpp
+@@ -37,6 +37,7 @@ static const std::map<llm_arch, const char *> LLM_ARCH_NAMES = {
+     { LLM_ARCH_MINICPM3,         "minicpm3"         },
+     { LLM_ARCH_GEMMA,            "gemma"            },
+     { LLM_ARCH_GEMMA2,           "gemma2"           },
++    { LLM_ARCH_GEMMA3,           "gemma3"           },
+     { LLM_ARCH_STARCODER2,       "starcoder2"       },
+     { LLM_ARCH_MAMBA,            "mamba"            },
+     { LLM_ARCH_XVERSE,           "xverse"           },
+@@ -804,6 +805,24 @@ static const std::map<llm_arch, std::map<llm_tensor, const char *>> LLM_TENSOR_N
+             { LLM_TENSOR_FFN_POST_NORM,   "blk.%d.post_ffw_norm" },
+         },
+     },
++    {
++        LLM_ARCH_GEMMA3,
++        {
++            { LLM_TENSOR_TOKEN_EMBD,      "token_embd" },
++            { LLM_TENSOR_OUTPUT_NORM,     "output_norm" },
++            { LLM_TENSOR_ATTN_NORM,       "blk.%d.attn_norm" },
++            { LLM_TENSOR_ATTN_Q,          "blk.%d.attn_q" },
++            { LLM_TENSOR_ATTN_K,          "blk.%d.attn_k" },
++            { LLM_TENSOR_ATTN_V,          "blk.%d.attn_v" },
++            { LLM_TENSOR_ATTN_OUT,        "blk.%d.attn_output" },
++            { LLM_TENSOR_ATTN_POST_NORM,  "blk.%d.post_attention_norm" },
++            { LLM_TENSOR_FFN_NORM,        "blk.%d.ffn_norm" },
++            { LLM_TENSOR_FFN_GATE,        "blk.%d.ffn_gate" },
++            { LLM_TENSOR_FFN_DOWN,        "blk.%d.ffn_down" },
++            { LLM_TENSOR_FFN_UP,          "blk.%d.ffn_up" },
++            { LLM_TENSOR_FFN_POST_NORM,   "blk.%d.post_ffw_norm" },
++        },
++    },
+     {
+         LLM_ARCH_STARCODER2,
+         {
+diff --git a/src/llama-arch.h b/src/llama-arch.h
+index ec742224..aad92a5d 100644
+--- a/src/llama-arch.h
++++ b/src/llama-arch.h
+@@ -41,6 +41,7 @@ enum llm_arch {
+     LLM_ARCH_MINICPM3,
+     LLM_ARCH_GEMMA,
+     LLM_ARCH_GEMMA2,
++    LLM_ARCH_GEMMA3,
+     LLM_ARCH_STARCODER2,
+     LLM_ARCH_MAMBA,
+     LLM_ARCH_XVERSE,
+diff --git a/src/llama-model.cpp b/src/llama-model.cpp
+index ab1a07d1..70183041 100644
+--- a/src/llama-model.cpp
++++ b/src/llama-model.cpp
+@@ -878,6 +878,9 @@ void llama_model::load_hparams(llama_model_loader & ml) {
+                     default: type = LLM_TYPE_UNKNOWN;
+                }
+             } break;
++        case LLM_ARCH_GEMMA3:
++            {
++            } break;
+         case LLM_ARCH_STARCODER2:
+             {
+                 ml.get_key(LLM_KV_ATTENTION_LAYERNORM_EPS, hparams.f_norm_eps);
+@@ -2537,6 +2540,9 @@ bool llama_model::load_tensors(llama_model_loader & ml) {
+                         layer.ffn_post_norm = create_tensor(tn(LLM_TENSOR_FFN_POST_NORM, "weight", i), {n_embd}, 0);
+                     }
+                 } break;
++            case LLM_ARCH_GEMMA3:
++                {
++                } break;
+             case LLM_ARCH_STARCODER2:
+                 {
+                     tok_embd = create_tensor(tn(LLM_TENSOR_TOKEN_EMBD, "weight"), {n_embd, n_vocab}, 0);
+@@ -4029,6 +4035,7 @@ enum llama_rope_type llama_model_rope_type(const struct llama_model * model) {
+         case LLM_ARCH_PHIMOE:
+         case LLM_ARCH_GEMMA:
+         case LLM_ARCH_GEMMA2:
++        case LLM_ARCH_GEMMA3:
+         case LLM_ARCH_STARCODER2:
+         case LLM_ARCH_OPENELM:
+         case LLM_ARCH_GPTNEOX:
+diff --git a/src/llama-quant.cpp b/src/llama-quant.cpp
+index 6eb1da08..d2f3a510 100644
+--- a/src/llama-quant.cpp
++++ b/src/llama-quant.cpp
+@@ -737,6 +737,15 @@ static void llama_model_quantize_impl(const std::string & fname_inp, const std::
+         // This used to be a regex, but <regex> has an extreme cost to compile times.
+         bool quantize = name.rfind("weight") == name.size() - 6; // ends with 'weight'?
+ 
++        // don't quantize vision stuff
++        quantize &= name.find("v.blk.") == std::string::npos;
++
++        quantize &= name.find("mm.mm_input_projection.weight") == std::string::npos;
++        quantize &= name.find("mm.mm_soft_emb_norm.weight") == std::string::npos;
++        quantize &= name.find("v.patch_embedding.weight") == std::string::npos;
++        quantize &= name.find("v.position_embedding.weight") == std::string::npos;
++        quantize &= name.find("v.post_layernorm.weight") == std::string::npos;
++
+         // quantize only 2D and 3D tensors (experts)
+         quantize &= (ggml_n_dims(tensor) >= 2);
+ 

From 8294676150dde3dd3d316644b86e42b07204ff9c Mon Sep 17 00:00:00 2001
From: Blake Mizerany <blake.mizerany@gmail.com>
Date: Fri, 14 Mar 2025 18:33:07 -0700
Subject: [PATCH 098/157] server/internal/client/ollama: set User-Agent for
 registry client (#9775)

This sets the agent header in DefaultRegistry to include the version of
the client, OS, and architecture in the previous format, with a minor
twist.

Note: The version is obtained from the build info, instead of the
version in version.Version, which should not longer be necessary, but we
can remove in a future commit. Using the build info is more accurate and
also provides extra build information if the build is not tagged, and if
it is "dirty". Previously, the version was just "0.0.0" with no other
helpful information. The ollama.com registry and others handle this
swimmingly.
---
 server/internal/client/ollama/registry.go | 12 ++++++++++++
 1 file changed, 12 insertions(+)

diff --git a/server/internal/client/ollama/registry.go b/server/internal/client/ollama/registry.go
index cf05f79a..d1d01ba4 100644
--- a/server/internal/client/ollama/registry.go
+++ b/server/internal/client/ollama/registry.go
@@ -25,6 +25,7 @@ import (
 	"os"
 	"path/filepath"
 	"runtime"
+	"runtime/debug"
 	"slices"
 	"strconv"
 	"strings"
@@ -259,6 +260,7 @@ func DefaultRegistry() (*Registry, error) {
 	}
 
 	var rc Registry
+	rc.UserAgent = UserAgent()
 	rc.Key, err = ssh.ParseRawPrivateKey(keyPEM)
 	if err != nil {
 		return nil, err
@@ -274,6 +276,16 @@ func DefaultRegistry() (*Registry, error) {
 	return &rc, nil
 }
 
+func UserAgent() string {
+	buildinfo, _ := debug.ReadBuildInfo()
+	return fmt.Sprintf("ollama/%s (%s %s) Go/%s",
+		buildinfo.Main.Version,
+		runtime.GOARCH,
+		runtime.GOOS,
+		runtime.Version(),
+	)
+}
+
 func (r *Registry) maxStreams() int {
 	return cmp.Or(r.MaxStreams, runtime.GOMAXPROCS(0))
 }

From 2c8b4846437747bd23e7a176f83011e39ec2128b Mon Sep 17 00:00:00 2001
From: Patrick Devine <patrick@infrahq.com>
Date: Sat, 15 Mar 2025 12:09:02 -0700
Subject: [PATCH 099/157] fix: correctly save in interactive mode (#9788)

This fixes the case where a FROM line in previous modelfile points to a
file which may/may not be present in a different ollama instance. We
shouldn't be relying on the filename though and instead just check if
the FROM line was instead a valid model name and point to that instead.
---
 cmd/cmd_test.go    | 129 +++++++++++++++++++++++++++++++++++++++++++++
 cmd/interactive.go |  12 ++++-
 2 files changed, 139 insertions(+), 2 deletions(-)

diff --git a/cmd/cmd_test.go b/cmd/cmd_test.go
index f21a8f50..41b03e1b 100644
--- a/cmd/cmd_test.go
+++ b/cmd/cmd_test.go
@@ -757,3 +757,132 @@ func TestCreateHandler(t *testing.T) {
 		})
 	}
 }
+
+func TestNewCreateRequest(t *testing.T) {
+	tests := []struct {
+		name     string
+		from     string
+		opts     runOptions
+		expected *api.CreateRequest
+	}{
+		{
+			"basic test",
+			"newmodel",
+			runOptions{
+				Model:       "mymodel",
+				ParentModel: "",
+				Prompt:      "You are a fun AI agent",
+				Messages:    []api.Message{},
+				WordWrap:    true,
+			},
+			&api.CreateRequest{
+				From:  "mymodel",
+				Model: "newmodel",
+			},
+		},
+		{
+			"parent model test",
+			"newmodel",
+			runOptions{
+				Model:       "mymodel",
+				ParentModel: "parentmodel",
+				Messages:    []api.Message{},
+				WordWrap:    true,
+			},
+			&api.CreateRequest{
+				From:  "parentmodel",
+				Model: "newmodel",
+			},
+		},
+		{
+			"parent model as filepath test",
+			"newmodel",
+			runOptions{
+				Model:       "mymodel",
+				ParentModel: "/some/file/like/etc/passwd",
+				Messages:    []api.Message{},
+				WordWrap:    true,
+			},
+			&api.CreateRequest{
+				From:  "mymodel",
+				Model: "newmodel",
+			},
+		},
+		{
+			"parent model as windows filepath test",
+			"newmodel",
+			runOptions{
+				Model:       "mymodel",
+				ParentModel: "D:\\some\\file\\like\\etc\\passwd",
+				Messages:    []api.Message{},
+				WordWrap:    true,
+			},
+			&api.CreateRequest{
+				From:  "mymodel",
+				Model: "newmodel",
+			},
+		},
+		{
+			"options test",
+			"newmodel",
+			runOptions{
+				Model:       "mymodel",
+				ParentModel: "parentmodel",
+				Options: map[string]any{
+					"temperature": 1.0,
+				},
+			},
+			&api.CreateRequest{
+				From:  "parentmodel",
+				Model: "newmodel",
+				Parameters: map[string]any{
+					"temperature": 1.0,
+				},
+			},
+		},
+		{
+			"messages test",
+			"newmodel",
+			runOptions{
+				Model:       "mymodel",
+				ParentModel: "parentmodel",
+				System:      "You are a fun AI agent",
+				Messages: []api.Message{
+					{
+						Role:    "user",
+						Content: "hello there!",
+					},
+					{
+						Role:    "assistant",
+						Content: "hello to you!",
+					},
+				},
+				WordWrap: true,
+			},
+			&api.CreateRequest{
+				From:   "parentmodel",
+				Model:  "newmodel",
+				System: "You are a fun AI agent",
+				Messages: []api.Message{
+					{
+						Role:    "user",
+						Content: "hello there!",
+					},
+					{
+						Role:    "assistant",
+						Content: "hello to you!",
+					},
+				},
+			},
+		},
+	}
+
+	for _, tt := range tests {
+		t.Run(tt.name, func(t *testing.T) {
+			actual := NewCreateRequest(tt.from, tt.opts)
+			if !cmp.Equal(actual, tt.expected) {
+				t.Errorf("expected output %#v, got %#v", tt.expected, actual)
+			}
+		})
+	}
+}
diff --git a/cmd/interactive.go b/cmd/interactive.go
index f3489b65..d85510d4 100644
--- a/cmd/interactive.go
+++ b/cmd/interactive.go
@@ -18,6 +18,7 @@ import (
 	"github.com/ollama/ollama/envconfig"
 	"github.com/ollama/ollama/readline"
 	"github.com/ollama/ollama/types/errtypes"
+	"github.com/ollama/ollama/types/model"
 )
 
 type MultilineState int
@@ -459,9 +460,16 @@ func generateInteractive(cmd *cobra.Command, opts runOptions) error {
 }
 
 func NewCreateRequest(name string, opts runOptions) *api.CreateRequest {
+	parentModel := opts.ParentModel
+
+	modelName := model.ParseName(parentModel)
+	if !modelName.IsValid() {
+		parentModel = ""
+	}
+
 	req := &api.CreateRequest{
-		Name: name,
-		From: cmp.Or(opts.ParentModel, opts.Model),
+		Model: name,
+		From:  cmp.Or(parentModel, opts.Model),
 	}
 
 	if opts.System != "" {

From 088514bbd48d3e60ed3fa89d27740b070ab1a4ff Mon Sep 17 00:00:00 2001
From: zeo <108888572+zeozeozeo@users.noreply.github.com>
Date: Mon, 17 Mar 2025 06:54:43 +0500
Subject: [PATCH 100/157] readme: add Ellama to list of community integrations
 (#9800)

---
 README.md | 1 +
 1 file changed, 1 insertion(+)

diff --git a/README.md b/README.md
index 60b23cde..adb69a0b 100644
--- a/README.md
+++ b/README.md
@@ -392,6 +392,7 @@ See the [API documentation](./docs/api.md) for all endpoints.
 - [1Panel](https://github.com/1Panel-dev/1Panel/) (Web-based Linux Server Management Tool)
 - [AstrBot](https://github.com/Soulter/AstrBot/) (User-friendly LLM-based multi-platform chatbot with a WebUI, supporting RAG, LLM agents, and plugins integration)
 - [Reins](https://github.com/ibrahimcetin/reins) (Easily tweak parameters, customize system prompts per chat, and enhance your AI experiments with reasoning model support.)
+- [Ellama](https://github.com/zeozeozeo/ellama) (Friendly native app to chat with an Ollama instance)
 
 ### Cloud
 

From e27e4a3c1b9cb3a34178d5476debf805910e990a Mon Sep 17 00:00:00 2001
From: Louis Beaumont <louis.beaumont@gmail.com>
Date: Sun, 16 Mar 2025 18:56:42 -0700
Subject: [PATCH 101/157] readme: add screenpipe to community integrations
 (#9786)

---
 README.md | 1 +
 1 file changed, 1 insertion(+)

diff --git a/README.md b/README.md
index adb69a0b..47d0aebd 100644
--- a/README.md
+++ b/README.md
@@ -393,6 +393,7 @@ See the [API documentation](./docs/api.md) for all endpoints.
 - [AstrBot](https://github.com/Soulter/AstrBot/) (User-friendly LLM-based multi-platform chatbot with a WebUI, supporting RAG, LLM agents, and plugins integration)
 - [Reins](https://github.com/ibrahimcetin/reins) (Easily tweak parameters, customize system prompts per chat, and enhance your AI experiments with reasoning model support.)
 - [Ellama](https://github.com/zeozeozeo/ellama) (Friendly native app to chat with an Ollama instance)
+- [screenpipe](https://github.com/mediar-ai/screenpipe) Build agents powered by your screen history
 
 ### Cloud
 

From 50b5962042d7c5026d5507af44ae28294f8568d9 Mon Sep 17 00:00:00 2001
From: Daniel Hiltgen <dhiltgen@users.noreply.github.com>
Date: Mon, 17 Mar 2025 09:33:57 -0700
Subject: [PATCH 102/157] Add support for ROCm gfx1151 (#9773)

---
 CMakePresets.json | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/CMakePresets.json b/CMakePresets.json
index 442cb2a6..f3507e3f 100644
--- a/CMakePresets.json
+++ b/CMakePresets.json
@@ -56,7 +56,7 @@
       "name": "ROCm 6",
       "inherits": [ "ROCm" ],
       "cacheVariables": {
-        "AMDGPU_TARGETS": "gfx900;gfx940;gfx941;gfx942;gfx1010;gfx1012;gfx1030;gfx1100;gfx1101;gfx1102;gfx906:xnack-;gfx908:xnack-;gfx90a:xnack+;gfx90a:xnack-"
+        "AMDGPU_TARGETS": "gfx900;gfx940;gfx941;gfx942;gfx1010;gfx1012;gfx1030;gfx1100;gfx1101;gfx1102;gfx1151;gfx906:xnack-;gfx908:xnack-;gfx90a:xnack+;gfx90a:xnack-"
       }
     }
   ],

From 4561fff36e7338f12f12872a5ba2ced4e670796c Mon Sep 17 00:00:00 2001
From: Michael Yang <mxyng@pm.me>
Date: Fri, 14 Mar 2025 14:01:13 -0700
Subject: [PATCH 103/157] conditionally enable parallel pipelines

---
 ml/backend/ggml/ggml.go | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/ml/backend/ggml/ggml.go b/ml/backend/ggml/ggml.go
index 03b9acb3..cc1b5936 100644
--- a/ml/backend/ggml/ggml.go
+++ b/ml/backend/ggml/ggml.go
@@ -371,7 +371,7 @@ func New(r *os.File, params ml.BackendParams) (ml.Backend, error) {
 			(*C.ggml_backend_buffer_type_t)(unsafe.Pointer(&schedBufts[0])),
 			C.int(len(schedBackends)),
 			C.size_t(maxGraphNodes),
-			true,
+			C._Bool(len(gpus) > 1 && slices.Contains(gpus, output.d)),
 		),
 		input:  deviceBufferTypes[input.d],
 		output: deviceBufferTypes[output.d],

From 108fe021657ea1f7a012299f424d673e86512df2 Mon Sep 17 00:00:00 2001
From: Parth Sareen <parth.sareen@ollama.com>
Date: Mon, 17 Mar 2025 11:24:18 -0700
Subject: [PATCH 104/157] sample: make mutations in transforms explicit (#9743)

* updated minP to use early exit making use of sorted tokens
---
 sample/samplers.go        |   5 +-
 sample/transforms.go      |  39 ++++-------
 sample/transforms_test.go | 138 ++++++++++++++++++++++++++------------
 3 files changed, 110 insertions(+), 72 deletions(-)

diff --git a/sample/samplers.go b/sample/samplers.go
index e302f914..7c12da08 100644
--- a/sample/samplers.go
+++ b/sample/samplers.go
@@ -87,8 +87,9 @@ func (s *Sampler) sample(tokens []token) (token, error) {
 	// topK also sorts the tokens in descending order of logits
 	tokens = topK(tokens, s.topK)
 
-	tokens = temperature(tokens, s.temperature)
-	tokens = softmax(tokens)
+	// scale and normalize the tokens in place
+	temperature(tokens, s.temperature)
+	softmax(tokens)
 
 	tokens = topP(tokens, s.topP)
 	tokens = minP(tokens, s.minP)
diff --git a/sample/transforms.go b/sample/transforms.go
index a5efa704..3f677553 100644
--- a/sample/transforms.go
+++ b/sample/transforms.go
@@ -26,17 +26,16 @@ func (h *tokenHeap) Pop() any {
 }
 
 // temperature applies scaling to the logits
-func temperature(ts []token, temp float32) []token {
+func temperature(ts []token, temp float32) {
 	// Ensure temperature clipping near 0 to avoid numerical instability
 	temp = max(temp, 1e-7)
 	for i := range ts {
 		ts[i].value = ts[i].value / temp
 	}
-	return ts
 }
 
 // softmax applies normalization to the logits
-func softmax(ts []token) []token {
+func softmax(ts []token) {
 	// Find max logit for numerical stability
 	maxLogit := float32(math.Inf(-1))
 	for _, t := range ts {
@@ -56,8 +55,6 @@ func softmax(ts []token) []token {
 	for i := range ts {
 		ts[i].value /= sum
 	}
-
-	return ts
 }
 
 // topK limits the number of tokens considered to the k highest logits
@@ -99,6 +96,7 @@ func topK(ts []token, k int) []token {
 }
 
 // topP limits tokens to those with cumulative probability p
+// requires ts to be sorted in descending order of probabilities
 func topP(ts []token, p float32) []token {
 	if p == 1.0 {
 		return ts
@@ -109,37 +107,24 @@ func topP(ts []token, p float32) []token {
 	for i, t := range ts {
 		sum += t.value
 		if sum > float32(p) {
-			ts = ts[:i+1]
-			return ts
+			return ts[:i+1]
 		}
 	}
 
 	return ts
 }
 
-// minP limits tokens to those with cumulative probability p
+// minP filters tokens with probabilities >= p * max_prob
+// requires ts to be sorted in descending order of probabilities
 func minP(ts []token, p float32) []token {
-	if p == 1.0 {
-		return ts
-	}
+	maxProb := ts[0].value
 
-	maxProb := float32(math.Inf(-1))
-	for _, token := range ts {
-		if token.value > maxProb {
-			maxProb = token.value
+	threshold := maxProb * p
+
+	for i, t := range ts {
+		if t.value < threshold {
+			return ts[:i]
 		}
 	}
-
-	threshold := maxProb * float32(p)
-
-	// Filter tokens in-place
-	validTokens := ts[:0]
-	for i, token := range ts {
-		if token.value >= threshold {
-			validTokens = append(validTokens, ts[i])
-		}
-	}
-
-	ts = validTokens
 	return ts
 }
diff --git a/sample/transforms_test.go b/sample/transforms_test.go
index 4880dd8f..7faf30a5 100644
--- a/sample/transforms_test.go
+++ b/sample/transforms_test.go
@@ -34,17 +34,22 @@ func compareLogits(t *testing.T, name string, want []float32, got []token) {
 
 func TestTemperature(t *testing.T) {
 	input := []float32{1.0, 4.0, -2.0, 0.0}
-	got := temperature(toTokens(input), 0.5)
+	tokens := toTokens(input)
+	temperature(tokens, 0.5)
 	want := []float32{2.0, 8.0, -4.0, 0.0}
-	compareLogits(t, "temperature(0.5)", want, got)
+	compareLogits(t, "temperature(0.5)", want, tokens)
 
-	got = temperature(toTokens(input), 1.0)
+	input = []float32{1.0, 4.0, -2.0, 0.0}
+	tokens = toTokens(input)
+	temperature(tokens, 1.0)
 	want = []float32{1.0, 4.0, -2.0, 0.0}
-	compareLogits(t, "temperature(1)", want, got)
+	compareLogits(t, "temperature(1)", want, tokens)
 
-	got = temperature(toTokens(input), 0.0)
+	input = []float32{1.0, 4.0, -2.0, 0.0}
+	tokens = toTokens(input)
+	temperature(tokens, 0.0)
 	want = []float32{1e7, 4e7, -2e7, 0.0}
-	compareLogits(t, "temperature(0)", want, got)
+	compareLogits(t, "temperature(0)", want, tokens)
 }
 
 func TestSoftmax(t *testing.T) {
@@ -90,16 +95,17 @@ func TestSoftmax(t *testing.T) {
 
 	for _, tt := range tests {
 		t.Run(tt.name, func(t *testing.T) {
-			got := softmax(toTokens(tt.input))
+			tokens := toTokens(tt.input)
+			softmax(tokens)
 
 			if tt.expected != nil {
-				compareLogits(t, tt.name, tt.expected, got)
+				compareLogits(t, tt.name, tt.expected, tokens)
 				return
 			}
 
 			// Check probabilities sum to 1
 			var sum float32
-			for _, token := range got {
+			for _, token := range tokens {
 				sum += token.value
 				if token.value < 0 || token.value > 1 {
 					t.Errorf("probability out of range [0,1]: got %f", token.value)
@@ -114,38 +120,44 @@ func TestSoftmax(t *testing.T) {
 
 func TestTopK(t *testing.T) {
 	input := []float32{0.026986899, 0.043722924, 0.036774673, 0.27755088, 0.0046718004, 0.08582123, 0.20409796, 0.00412893, 0.15720603, 0.045046154, 0.0030491839, 0.01681367}
-
-	// Test k=5
-	got := topK(toTokens(input), 5)
-	if len(got) != 5 {
-		t.Errorf("topK(5): wrong length: want 5, got %d", len(got))
+	tokens := toTokens(input)
+	tokens = topK(tokens, 5)
+	if len(tokens) != 5 {
+		t.Errorf("topK(5): wrong length: want 5, got %d", len(tokens))
 	}
-	// Should keep highest 3 values in descending order
 	want := []float32{0.27755088, 0.20409796, 0.15720603, 0.08582123, 0.045046154}
-	compareLogits(t, "topK(3)", want, got)
+	compareLogits(t, "topK(3)", want, tokens)
 
-	got = topK(toTokens(input), 20)
-	if len(got) != len(input) {
-		t.Errorf("topK(20): wrong length: want %d, got %d", len(input), len(got))
+	tokens = toTokens(input)
+	tokens = topK(tokens, 20)
+	if len(tokens) != len(input) {
+		t.Errorf("topK(20): wrong length: want %d, got %d", len(input), len(tokens))
 	}
 
-	// Test k=-1
 	input = []float32{0.026986899, 0.043722924, 0.036774673, 0.27755088, 0.0046718004, 0.08582123, 0.20409796, 0.00412893, 0.15720603, 0.045046154, 0.0030491839, 0.01681367}
 	want = []float32{0.27755088, 0.20409796, 0.15720603, 0.08582123, 0.045046154, 0.043722924, 0.036774673, 0.026986899, 0.01681367, 0.0046718004, 0.00412893, 0.0030491839}
-	got = topK(toTokens(input), -1)
-	if len(got) != len(input) {
-		t.Errorf("topK(-1): wrong length: want %d, got %d", len(input), len(got))
+	tokens = toTokens(input)
+	tokens = topK(tokens, -1)
+	if len(tokens) != len(input) {
+		t.Errorf("topK(-1): wrong length: want %d, got %d", len(input), len(tokens))
 	}
-	compareLogits(t, "topK(-1)", want, got)
+	compareLogits(t, "topK(-1)", want, tokens)
 
-	// Test k=0
 	input = []float32{0.026986899, 0.043722924, 0.036774673, 0.27755088, 0.0046718004, 0.08582123, 0.20409796, 0.00412893, 0.15720603, 0.045046154, 0.0030491839, 0.01681367}
 	want = []float32{0.27755088, 0.20409796, 0.15720603, 0.08582123, 0.045046154, 0.043722924, 0.036774673, 0.026986899, 0.01681367, 0.0046718004, 0.00412893, 0.0030491839}
-	got = topK(toTokens(input), 0)
-	if len(got) != len(input) {
-		t.Errorf("topK(-1): wrong length: want %d, got %d", len(input), len(got))
+	tokens = toTokens(input)
+	tokens = topK(tokens, 0)
+	if len(tokens) != len(input) {
+		t.Errorf("topK(-1): wrong length: want %d, got %d", len(input), len(tokens))
+	}
+	compareLogits(t, "topK(-1)", want, tokens)
+
+	input = []float32{-1e7, -2e7, -3e7, -4e7}
+	tokens = toTokens(input)
+	tokens = topK(tokens, 1)
+	if len(tokens) < 1 {
+		t.Error("topK should keep at least one token")
 	}
-	compareLogits(t, "topK(-1)", want, got)
 }
 
 func TestTopP(t *testing.T) {
@@ -153,16 +165,25 @@ func TestTopP(t *testing.T) {
 	tokens := toTokens(input)
 
 	// First apply temperature and softmax to get probabilities
-	tokens = softmax(tokens)
+	softmax(tokens)
 	tokens = topK(tokens, 20)
 
 	// Then apply topP
-	got := topP(tokens, 0.95)
+	tokens = topP(tokens, 0.95)
 
 	// Should keep tokens until cumsum > 0.95
-	if len(got) > 3 {
-		t.Errorf("topP(0.95): kept too many tokens: got %d", len(got))
-		t.Logf("got: %v", got)
+	if len(tokens) > 3 {
+		t.Errorf("topP(0.95): kept too many tokens: got %d", len(tokens))
+		t.Logf("got: %v", tokens)
+	}
+
+	// Test edge case - ensure at least one token remains
+	input = []float32{-1e6, -1e6, -1e6} // One dominant token
+	tokens = toTokens(input)
+	softmax(tokens)
+	tokens = topP(tokens, 0.0) // Very small p
+	if len(tokens) < 1 {
+		t.Error("topP should keep at least one token")
 	}
 }
 
@@ -171,14 +192,45 @@ func TestMinP(t *testing.T) {
 	tokens := toTokens(input)
 
 	// First apply temperature and softmax
-	tokens = softmax(tokens)
+	tokens = topK(tokens, 20)
+	softmax(tokens)
 
-	// Then apply minP
-	got := minP(tokens, 0.2)
+	tokens = minP(tokens, 1.0)
+
+	if len(tokens) != 1 {
+		t.Errorf("minP(1.0): should keep all tokens, got %d, want %d", len(tokens), len(tokens))
+	}
+
+	// Test with normal p value
+	tokens = toTokens(input) // Reset tokens
+	tokens = topK(tokens, 20)
+	softmax(tokens)
+	tokens = minP(tokens, 0.2)
 
 	// Should keep tokens with prob >= 0.2 * max_prob
-	if len(got) > 3 {
-		t.Errorf("minP(0.2): kept too many tokens: got %d", len(got))
+	if len(tokens) > 3 {
+		t.Errorf("minP(0.2): kept too many tokens: got %d", len(tokens))
+		t.Logf("got: %v", tokens)
+	}
+
+	// Test with zero p value
+	tokens = toTokens(input) // Reset tokens
+	tokens = topK(tokens, 20)
+	softmax(tokens)
+	tokens = minP(tokens, 0.0)
+
+	// Should keep only the highest probability token
+	if len(tokens) != len(input) {
+		t.Errorf("minP(0.0): should keep only one token, got %d", len(tokens))
+		t.Logf("got: %v", tokens)
+	}
+
+	input = []float32{1e-10, 1e-10, 1e-10}
+	tokens = toTokens(input)
+	softmax(tokens)
+	tokens = minP(tokens, 1.0)
+	if len(tokens) < 1 {
+		t.Error("minP should keep at least one token even with extreme probabilities")
 	}
 }
 
@@ -231,7 +283,7 @@ func BenchmarkTransforms(b *testing.B) {
 		b.ResetTimer()
 		for b.Loop() {
 			copy(tokensCopy, tokens)
-			topK(tokensCopy, 10)
+			tokens = topK(tokensCopy, 10)
 		}
 	})
 
@@ -239,7 +291,7 @@ func BenchmarkTransforms(b *testing.B) {
 		b.ResetTimer()
 		for b.Loop() {
 			copy(tokensCopy, tokens)
-			topP(tokensCopy, 0.9)
+			tokens = topP(tokensCopy, 0.9)
 		}
 	})
 
@@ -247,7 +299,7 @@ func BenchmarkTransforms(b *testing.B) {
 		b.ResetTimer()
 		for b.Loop() {
 			copy(tokensCopy, tokens)
-			minP(tokensCopy, 0.2)
+			tokens = minP(tokensCopy, 0.2)
 		}
 	})
 
@@ -255,7 +307,7 @@ func BenchmarkTransforms(b *testing.B) {
 		b.ResetTimer()
 		for b.Loop() {
 			copy(tokensCopy, tokens)
-			topK(tokensCopy, 200000)
+			tokens = topK(tokensCopy, 200000)
 		}
 	})
 }

From 364629b8d6e004309ea348cb0375810967c160b8 Mon Sep 17 00:00:00 2001
From: Jeffrey Morgan <jmorganca@gmail.com>
Date: Mon, 17 Mar 2025 16:32:40 -0400
Subject: [PATCH 105/157] ml/backend/ggml: allocate memory with malloc when
 loading model (#9822)

---
 ml/backend/ggml/ggml.go | 20 +++++++++++---------
 1 file changed, 11 insertions(+), 9 deletions(-)

diff --git a/ml/backend/ggml/ggml.go b/ml/backend/ggml/ggml.go
index 03b9acb3..fcd28aec 100644
--- a/ml/backend/ggml/ggml.go
+++ b/ml/backend/ggml/ggml.go
@@ -312,17 +312,19 @@ func New(r *os.File, params ml.BackendParams) (ml.Backend, error) {
 					return fmt.Errorf("unassigned tensor: %s", t.Name)
 				}
 
-				bts := make([]byte, t.Size())
-				n, err := io.ReadFull(io.NewSectionReader(sr, int64(t.Offset), int64(t.Size())), bts)
-				if err != nil {
-					return err
+				bts := C.malloc(C.size_t(t.Size()))
+				if bts == nil {
+					return errors.New("failed to allocate tensor buffer")
+				}
+				defer C.free(bts)
+
+				buf := unsafe.Slice((*byte)(bts), t.Size())
+				n, err := io.ReadFull(io.NewSectionReader(sr, int64(t.Offset), int64(t.Size())), buf)
+				if err != nil || n != len(buf) {
+					return errors.New("read failed")
 				}
 
-				if n != len(bts) {
-					return errors.New("short read")
-				}
-
-				C.ggml_backend_tensor_set(tt, unsafe.Pointer(&bts[0]), 0, C.size_t(t.Size()))
+				C.ggml_backend_tensor_set(tt, bts, 0, C.size_t(t.Size()))
 				return nil
 			})
 		}

From 95e271d98f0b5717bde2b7e5c4c7639c19fd3763 Mon Sep 17 00:00:00 2001
From: Bruce MacDonald <brucewmacdonald@gmail.com>
Date: Mon, 17 Mar 2025 15:11:15 -0700
Subject: [PATCH 106/157] runner: remove cache prompt flag from ollama runner
 (#9826)

We do not need to bypass the prompt caching in the ollama runner yet, as
only embedding models needed to bypass the prompt caching. When embedding
models are implemented they can skip initializing this cache completely.
---
 runner/ollamarunner/cache.go      |   7 +-
 runner/ollamarunner/cache_test.go | 128 ++++++++++++++++++++++++++++++
 runner/ollamarunner/runner.go     |   2 +-
 3 files changed, 130 insertions(+), 7 deletions(-)

diff --git a/runner/ollamarunner/cache.go b/runner/ollamarunner/cache.go
index adcb3f73..cf5e6b91 100644
--- a/runner/ollamarunner/cache.go
+++ b/runner/ollamarunner/cache.go
@@ -89,7 +89,7 @@ type InputCacheSlot struct {
 	lastUsed time.Time
 }
 
-func (c *InputCache) LoadCacheSlot(prompt []input.Input, cachePrompt bool) (*InputCacheSlot, []input.Input, error) {
+func (c *InputCache) LoadCacheSlot(prompt []input.Input) (*InputCacheSlot, []input.Input, error) {
 	var slot *InputCacheSlot
 	var numPast int32
 	var err error
@@ -107,11 +107,6 @@ func (c *InputCache) LoadCacheSlot(prompt []input.Input, cachePrompt bool) (*Inp
 		return nil, nil, err
 	}
 
-	// TODO (brucemacd): cachePrompt is always true for completion, but false for embedding, can this be improved?
-	if !cachePrompt {
-		numPast = 0
-	}
-
 	slot.InUse = true
 	slot.lastUsed = time.Now()
 
diff --git a/runner/ollamarunner/cache_test.go b/runner/ollamarunner/cache_test.go
index 0a1b73f5..f8925d11 100644
--- a/runner/ollamarunner/cache_test.go
+++ b/runner/ollamarunner/cache_test.go
@@ -297,3 +297,131 @@ func TestShiftDiscard(t *testing.T) {
 		})
 	}
 }
+
+func TestLoadCacheSlot(t *testing.T) {
+	tests := []struct {
+		name           string
+		cache          InputCache
+		prompt         []input.Input
+		wantErr        bool
+		expectedSlotId int
+		expectedPrompt int // expected length of remaining prompt
+	}{
+		{
+			name: "Basic cache hit - single user",
+			cache: InputCache{
+				multiUserCache: false,
+				slots: []InputCacheSlot{
+					{
+						Id:       0,
+						Inputs:   []input.Input{{Token: 1}, {Token: 2}},
+						InUse:    false,
+						lastUsed: time.Now().Add(-time.Second),
+					},
+					{
+						Id:       1,
+						Inputs:   []input.Input{},
+						InUse:    false,
+						lastUsed: time.Now().Add(-2 * time.Second),
+					},
+				},
+			},
+			prompt:         []input.Input{{Token: 1}, {Token: 2}, {Token: 3}},
+			wantErr:        false,
+			expectedSlotId: 0,
+			expectedPrompt: 1, // Only token 3 remains
+		},
+		{
+			name: "Basic cache hit - multi user",
+			cache: InputCache{
+				multiUserCache: true,
+				slots: []InputCacheSlot{
+					{
+						Id:       0,
+						Inputs:   []input.Input{{Token: 1}, {Token: 2}},
+						InUse:    false,
+						lastUsed: time.Now().Add(-time.Second),
+					},
+					{
+						Id:       1,
+						Inputs:   []input.Input{},
+						InUse:    false,
+						lastUsed: time.Now().Add(-2 * time.Second),
+					},
+				},
+			},
+			prompt:         []input.Input{{Token: 1}, {Token: 2}, {Token: 3}},
+			wantErr:        false,
+			expectedSlotId: 0,
+			expectedPrompt: 1, // Only token 3 remains
+		},
+		{
+			name: "Exact match - leave one input",
+			cache: InputCache{
+				multiUserCache: false,
+				slots: []InputCacheSlot{
+					{
+						Id:       0,
+						Inputs:   []input.Input{{Token: 1}, {Token: 2}},
+						InUse:    false,
+						lastUsed: time.Now().Add(-time.Second),
+					},
+				},
+			},
+			prompt:         []input.Input{{Token: 1}, {Token: 2}},
+			wantErr:        false,
+			expectedSlotId: 0,
+			expectedPrompt: 1, // Should leave 1 token for sampling
+		},
+		{
+			name: "No available slots",
+			cache: InputCache{
+				multiUserCache: false,
+				slots: []InputCacheSlot{
+					{
+						Id:       0,
+						Inputs:   []input.Input{{Token: 1}, {Token: 2}},
+						InUse:    true,
+						lastUsed: time.Now().Add(-time.Second),
+					},
+				},
+			},
+			prompt:         []input.Input{{Token: 1}, {Token: 2}, {Token: 3}},
+			wantErr:        true,
+			expectedSlotId: -1,
+			expectedPrompt: -1,
+		},
+	}
+
+	for _, tt := range tests {
+		t.Run(tt.name, func(t *testing.T) {
+			slot, remainingPrompt, err := tt.cache.LoadCacheSlot(tt.prompt)
+
+			// Check error state
+			if (err != nil) != tt.wantErr {
+				t.Errorf("LoadCacheSlot() error = %v, wantErr %v", err, tt.wantErr)
+				return
+			}
+
+			if tt.wantErr {
+				return // Skip further checks if we expected an error
+			}
+
+			// Verify slot ID
+			if slot.Id != tt.expectedSlotId {
+				t.Errorf("LoadCacheSlot() slot ID = %v, expected %v", slot.Id, tt.expectedSlotId)
+			}
+
+			// Verify slot is now marked in use
+			if !slot.InUse {
+				t.Errorf("LoadCacheSlot() slot not marked InUse")
+			}
+
+			// Verify remaining prompt length
+			if len(remainingPrompt) != tt.expectedPrompt {
+				t.Errorf("LoadCacheSlot() remaining prompt length = %v, expected %v",
+					len(remainingPrompt), tt.expectedPrompt)
+			}
+		})
+	}
+}
diff --git a/runner/ollamarunner/runner.go b/runner/ollamarunner/runner.go
index d4c24556..98fcf2c0 100644
--- a/runner/ollamarunner/runner.go
+++ b/runner/ollamarunner/runner.go
@@ -590,7 +590,7 @@ func (s *Server) completion(w http.ResponseWriter, r *http.Request) {
 	found := false
 	for i, sq := range s.seqs {
 		if sq == nil {
-			seq.cache, seq.inputs, err = s.cache.LoadCacheSlot(seq.inputs, true)
+			seq.cache, seq.inputs, err = s.cache.LoadCacheSlot(seq.inputs)
 			if err != nil {
 				s.mu.Unlock()
 				http.Error(w, fmt.Sprintf("Failed to load cache: %v", err), http.StatusInternalServerError)

From bf24498b1ea2728ef735030f186d1c970c38eaa6 Mon Sep 17 00:00:00 2001
From: Jesse Gross <jesse@ollama.com>
Date: Mon, 17 Mar 2025 12:03:06 -0700
Subject: [PATCH 107/157] ollamarunner: Check for minBatch of context space
 when shifting

Models can specify that a group of inputs need to be handled a single
batch. However, context shifting didn't respect this and could trigger
a break anyways. In this case, we should instead trigger a context
shift earlier so that it occurs before the grouped batch.

Note that there still some corner cases:
 - A long prompt that exceeds the context window can get truncated
   in the middle of an image. With the current models, this will
   result in the model not recognizing the image at all, which is
   pretty much the expected result with truncation.
 - The context window is set less than the minimum batch size. The
   only solution to this is to refuse to load the model with these
   settings. However, this can never occur with current models and
   default settings.

Since users are unlikely to run into these scenarios, fixing them is
left as a follow up.
---
 runner/ollamarunner/runner.go | 28 +++++++++++++++++-----------
 1 file changed, 17 insertions(+), 11 deletions(-)

diff --git a/runner/ollamarunner/runner.go b/runner/ollamarunner/runner.go
index 98fcf2c0..9a1a549c 100644
--- a/runner/ollamarunner/runner.go
+++ b/runner/ollamarunner/runner.go
@@ -115,6 +115,9 @@ func (s *Server) NewSequence(prompt string, images []llm.ImageData, params NewSe
 		params.numKeep = int32(len(inputs))
 	}
 
+	// TODO(jessegross): We should ensure that we always leave minBatch of context space to shift,
+	// otherwise we might truncate or split the batch against the model's wishes
+
 	// Ensure that at least 1 input can be discarded during shift
 	params.numKeep = min(params.numKeep, s.cache.numCtx-1)
 
@@ -366,17 +369,6 @@ func (s *Server) processBatch() error {
 		batchSize := s.batchSize
 
 		for j, inp := range seq.inputs {
-			if int32(len(seq.cache.Inputs)+len(seq.pendingInputs)+1) > s.cache.numCtx {
-				if len(seq.pendingInputs) == 0 {
-					err := s.cache.ShiftCacheSlot(seq.cache, seq.numKeep)
-					if err != nil {
-						return err
-					}
-				} else {
-					break
-				}
-			}
-
 			// If we are required to put following inputs into a single batch then extend the
 			// batch size. Since we are only extending the size the minimum amount possible, this
 			// will cause a break if we have pending inputs.
@@ -389,6 +381,20 @@ func (s *Server) processBatch() error {
 				break
 			}
 
+			// If the sum of our working set (already processed tokens, tokens we added to this
+			// batch, required following tokens) exceeds the context size, then trigger a shift
+			// now so we don't have to do one later when we can't break the batch.
+			if int32(len(seq.cache.Inputs)+len(seq.pendingInputs)+minBatch) > s.cache.numCtx {
+				if len(seq.pendingInputs) != 0 {
+					break
+				}
+
+				err := s.cache.ShiftCacheSlot(seq.cache, seq.numKeep)
+				if err != nil {
+					return err
+				}
+			}
+
 			options.Inputs = append(options.Inputs, inp.Token)
 			if inp.Multimodal != nil {
 				options.Multimodal = append(options.Multimodal, input.MultimodalIndex{Index: len(options.Inputs) - 1, Multimodal: inp.Multimodal})

From 61a882521657a27b5e1a0834eb6ab69617290ef2 Mon Sep 17 00:00:00 2001
From: Bruce MacDonald <brucewmacdonald@gmail.com>
Date: Tue, 18 Mar 2025 10:38:28 -0700
Subject: [PATCH 108/157] convert: return name of unsupported architecture
 (#9862)

When a model's architecture cannot be converted return the name of the unsupported arch in the error message.
---
 convert/convert.go | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/convert/convert.go b/convert/convert.go
index 7b9fe31f..a31b0d6c 100644
--- a/convert/convert.go
+++ b/convert/convert.go
@@ -201,7 +201,7 @@ func ConvertModel(fsys fs.FS, ws io.WriteSeeker) error {
 	case "CohereForCausalLM":
 		conv = &commandrModel{}
 	default:
-		return errors.New("unsupported architecture")
+		return fmt.Errorf("unsupported architecture %q", p.Architectures[0])
 	}
 
 	if err := json.Unmarshal(bts, conv); err != nil {

From df94175a0fb0356c9b9e9a62b73d908633c08810 Mon Sep 17 00:00:00 2001
From: Bruce MacDonald <brucewmacdonald@gmail.com>
Date: Tue, 18 Mar 2025 16:51:33 -0700
Subject: [PATCH 109/157] ggml: return error on failure to read tensor data
 (#9872)

When converting a ggml model if there is a failure to read tensor data a nil error value was being returned. It should be assigned to the actual error from reading.
---
 ml/backend/ggml/ggml.go | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/ml/backend/ggml/ggml.go b/ml/backend/ggml/ggml.go
index 0c6f1c76..6732470e 100644
--- a/ml/backend/ggml/ggml.go
+++ b/ml/backend/ggml/ggml.go
@@ -330,7 +330,7 @@ func New(r *os.File, params ml.BackendParams) (ml.Backend, error) {
 		}
 	}
 
-	if g.Wait() != nil {
+	if err := g.Wait(); err != nil {
 		return nil, err
 	}
 

From da0e345200fbb47653d2f9c60fcc60ba7b0a7187 Mon Sep 17 00:00:00 2001
From: Jeffrey Morgan <jmorganca@gmail.com>
Date: Tue, 18 Mar 2025 18:08:19 -0700
Subject: [PATCH 110/157] ml: use input context for extracting outputs (#9875)

---
 model/models/gemma2/model.go | 2 +-
 model/models/gemma3/model.go | 2 +-
 model/models/llama/model.go  | 2 +-
 model/models/mllama/model.go | 2 +-
 4 files changed, 4 insertions(+), 4 deletions(-)

diff --git a/model/models/gemma2/model.go b/model/models/gemma2/model.go
index 2b8597c4..fbefebe2 100644
--- a/model/models/gemma2/model.go
+++ b/model/models/gemma2/model.go
@@ -179,7 +179,7 @@ func (m *Model) Forward(ctx ml.Context, opts input.Options) (ml.Tensor, error) {
 		return nil, err
 	}
 
-	outputs, err := ctx.Output().FromIntSlice(opts.Outputs, len(opts.Outputs))
+	outputs, err := ctx.Input().FromIntSlice(opts.Outputs, len(opts.Outputs))
 	if err != nil {
 		return nil, err
 	}
diff --git a/model/models/gemma3/model.go b/model/models/gemma3/model.go
index 32ad80f4..95f89ad4 100644
--- a/model/models/gemma3/model.go
+++ b/model/models/gemma3/model.go
@@ -150,7 +150,7 @@ func (m *Model) Forward(ctx ml.Context, opts input.Options) (ml.Tensor, error) {
 		return nil, err
 	}
 
-	outputs, err := ctx.Output().FromIntSlice(opts.Outputs, len(opts.Outputs))
+	outputs, err := ctx.Input().FromIntSlice(opts.Outputs, len(opts.Outputs))
 	if err != nil {
 		return nil, err
 	}
diff --git a/model/models/llama/model.go b/model/models/llama/model.go
index 19a2ab8c..87eb9b75 100644
--- a/model/models/llama/model.go
+++ b/model/models/llama/model.go
@@ -150,7 +150,7 @@ func (m *Model) Forward(ctx ml.Context, opts input.Options) (ml.Tensor, error) {
 		return nil, err
 	}
 
-	outputs, err := ctx.Output().FromIntSlice(opts.Outputs, len(opts.Outputs))
+	outputs, err := ctx.Input().FromIntSlice(opts.Outputs, len(opts.Outputs))
 	if err != nil {
 		return nil, err
 	}
diff --git a/model/models/mllama/model.go b/model/models/mllama/model.go
index fa4d570c..0aa11f17 100644
--- a/model/models/mllama/model.go
+++ b/model/models/mllama/model.go
@@ -154,7 +154,7 @@ func (m *Model) Forward(ctx ml.Context, opts input.Options) (ml.Tensor, error) {
 		return nil, err
 	}
 
-	outputs, err := ctx.Output().FromIntSlice(opts.Outputs, len(opts.Outputs))
+	outputs, err := ctx.Input().FromIntSlice(opts.Outputs, len(opts.Outputs))
 	if err != nil {
 		return nil, err
 	}

From 2ddacd7516aa78d2ad4899681c7a7f9af2eedc65 Mon Sep 17 00:00:00 2001
From: Blake Mizerany <blake.mizerany@gmail.com>
Date: Wed, 19 Mar 2025 14:59:57 -0700
Subject: [PATCH 111/157] server/internal/client/ollama: confirm all chunksums
 were received (#9893)

If the chunksums response is missing a chunk, the client should fail
the download. This changes the client to check that all bytes are
accounted for in the chunksums response.

It is possible there are overlaps or gaps in the chunksums response and
so the size is not the only thing left to check, but this provides
enough coverage for now. We may want to check that chunks are contiguous
later.
---
 server/internal/client/ollama/registry.go     | 120 ++++++++----------
 .../internal/client/ollama/registry_test.go   |  92 ++++++++++++--
 2 files changed, 134 insertions(+), 78 deletions(-)

diff --git a/server/internal/client/ollama/registry.go b/server/internal/client/ollama/registry.go
index d1d01ba4..fdac71bb 100644
--- a/server/internal/client/ollama/registry.go
+++ b/server/internal/client/ollama/registry.go
@@ -37,7 +37,6 @@ import (
 	"golang.org/x/sync/errgroup"
 
 	"github.com/ollama/ollama/server/internal/cache/blob"
-	"github.com/ollama/ollama/server/internal/internal/backoff"
 	"github.com/ollama/ollama/server/internal/internal/names"
 
 	_ "embed"
@@ -213,12 +212,6 @@ type Registry struct {
 	// request. If zero, [DefaultChunkingThreshold] is used.
 	ChunkingThreshold int64
 
-	// MaxChunkSize is the maximum size of a chunk to download. If zero,
-	// the default is [DefaultMaxChunkSize].
-	//
-	// It is only used when a layer is larger than [MaxChunkingThreshold].
-	MaxChunkSize int64
-
 	// Mask, if set, is the name used to convert non-fully qualified names
 	// to fully qualified names. If empty, [DefaultMask] is used.
 	Mask string
@@ -447,6 +440,11 @@ func (r *Registry) Pull(ctx context.Context, name string) error {
 	if err != nil {
 		return err
 	}
+
+	// TODO(bmizerany): decide if this should be considered valid. Maybe
+	// server-side we special case '{}' to have some special meaning? Maybe
+	// "archiving" a tag (which is how we reason about it in the registry
+	// already, just with a different twist).
 	if len(m.Layers) == 0 {
 		return fmt.Errorf("%w: no layers", ErrManifestInvalid)
 	}
@@ -456,11 +454,7 @@ func (r *Registry) Pull(ctx context.Context, name string) error {
 		return err
 	}
 
-	exists := func(l *Layer) bool {
-		info, err := c.Get(l.Digest)
-		return err == nil && info.Size == l.Size
-	}
-
+	// TODO(bmizerany): work to remove the need to do this
 	layers := m.Layers
 	if m.Config != nil && m.Config.Digest.IsValid() {
 		layers = append(layers, m.Config)
@@ -469,19 +463,16 @@ func (r *Registry) Pull(ctx context.Context, name string) error {
 	// Send initial layer trace events to allow clients to have an
 	// understanding of work to be done before work starts.
 	t := traceFromContext(ctx)
-	skip := make([]bool, len(layers))
-	for i, l := range layers {
+	for _, l := range layers {
 		t.update(l, 0, nil)
-		if exists(l) {
-			skip[i] = true
-			t.update(l, l.Size, ErrCached)
-		}
 	}
 
-	g, ctx := errgroup.WithContext(ctx)
+	var g errgroup.Group
 	g.SetLimit(r.maxStreams())
-	for i, l := range layers {
-		if skip[i] {
+	for _, l := range layers {
+		info, err := c.Get(l.Digest)
+		if err == nil && info.Size == l.Size {
+			t.update(l, l.Size, ErrCached)
 			continue
 		}
 
@@ -490,63 +481,50 @@ func (r *Registry) Pull(ctx context.Context, name string) error {
 			t.update(l, 0, err)
 			continue
 		}
+		// TODO(bmizerany): fix this unbounded use of defer
 		defer chunked.Close()
 
 		var progress atomic.Int64
 		for cs, err := range r.chunksums(ctx, name, l) {
 			if err != nil {
+				// Bad chunksums response, update tracing
+				// clients and then bail.
 				t.update(l, progress.Load(), err)
-				break
+				return err
 			}
 
 			g.Go(func() (err error) {
-				defer func() { t.update(l, progress.Load(), err) }()
-
-				for _, err := range backoff.Loop(ctx, 3*time.Second) {
+				defer func() {
 					if err != nil {
-						return err
+						err = fmt.Errorf("error downloading %s: %w", cs.Digest.Short(), err)
 					}
-					err := func() error {
-						req, err := http.NewRequestWithContext(ctx, "GET", cs.URL, nil)
-						if err != nil {
-							return err
-						}
-						req.Header.Set("Range", fmt.Sprintf("bytes=%d-%d", cs.Chunk.Start, cs.Chunk.End))
-						res, err := sendRequest(r.client(), req)
-						if err != nil {
-							return err
-						}
-						defer res.Body.Close()
+					t.update(l, progress.Load(), err)
+				}()
 
-						// Count bytes towards
-						// progress, as they arrive, so
-						// that our bytes piggyback
-						// other chunk updates on
-						// completion.
-						//
-						// This tactic is enough to
-						// show "smooth" progress given
-						// the current CLI client. In
-						// the near future, the server
-						// should report download rate
-						// since it knows better than
-						// a client that is measuring
-						// rate based on wall-clock
-						// time-since-last-update.
-						body := &trackingReader{r: res.Body, n: &progress}
-
-						err = chunked.Put(cs.Chunk, cs.Digest, body)
-						if err != nil {
-							return err
-						}
-
-						return nil
-					}()
-					if !canRetry(err) {
-						return err
-					}
+				req, err := http.NewRequestWithContext(ctx, "GET", cs.URL, nil)
+				if err != nil {
+					return err
 				}
-				return nil
+				req.Header.Set("Range", fmt.Sprintf("bytes=%d-%d", cs.Chunk.Start, cs.Chunk.End))
+				res, err := sendRequest(r.client(), req)
+				if err != nil {
+					return err
+				}
+				defer res.Body.Close()
+
+				// Count bytes towards progress, as they
+				// arrive, so that our bytes piggyback other
+				// chunk updates on completion.
+				//
+				// This tactic is enough to show "smooth"
+				// progress given the current CLI client. In
+				// the near future, the server should report
+				// download rate since it knows better than a
+				// client that is measuring rate based on
+				// wall-clock time-since-last-update.
+				body := &trackingReader{r: res.Body, n: &progress}
+
+				return chunked.Put(cs.Chunk, cs.Digest, body)
 			})
 		}
 	}
@@ -554,13 +532,10 @@ func (r *Registry) Pull(ctx context.Context, name string) error {
 		return err
 	}
 
-	// store the manifest blob
 	md := blob.DigestFromBytes(m.Data)
 	if err := blob.PutBytes(c, md, m.Data); err != nil {
 		return err
 	}
-
-	// commit the manifest with a link
 	return c.Link(m.Name, md)
 }
 
@@ -782,12 +757,15 @@ func (r *Registry) chunksums(ctx context.Context, name string, l *Layer) iter.Se
 		}
 		blobURL := res.Header.Get("Content-Location")
 
+		var size int64
 		s := bufio.NewScanner(res.Body)
 		s.Split(bufio.ScanWords)
 		for {
 			if !s.Scan() {
 				if s.Err() != nil {
 					yield(chunksum{}, s.Err())
+				} else if size != l.Size {
+					yield(chunksum{}, fmt.Errorf("size mismatch: layer size %d != sum of chunks %d", size, l.Size))
 				}
 				return
 			}
@@ -811,6 +789,12 @@ func (r *Registry) chunksums(ctx context.Context, name string, l *Layer) iter.Se
 				return
 			}
 
+			size += chunk.Size()
+			if size > l.Size {
+				yield(chunksum{}, fmt.Errorf("chunk size %d exceeds layer size %d", size, l.Size))
+				return
+			}
+
 			cs := chunksum{
 				URL:    blobURL,
 				Chunk:  chunk,
diff --git a/server/internal/client/ollama/registry_test.go b/server/internal/client/ollama/registry_test.go
index 30fb58ab..30529543 100644
--- a/server/internal/client/ollama/registry_test.go
+++ b/server/internal/client/ollama/registry_test.go
@@ -17,6 +17,7 @@ import (
 	"reflect"
 	"slices"
 	"strings"
+	"sync"
 	"testing"
 	"time"
 
@@ -56,21 +57,21 @@ func (rr recordRoundTripper) RoundTrip(req *http.Request) (*http.Response, error
 
 // newClient constructs a cache with predefined manifests for testing. The manifests are:
 //
-//	empty: no data
-//	zero: no layers
-//	single: one layer with the contents "exists"
-//	multiple: two layers with the contents "exists" and "here"
-//	notfound: a layer that does not exist in the cache
-//	null: one null layer (e.g. [null])
-//	sizemismatch: one valid layer, and one with a size mismatch (file size is less than the reported size)
-//	invalid: a layer with invalid JSON data
+//	empty:         no data
+//	zero:          no layers
+//	single:        one layer with the contents "exists"
+//	multiple:      two layers with the contents "exists" and "here"
+//	notfound:      a layer that does not exist in the cache
+//	null:          one null layer (e.g. [null])
+//	sizemismatch:  one valid layer, and one with a size mismatch (file size is less than the reported size)
+//	invalid:       a layer with invalid JSON data
 //
 // Tests that want to ensure the client does not communicate with the upstream
 // registry should pass a nil handler, which will cause a panic if
 // communication is attempted.
 //
 // To simulate a network error, pass a handler that returns a 499 status code.
-func newClient(t *testing.T, h http.HandlerFunc) (*Registry, *blob.DiskCache) {
+func newClient(t *testing.T, upstreamRegistry http.HandlerFunc) (*Registry, *blob.DiskCache) {
 	t.Helper()
 
 	c, err := blob.Open(t.TempDir())
@@ -88,7 +89,7 @@ func newClient(t *testing.T, h http.HandlerFunc) (*Registry, *blob.DiskCache) {
 	r := &Registry{
 		Cache: c,
 		HTTPClient: &http.Client{
-			Transport: recordRoundTripper(h),
+			Transport: recordRoundTripper(upstreamRegistry),
 		},
 	}
 
@@ -767,3 +768,74 @@ func TestUnlink(t *testing.T) {
 		}
 	})
 }
+
+func TestPullChunksums(t *testing.T) {
+	check := testutil.Checker(t)
+
+	content := "hello"
+	var chunksums string
+	contentDigest := func() blob.Digest {
+		return blob.DigestFromBytes(content)
+	}
+	rc, c := newClient(t, func(w http.ResponseWriter, r *http.Request) {
+		switch {
+		case strings.Contains(r.URL.Path, "/manifests/latest"):
+			fmt.Fprintf(w, `{"layers":[{"digest":%q,"size":%d}]}`, contentDigest(), len(content))
+		case strings.HasSuffix(r.URL.Path, "/chunksums/"+contentDigest().String()):
+			loc := fmt.Sprintf("http://blob.store/v2/library/test/blobs/%s", contentDigest())
+			w.Header().Set("Content-Location", loc)
+			io.WriteString(w, chunksums)
+		case strings.Contains(r.URL.Path, "/blobs/"+contentDigest().String()):
+			http.ServeContent(w, r, contentDigest().String(), time.Time{}, strings.NewReader(content))
+		default:
+			t.Errorf("unexpected request: %v", r)
+			http.NotFound(w, r)
+		}
+	})
+
+	rc.MaxStreams = 1        // prevent concurrent chunk downloads
+	rc.ChunkingThreshold = 1 // for all blobs to be chunked
+
+	var mu sync.Mutex
+	var reads []int64
+	ctx := WithTrace(t.Context(), &Trace{
+		Update: func(l *Layer, n int64, err error) {
+			t.Logf("Update: %v %d %v", l, n, err)
+			mu.Lock()
+			reads = append(reads, n)
+			mu.Unlock()
+		},
+	})
+
+	chunksums = fmt.Sprintf("%s 0-2\n%s 3-4\n",
+		blob.DigestFromBytes("hel"),
+		blob.DigestFromBytes("lo"),
+	)
+	err := rc.Pull(ctx, "test")
+	check(err)
+	if !slices.Equal(reads, []int64{0, 3, 5}) {
+		t.Errorf("reads = %v; want %v", reads, []int64{0, 3, 5})
+	}
+
+	mw, err := rc.Resolve(t.Context(), "test")
+	check(err)
+	mg, err := rc.ResolveLocal("test")
+	check(err)
+	if !reflect.DeepEqual(mw, mg) {
+		t.Errorf("mw = %v; mg = %v", mw, mg)
+	}
+	for i := range mg.Layers {
+		_, err = c.Get(mg.Layers[i].Digest)
+		if err != nil {
+			t.Errorf("Get(%v): %v", mg.Layers[i].Digest, err)
+		}
+	}
+
+	// missing chunks
+	content = "llama"
+	chunksums = fmt.Sprintf("%s 0-1\n", blob.DigestFromBytes("ll"))
+	err = rc.Pull(ctx, "missingchunks")
+	if err == nil {
+		t.Error("expected error because of missing chunks")
+	}
+}

From b078dd157cbca4ba31ce49128b0d8e1e4da99b39 Mon Sep 17 00:00:00 2001
From: Jesse Gross <jesse@ollama.com>
Date: Wed, 19 Mar 2025 15:34:41 -0700
Subject: [PATCH 112/157] gemma2: Remove second call to Rows

Looks like a merge conflict that broke the model.
---
 model/models/gemma2/model.go | 3 +--
 1 file changed, 1 insertion(+), 2 deletions(-)

diff --git a/model/models/gemma2/model.go b/model/models/gemma2/model.go
index fbefebe2..29ffa231 100644
--- a/model/models/gemma2/model.go
+++ b/model/models/gemma2/model.go
@@ -211,8 +211,7 @@ func (m *Model) Forward(ctx ml.Context, opts input.Options) (ml.Tensor, error) {
 	// final logit softcap
 	hiddenState = hiddenState.Scale(ctx, 1.0/float64(m.Options.finalLogitSoftcap))
 	hiddenState = hiddenState.Tanh(ctx)
-	hiddenState = hiddenState.Scale(ctx, float64(m.Options.finalLogitSoftcap))
-	return hiddenState.Rows(ctx, outputs), nil
+	return hiddenState.Scale(ctx, float64(m.Options.finalLogitSoftcap)), nil
 }
 
 func init() {

From f8c3dbe5b5ee342d97e4c71d684b85b00273c33d Mon Sep 17 00:00:00 2001
From: Patrick Devine <patrick@infrahq.com>
Date: Thu, 20 Mar 2025 00:15:30 -0700
Subject: [PATCH 113/157] templates: add autotemplate for gemma3 (#9880)

This change allows the gemma3 template to be autodetected during `ollama
create`.
---
 server/model.go                                     |  2 +-
 template/gemma3-instruct.gotmpl                     | 13 +++++++++++++
 template/gemma3-instruct.json                       |  6 ++++++
 template/index.json                                 |  4 ++++
 .../system-user-assistant-user                      | 10 ++++++++++
 template/testdata/gemma3-instruct.gotmpl/user       |  4 ++++
 .../gemma3-instruct.gotmpl/user-assistant-user      |  8 ++++++++
 7 files changed, 46 insertions(+), 1 deletion(-)
 create mode 100644 template/gemma3-instruct.gotmpl
 create mode 100644 template/gemma3-instruct.json
 create mode 100644 template/testdata/gemma3-instruct.gotmpl/system-user-assistant-user
 create mode 100644 template/testdata/gemma3-instruct.gotmpl/user
 create mode 100644 template/testdata/gemma3-instruct.gotmpl/user-assistant-user

diff --git a/server/model.go b/server/model.go
index 4c82fb99..d0f503e2 100644
--- a/server/model.go
+++ b/server/model.go
@@ -82,7 +82,7 @@ func detectChatTemplate(layers []*layerGGML) ([]*layerGGML, error) {
 	for _, layer := range layers {
 		if s := layer.GGML.KV().ChatTemplate(); s != "" {
 			if t, err := template.Named(s); err != nil {
-				slog.Debug("template detection", "error", err)
+				slog.Debug("template detection", "error", err, "template", s)
 			} else {
 				layer, err := NewLayer(t.Reader(), "application/vnd.ollama.image.template")
 				if err != nil {
diff --git a/template/gemma3-instruct.gotmpl b/template/gemma3-instruct.gotmpl
new file mode 100644
index 00000000..eb69d9f5
--- /dev/null
+++ b/template/gemma3-instruct.gotmpl
@@ -0,0 +1,13 @@
+{{- range $i, $_ := .Messages }}
+{{- $last := eq (len (slice $.Messages $i)) 1 }}
+{{- if eq .Role "user" }}<start_of_turn>user
+{{- if and (eq $i 1) $.System }}
+{{ $.System }}
+{{ end }}
+{{ .Content }}<end_of_turn>
+{{ else if eq .Role "assistant" }}<start_of_turn>model
+{{ .Content }}<end_of_turn>
+{{ end }}
+{{- if $last }}<start_of_turn>model
+{{ end }}
+{{- end }}
diff --git a/template/gemma3-instruct.json b/template/gemma3-instruct.json
new file mode 100644
index 00000000..b1dac3fe
--- /dev/null
+++ b/template/gemma3-instruct.json
@@ -0,0 +1,6 @@
+{
+  "stop": [
+    "<end_of_turn>"
+  ],
+  "temperature": 0.1
+}
diff --git a/template/index.json b/template/index.json
index 7a27747c..5714665a 100644
--- a/template/index.json
+++ b/template/index.json
@@ -87,6 +87,10 @@
     "template": "{{ bos_token }}{% if messages[0]['role'] == 'system' %}{{ raise_exception('System role not supported') }}{% endif %}{% for message in messages %}{% if (message['role'] == 'user') != (loop.index0 % 2 == 0) %}{{ raise_exception('Conversation roles must alternate user/assistant/user/assistant/...') }}{% endif %}{% if (message['role'] == 'assistant') %}{% set role = 'model' %}{% else %}{% set role = message['role'] %}{% endif %}{{ '<start_of_turn>' + role + '\n' + message['content'] | trim + '<end_of_turn>\n' }}{% endfor %}{% if add_generation_prompt %}{{'<start_of_turn>model\n'}}{% endif %}",
     "name": "gemma-instruct"
   },
+  {
+    "template": "{{ bos_token }}\n{%- if messages[0]['role'] == 'system' -%}\n    {%- if messages[0]['content'] is string -%}\n        {%- set first_user_prefix = messages[0]['content'] + '\n\n' -%}\n    {%- else -%}\n        {%- set first_user_prefix = messages[0]['content'][0]['text'] + '\n\n' -%}\n    {%- endif -%}\n    {%- set loop_messages = messages[1:] -%}\n{%- else -%}\n    {%- set first_user_prefix = \"\" -%}\n    {%- set loop_messages = messages -%}\n{%- endif -%}\n{%- for message in loop_messages -%}\n    {%- if (message['role'] == 'user') != (loop.index0 % 2 == 0) -%}\n        {{ raise_exception(\"Conversation roles must alternate user/assistant/user/assistant/...\") }}\n    {%- endif -%}\n    {%- if (message['role'] == 'assistant') -%}\n        {%- set role = \"model\" -%}\n    {%- else -%}\n        {%- set role = message['role'] -%}\n    {%- endif -%}\n    {{ '<start_of_turn>' + role + '\n' + (first_user_prefix if loop.first else \"\") }}\n    {%- if message['content'] is string -%}\n        {{ message['content'] | trim }}\n    {%- elif message['content'] is iterable -%}\n        {%- for item in message['content'] -%}\n            {%- if item['type'] == 'image' -%}\n                {{ '<start_of_image>' }}\n            {%- elif item['type'] == 'text' -%}\n                {{ item['text'] | trim }}\n            {%- endif -%}\n        {%- endfor -%}\n    {%- else -%}\n        {{ raise_exception(\"Invalid content type\") }}\n    {%- endif -%}\n    {{ '<end_of_turn>\n' }}\n{%- endfor -%}\n{%- if add_generation_prompt -%}\n    {{'<start_of_turn>model\n'}}\n{%- endif -%}\n",
+    "name": "gemma3-instruct"
+  },
   {
     "template": "{% set loop_messages = messages %}{% for message in loop_messages %}{% set content = '<|start_header_id|>' + message['role'] + '<|end_header_id|>\n\n'+ message['content'] | trim + '<|eot_id|>' %}{% if loop.index0 == 0 %}{% set content = bos_token + content %}{% endif %}{{ content }}{% endfor %}{% if add_generation_prompt %}{{ '<|start_header_id|>assistant<|end_header_id|>\n\n' }}{% endif %}",
     "name": "llama3-instruct"
diff --git a/template/testdata/gemma3-instruct.gotmpl/system-user-assistant-user b/template/testdata/gemma3-instruct.gotmpl/system-user-assistant-user
new file mode 100644
index 00000000..5453a1db
--- /dev/null
+++ b/template/testdata/gemma3-instruct.gotmpl/system-user-assistant-user
@@ -0,0 +1,10 @@
+<start_of_turn>user
+You are a helpful assistant.
+
+Hello, how are you?<end_of_turn>
+<start_of_turn>model
+I'm doing great. How can I help you today?<end_of_turn>
+<start_of_turn>user
+I'd like to show off how chat templating works!<end_of_turn>
+<start_of_turn>model
+
diff --git a/template/testdata/gemma3-instruct.gotmpl/user b/template/testdata/gemma3-instruct.gotmpl/user
new file mode 100644
index 00000000..fed1f5fa
--- /dev/null
+++ b/template/testdata/gemma3-instruct.gotmpl/user
@@ -0,0 +1,4 @@
+<start_of_turn>user
+Hello, how are you?<end_of_turn>
+<start_of_turn>model
+
diff --git a/template/testdata/gemma3-instruct.gotmpl/user-assistant-user b/template/testdata/gemma3-instruct.gotmpl/user-assistant-user
new file mode 100644
index 00000000..ab15a071
--- /dev/null
+++ b/template/testdata/gemma3-instruct.gotmpl/user-assistant-user
@@ -0,0 +1,8 @@
+<start_of_turn>user
+Hello, how are you?<end_of_turn>
+<start_of_turn>model
+I'm doing great. How can I help you today?<end_of_turn>
+<start_of_turn>user
+I'd like to show off how chat templating works!<end_of_turn>
+<start_of_turn>model
+

From 42a14f7f633110ab83343848865d4612cfefb398 Mon Sep 17 00:00:00 2001
From: Parth Sareen <parth.sareen@ollama.com>
Date: Thu, 20 Mar 2025 11:11:18 -0700
Subject: [PATCH 114/157] sample: add error handling for empty logits (#9740)

---
 sample/samplers.go        | 14 +++----
 sample/samplers_test.go   | 24 +++++++++++
 sample/transforms_test.go | 88 +++++++++++++++++++++++++++++----------
 3 files changed, 97 insertions(+), 29 deletions(-)

diff --git a/sample/samplers.go b/sample/samplers.go
index 7c12da08..ef803369 100644
--- a/sample/samplers.go
+++ b/sample/samplers.go
@@ -26,6 +26,10 @@ type Sampler struct {
 }
 
 func (s *Sampler) Sample(logits []float32) (int32, error) {
+	if len(logits) == 0 {
+		return -1, errors.New("sample: no logits provided to sample")
+	}
+
 	tokens := make([]token, len(logits))
 	for i := range logits {
 		tokens[i].id = int32(i)
@@ -94,13 +98,6 @@ func (s *Sampler) sample(tokens []token) (token, error) {
 	tokens = topP(tokens, s.topP)
 	tokens = minP(tokens, s.minP)
 
-	// TODO: this should fall back to greedy sampling
-	// or topP, topK values etc should be such that
-	// there are always tokens to sample from
-	if len(tokens) == 0 {
-		return token{}, errors.New("no tokens to sample from")
-	}
-
 	var r float32
 	if s.rng != nil {
 		r = s.rng.Float32()
@@ -123,6 +120,9 @@ func (s *Sampler) sample(tokens []token) (token, error) {
 		return 1
 	})
 
+	if math.IsNaN(float64(sum)) {
+		return token{}, errors.New("sample: logits sum to NaN, check model output")
+	}
 	return tokens[idx], nil
 }
 
diff --git a/sample/samplers_test.go b/sample/samplers_test.go
index 38b9b352..d79dce47 100644
--- a/sample/samplers_test.go
+++ b/sample/samplers_test.go
@@ -1,6 +1,7 @@
 package sample
 
 import (
+	"math"
 	"math/rand/v2"
 	"testing"
 )
@@ -29,6 +30,29 @@ func TestWeighted(t *testing.T) {
 	if want != got {
 		t.Errorf("index mismatch: want %d, got %d", want, got)
 	}
+
+	// Test very high p
+	logits = []float32{1.0, 0.9999999999999999, 0.5, 0.1}
+	// Use extremely small topP to filter out all tokens
+	sampler = NewSampler(1.0, 0, 1e-10, 0, 0, nil)
+	got, err = sampler.Sample(logits)
+	if err != nil {
+		t.Error(err)
+		return
+	}
+	// Should get the token with the highest logit
+	want = int32(0)
+	if want != got {
+		t.Errorf("index mismatch: want %d, got %d", want, got)
+	}
+
+	logits = []float32{float32(math.NaN()), float32(math.NaN()), float32(math.NaN())}
+	sampler = NewSampler(1, 0, 0.95, 0.05, 0, nil)
+	got, err = sampler.Sample(logits)
+	if err == nil {
+		t.Errorf("expected error, got %d", got)
+		return
+	}
 }
 
 func BenchmarkSample(b *testing.B) {
diff --git a/sample/transforms_test.go b/sample/transforms_test.go
index 7faf30a5..5307c5f8 100644
--- a/sample/transforms_test.go
+++ b/sample/transforms_test.go
@@ -168,27 +168,53 @@ func TestTopP(t *testing.T) {
 	softmax(tokens)
 	tokens = topK(tokens, 20)
 
-	// Then apply topP
-	tokens = topP(tokens, 0.95)
+	// Test with very high p value
+	got := topP(tokens, 1.0)
 
-	// Should keep tokens until cumsum > 0.95
-	if len(tokens) > 3 {
+	// Should keep all tokens since p is 1
+	if len(got) != len(input) {
+		t.Errorf("topP(1.0): should keep all tokens, got %d, want %d", len(got), len(input))
+	}
+
+	// Test with normal p value
+	got = topP(tokens, 0.95)
+
+	if len(got) > 3 {
 		t.Errorf("topP(0.95): kept too many tokens: got %d", len(tokens))
-		t.Logf("got: %v", tokens)
+		t.Logf("got: %v", got)
 	}
 
 	// Test edge case - ensure at least one token remains
-	input = []float32{-1e6, -1e6, -1e6} // One dominant token
+	input = []float32{-1e6, -1e6, -1e7}
 	tokens = toTokens(input)
+	tokens = topK(tokens, 20)
 	softmax(tokens)
-	tokens = topP(tokens, 0.0) // Very small p
-	if len(tokens) < 1 {
+	got = topP(tokens, 0.0)
+	if len(got) < 1 {
 		t.Error("topP should keep at least one token")
 	}
+
+	// Test with zero p value
+	got = topP(tokens, 0.0)
+
+	// Should keep only the highest probability token
+	if len(got) != 1 {
+		t.Errorf("topP(0.0): should keep only one token, got %d", len(got))
+		t.Logf("got: %v", got)
+	}
+
+	tokens = toTokens(input)
+	tokens = topK(tokens, 20)
+	softmax(tokens)
+	got = topP(tokens, 1e-10)
+	if len(got) == 0 {
+		t.Errorf("topP(1e-10): should keep at least one token, got %d", len(got))
+		t.Logf("got: %v", got)
+	}
 }
 
 func TestMinP(t *testing.T) {
-	input := []float32{-3, -2, -1, 0, 1, 2, 4, 3}
+	input := []float32{-2, 0, -1, -3, 2, 1, 4, 3}
 	tokens := toTokens(input)
 
 	// First apply temperature and softmax
@@ -225,30 +251,48 @@ func TestMinP(t *testing.T) {
 		t.Logf("got: %v", tokens)
 	}
 
+	// Test with single token
+	tokens = toTokens(input[:1])
+	tokens = topK(tokens, 20)
+	softmax(tokens)
+	tokens = minP(tokens, 0.1)
+
+	// Should keep only the highest probability token
+	if len(tokens) != 1 {
+		t.Errorf("minP(0.1): should return single token, got %d", len(tokens))
+		t.Logf("got: %v", tokens)
+	}
+
 	input = []float32{1e-10, 1e-10, 1e-10}
 	tokens = toTokens(input)
 	softmax(tokens)
 	tokens = minP(tokens, 1.0)
 	if len(tokens) < 1 {
 		t.Error("minP should keep at least one token even with extreme probabilities")
-	}
-}
+		got := minP(tokens, 1.0)
 
-func TestSortLogits(t *testing.T) {
-	input := []float32{0.026986899, 0.043722924, 0.036774673, 0.27755088, 0.0046718004, 0.08582123, 0.20409796, 0.00412893, 0.15720603, 0.045046154, 0.0030491839, 0.01681367}
-	tokens := toTokens(input)
+		if len(got) != 1 {
+			t.Errorf("minP(1.0): should keep all tokens, got %d, want %d", len(got), len(tokens))
+		}
 
-	tokens = topK(tokens, 20)
+		// Test with normal p value
+		got = minP(tokens, 0.2)
 
-	for i := 1; i < len(tokens); i++ {
-		if tokens[i].value > tokens[i-1].value {
-			t.Errorf("sortLogits: tokens not sorted in descending order at index %d: %f > %f",
-				i, tokens[i].value, tokens[i-1].value)
+		// Should keep tokens with prob >= 0.2 * max_prob
+		if len(got) > 3 {
+			t.Errorf("minP(0.2): kept too many tokens: got %d", len(got))
+			t.Logf("got: %v", got)
+		}
+
+		// Test with zero p value
+		got = minP(tokens, 0.0)
+
+		// Should keep only the highest probability token
+		if len(got) != len(tokens) {
+			t.Errorf("minP(0.0): should keep only one token, got %d", len(got))
+			t.Logf("got: %v", got)
 		}
 	}
-
-	want := []float32{0.27755088, 0.20409796, 0.15720603, 0.08582123, 0.045046154, 0.043722924, 0.036774673, 0.026986899, 0.01681367, 0.0046718004, 0.00412893, 0.0030491839}
-	compareLogits(t, "sortLogits", want, tokens)
 }
 
 func BenchmarkTransforms(b *testing.B) {

From ffbfe833da387f9b6806fe887b85992c11d26eaa Mon Sep 17 00:00:00 2001
From: rylativity <41017744+rylativity@users.noreply.github.com>
Date: Thu, 20 Mar 2025 16:11:17 -0400
Subject: [PATCH 115/157] parser: remove role validation from Modelfile parser
 (#9874)

* updates parser/parser.go to allow arbitrary roles in Modelfile MESSAGE blocks
---
 parser/parser.go      | 18 +++++++-----------
 parser/parser_test.go | 10 +++++-----
 2 files changed, 12 insertions(+), 16 deletions(-)

diff --git a/parser/parser.go b/parser/parser.go
index 6832351f..0a32d571 100644
--- a/parser/parser.go
+++ b/parser/parser.go
@@ -7,6 +7,7 @@ import (
 	"errors"
 	"fmt"
 	"io"
+	"log/slog"
 	"net/http"
 	"os"
 	"os/user"
@@ -300,9 +301,8 @@ const (
 )
 
 var (
-	errMissingFrom        = errors.New("no FROM line")
-	errInvalidMessageRole = errors.New("message role must be one of \"system\", \"user\", or \"assistant\"")
-	errInvalidCommand     = errors.New("command must be one of \"from\", \"license\", \"template\", \"system\", \"adapter\", \"parameter\", or \"message\"")
+	errMissingFrom    = errors.New("no FROM line")
+	errInvalidCommand = errors.New("command must be one of \"from\", \"license\", \"template\", \"system\", \"adapter\", \"parameter\", or \"message\"")
 )
 
 type ParserError struct {
@@ -379,14 +379,10 @@ func ParseFile(r io.Reader) (*Modelfile, error) {
 			case stateParameter:
 				cmd.Name = b.String()
 			case stateMessage:
-				if !isValidMessageRole(b.String()) {
-					return nil, &ParserError{
-						LineNumber: currLine,
-						Msg:        errInvalidMessageRole.Error(),
-					}
-				}
-
 				role = b.String()
+				if !isKnownMessageRole(b.String()) {
+					slog.Warn("received non-standard role", "role", role)
+				}
 			case stateComment, stateNil:
 				// pass
 			case stateValue:
@@ -556,7 +552,7 @@ func isNewline(r rune) bool {
 	return r == '\r' || r == '\n'
 }
 
-func isValidMessageRole(role string) bool {
+func isKnownMessageRole(role string) bool {
 	return role == "system" || role == "user" || role == "assistant"
 }
 
diff --git a/parser/parser_test.go b/parser/parser_test.go
index 097c058f..c4f8f4aa 100644
--- a/parser/parser_test.go
+++ b/parser/parser_test.go
@@ -256,13 +256,13 @@ You are a multiline file parser. Always parse things.
 		{
 			`
 FROM foo
-MESSAGE badguy I'm a bad guy!
+MESSAGE somerandomrole I'm ok with you adding any role message now!
 `,
-			nil,
-			&ParserError{
-				LineNumber: 3,
-				Msg:        errInvalidMessageRole.Error(),
+			[]Command{
+				{Name: "model", Args: "foo"},
+				{Name: "message", Args: "somerandomrole: I'm ok with you adding any role message now!"},
 			},
+			nil,
 		},
 		{
 			`

From 0c220935bd9e23339af1c8f943f5418cbe1b705b Mon Sep 17 00:00:00 2001
From: Jesse Gross <jesse@ollama.com>
Date: Wed, 19 Mar 2025 14:28:15 -0700
Subject: [PATCH 116/157] input: Rename Options to Batch

Options is no longer very descriptive of this struct.
---
 kvcache/cache.go                  |  2 +-
 kvcache/causal.go                 | 12 ++++++------
 kvcache/causal_test.go            |  2 +-
 kvcache/encoder.go                |  6 +++---
 kvcache/wrapper.go                |  8 ++++----
 model/input/input.go              | 25 +++++++++++++++++++------
 model/model.go                    | 14 +++++++-------
 model/model_test.go               |  2 +-
 model/models/gemma2/model.go      |  8 ++++----
 model/models/gemma3/model.go      | 10 +++++-----
 model/models/gemma3/model_text.go |  4 ++--
 model/models/llama/model.go       |  8 ++++----
 model/models/mllama/model.go      | 12 ++++++------
 runner/ollamarunner/runner.go     | 20 ++++++++++----------
 14 files changed, 73 insertions(+), 60 deletions(-)

diff --git a/kvcache/cache.go b/kvcache/cache.go
index d3548905..aa0a2056 100644
--- a/kvcache/cache.go
+++ b/kvcache/cache.go
@@ -52,7 +52,7 @@ type Cache interface {
 	// StartForward is called before the start of the model's forward pass.
 	// For each token in the coming batch, there must be a corresponding
 	// entry in positions and seqs.
-	StartForward(ctx ml.Context, opts input.Options) error
+	StartForward(ctx ml.Context, batch input.Batch) error
 
 	// CopyPrefix copies tokens in the range [0, len) from srcSeq to dstSeq
 	CopyPrefix(srcSeq, dstSeq int, len int32)
diff --git a/kvcache/causal.go b/kvcache/causal.go
index edf6666d..79fa24e8 100644
--- a/kvcache/causal.go
+++ b/kvcache/causal.go
@@ -140,10 +140,10 @@ func (c *Causal) Close() {
 	}
 }
 
-func (c *Causal) StartForward(ctx ml.Context, opts input.Options) error {
-	c.curBatchSize = len(opts.Positions)
-	c.curSequences = opts.Sequences
-	c.curPositions = opts.Positions
+func (c *Causal) StartForward(ctx ml.Context, batch input.Batch) error {
+	c.curBatchSize = len(batch.Positions)
+	c.curSequences = batch.Sequences
+	c.curPositions = batch.Positions
 	c.opts.Except = nil
 
 	var err error
@@ -157,8 +157,8 @@ func (c *Causal) StartForward(ctx ml.Context, opts input.Options) error {
 	}
 
 	c.curCellRange = newRange()
-	for i, pos := range opts.Positions {
-		seq := opts.Sequences[i]
+	for i, pos := range batch.Positions {
+		seq := batch.Sequences[i]
 
 		c.cells[c.curLoc+i] = cacheCell{pos: pos, sequences: []int{seq}}
 
diff --git a/kvcache/causal_test.go b/kvcache/causal_test.go
index 56d85ceb..0f2385db 100644
--- a/kvcache/causal_test.go
+++ b/kvcache/causal_test.go
@@ -270,7 +270,7 @@ func testCache(t *testing.T, backend ml.Backend, cache Cache, tests []testCase)
 			context := backend.NewContext()
 			defer context.Close()
 
-			err := cache.StartForward(context, input.Options{Positions: test.pos, Sequences: test.seqs})
+			err := cache.StartForward(context, input.Batch{Positions: test.pos, Sequences: test.seqs})
 			if err != nil {
 				panic(err)
 			}
diff --git a/kvcache/encoder.go b/kvcache/encoder.go
index 6a9df2ab..94c5d99c 100644
--- a/kvcache/encoder.go
+++ b/kvcache/encoder.go
@@ -79,10 +79,10 @@ func (c *EncoderCache) Close() {
 	}
 }
 
-func (c *EncoderCache) StartForward(ctx ml.Context, opts input.Options) error {
+func (c *EncoderCache) StartForward(ctx ml.Context, batch input.Batch) error {
 	// We work with the most recent image
-	if len(opts.Multimodal) > 0 {
-		c.curPos = opts.Positions[opts.Multimodal[len(opts.Multimodal)-1].Index]
+	if len(batch.Multimodal) > 0 {
+		c.curPos = batch.Positions[batch.Multimodal[len(batch.Multimodal)-1].Index]
 	}
 
 	return nil
diff --git a/kvcache/wrapper.go b/kvcache/wrapper.go
index aaccd166..c85807a0 100644
--- a/kvcache/wrapper.go
+++ b/kvcache/wrapper.go
@@ -41,14 +41,14 @@ func (c *WrapperCache) Close() {
 	}
 }
 
-func (c *WrapperCache) StartForward(ctx ml.Context, opts input.Options) error {
+func (c *WrapperCache) StartForward(ctx ml.Context, batch input.Batch) error {
 	for i, cache := range c.caches {
-		err := cache.StartForward(ctx, opts)
+		err := cache.StartForward(ctx, batch)
 		if err != nil {
 			// unwind on error - Remove with endIndex set to math.MaxInt32 does not fail
 			for j := i - 1; j >= 0; j-- {
-				for k := range opts.Positions {
-					_ = c.caches[j].Remove(opts.Sequences[k], opts.Positions[k], math.MaxInt32)
+				for k := range batch.Positions {
+					_ = c.caches[j].Remove(batch.Sequences[k], batch.Positions[k], math.MaxInt32)
 				}
 			}
 			return err
diff --git a/model/input/input.go b/model/input/input.go
index 30bdcf06..ce43efb5 100644
--- a/model/input/input.go
+++ b/model/input/input.go
@@ -33,11 +33,24 @@ type MultimodalIndex struct {
 	Multimodal any
 }
 
-// Options contains the inputs for a model forward pass
-type Options struct {
-	Inputs     []int32
+// Batch contains the inputs for a model forward pass
+type Batch struct {
+	// Inputs is the input tokens, including placeholders for multimodal inputs.
+	Inputs []int32
+
+	// Multimodal is a set of multimodal embeddings previously created by
+	// EncodeMultimodal, along with an index into Inputs. Unused for text-only
+	// models or for batches without multimodal elements.
 	Multimodal []MultimodalIndex
-	Positions  []int32
-	Sequences  []int
-	Outputs    []int32
+
+	// Positions is the position for each Input, relative to its sequence. Equal
+	// in length to Inputs.
+	Positions []int32
+
+	// Sequences is the sequence for each Input. Equal in length to Inputs.
+	Sequences []int
+
+	// Outputs are the set of indicies into Inputs for which output data should
+	// be returned.
+	Outputs []int32
 }
diff --git a/model/model.go b/model/model.go
index 53e47add..94156ae2 100644
--- a/model/model.go
+++ b/model/model.go
@@ -26,7 +26,7 @@ var ErrNoVisionModel = errors.New("this model is missing data required for image
 
 // Model implements a specific model architecture, defining the forward pass and any model-specific configuration
 type Model interface {
-	Forward(ml.Context, input.Options) (ml.Tensor, error)
+	Forward(ml.Context, input.Batch) (ml.Tensor, error)
 
 	Backend() ml.Backend
 	Config() config
@@ -280,24 +280,24 @@ func canNil(t reflect.Type) bool {
 		t.Kind() == reflect.Slice
 }
 
-func Forward(ctx ml.Context, m Model, opts input.Options) (ml.Tensor, error) {
-	if len(opts.Positions) != len(opts.Sequences) {
-		return nil, fmt.Errorf("length of positions (%v) must match length of seqs (%v)", len(opts.Positions), len(opts.Sequences))
+func Forward(ctx ml.Context, m Model, batch input.Batch) (ml.Tensor, error) {
+	if len(batch.Positions) != len(batch.Sequences) {
+		return nil, fmt.Errorf("length of positions (%v) must match length of seqs (%v)", len(batch.Positions), len(batch.Sequences))
 	}
 
-	if len(opts.Positions) < 1 {
+	if len(batch.Positions) < 1 {
 		return nil, errors.New("batch size cannot be less than 1")
 	}
 
 	cache := m.Config().Cache
 	if cache != nil {
-		err := cache.StartForward(ctx, opts)
+		err := cache.StartForward(ctx, batch)
 		if err != nil {
 			return nil, err
 		}
 	}
 
-	t, err := m.Forward(ctx, opts)
+	t, err := m.Forward(ctx, batch)
 	if err != nil {
 		return nil, err
 	}
diff --git a/model/model_test.go b/model/model_test.go
index 354dd1d8..0b1ea08e 100644
--- a/model/model_test.go
+++ b/model/model_test.go
@@ -163,7 +163,7 @@ func TestGetTextProcessor(t *testing.T) {
 
 type notTextProcessorModel struct{}
 
-func (notTextProcessorModel) Forward(ml.Context, input.Options) (ml.Tensor, error) {
+func (notTextProcessorModel) Forward(ml.Context, input.Batch) (ml.Tensor, error) {
 	panic("unimplemented")
 }
 
diff --git a/model/models/gemma2/model.go b/model/models/gemma2/model.go
index 29ffa231..2b347d72 100644
--- a/model/models/gemma2/model.go
+++ b/model/models/gemma2/model.go
@@ -168,18 +168,18 @@ func (l *Layer) Forward(ctx ml.Context, hiddenState, positionIDs, outputs ml.Ten
 	return hiddenState.Add(ctx, residual)
 }
 
-func (m *Model) Forward(ctx ml.Context, opts input.Options) (ml.Tensor, error) {
-	inputs, err := ctx.Input().FromIntSlice(opts.Inputs, len(opts.Inputs))
+func (m *Model) Forward(ctx ml.Context, batch input.Batch) (ml.Tensor, error) {
+	inputs, err := ctx.Input().FromIntSlice(batch.Inputs, len(batch.Inputs))
 	if err != nil {
 		return nil, err
 	}
 
-	positions, err := ctx.Input().FromIntSlice(opts.Positions, len(opts.Positions))
+	positions, err := ctx.Input().FromIntSlice(batch.Positions, len(batch.Positions))
 	if err != nil {
 		return nil, err
 	}
 
-	outputs, err := ctx.Input().FromIntSlice(opts.Outputs, len(opts.Outputs))
+	outputs, err := ctx.Input().FromIntSlice(batch.Outputs, len(batch.Outputs))
 	if err != nil {
 		return nil, err
 	}
diff --git a/model/models/gemma3/model.go b/model/models/gemma3/model.go
index 95f89ad4..900bf31e 100644
--- a/model/models/gemma3/model.go
+++ b/model/models/gemma3/model.go
@@ -139,23 +139,23 @@ func (m *Model) PostTokenize(inputs []input.Input) ([]input.Input, error) {
 	return result, nil
 }
 
-func (m *Model) Forward(ctx ml.Context, opts input.Options) (ml.Tensor, error) {
-	inputs, err := ctx.Input().FromIntSlice(opts.Inputs, len(opts.Inputs))
+func (m *Model) Forward(ctx ml.Context, batch input.Batch) (ml.Tensor, error) {
+	inputs, err := ctx.Input().FromIntSlice(batch.Inputs, len(batch.Inputs))
 	if err != nil {
 		return nil, err
 	}
 
-	positions, err := ctx.Input().FromIntSlice(opts.Positions, len(opts.Positions))
+	positions, err := ctx.Input().FromIntSlice(batch.Positions, len(batch.Positions))
 	if err != nil {
 		return nil, err
 	}
 
-	outputs, err := ctx.Input().FromIntSlice(opts.Outputs, len(opts.Outputs))
+	outputs, err := ctx.Input().FromIntSlice(batch.Outputs, len(batch.Outputs))
 	if err != nil {
 		return nil, err
 	}
 
-	return m.TextModel.Forward(ctx, inputs, positions, outputs, opts, m.Cache), nil
+	return m.TextModel.Forward(ctx, inputs, positions, outputs, batch, m.Cache), nil
 }
 
 func init() {
diff --git a/model/models/gemma3/model_text.go b/model/models/gemma3/model_text.go
index 567f65a5..7d8b6577 100644
--- a/model/models/gemma3/model_text.go
+++ b/model/models/gemma3/model_text.go
@@ -171,13 +171,13 @@ func (l *TextLayer) Forward(ctx ml.Context, layer int, hiddenState, positionIDs,
 	return hiddenState.Add(ctx, residual)
 }
 
-func (m *TextModel) Forward(ctx ml.Context, inputs, positions, outputs ml.Tensor, opts input.Options, cache kvcache.Cache) ml.Tensor {
+func (m *TextModel) Forward(ctx ml.Context, inputs, positions, outputs ml.Tensor, batch input.Batch, cache kvcache.Cache) ml.Tensor {
 	hiddenState := m.TokenEmbedding.Forward(ctx, inputs)
 	hiddenState = hiddenState.Scale(ctx, math.Sqrt(float64(m.TextOptions.hiddenSize)))
 
 	// set image embeddings
 	var except []int
-	for _, image := range opts.Multimodal {
+	for _, image := range batch.Multimodal {
 		visionOutputs := image.Multimodal.(ml.Tensor)
 		ctx.Forward(visionOutputs.Copy(ctx, hiddenState.View(ctx, image.Index*hiddenState.Stride(1), visionOutputs.Dim(0)*visionOutputs.Dim(1))))
 
diff --git a/model/models/llama/model.go b/model/models/llama/model.go
index 87eb9b75..e5ecd29e 100644
--- a/model/models/llama/model.go
+++ b/model/models/llama/model.go
@@ -139,18 +139,18 @@ func (l *Layer) Forward(ctx ml.Context, hiddenState, positionIDs, outputs ml.Ten
 	return hiddenState.Add(ctx, residual)
 }
 
-func (m *Model) Forward(ctx ml.Context, opts input.Options) (ml.Tensor, error) {
-	inputs, err := ctx.Input().FromIntSlice(opts.Inputs, len(opts.Inputs))
+func (m *Model) Forward(ctx ml.Context, batch input.Batch) (ml.Tensor, error) {
+	inputs, err := ctx.Input().FromIntSlice(batch.Inputs, len(batch.Inputs))
 	if err != nil {
 		return nil, err
 	}
 
-	positions, err := ctx.Input().FromIntSlice(opts.Positions, len(opts.Positions))
+	positions, err := ctx.Input().FromIntSlice(batch.Positions, len(batch.Positions))
 	if err != nil {
 		return nil, err
 	}
 
-	outputs, err := ctx.Input().FromIntSlice(opts.Outputs, len(opts.Outputs))
+	outputs, err := ctx.Input().FromIntSlice(batch.Outputs, len(batch.Outputs))
 	if err != nil {
 		return nil, err
 	}
diff --git a/model/models/mllama/model.go b/model/models/mllama/model.go
index 0aa11f17..6d9c608e 100644
--- a/model/models/mllama/model.go
+++ b/model/models/mllama/model.go
@@ -135,26 +135,26 @@ func (m *Model) PostTokenize(inputs []input.Input) ([]input.Input, error) {
 	return inputs, nil
 }
 
-func (m *Model) Forward(ctx ml.Context, opts input.Options) (ml.Tensor, error) {
+func (m *Model) Forward(ctx ml.Context, batch input.Batch) (ml.Tensor, error) {
 	var crossAttentionStates ml.Tensor
-	if len(opts.Multimodal) > 0 {
-		images := opts.Multimodal[len(opts.Multimodal)-1].Multimodal.([]ml.Tensor)
+	if len(batch.Multimodal) > 0 {
+		images := batch.Multimodal[len(batch.Multimodal)-1].Multimodal.([]ml.Tensor)
 		if len(images) > 0 {
 			crossAttentionStates = images[len(images)-1]
 		}
 	}
 
-	inputs, err := ctx.Input().FromIntSlice(opts.Inputs, len(opts.Inputs))
+	inputs, err := ctx.Input().FromIntSlice(batch.Inputs, len(batch.Inputs))
 	if err != nil {
 		return nil, err
 	}
 
-	positions, err := ctx.Input().FromIntSlice(opts.Positions, len(opts.Positions))
+	positions, err := ctx.Input().FromIntSlice(batch.Positions, len(batch.Positions))
 	if err != nil {
 		return nil, err
 	}
 
-	outputs, err := ctx.Input().FromIntSlice(opts.Outputs, len(opts.Outputs))
+	outputs, err := ctx.Input().FromIntSlice(batch.Outputs, len(batch.Outputs))
 	if err != nil {
 		return nil, err
 	}
diff --git a/runner/ollamarunner/runner.go b/runner/ollamarunner/runner.go
index 9a1a549c..91463f93 100644
--- a/runner/ollamarunner/runner.go
+++ b/runner/ollamarunner/runner.go
@@ -348,7 +348,7 @@ func (s *Server) processBatch() error {
 	}
 	defer s.mu.Unlock()
 
-	var options input.Options
+	var batch input.Batch
 
 	for i, seq := range s.seqs {
 		if seq == nil {
@@ -395,17 +395,17 @@ func (s *Server) processBatch() error {
 				}
 			}
 
-			options.Inputs = append(options.Inputs, inp.Token)
+			batch.Inputs = append(batch.Inputs, inp.Token)
 			if inp.Multimodal != nil {
-				options.Multimodal = append(options.Multimodal, input.MultimodalIndex{Index: len(options.Inputs) - 1, Multimodal: inp.Multimodal})
+				batch.Multimodal = append(batch.Multimodal, input.MultimodalIndex{Index: len(batch.Inputs) - 1, Multimodal: inp.Multimodal})
 			}
 
-			options.Positions = append(options.Positions, int32(len(seq.cache.Inputs)+len(seq.pendingInputs)))
-			options.Sequences = append(options.Sequences, seq.cache.Id)
+			batch.Positions = append(batch.Positions, int32(len(seq.cache.Inputs)+len(seq.pendingInputs)))
+			batch.Sequences = append(batch.Sequences, seq.cache.Id)
 
-			seq.iBatch = len(options.Outputs)
+			seq.iBatch = len(batch.Outputs)
 			if j+1 == len(seq.inputs) {
-				options.Outputs = append(options.Outputs, int32(len(options.Inputs)-1))
+				batch.Outputs = append(batch.Outputs, int32(len(batch.Inputs)-1))
 			}
 			seq.pendingInputs = append(seq.pendingInputs, inp)
 		}
@@ -413,14 +413,14 @@ func (s *Server) processBatch() error {
 		seq.inputs = seq.inputs[len(seq.pendingInputs):]
 	}
 
-	if len(options.Inputs) == 0 {
+	if len(batch.Inputs) == 0 {
 		return nil
 	}
 
 	ctx := s.model.Backend().NewContext()
 	defer ctx.Close()
 
-	modelOutput, err := model.Forward(ctx, s.model, options)
+	modelOutput, err := model.Forward(ctx, s.model, batch)
 	if err != nil {
 		return fmt.Errorf("failed to decode batch: %w", err)
 	}
@@ -460,7 +460,7 @@ func (s *Server) processBatch() error {
 		}
 
 		// sample a token
-		vocabSize := len(logits) / len(options.Outputs)
+		vocabSize := len(logits) / len(batch.Outputs)
 
 		token, err := seq.sampler.Sample(logits[seq.iBatch*vocabSize : (seq.iBatch+1)*vocabSize])
 		if err != nil {

From 0fbfcf3c9c7bfdbf4616238595eafd7eca2a916c Mon Sep 17 00:00:00 2001
From: Jesse Gross <jesse@ollama.com>
Date: Wed, 19 Mar 2025 14:36:21 -0700
Subject: [PATCH 117/157] model: Pass input tensor instead of raw data to
 models

Rather than directly giving the input data to models, we can
pass a tensor instead. In the short term, this saves some duplicated
code.

Longer term, we will want to overlap setting up the next batch with
processing of the current one. In this case, we will only have the
shape of tensor but it will not be loaded with data at the time of
graph generation. By passing only a tensor to models now, we set up
this possibility and prevent them from relying on data that they won't
have in the future.

Although the same could be done for Positions and Outputs, in some
cases we either need the raw input data or don't use them at all.
Therefore, for now we leave them as they are and allow models to
convert them to tensors as needed.
---
 model/input/input.go          |  4 +++-
 model/model.go                |  8 +++++++-
 model/models/gemma2/model.go  |  7 +------
 model/models/gemma3/model.go  |  7 +------
 model/models/llama/model.go   |  7 +------
 model/models/mllama/model.go  |  7 +------
 runner/ollamarunner/runner.go | 11 ++++++-----
 7 files changed, 20 insertions(+), 31 deletions(-)

diff --git a/model/input/input.go b/model/input/input.go
index ce43efb5..d66f52a0 100644
--- a/model/input/input.go
+++ b/model/input/input.go
@@ -1,5 +1,7 @@
 package input
 
+import "github.com/ollama/ollama/ml"
+
 // Input represents one token in the input stream
 type Input struct {
 	// Token is a single element of text.
@@ -36,7 +38,7 @@ type MultimodalIndex struct {
 // Batch contains the inputs for a model forward pass
 type Batch struct {
 	// Inputs is the input tokens, including placeholders for multimodal inputs.
-	Inputs []int32
+	Inputs ml.Tensor
 
 	// Multimodal is a set of multimodal embeddings previously created by
 	// EncodeMultimodal, along with an index into Inputs. Unused for text-only
diff --git a/model/model.go b/model/model.go
index 94156ae2..ab29916a 100644
--- a/model/model.go
+++ b/model/model.go
@@ -280,7 +280,7 @@ func canNil(t reflect.Type) bool {
 		t.Kind() == reflect.Slice
 }
 
-func Forward(ctx ml.Context, m Model, batch input.Batch) (ml.Tensor, error) {
+func Forward(ctx ml.Context, m Model, inputs []int32, batch input.Batch) (ml.Tensor, error) {
 	if len(batch.Positions) != len(batch.Sequences) {
 		return nil, fmt.Errorf("length of positions (%v) must match length of seqs (%v)", len(batch.Positions), len(batch.Sequences))
 	}
@@ -289,6 +289,12 @@ func Forward(ctx ml.Context, m Model, batch input.Batch) (ml.Tensor, error) {
 		return nil, errors.New("batch size cannot be less than 1")
 	}
 
+	var err error
+	batch.Inputs, err = ctx.Input().FromIntSlice(inputs, len(inputs))
+	if err != nil {
+		return nil, err
+	}
+
 	cache := m.Config().Cache
 	if cache != nil {
 		err := cache.StartForward(ctx, batch)
diff --git a/model/models/gemma2/model.go b/model/models/gemma2/model.go
index 2b347d72..67c69ee8 100644
--- a/model/models/gemma2/model.go
+++ b/model/models/gemma2/model.go
@@ -169,11 +169,6 @@ func (l *Layer) Forward(ctx ml.Context, hiddenState, positionIDs, outputs ml.Ten
 }
 
 func (m *Model) Forward(ctx ml.Context, batch input.Batch) (ml.Tensor, error) {
-	inputs, err := ctx.Input().FromIntSlice(batch.Inputs, len(batch.Inputs))
-	if err != nil {
-		return nil, err
-	}
-
 	positions, err := ctx.Input().FromIntSlice(batch.Positions, len(batch.Positions))
 	if err != nil {
 		return nil, err
@@ -184,7 +179,7 @@ func (m *Model) Forward(ctx ml.Context, batch input.Batch) (ml.Tensor, error) {
 		return nil, err
 	}
 
-	hiddenState := m.TokenEmbedding.Forward(ctx, inputs)
+	hiddenState := m.TokenEmbedding.Forward(ctx, batch.Inputs)
 	hiddenState = hiddenState.Scale(ctx, math.Sqrt(float64(m.Options.hiddenSize)))
 
 	if len(m.Layers) == gemma27BLayerCount {
diff --git a/model/models/gemma3/model.go b/model/models/gemma3/model.go
index 900bf31e..567ad1a4 100644
--- a/model/models/gemma3/model.go
+++ b/model/models/gemma3/model.go
@@ -140,11 +140,6 @@ func (m *Model) PostTokenize(inputs []input.Input) ([]input.Input, error) {
 }
 
 func (m *Model) Forward(ctx ml.Context, batch input.Batch) (ml.Tensor, error) {
-	inputs, err := ctx.Input().FromIntSlice(batch.Inputs, len(batch.Inputs))
-	if err != nil {
-		return nil, err
-	}
-
 	positions, err := ctx.Input().FromIntSlice(batch.Positions, len(batch.Positions))
 	if err != nil {
 		return nil, err
@@ -155,7 +150,7 @@ func (m *Model) Forward(ctx ml.Context, batch input.Batch) (ml.Tensor, error) {
 		return nil, err
 	}
 
-	return m.TextModel.Forward(ctx, inputs, positions, outputs, batch, m.Cache), nil
+	return m.TextModel.Forward(ctx, batch.Inputs, positions, outputs, batch, m.Cache), nil
 }
 
 func init() {
diff --git a/model/models/llama/model.go b/model/models/llama/model.go
index e5ecd29e..5c173997 100644
--- a/model/models/llama/model.go
+++ b/model/models/llama/model.go
@@ -140,11 +140,6 @@ func (l *Layer) Forward(ctx ml.Context, hiddenState, positionIDs, outputs ml.Ten
 }
 
 func (m *Model) Forward(ctx ml.Context, batch input.Batch) (ml.Tensor, error) {
-	inputs, err := ctx.Input().FromIntSlice(batch.Inputs, len(batch.Inputs))
-	if err != nil {
-		return nil, err
-	}
-
 	positions, err := ctx.Input().FromIntSlice(batch.Positions, len(batch.Positions))
 	if err != nil {
 		return nil, err
@@ -155,7 +150,7 @@ func (m *Model) Forward(ctx ml.Context, batch input.Batch) (ml.Tensor, error) {
 		return nil, err
 	}
 
-	hiddenState := m.TokenEmbedding.Forward(ctx, inputs)
+	hiddenState := m.TokenEmbedding.Forward(ctx, batch.Inputs)
 
 	for i, layer := range m.Layers {
 		m.Cache.SetLayer(i)
diff --git a/model/models/mllama/model.go b/model/models/mllama/model.go
index 6d9c608e..988a189d 100644
--- a/model/models/mllama/model.go
+++ b/model/models/mllama/model.go
@@ -144,11 +144,6 @@ func (m *Model) Forward(ctx ml.Context, batch input.Batch) (ml.Tensor, error) {
 		}
 	}
 
-	inputs, err := ctx.Input().FromIntSlice(batch.Inputs, len(batch.Inputs))
-	if err != nil {
-		return nil, err
-	}
-
 	positions, err := ctx.Input().FromIntSlice(batch.Positions, len(batch.Positions))
 	if err != nil {
 		return nil, err
@@ -160,7 +155,7 @@ func (m *Model) Forward(ctx ml.Context, batch input.Batch) (ml.Tensor, error) {
 	}
 
 	// TODO: attention mask, cross attention mask
-	return m.TextModel.Forward(ctx, inputs, positions, outputs, nil, crossAttentionStates, nil, m.Cache.(*kvcache.WrapperCache)), nil
+	return m.TextModel.Forward(ctx, batch.Inputs, positions, outputs, nil, crossAttentionStates, nil, m.Cache.(*kvcache.WrapperCache)), nil
 }
 
 func init() {
diff --git a/runner/ollamarunner/runner.go b/runner/ollamarunner/runner.go
index 91463f93..443b34b0 100644
--- a/runner/ollamarunner/runner.go
+++ b/runner/ollamarunner/runner.go
@@ -348,6 +348,7 @@ func (s *Server) processBatch() error {
 	}
 	defer s.mu.Unlock()
 
+	var batchInputs []int32
 	var batch input.Batch
 
 	for i, seq := range s.seqs {
@@ -395,9 +396,9 @@ func (s *Server) processBatch() error {
 				}
 			}
 
-			batch.Inputs = append(batch.Inputs, inp.Token)
+			batchInputs = append(batchInputs, inp.Token)
 			if inp.Multimodal != nil {
-				batch.Multimodal = append(batch.Multimodal, input.MultimodalIndex{Index: len(batch.Inputs) - 1, Multimodal: inp.Multimodal})
+				batch.Multimodal = append(batch.Multimodal, input.MultimodalIndex{Index: len(batchInputs) - 1, Multimodal: inp.Multimodal})
 			}
 
 			batch.Positions = append(batch.Positions, int32(len(seq.cache.Inputs)+len(seq.pendingInputs)))
@@ -405,7 +406,7 @@ func (s *Server) processBatch() error {
 
 			seq.iBatch = len(batch.Outputs)
 			if j+1 == len(seq.inputs) {
-				batch.Outputs = append(batch.Outputs, int32(len(batch.Inputs)-1))
+				batch.Outputs = append(batch.Outputs, int32(len(batchInputs)-1))
 			}
 			seq.pendingInputs = append(seq.pendingInputs, inp)
 		}
@@ -413,14 +414,14 @@ func (s *Server) processBatch() error {
 		seq.inputs = seq.inputs[len(seq.pendingInputs):]
 	}
 
-	if len(batch.Inputs) == 0 {
+	if len(batchInputs) == 0 {
 		return nil
 	}
 
 	ctx := s.model.Backend().NewContext()
 	defer ctx.Close()
 
-	modelOutput, err := model.Forward(ctx, s.model, batch)
+	modelOutput, err := model.Forward(ctx, s.model, batchInputs, batch)
 	if err != nil {
 		return fmt.Errorf("failed to decode batch: %w", err)
 	}

From d3e9ca3eda5585204358f4ba23b3c7cb23bdb3e2 Mon Sep 17 00:00:00 2001
From: Jesse Gross <jesse@ollama.com>
Date: Thu, 20 Mar 2025 14:27:17 -0700
Subject: [PATCH 118/157] kvcache: Account for source tensors in defrag
 operation count

Defragging the KV cache can generate a lot of operations, so we
need to be careful that we don't overflow the number that the graph
can support. We currently account for all of the nodes that we add
to the graph for each move but we also need to include the original
cache tensors as well.

Fixes #9904
---
 kvcache/causal.go | 5 +++--
 1 file changed, 3 insertions(+), 2 deletions(-)

diff --git a/kvcache/causal.go b/kvcache/causal.go
index 79fa24e8..e5216d58 100644
--- a/kvcache/causal.go
+++ b/kvcache/causal.go
@@ -321,7 +321,8 @@ func (c *Causal) defrag() {
 	ctx := c.backend.NewContext()
 
 	// For every move, 6 tensors are required per layer (2 views and a
-	// copy for each of k and v).
+	// copy for each of k and v). We also need to refer to the original
+	// k and v cache tensors - once per layer, not per move.
 	layers := 0
 	for _, key := range c.keys {
 		if key == nil {
@@ -330,7 +331,7 @@ func (c *Causal) defrag() {
 		layers++
 	}
 
-	maxMoves := ctx.MaxGraphNodes() / (6 * layers)
+	maxMoves := (ctx.MaxGraphNodes() - 2*layers) / (6 * layers)
 	moves := 0
 
 	var pendingSrc, pendingDst, pendingLen int

From 0ff28758b3a5e9dc0149a93d87677dd0585590c1 Mon Sep 17 00:00:00 2001
From: Jesse Gross <jesse@ollama.com>
Date: Thu, 20 Mar 2025 10:35:19 -0700
Subject: [PATCH 119/157] ollamarunner: Provide mechanism for backends to
 report loading progress

This enables the runner to report progress back to the Ollama server,
both for showing status to the user and also to prevent the server
from killing the runner if it thinks things have stalled.

Most of the infrastructure was already there, this extends it to
be available to the backends.
---
 ml/backend.go                 | 4 ++++
 runner/ollamarunner/runner.go | 3 +++
 2 files changed, 7 insertions(+)

diff --git a/ml/backend.go b/ml/backend.go
index c63c73d4..66eb37f7 100644
--- a/ml/backend.go
+++ b/ml/backend.go
@@ -60,6 +60,10 @@ type CacheConfig struct {
 
 // BackendParams controls how the backend loads and executes models
 type BackendParams struct {
+	// Progress is a callback function that allows reporting percentage completion
+	// of model loading
+	Progress func(float32)
+
 	// NumThreads sets the number of threads to use if running on the CPU
 	NumThreads int
 
diff --git a/runner/ollamarunner/runner.go b/runner/ollamarunner/runner.go
index 443b34b0..90eb0de6 100644
--- a/runner/ollamarunner/runner.go
+++ b/runner/ollamarunner/runner.go
@@ -783,6 +783,9 @@ func Execute(args []string) error {
 	}
 
 	params := ml.BackendParams{
+		Progress: func(progress float32) {
+			server.progress = progress
+		},
 		NumThreads:     *threads,
 		NumGPULayers:   *numGPULayers,
 		MainGPU:        *mainGPU,

From 6d1103048eac63f27148d6d8fe47c98cbb6f184f Mon Sep 17 00:00:00 2001
From: Patrick Devine <patrick@infrahq.com>
Date: Fri, 21 Mar 2025 11:13:54 -0700
Subject: [PATCH 120/157] fix: show correct bool value for kv in verbose show
 information (#9928)

---
 cmd/cmd.go      | 2 ++
 cmd/cmd_test.go | 4 ++++
 2 files changed, 6 insertions(+)

diff --git a/cmd/cmd.go b/cmd/cmd.go
index 710f49a7..abb4806b 100644
--- a/cmd/cmd.go
+++ b/cmd/cmd.go
@@ -703,6 +703,8 @@ func showInfo(resp *api.ShowResponse, verbose bool, w io.Writer) error {
 			for _, k := range keys {
 				var v string
 				switch vData := resp.ModelInfo[k].(type) {
+				case bool:
+					v = fmt.Sprintf("%t", vData)
 				case string:
 					v = vData
 				case float64:
diff --git a/cmd/cmd_test.go b/cmd/cmd_test.go
index 41b03e1b..ea3bdffe 100644
--- a/cmd/cmd_test.go
+++ b/cmd/cmd_test.go
@@ -87,6 +87,8 @@ func TestShowInfo(t *testing.T) {
 			ModelInfo: map[string]any{
 				"general.architecture":    "test",
 				"general.parameter_count": float64(8_000_000_000),
+				"some.true_bool":          true,
+				"some.false_bool":         false,
 				"test.context_length":     float64(1000),
 				"test.embedding_length":   float64(11434),
 			},
@@ -111,6 +113,8 @@ func TestShowInfo(t *testing.T) {
   Metadata
     general.architecture       test     
     general.parameter_count    8e+09    
+    some.false_bool            false    
+    some.true_bool             true     
     test.context_length        1000     
     test.embedding_length      11434    
 

From 3ed7ad3ab32b458aa2fdb8d0144c546efdb26a72 Mon Sep 17 00:00:00 2001
From: Jesse Gross <jesse@ollama.com>
Date: Tue, 18 Mar 2025 14:31:52 -0700
Subject: [PATCH 121/157] kvcache: Pass granular cache size into
 implementations

Currently the runner computes the kv size needed and creates a
cache of that size. This is the context size times number of
parallel sequences.

Cache implementations can make better decisions about their memory
usage, so instead pass in the required capacity, number of sequences
and maximum batch size. For now, the causal cache just uses this to
compute the size in the same way as before.
---
 kvcache/cache.go              |  9 +++++++--
 kvcache/causal.go             | 33 +++++++++++++++++----------------
 kvcache/causal_test.go        | 12 ++++++------
 kvcache/encoder.go            |  6 +++++-
 kvcache/wrapper.go            |  4 ++--
 runner/ollamarunner/cache.go  | 10 ++++++----
 runner/ollamarunner/runner.go |  2 +-
 7 files changed, 44 insertions(+), 32 deletions(-)

diff --git a/kvcache/cache.go b/kvcache/cache.go
index aa0a2056..18aec800 100644
--- a/kvcache/cache.go
+++ b/kvcache/cache.go
@@ -43,8 +43,13 @@ type Cache interface {
 
 	// ** cache management **
 
-	// Init sets up runtime parameters
-	Init(backend ml.Backend, dtype ml.DType, capacity int32)
+	// Init sets up runtime parameters.
+	// backend: Used to allocate cache data storage and execute management operations (such as defrag)
+	// dtype: The data type for storing cache entries
+	// maxSequences: The maximum number of sequences stored in the cache - across all batches
+	// capacity: The number of cache entries to store, per sequence
+	// maxBatch: The maximum number of tokens that can occur in a single batch
+	Init(backend ml.Backend, dtype ml.DType, maxSequences, capacity, maxBatch int)
 
 	// Close closes the cache and frees resources associated with it
 	Close()
diff --git a/kvcache/causal.go b/kvcache/causal.go
index e5216d58..ced409c3 100644
--- a/kvcache/causal.go
+++ b/kvcache/causal.go
@@ -20,7 +20,6 @@ type shiftFn func(ctx ml.Context, layer int, key, shift ml.Tensor) (ml.Tensor, e
 // The mask is of shape history size, batch size
 type Causal struct {
 	DType      ml.DType
-	Capacity   int32
 	windowSize int32
 
 	opts CausalOptions
@@ -98,7 +97,7 @@ func NewSWACache(windowSize int32, shift shiftFn) *Causal {
 	}
 }
 
-func (c *Causal) Init(backend ml.Backend, dtype ml.DType, capacity int32) {
+func (c *Causal) Init(backend ml.Backend, dtype ml.DType, maxSequences, capacity, maxBatch int) {
 	if c.config == nil {
 		var config ml.CacheConfig
 		if cc, ok := backend.(ml.BackendCacheConfig); ok {
@@ -119,9 +118,11 @@ func (c *Causal) Init(backend ml.Backend, dtype ml.DType, capacity int32) {
 		c.config.MaskDType = ml.DTypeF32
 	}
 
+	cacheSize := maxSequences * capacity
+	cacheSize = roundUp(cacheSize, c.config.CachePadding)
+	c.cells = make([]cacheCell, cacheSize)
+
 	c.DType = dtype
-	c.Capacity = int32(roundUp(int(capacity), c.config.CachePadding))
-	c.cells = make([]cacheCell, c.Capacity)
 	c.cellRanges = make(map[int]cellRange)
 	c.backend = backend
 }
@@ -210,7 +211,7 @@ func (c *Causal) findStartLoc() (int, error) {
 		}
 	}
 
-	return 0, fmt.Errorf("%w (length: %v)", ErrKvCacheFull, c.Capacity)
+	return 0, fmt.Errorf("%w (length: %v)", ErrKvCacheFull, len(c.cells))
 }
 
 func roundDown(length, pad int) int {
@@ -265,7 +266,7 @@ func (c *Causal) buildMask(ctx ml.Context) (ml.Tensor, error) {
 	return maskTensor, nil
 }
 
-func (c *Causal) moveCells(ctx ml.Context, src, dst, len int) {
+func (c *Causal) moveCells(ctx ml.Context, src, dst, length int) {
 	for i, key := range c.keys {
 		if key == nil {
 			continue
@@ -275,8 +276,8 @@ func (c *Causal) moveCells(ctx ml.Context, src, dst, len int) {
 		numKVHeads := key.Dim(1)
 		rowSize := key.Stride(2)
 
-		kSrcView := key.View(ctx, rowSize*src, kHeadDim*numKVHeads*len)
-		kDstView := key.View(ctx, rowSize*dst, kHeadDim*numKVHeads*len)
+		kSrcView := key.View(ctx, rowSize*src, kHeadDim*numKVHeads*length)
+		kDstView := key.View(ctx, rowSize*dst, kHeadDim*numKVHeads*length)
 
 		value := c.values[i]
 		var vSrcView, vDstView ml.Tensor
@@ -284,14 +285,14 @@ func (c *Causal) moveCells(ctx ml.Context, src, dst, len int) {
 			vHeadDim := value.Dim(1)
 			elemSize := value.Stride(0)
 
-			vSrcView = value.View(ctx, elemSize*src, len, int(c.Capacity)*elemSize, vHeadDim*numKVHeads)
-			vDstView = value.View(ctx, elemSize*dst, len, int(c.Capacity)*elemSize, vHeadDim*numKVHeads)
+			vSrcView = value.View(ctx, elemSize*src, length, len(c.cells)*elemSize, vHeadDim*numKVHeads)
+			vDstView = value.View(ctx, elemSize*dst, length, len(c.cells)*elemSize, vHeadDim*numKVHeads)
 		} else {
 			vHeadDim := value.Dim(0)
 			rowSize := value.Stride(2)
 
-			vSrcView = value.View(ctx, rowSize*src, vHeadDim*numKVHeads*len)
-			vDstView = value.View(ctx, rowSize*dst, vHeadDim*numKVHeads*len)
+			vSrcView = value.View(ctx, rowSize*src, vHeadDim*numKVHeads*length)
+			vDstView = value.View(ctx, rowSize*dst, vHeadDim*numKVHeads*length)
 		}
 
 		ctx.Forward(
@@ -480,14 +481,14 @@ func (c *Causal) Put(ctx ml.Context, key, value ml.Tensor) {
 	}
 
 	if _, ok := c.keys[c.curLayer]; !ok {
-		c.keys[c.curLayer] = c.ctxs[c.curLayer].Zeros(c.DType, kHeadDim, numKVHeads, int(c.Capacity))
+		c.keys[c.curLayer] = c.ctxs[c.curLayer].Zeros(c.DType, kHeadDim, numKVHeads, len(c.cells))
 	}
 
 	if _, ok := c.values[c.curLayer]; !ok {
 		if c.config.PermutedV {
-			c.values[c.curLayer] = c.ctxs[c.curLayer].Zeros(c.DType, int(c.Capacity), vHeadDim, numKVHeads)
+			c.values[c.curLayer] = c.ctxs[c.curLayer].Zeros(c.DType, len(c.cells), vHeadDim, numKVHeads)
 		} else {
-			c.values[c.curLayer] = c.ctxs[c.curLayer].Zeros(c.DType, vHeadDim, numKVHeads, int(c.Capacity))
+			c.values[c.curLayer] = c.ctxs[c.curLayer].Zeros(c.DType, vHeadDim, numKVHeads, len(c.cells))
 		}
 	}
 
@@ -498,7 +499,7 @@ func (c *Causal) Put(ctx ml.Context, key, value ml.Tensor) {
 		elemSize := c.values[c.curLayer].Stride(0)
 
 		value = value.Permute(ctx, 1, 2, 0, 3)
-		ctx.Forward(value.Copy(ctx, c.values[c.curLayer].View(ctx, elemSize*c.curLoc, batchSize, int(c.Capacity)*elemSize, vHeadDim*numKVHeads)))
+		ctx.Forward(value.Copy(ctx, c.values[c.curLayer].View(ctx, elemSize*c.curLoc, batchSize, len(c.cells)*elemSize, vHeadDim*numKVHeads)))
 	} else {
 		rowSize := c.values[c.curLayer].Stride(2)
 
diff --git a/kvcache/causal_test.go b/kvcache/causal_test.go
index 0f2385db..66a2e835 100644
--- a/kvcache/causal_test.go
+++ b/kvcache/causal_test.go
@@ -25,7 +25,7 @@ func TestStore(t *testing.T) {
 	cache := NewCausalCache(nil)
 	defer cache.Close()
 
-	cache.Init(backend, ml.DTypeF16, 16)
+	cache.Init(backend, ml.DTypeF16, 1, 16, 16)
 
 	tests := []testCase{
 		{
@@ -58,7 +58,7 @@ func TestSWA(t *testing.T) {
 	cache := NewSWACache(1, nil)
 	defer cache.Close()
 
-	cache.Init(backend, ml.DTypeF32, 16)
+	cache.Init(backend, ml.DTypeF32, 1, 16, 16)
 
 	tests := []testCase{
 		{
@@ -81,7 +81,7 @@ func TestSequences(t *testing.T) {
 	cache := NewCausalCache(nil)
 	defer cache.Close()
 
-	cache.Init(backend, ml.DTypeF16, 16)
+	cache.Init(backend, ml.DTypeF16, 1, 16, 16)
 
 	tests := []testCase{
 		{
@@ -116,7 +116,7 @@ func TestRemove(t *testing.T) {
 	})
 	defer cache.Close()
 
-	cache.Init(backend, ml.DTypeF16, 16)
+	cache.Init(backend, ml.DTypeF16, 1, 16, 16)
 
 	tests := []testCase{
 		{
@@ -181,7 +181,7 @@ func TestDefrag(t *testing.T) {
 	})
 	defer cache.Close()
 
-	cache.Init(backend, ml.DTypeF16, 16)
+	cache.Init(backend, ml.DTypeF16, 1, 16, 16)
 
 	tests := []testCase{
 		{
@@ -229,7 +229,7 @@ func TestCopy(t *testing.T) {
 	cache := NewCausalCache(func(ctx ml.Context, layer int, key, shift ml.Tensor) (ml.Tensor, error) { return key, nil })
 	defer cache.Close()
 
-	cache.Init(backend, ml.DTypeF16, 16)
+	cache.Init(backend, ml.DTypeF16, 1, 16, 16)
 
 	tests := []testCase{
 		{
diff --git a/kvcache/encoder.go b/kvcache/encoder.go
index 94c5d99c..07ff4291 100644
--- a/kvcache/encoder.go
+++ b/kvcache/encoder.go
@@ -49,7 +49,7 @@ func NewEncoderCache() *EncoderCache {
 	}
 }
 
-func (c *EncoderCache) Init(backend ml.Backend, dtype ml.DType, capacity int32) {
+func (c *EncoderCache) Init(backend ml.Backend, dtype ml.DType, maxSequences, capacity, maxBatch int) {
 	if c.config == nil {
 		var config ml.CacheConfig
 		if cc, ok := backend.(ml.BackendCacheConfig); ok {
@@ -58,6 +58,10 @@ func (c *EncoderCache) Init(backend ml.Backend, dtype ml.DType, capacity int32)
 		c.config = &config
 	}
 
+	if maxSequences > 1 {
+		panic(fmt.Errorf("encoder cache does not support multiple sequences; requested: %v", maxSequences))
+	}
+
 	if c.config.CachePadding != 0 && c.config.CachePadding != 1 {
 		panic(fmt.Errorf("encoder cache is unable to enforce requested CachePadding (%v)", c.config.CachePadding))
 	}
diff --git a/kvcache/wrapper.go b/kvcache/wrapper.go
index c85807a0..0e8ff1f3 100644
--- a/kvcache/wrapper.go
+++ b/kvcache/wrapper.go
@@ -23,9 +23,9 @@ func NewWrapperCache(caches ...Cache) *WrapperCache {
 	}
 }
 
-func (c *WrapperCache) Init(backend ml.Backend, dtype ml.DType, capacity int32) {
+func (c *WrapperCache) Init(backend ml.Backend, dtype ml.DType, maxSequences, capacity, maxBatch int) {
 	for _, cache := range c.caches {
-		cache.Init(backend, dtype, capacity)
+		cache.Init(backend, dtype, maxSequences, capacity, maxBatch)
 	}
 }
 
diff --git a/runner/ollamarunner/cache.go b/runner/ollamarunner/cache.go
index cf5e6b91..aa56c982 100644
--- a/runner/ollamarunner/cache.go
+++ b/runner/ollamarunner/cache.go
@@ -31,8 +31,10 @@ type InputCache struct {
 	cache kvcache.Cache
 }
 
-func NewInputCache(model model.Model, kvCacheType string, kvSize int32, numSlots int, multiUserCache bool) (*InputCache, error) {
-	if kvSize/int32(numSlots) < 1 {
+func NewInputCache(model model.Model, kvCacheType string, kvSize int32, numSlots int, batchSize int, multiUserCache bool) (*InputCache, error) {
+	numCtx := kvSize / int32(numSlots)
+
+	if numCtx < 1 {
 		return nil, fmt.Errorf("must have at least one kv cache entry per parallel sequence (kv: %v parallel: %v)", kvSize, numSlots)
 	}
 
@@ -44,11 +46,11 @@ func NewInputCache(model model.Model, kvCacheType string, kvSize int32, numSlots
 
 	cache := model.Config().Cache
 	if cache != nil {
-		cache.Init(model.Backend(), kvCacheTypeFromStr(kvCacheType), kvSize)
+		cache.Init(model.Backend(), kvCacheTypeFromStr(kvCacheType), numSlots, int(numCtx), batchSize)
 	}
 
 	return &InputCache{
-		numCtx:         kvSize / int32(numSlots),
+		numCtx:         numCtx,
 		enabled:        cache != nil,
 		slots:          slots,
 		multiUserCache: multiUserCache,
diff --git a/runner/ollamarunner/runner.go b/runner/ollamarunner/runner.go
index 90eb0de6..67d9a1b0 100644
--- a/runner/ollamarunner/runner.go
+++ b/runner/ollamarunner/runner.go
@@ -699,7 +699,7 @@ func (s *Server) loadModel(
 		panic("loras are not yet implemented")
 	}
 
-	s.cache, err = NewInputCache(s.model, kvCacheType, int32(kvSize), parallel, multiUserCache)
+	s.cache, err = NewInputCache(s.model, kvCacheType, int32(kvSize), parallel, s.batchSize, multiUserCache)
 	if err != nil {
 		panic(err)
 	}

From 2d6eac9084a29060ccff69014e28e206a3a7a663 Mon Sep 17 00:00:00 2001
From: Jesse Gross <jesse@ollama.com>
Date: Tue, 18 Mar 2025 13:13:32 -0700
Subject: [PATCH 122/157] kvcache: Optimize sliding window attention

Currently sliding window attention allocates and uses the full
context size and just masks out any tokens that are outside of the
window. However, we really only need (roughly) the sliding window
size.

At large context sizes this improves two things:
 - Memory allocated - since the fully context size is allocated up front,
   memory requirements drop substantially. On Gemma3:4b with a 32k
   context window, total memory usage (including weights and non-sliding
   layers) drops from ~20GB to ~8GB.
 - Computation - ranges that are completely outside of the sliding
   window are now removed from the tensors that are returned from the
   cache rather than simply being masked out. This results in more
   efficient processing, scaling with the size of the context that
   has actually been used.

Notable, this does not update the scheduler for any model to be aware of
the smaller memory requirements. This is difficult for Gemma3 because
the layers are heterogeneous between sliding and non-sliding attention.
As a result, while actual memory consumption will be reduced, the
scheduler will over-estimate the requirements of the model. This means
that splitting between GPUs or GPUs and CPUs will still be suboptimal.

Bug #9730
---
 kvcache/causal.go      | 53 +++++++++++++++++++++++++++++++++++++++++-
 kvcache/causal_test.go | 14 +++++++++--
 2 files changed, 64 insertions(+), 3 deletions(-)

diff --git a/kvcache/causal.go b/kvcache/causal.go
index ced409c3..aacaf540 100644
--- a/kvcache/causal.go
+++ b/kvcache/causal.go
@@ -118,7 +118,12 @@ func (c *Causal) Init(backend ml.Backend, dtype ml.DType, maxSequences, capacity
 		c.config.MaskDType = ml.DTypeF32
 	}
 
-	cacheSize := maxSequences * capacity
+	var cacheSize int
+	if c.windowSize == math.MaxInt32 || capacity < int(c.windowSize)+maxBatch {
+		cacheSize = maxSequences * capacity
+	} else {
+		cacheSize = maxSequences * (int(c.windowSize) + maxBatch)
+	}
 	cacheSize = roundUp(cacheSize, c.config.CachePadding)
 	c.cells = make([]cacheCell, cacheSize)
 
@@ -147,6 +152,8 @@ func (c *Causal) StartForward(ctx ml.Context, batch input.Batch) error {
 	c.curPositions = batch.Positions
 	c.opts.Except = nil
 
+	c.updateSlidingWindow()
+
 	var err error
 	c.curLoc, err = c.findStartLoc()
 	if errors.Is(err, ErrKvCacheFull) {
@@ -214,6 +221,50 @@ func (c *Causal) findStartLoc() (int, error) {
 	return 0, fmt.Errorf("%w (length: %v)", ErrKvCacheFull, len(c.cells))
 }
 
+func (c *Causal) updateSlidingWindow() {
+	if c.windowSize == math.MaxInt32 {
+		return
+	}
+
+	// create a map of unique sequences to the lowest position in that sequence
+	lowestPos := make(map[int]int32)
+	for i := range c.curPositions {
+		seq := c.curSequences[i]
+
+		pos, ok := lowestPos[seq]
+		if !ok {
+			pos = c.curPositions[i]
+		} else if c.curPositions[i] < pos {
+			pos = c.curPositions[i]
+		}
+
+		lowestPos[seq] = pos
+	}
+
+	// delete any entries that are beyond the window of the oldest position in the sequence
+	for seq, pos := range lowestPos {
+		oldRange, ok := c.cellRanges[seq]
+		if !ok {
+			continue
+		}
+
+		newRange := newRange()
+
+		for i := oldRange.min; i <= oldRange.max; i++ {
+			if slices.Contains(c.cells[i].sequences, seq) {
+				if c.cells[i].pos < pos-c.windowSize {
+					c.cells[i].sequences = slices.DeleteFunc(c.cells[i].sequences, func(s int) bool { return s == seq })
+				} else {
+					newRange.min = min(newRange.min, i)
+					newRange.max = max(newRange.max, i)
+				}
+			}
+		}
+
+		c.cellRanges[seq] = newRange
+	}
+}
+
 func roundDown(length, pad int) int {
 	return (length / pad) * pad
 }
diff --git a/kvcache/causal_test.go b/kvcache/causal_test.go
index 66a2e835..617f5363 100644
--- a/kvcache/causal_test.go
+++ b/kvcache/causal_test.go
@@ -58,11 +58,11 @@ func TestSWA(t *testing.T) {
 	cache := NewSWACache(1, nil)
 	defer cache.Close()
 
-	cache.Init(backend, ml.DTypeF32, 1, 16, 16)
+	cache.Init(backend, ml.DTypeF16, 1, 16, 16)
 
 	tests := []testCase{
 		{
-			name:          "SlidingWindow",
+			name:          "FirstBatch",
 			in:            []float32{1, 2, 3, 4},
 			inShape:       []int{1, 1, 4},
 			seqs:          []int{0, 0, 0, 0},
@@ -71,6 +71,16 @@ func TestSWA(t *testing.T) {
 			expectedShape: []int{1, 1, 4},
 			expectedMask:  []float32{0, float32(math.Inf(-1)), float32(math.Inf(-1)), float32(math.Inf(-1)), 0, 0, float32(math.Inf(-1)), float32(math.Inf(-1)), float32(math.Inf(-1)), 0, 0, float32(math.Inf(-1)), float32(math.Inf(-1)), float32(math.Inf(-1)), 0, 0},
 		},
+		{
+			name:          "SecondBatch",
+			in:            []float32{5, 6},
+			inShape:       []int{1, 1, 2},
+			seqs:          []int{0, 0},
+			pos:           []int32{4, 5},
+			expected:      []float32{5, 6, 3, 4},
+			expectedShape: []int{1, 1, 4},
+			expectedMask:  []float32{0, float32(math.Inf(-1)), float32(math.Inf(-1)), 0, 0, 0, float32(math.Inf(-1)), float32(math.Inf(-1))},
+		},
 	}
 
 	testCache(t, backend, cache, tests)

From d14ce75b95430eedecdf9c1dacd6912df61a1ad7 Mon Sep 17 00:00:00 2001
From: Parth Sareen <parth.sareen@ollama.com>
Date: Fri, 21 Mar 2025 12:35:47 -0700
Subject: [PATCH 123/157] docs: update final response for /api/chat stream
 (#9919)

---
 docs/api.md | 4 ++++
 1 file changed, 4 insertions(+)

diff --git a/docs/api.md b/docs/api.md
index 7de81049..fe044d79 100644
--- a/docs/api.md
+++ b/docs/api.md
@@ -558,6 +558,10 @@ Final response:
 {
   "model": "llama3.2",
   "created_at": "2023-08-04T19:22:45.499127Z",
+  "message": {
+    "role": "assistant",
+    "content": ""
+  },
   "done": true,
   "total_duration": 4883583458,
   "load_duration": 1334875,

From 00ebda8cc4f2031096973b26d6b0de7425a9ca82 Mon Sep 17 00:00:00 2001
From: Parth Sareen <parth.sareen@ollama.com>
Date: Fri, 21 Mar 2025 12:38:09 -0700
Subject: [PATCH 124/157] Revert "parser: remove role validation from Modelfile
 parser" (#9917)

This reverts commit ffbfe833da387f9b6806fe887b85992c11d26eaa.
---
 parser/parser.go      | 18 +++++++++++-------
 parser/parser_test.go | 10 +++++-----
 2 files changed, 16 insertions(+), 12 deletions(-)

diff --git a/parser/parser.go b/parser/parser.go
index 0a32d571..6832351f 100644
--- a/parser/parser.go
+++ b/parser/parser.go
@@ -7,7 +7,6 @@ import (
 	"errors"
 	"fmt"
 	"io"
-	"log/slog"
 	"net/http"
 	"os"
 	"os/user"
@@ -301,8 +300,9 @@ const (
 )
 
 var (
-	errMissingFrom    = errors.New("no FROM line")
-	errInvalidCommand = errors.New("command must be one of \"from\", \"license\", \"template\", \"system\", \"adapter\", \"parameter\", or \"message\"")
+	errMissingFrom        = errors.New("no FROM line")
+	errInvalidMessageRole = errors.New("message role must be one of \"system\", \"user\", or \"assistant\"")
+	errInvalidCommand     = errors.New("command must be one of \"from\", \"license\", \"template\", \"system\", \"adapter\", \"parameter\", or \"message\"")
 )
 
 type ParserError struct {
@@ -379,10 +379,14 @@ func ParseFile(r io.Reader) (*Modelfile, error) {
 			case stateParameter:
 				cmd.Name = b.String()
 			case stateMessage:
-				role = b.String()
-				if !isKnownMessageRole(b.String()) {
-					slog.Warn("received non-standard role", "role", role)
+				if !isValidMessageRole(b.String()) {
+					return nil, &ParserError{
+						LineNumber: currLine,
+						Msg:        errInvalidMessageRole.Error(),
+					}
 				}
+
+				role = b.String()
 			case stateComment, stateNil:
 				// pass
 			case stateValue:
@@ -552,7 +556,7 @@ func isNewline(r rune) bool {
 	return r == '\r' || r == '\n'
 }
 
-func isKnownMessageRole(role string) bool {
+func isValidMessageRole(role string) bool {
 	return role == "system" || role == "user" || role == "assistant"
 }
 
diff --git a/parser/parser_test.go b/parser/parser_test.go
index c4f8f4aa..097c058f 100644
--- a/parser/parser_test.go
+++ b/parser/parser_test.go
@@ -256,13 +256,13 @@ You are a multiline file parser. Always parse things.
 		{
 			`
 FROM foo
-MESSAGE somerandomrole I'm ok with you adding any role message now!
+MESSAGE badguy I'm a bad guy!
 `,
-			[]Command{
-				{Name: "model", Args: "foo"},
-				{Name: "message", Args: "somerandomrole: I'm ok with you adding any role message now!"},
-			},
 			nil,
+			&ParserError{
+				LineNumber: 3,
+				Msg:        errInvalidMessageRole.Error(),
+			},
 		},
 		{
 			`

From c794fef2f27d141393064665d2774b341d091393 Mon Sep 17 00:00:00 2001
From: Blake Mizerany <blake.mizerany@gmail.com>
Date: Fri, 21 Mar 2025 13:03:43 -0700
Subject: [PATCH 125/157] server/internal/client/ollama: persist through chunk
 download errors (#9923)

---
 server/internal/client/ollama/registry.go     | 61 ++++++++++++-------
 .../internal/client/ollama/registry_test.go   | 31 +++++++++-
 server/internal/registry/server.go            | 33 ++++++----
 3 files changed, 89 insertions(+), 36 deletions(-)

diff --git a/server/internal/client/ollama/registry.go b/server/internal/client/ollama/registry.go
index fdac71bb..59041867 100644
--- a/server/internal/client/ollama/registry.go
+++ b/server/internal/client/ollama/registry.go
@@ -59,6 +59,11 @@ var (
 	// ErrCached is passed to [Trace.PushUpdate] when a layer already
 	// exists. It is a non-fatal error and is never returned by [Registry.Push].
 	ErrCached = errors.New("cached")
+
+	// ErrIncomplete is returned by [Registry.Pull] when a model pull was
+	// incomplete due to one or more layer download failures. Users that
+	// want specific errors should use [WithTrace].
+	ErrIncomplete = errors.New("incomplete")
 )
 
 // Defaults
@@ -271,8 +276,19 @@ func DefaultRegistry() (*Registry, error) {
 
 func UserAgent() string {
 	buildinfo, _ := debug.ReadBuildInfo()
+
+	version := buildinfo.Main.Version
+	if version == "(devel)" {
+		// When using `go run .` the version is "(devel)". This is seen
+		// as an invalid version by ollama.com and so it defaults to
+		// "needs upgrade" for some requests, such as pulls. These
+		// checks can be skipped by using the special version "v0.0.0",
+		// so we set it to that here.
+		version = "v0.0.0"
+	}
+
 	return fmt.Sprintf("ollama/%s (%s %s) Go/%s",
-		buildinfo.Main.Version,
+		version,
 		runtime.GOARCH,
 		runtime.GOOS,
 		runtime.Version(),
@@ -418,13 +434,14 @@ func canRetry(err error) bool {
 //
 // It always calls update with a nil error.
 type trackingReader struct {
-	r io.Reader
-	n *atomic.Int64
+	l      *Layer
+	r      io.Reader
+	update func(l *Layer, n int64, err error)
 }
 
 func (r *trackingReader) Read(p []byte) (n int, err error) {
 	n, err = r.r.Read(p)
-	r.n.Add(int64(n))
+	r.update(r.l, int64(n), nil)
 	return
 }
 
@@ -462,16 +479,20 @@ func (r *Registry) Pull(ctx context.Context, name string) error {
 
 	// Send initial layer trace events to allow clients to have an
 	// understanding of work to be done before work starts.
+	var expected int64
 	t := traceFromContext(ctx)
 	for _, l := range layers {
 		t.update(l, 0, nil)
+		expected += l.Size
 	}
 
+	var total atomic.Int64
 	var g errgroup.Group
 	g.SetLimit(r.maxStreams())
 	for _, l := range layers {
 		info, err := c.Get(l.Digest)
 		if err == nil && info.Size == l.Size {
+			total.Add(l.Size)
 			t.update(l, l.Size, ErrCached)
 			continue
 		}
@@ -484,21 +505,25 @@ func (r *Registry) Pull(ctx context.Context, name string) error {
 		// TODO(bmizerany): fix this unbounded use of defer
 		defer chunked.Close()
 
-		var progress atomic.Int64
 		for cs, err := range r.chunksums(ctx, name, l) {
 			if err != nil {
-				// Bad chunksums response, update tracing
-				// clients and then bail.
-				t.update(l, progress.Load(), err)
-				return err
+				// Chunksum stream was interrupted, so tell
+				// trace about it, and let in-flight chunk
+				// downloads finish. Once they finish, return
+				// ErrIncomplete, which is triggered by the
+				// fact that the total bytes received is less
+				// than the expected bytes.
+				t.update(l, 0, err)
+				break
 			}
 
 			g.Go(func() (err error) {
 				defer func() {
-					if err != nil {
+					if err == nil || errors.Is(err, ErrCached) {
+						total.Add(cs.Chunk.Size())
+					} else {
 						err = fmt.Errorf("error downloading %s: %w", cs.Digest.Short(), err)
 					}
-					t.update(l, progress.Load(), err)
 				}()
 
 				req, err := http.NewRequestWithContext(ctx, "GET", cs.URL, nil)
@@ -522,7 +547,7 @@ func (r *Registry) Pull(ctx context.Context, name string) error {
 				// download rate since it knows better than a
 				// client that is measuring rate based on
 				// wall-clock time-since-last-update.
-				body := &trackingReader{r: res.Body, n: &progress}
+				body := &trackingReader{l: l, r: res.Body, update: t.update}
 
 				return chunked.Put(cs.Chunk, cs.Digest, body)
 			})
@@ -531,6 +556,9 @@ func (r *Registry) Pull(ctx context.Context, name string) error {
 	if err := g.Wait(); err != nil {
 		return err
 	}
+	if total.Load() != expected {
+		return fmt.Errorf("%w: received %d/%d", ErrIncomplete, total.Load(), expected)
+	}
 
 	md := blob.DigestFromBytes(m.Data)
 	if err := blob.PutBytes(c, md, m.Data); err != nil {
@@ -757,15 +785,12 @@ func (r *Registry) chunksums(ctx context.Context, name string, l *Layer) iter.Se
 		}
 		blobURL := res.Header.Get("Content-Location")
 
-		var size int64
 		s := bufio.NewScanner(res.Body)
 		s.Split(bufio.ScanWords)
 		for {
 			if !s.Scan() {
 				if s.Err() != nil {
 					yield(chunksum{}, s.Err())
-				} else if size != l.Size {
-					yield(chunksum{}, fmt.Errorf("size mismatch: layer size %d != sum of chunks %d", size, l.Size))
 				}
 				return
 			}
@@ -789,12 +814,6 @@ func (r *Registry) chunksums(ctx context.Context, name string, l *Layer) iter.Se
 				return
 			}
 
-			size += chunk.Size()
-			if size > l.Size {
-				yield(chunksum{}, fmt.Errorf("chunk size %d exceeds layer size %d", size, l.Size))
-				return
-			}
-
 			cs := chunksum{
 				URL:    blobURL,
 				Chunk:  chunk,
diff --git a/server/internal/client/ollama/registry_test.go b/server/internal/client/ollama/registry_test.go
index 30529543..f8136c06 100644
--- a/server/internal/client/ollama/registry_test.go
+++ b/server/internal/client/ollama/registry_test.go
@@ -25,6 +25,28 @@ import (
 	"github.com/ollama/ollama/server/internal/testutil"
 )
 
+func ExampleRegistry_cancelOnFirstError() {
+	ctx, cancel := context.WithCancel(context.Background())
+	defer cancel()
+
+	ctx = WithTrace(ctx, &Trace{
+		Update: func(l *Layer, n int64, err error) {
+			if err != nil {
+				// Discontinue pulling layers if there is an
+				// error instead of continuing to pull more
+				// data.
+				cancel()
+			}
+		},
+	})
+
+	var r Registry
+	if err := r.Pull(ctx, "model"); err != nil {
+		// panic for demo purposes
+		panic(err)
+	}
+}
+
 func TestManifestMarshalJSON(t *testing.T) {
 	// All manifests should contain an "empty" config object.
 	var m Manifest
@@ -813,8 +835,13 @@ func TestPullChunksums(t *testing.T) {
 	)
 	err := rc.Pull(ctx, "test")
 	check(err)
-	if !slices.Equal(reads, []int64{0, 3, 5}) {
-		t.Errorf("reads = %v; want %v", reads, []int64{0, 3, 5})
+	wantReads := []int64{
+		0, // initial signaling of layer pull starting
+		3, // first chunk read
+		2, // second chunk read
+	}
+	if !slices.Equal(reads, wantReads) {
+		t.Errorf("reads = %v; want %v", reads, wantReads)
 	}
 
 	mw, err := rc.Resolve(t.Context(), "test")
diff --git a/server/internal/registry/server.go b/server/internal/registry/server.go
index 2a935b52..1910b187 100644
--- a/server/internal/registry/server.go
+++ b/server/internal/registry/server.go
@@ -200,7 +200,7 @@ type params struct {
 	//
 	// Unfortunately, this API was designed to be a bit awkward. Stream is
 	// defined to default to true if not present, so we need a way to check
-	// if the client decisively it to false. So, we use a pointer to a
+	// if the client decisively set it to false. So, we use a pointer to a
 	// bool. Gross.
 	//
 	// Use [stream()] to get the correct value for this field.
@@ -280,17 +280,17 @@ func (s *Local) handlePull(w http.ResponseWriter, r *http.Request) error {
 	progress := make(map[*ollama.Layer]int64)
 
 	progressCopy := make(map[*ollama.Layer]int64, len(progress))
-	pushUpdate := func() {
+	flushProgress := func() {
 		defer maybeFlush()
 
-		// TODO(bmizerany): This scales poorly with more layers due to
-		// needing to flush out them all in one big update. We _could_
-		// just flush on the changed ones, or just track the whole
-		// download. Needs more thought. This is fine for now.
+		// TODO(bmizerany): Flushing every layer in one update doesn't
+		// scale well. We could flush only the modified layers or track
+		// the full download. Needs further consideration, though it's
+		// fine for now.
 		mu.Lock()
 		maps.Copy(progressCopy, progress)
 		mu.Unlock()
-		for l, n := range progress {
+		for l, n := range progressCopy {
 			enc.Encode(progressUpdateJSON{
 				Digest:    l.Digest,
 				Total:     l.Size,
@@ -298,19 +298,26 @@ func (s *Local) handlePull(w http.ResponseWriter, r *http.Request) error {
 			})
 		}
 	}
+	defer flushProgress()
 
-	t := time.NewTicker(time.Hour) // "unstarted" timer
+	t := time.NewTicker(1000 * time.Hour) // "unstarted" timer
 	start := sync.OnceFunc(func() {
-		pushUpdate()
+		flushProgress() // flush initial state
 		t.Reset(100 * time.Millisecond)
 	})
 	ctx := ollama.WithTrace(r.Context(), &ollama.Trace{
 		Update: func(l *ollama.Layer, n int64, err error) {
 			if n > 0 {
-				start() // flush initial state
+				// Block flushing progress updates until every
+				// layer is accounted for. Clients depend on a
+				// complete model size to calculate progress
+				// correctly; if they use an incomplete total,
+				// progress indicators would erratically jump
+				// as new layers are registered.
+				start()
 			}
 			mu.Lock()
-			progress[l] = n
+			progress[l] += n
 			mu.Unlock()
 		},
 	})
@@ -323,9 +330,9 @@ func (s *Local) handlePull(w http.ResponseWriter, r *http.Request) error {
 	for {
 		select {
 		case <-t.C:
-			pushUpdate()
+			flushProgress()
 		case err := <-done:
-			pushUpdate()
+			flushProgress()
 			if err != nil {
 				var status string
 				if errors.Is(err, ollama.ErrModelNotFound) {

From fb6252d786c9cafdd2dbfa434535d85c611c0ff0 Mon Sep 17 00:00:00 2001
From: Bruce MacDonald <brucewmacdonald@gmail.com>
Date: Fri, 21 Mar 2025 13:08:20 -0700
Subject: [PATCH 126/157] benchmark: performance of running ollama server
 (#8643)

---
 benchmark/server_benchmark_test.go | 178 +++++++++++++++++++++++++++++
 docs/benchmark.md                  |  59 ++++++++++
 2 files changed, 237 insertions(+)
 create mode 100644 benchmark/server_benchmark_test.go
 create mode 100644 docs/benchmark.md

diff --git a/benchmark/server_benchmark_test.go b/benchmark/server_benchmark_test.go
new file mode 100644
index 00000000..b27aa630
--- /dev/null
+++ b/benchmark/server_benchmark_test.go
@@ -0,0 +1,178 @@
+package benchmark
+
+import (
+	"context"
+	"flag"
+	"fmt"
+	"testing"
+	"time"
+
+	"github.com/ollama/ollama/api"
+)
+
+// Command line flags
+var modelFlag string
+
+func init() {
+	flag.StringVar(&modelFlag, "m", "", "Name of the model to benchmark")
+	flag.Lookup("m").DefValue = "model"
+}
+
+// modelName returns the model name from flags, failing the test if not set
+func modelName(b *testing.B) string {
+	if modelFlag == "" {
+		b.Fatal("Error: -m flag is required for benchmark tests")
+	}
+	return modelFlag
+}
+
+type TestCase struct {
+	name      string
+	prompt    string
+	maxTokens int
+}
+
+// runGenerateBenchmark contains the common generate and metrics logic
+func runGenerateBenchmark(b *testing.B, ctx context.Context, client *api.Client, req *api.GenerateRequest) {
+	start := time.Now()
+	var ttft time.Duration
+	var metrics api.Metrics
+
+	err := client.Generate(ctx, req, func(resp api.GenerateResponse) error {
+		if ttft == 0 && resp.Response != "" {
+			ttft = time.Since(start)
+		}
+		if resp.Done {
+			metrics = resp.Metrics
+		}
+		return nil
+	})
+
+	// Report custom metrics as part of the benchmark results
+	b.ReportMetric(float64(ttft.Milliseconds()), "ttft_ms")
+	b.ReportMetric(float64(metrics.LoadDuration.Milliseconds()), "load_ms")
+
+	// Token throughput metrics
+	promptThroughput := float64(metrics.PromptEvalCount) / metrics.PromptEvalDuration.Seconds()
+	genThroughput := float64(metrics.EvalCount) / metrics.EvalDuration.Seconds()
+	b.ReportMetric(promptThroughput, "prompt_tok/s")
+	b.ReportMetric(genThroughput, "gen_tok/s")
+
+	// Token counts
+	b.ReportMetric(float64(metrics.PromptEvalCount), "prompt_tokens")
+	b.ReportMetric(float64(metrics.EvalCount), "gen_tokens")
+	if err != nil {
+		b.Fatal(err)
+	}
+}
+
+// BenchmarkColdStart runs benchmarks with model loading from cold state
+func BenchmarkColdStart(b *testing.B) {
+	client := setup(b)
+	tests := []TestCase{
+		{"short_prompt", "Write a long story", 100},
+		{"medium_prompt", "Write a detailed economic analysis", 500},
+		{"long_prompt", "Write a comprehensive AI research paper", 1000},
+	}
+	m := modelName(b)
+
+	for _, tt := range tests {
+		b.Run(fmt.Sprintf("%s/cold/%s", m, tt.name), func(b *testing.B) {
+			ctx := context.Background()
+
+			// Set number of tokens as our throughput metric
+			b.SetBytes(int64(tt.maxTokens))
+
+			for b.Loop() {
+				b.StopTimer()
+				// Ensure model is unloaded before each iteration
+				unload(client, m, b)
+				b.StartTimer()
+
+				req := &api.GenerateRequest{
+					Model:   m,
+					Prompt:  tt.prompt,
+					Options: map[string]interface{}{"num_predict": tt.maxTokens, "temperature": 0.1},
+				}
+
+				runGenerateBenchmark(b, ctx, client, req)
+			}
+		})
+	}
+}
+
+// BenchmarkWarmStart runs benchmarks with pre-loaded model
+func BenchmarkWarmStart(b *testing.B) {
+	client := setup(b)
+	tests := []TestCase{
+		{"short_prompt", "Write a long story", 100},
+		{"medium_prompt", "Write a detailed economic analysis", 500},
+		{"long_prompt", "Write a comprehensive AI research paper", 1000},
+	}
+	m := modelName(b)
+
+	for _, tt := range tests {
+		b.Run(fmt.Sprintf("%s/warm/%s", m, tt.name), func(b *testing.B) {
+			ctx := context.Background()
+
+			// Pre-warm the model
+			warmup(client, m, tt.prompt, b)
+
+			// Set number of tokens as our throughput metric
+			b.SetBytes(int64(tt.maxTokens))
+
+			for b.Loop() {
+				req := &api.GenerateRequest{
+					Model:   m,
+					Prompt:  tt.prompt,
+					Options: map[string]any{"num_predict": tt.maxTokens, "temperature": 0.1},
+				}
+
+				runGenerateBenchmark(b, ctx, client, req)
+			}
+		})
+	}
+}
+
+// setup verifies server and model availability
+func setup(b *testing.B) *api.Client {
+	client, err := api.ClientFromEnvironment()
+	if err != nil {
+		b.Fatal(err)
+	}
+	if _, err := client.Show(context.Background(), &api.ShowRequest{Model: modelName(b)}); err != nil {
+		b.Fatalf("Model unavailable: %v", err)
+	}
+
+	return client
+}
+
+// warmup ensures the model is loaded and warmed up
+func warmup(client *api.Client, model string, prompt string, b *testing.B) {
+	for range 3 {
+		err := client.Generate(
+			context.Background(),
+			&api.GenerateRequest{
+				Model:   model,
+				Prompt:  prompt,
+				Options: map[string]interface{}{"num_predict": 50, "temperature": 0.1},
+			},
+			func(api.GenerateResponse) error { return nil },
+		)
+		if err != nil {
+			b.Logf("Error during model warm-up: %v", err)
+		}
+	}
+}
+
+// unload forces model unloading using KeepAlive: 0 parameter
+func unload(client *api.Client, model string, b *testing.B) {
+	req := &api.GenerateRequest{
+		Model:     model,
+		KeepAlive: &api.Duration{Duration: 0},
+	}
+	if err := client.Generate(context.Background(), req, func(api.GenerateResponse) error { return nil }); err != nil {
+		b.Logf("Unload error: %v", err)
+	}
+	time.Sleep(1 * time.Second)
+}
diff --git a/docs/benchmark.md b/docs/benchmark.md
new file mode 100644
index 00000000..a7bed808
--- /dev/null
+++ b/docs/benchmark.md
@@ -0,0 +1,59 @@
+# Benchmark
+
+Go benchmark tests that measure end-to-end performance of a running Ollama server. Run these tests to evaluate model inference performance on your hardware and measure the impact of code changes.
+
+## When to use
+
+Run these benchmarks when:
+- Making changes to the model inference engine
+- Modifying model loading/unloading logic
+- Changing prompt processing or token generation code
+- Implementing a new model architecture
+- Testing performance across different hardware setups
+
+## Prerequisites
+- Ollama server running locally with `ollama serve` on `127.0.0.1:11434`
+## Usage and Examples
+
+>[!NOTE]
+>All commands must be run from the root directory of the Ollama project.
+
+Basic syntax:
+```bash
+go test -bench=. ./benchmark/... -m $MODEL_NAME
+```
+
+Required flags:
+- `-bench=.`: Run all benchmarks
+- `-m`: Model name to benchmark
+
+Optional flags:
+- `-count N`: Number of times to run the benchmark (useful for statistical analysis)
+- `-timeout T`: Maximum time for the benchmark to run (e.g. "10m" for 10 minutes)
+
+Common usage patterns:
+
+Single benchmark run with a model specified:
+```bash
+go test -bench=. ./benchmark/... -m llama3.3
+```
+
+## Output metrics
+
+The benchmark reports several key metrics:
+
+- `gen_tok/s`: Generated tokens per second
+- `prompt_tok/s`: Prompt processing tokens per second
+- `ttft_ms`: Time to first token in milliseconds
+- `load_ms`: Model load time in milliseconds
+- `gen_tokens`: Total tokens generated
+- `prompt_tokens`: Total prompt tokens processed
+
+Each benchmark runs two scenarios:
+- Cold start: Model is loaded from disk for each test
+- Warm start: Model is pre-loaded in memory
+
+Three prompt lengths are tested for each scenario:
+- Short prompt (100 tokens)
+- Medium prompt (500 tokens)
+- Long prompt (1000 tokens)

From 74bd09652d69c77a4bed34b3afda74c87295115b Mon Sep 17 00:00:00 2001
From: Michael Yang <mxyng@pm.me>
Date: Wed, 19 Mar 2025 13:03:16 -0700
Subject: [PATCH 127/157] ml/backend/ggml: load tensors in 32KiB chunks

---
 ml/backend.go                 |  9 ++---
 ml/backend/ggml/ggml.go       | 65 ++++++++++++++++++++++++-----------
 model/model.go                |  5 +--
 runner/ollamarunner/runner.go | 11 +++---
 4 files changed, 59 insertions(+), 31 deletions(-)

diff --git a/ml/backend.go b/ml/backend.go
index 66eb37f7..354faf43 100644
--- a/ml/backend.go
+++ b/ml/backend.go
@@ -2,6 +2,7 @@ package ml
 
 import (
 	"bytes"
+	"context"
 	"encoding/binary"
 	"fmt"
 	"os"
@@ -80,9 +81,9 @@ type BackendParams struct {
 	FlashAttention bool
 }
 
-var backends = make(map[string]func(*os.File, BackendParams) (Backend, error))
+var backends = make(map[string]func(context.Context, *os.File, BackendParams) (Backend, error))
 
-func RegisterBackend(name string, f func(*os.File, BackendParams) (Backend, error)) {
+func RegisterBackend(name string, f func(context.Context, *os.File, BackendParams) (Backend, error)) {
 	if _, ok := backends[name]; ok {
 		panic("backend: backend already registered")
 	}
@@ -90,9 +91,9 @@ func RegisterBackend(name string, f func(*os.File, BackendParams) (Backend, erro
 	backends[name] = f
 }
 
-func NewBackend(f *os.File, params BackendParams) (Backend, error) {
+func NewBackend(ctx context.Context, f *os.File, params BackendParams) (Backend, error) {
 	if backend, ok := backends["ggml"]; ok {
-		return backend(f, params)
+		return backend(ctx, f, params)
 	}
 
 	return nil, fmt.Errorf("unsupported backend")
diff --git a/ml/backend/ggml/ggml.go b/ml/backend/ggml/ggml.go
index 6732470e..f6b01774 100644
--- a/ml/backend/ggml/ggml.go
+++ b/ml/backend/ggml/ggml.go
@@ -9,15 +9,17 @@ package ggml
 import "C"
 
 import (
-	"errors"
+	"context"
 	"fmt"
 	"io"
 	"log/slog"
 	"maps"
 	"os"
+	"runtime"
 	"slices"
 	"strconv"
 	"strings"
+	"sync/atomic"
 	"unicode"
 	"unsafe"
 
@@ -58,7 +60,7 @@ type Backend struct {
 	maxGraphNodes int
 }
 
-func New(r *os.File, params ml.BackendParams) (ml.Backend, error) {
+func New(ctx context.Context, r *os.File, params ml.BackendParams) (ml.Backend, error) {
 	meta, n, err := fs.Decode(r, -1)
 	if err != nil {
 		return nil, err
@@ -297,12 +299,16 @@ func New(r *os.File, params ml.BackendParams) (ml.Backend, error) {
 		}
 	}
 
-	// concurrently read in tensor data. uses a section reader which is safe for concurrent reads
-	sr := io.NewSectionReader(r, int64(meta.Tensors().Offset), n-int64(meta.Tensors().Offset))
-	var g errgroup.Group
+	var doneBytes atomic.Uint64
+	totalBytes := uint64(n) - meta.Tensors().Offset
+
+	g, ctx := errgroup.WithContext(ctx)
+	g.SetLimit(runtime.GOMAXPROCS(0))
 	for _, t := range meta.Tensors().Items() {
-		for _, target := range targets[t.Name] {
-			g.Go(func() error {
+		g.Go(func() error {
+			tts := make([]*C.struct_ggml_tensor, max(1, len(targets[t.Name])))
+			for i := range tts {
+				target := targets[t.Name][i]
 				if target == "" {
 					target = t.Name
 				}
@@ -312,24 +318,43 @@ func New(r *os.File, params ml.BackendParams) (ml.Backend, error) {
 					return fmt.Errorf("unassigned tensor: %s", t.Name)
 				}
 
-				bts := C.malloc(C.size_t(t.Size()))
-				if bts == nil {
-					return errors.New("failed to allocate tensor buffer")
-				}
-				defer C.free(bts)
+				tts[i] = tt
+			}
 
-				buf := unsafe.Slice((*byte)(bts), t.Size())
-				n, err := io.ReadFull(io.NewSectionReader(sr, int64(t.Offset), int64(t.Size())), buf)
-				if err != nil || n != len(buf) {
-					return errors.New("read failed")
+			sr := io.NewSectionReader(r, int64(meta.Tensors().Offset+t.Offset), int64(t.Size()))
+			bts := make([]byte, 128*format.KibiByte)
+
+			var s uint64
+			for s < t.Size() {
+				n, err := io.ReadFull(sr, bts[:min(len(bts), int(t.Size()-s))])
+				if err != nil {
+					return err
 				}
 
-				C.ggml_backend_tensor_set(tt, bts, 0, C.size_t(t.Size()))
-				return nil
-			})
-		}
+				for _, tt := range tts {
+					C.ggml_backend_tensor_set(tt, unsafe.Pointer(&bts[0]), C.size_t(s), C.size_t(n))
+				}
+
+				s += uint64(n)
+
+				if params.Progress != nil {
+					done := doneBytes.Add(uint64(n))
+					params.Progress(float32(done) / float32(totalBytes))
+				}
+			}
+
+			return nil
+		})
 	}
 
+	// start a goroutine to cancel the errgroup if the parent context is done
+	go func() {
+		<-ctx.Done()
+		g.Go(func() error {
+			return ctx.Err()
+		})
+	}()
+
 	if err := g.Wait(); err != nil {
 		return nil, err
 	}
diff --git a/model/model.go b/model/model.go
index ab29916a..8355a55a 100644
--- a/model/model.go
+++ b/model/model.go
@@ -1,6 +1,7 @@
 package model
 
 import (
+	"context"
 	"errors"
 	"fmt"
 	_ "image/jpeg"
@@ -94,14 +95,14 @@ func Register(name string, f func(ml.Config) (Model, error)) {
 }
 
 // New initializes a new model instance with the provided configuration based on the metadata in the model file
-func New(modelPath string, params ml.BackendParams) (Model, error) {
+func New(ctx context.Context, modelPath string, params ml.BackendParams) (Model, error) {
 	r, err := os.Open(modelPath)
 	if err != nil {
 		return nil, err
 	}
 	defer r.Close()
 
-	b, err := ml.NewBackend(r, params)
+	b, err := ml.NewBackend(ctx, r, params)
 	if err != nil {
 		return nil, err
 	}
diff --git a/runner/ollamarunner/runner.go b/runner/ollamarunner/runner.go
index 67d9a1b0..31d20db8 100644
--- a/runner/ollamarunner/runner.go
+++ b/runner/ollamarunner/runner.go
@@ -678,6 +678,7 @@ func (m *multiLPath) String() string {
 }
 
 func (s *Server) loadModel(
+	ctx context.Context,
 	mpath string,
 	params ml.BackendParams,
 	lpath multiLPath,
@@ -687,7 +688,7 @@ func (s *Server) loadModel(
 	multiUserCache bool,
 ) {
 	var err error
-	s.model, err = model.New(mpath, params)
+	s.model, err = model.New(ctx, mpath, params)
 	if err != nil {
 		panic(err)
 	}
@@ -794,13 +795,13 @@ func Execute(args []string) error {
 	}
 
 	server.ready.Add(1)
-	go server.loadModel(*mpath, params, lpaths, *parallel, *kvCacheType, *kvSize, *multiUserCache)
-
-	server.cond = sync.NewCond(&server.mu)
-
 	ctx, cancel := context.WithCancel(context.Background())
 	defer cancel()
 
+	go server.loadModel(ctx, *mpath, params, lpaths, *parallel, *kvCacheType, *kvSize, *multiUserCache)
+
+	server.cond = sync.NewCond(&server.mu)
+
 	go server.run(ctx)
 
 	addr := "127.0.0.1:" + strconv.Itoa(*port)

From ce929984a33230269905e0e3cfa335cb8d6ba781 Mon Sep 17 00:00:00 2001
From: Blake Mizerany <blake.mizerany@gmail.com>
Date: Fri, 21 Mar 2025 16:16:38 -0700
Subject: [PATCH 128/157] server/internal/client/ollama: fix file descriptor
 management in Pull (#9931)

Close chunked writers as soon as downloads complete, rather than
deferring closure until Pull exits. This prevents exhausting file
descriptors when pulling many layers.

Instead of unbounded defers, use a WaitGroup and background goroutine
to close each chunked writer as soon as its downloads finish.

Also rename 'total' to 'received' for clarity.
---
 server/internal/client/ollama/registry.go | 56 +++++++++++++----------
 1 file changed, 31 insertions(+), 25 deletions(-)

diff --git a/server/internal/client/ollama/registry.go b/server/internal/client/ollama/registry.go
index 59041867..665defd5 100644
--- a/server/internal/client/ollama/registry.go
+++ b/server/internal/client/ollama/registry.go
@@ -486,44 +486,43 @@ func (r *Registry) Pull(ctx context.Context, name string) error {
 		expected += l.Size
 	}
 
-	var total atomic.Int64
+	var received atomic.Int64
 	var g errgroup.Group
 	g.SetLimit(r.maxStreams())
 	for _, l := range layers {
 		info, err := c.Get(l.Digest)
 		if err == nil && info.Size == l.Size {
-			total.Add(l.Size)
+			received.Add(l.Size)
 			t.update(l, l.Size, ErrCached)
 			continue
 		}
 
+		var wg sync.WaitGroup
 		chunked, err := c.Chunked(l.Digest, l.Size)
 		if err != nil {
 			t.update(l, 0, err)
 			continue
 		}
-		// TODO(bmizerany): fix this unbounded use of defer
-		defer chunked.Close()
 
 		for cs, err := range r.chunksums(ctx, name, l) {
 			if err != nil {
-				// Chunksum stream was interrupted, so tell
-				// trace about it, and let in-flight chunk
-				// downloads finish. Once they finish, return
-				// ErrIncomplete, which is triggered by the
-				// fact that the total bytes received is less
-				// than the expected bytes.
+				// Chunksum stream interrupted. Note in trace
+				// log and let in-flight downloads complete.
+				// This will naturally trigger ErrIncomplete
+				// since received < expected bytes.
 				t.update(l, 0, err)
 				break
 			}
 
+			wg.Add(1)
 			g.Go(func() (err error) {
 				defer func() {
-					if err == nil || errors.Is(err, ErrCached) {
-						total.Add(cs.Chunk.Size())
+					if err == nil {
+						received.Add(cs.Chunk.Size())
 					} else {
 						err = fmt.Errorf("error downloading %s: %w", cs.Digest.Short(), err)
 					}
+					wg.Done()
 				}()
 
 				req, err := http.NewRequestWithContext(ctx, "GET", cs.URL, nil)
@@ -537,27 +536,34 @@ func (r *Registry) Pull(ctx context.Context, name string) error {
 				}
 				defer res.Body.Close()
 
-				// Count bytes towards progress, as they
-				// arrive, so that our bytes piggyback other
-				// chunk updates on completion.
-				//
-				// This tactic is enough to show "smooth"
-				// progress given the current CLI client. In
-				// the near future, the server should report
-				// download rate since it knows better than a
-				// client that is measuring rate based on
-				// wall-clock time-since-last-update.
 				body := &trackingReader{l: l, r: res.Body, update: t.update}
-
 				return chunked.Put(cs.Chunk, cs.Digest, body)
 			})
 		}
+
+		// Close writer immediately after downloads finish, not at Pull
+		// exit. Using defer would keep file descriptors open until all
+		// layers complete, potentially exhausting system limits with
+		// many layers.
+		//
+		// The WaitGroup tracks when all chunks finish downloading,
+		// allowing precise writer closure in a background goroutine.
+		// Each layer briefly uses one extra goroutine while at most
+		// maxStreams()-1 chunks download in parallel.
+		//
+		// This caps file descriptors at maxStreams() instead of
+		// growing with layer count.
+		g.Go(func() error {
+			wg.Wait()
+			chunked.Close()
+			return nil
+		})
 	}
 	if err := g.Wait(); err != nil {
 		return err
 	}
-	if total.Load() != expected {
-		return fmt.Errorf("%w: received %d/%d", ErrIncomplete, total.Load(), expected)
+	if received.Load() != expected {
+		return fmt.Errorf("%w: received %d/%d", ErrIncomplete, received.Load(), expected)
 	}
 
 	md := blob.DigestFromBytes(m.Data)

From 131f0355a59f4840b057fb8f3c2e59e456f91041 Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?Matheus=20C=2E=20Fran=C3=A7a?=
 <matheus-catarino@hotmail.com>
Date: Mon, 24 Mar 2025 13:25:58 -0300
Subject: [PATCH 129/157] readme: add ollama-d library (#9907)

---
 README.md | 1 +
 1 file changed, 1 insertion(+)

diff --git a/README.md b/README.md
index 47d0aebd..50e8dba0 100644
--- a/README.md
+++ b/README.md
@@ -512,6 +512,7 @@ See the [API documentation](./docs/api.md) for all endpoints.
 - [Ollama for Zig](https://github.com/dravenk/ollama-zig)
 - [Abso](https://github.com/lunary-ai/abso) (OpenAI-compatible TypeScript SDK for any LLM provider)
 - [Nichey](https://github.com/goodreasonai/nichey) is a Python package for generating custom wikis for your research topic
+- [Ollama for D](https://github.com/kassane/ollama-d)
 
 ### Mobile
 

From 5e0b904e887fc648fb8a3a55283f8f33063a78eb Mon Sep 17 00:00:00 2001
From: copeland3300 <copeland3300@gmail.com>
Date: Tue, 25 Mar 2025 12:52:23 -0400
Subject: [PATCH 130/157] docs: add flags to example linux log output command
 (#9852)

---
 docs/troubleshooting.md | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/docs/troubleshooting.md b/docs/troubleshooting.md
index 4275cdf3..32ad48c4 100644
--- a/docs/troubleshooting.md
+++ b/docs/troubleshooting.md
@@ -9,7 +9,7 @@ cat ~/.ollama/logs/server.log
 On **Linux** systems with systemd, the logs can be found with this command:
 
 ```shell
-journalctl -u ollama --no-pager
+journalctl -u ollama --no-pager --follow --pager-end 
 ```
 
 When you run Ollama in a **container**, the logs go to stdout/stderr in the container:

From 1feff619779115d76f033eb59a7a896aad6c2e18 Mon Sep 17 00:00:00 2001
From: Jesse Gross <jesse@ollama.com>
Date: Mon, 24 Mar 2025 21:17:53 -0700
Subject: [PATCH 131/157] kvcache: Sliding window cache only needs a single
 batch total

When computing the size of the cache for sliding window attention,
we don't need to multiple the batch size by the number of parallel
sequences - the batch size is constant.

This also simplifies the check for whether to allocate the cache
size based on capacity or window size as the batch size is already
incorporated into the capacity when handled by the runner.
---
 kvcache/causal.go | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/kvcache/causal.go b/kvcache/causal.go
index aacaf540..fb4f0f74 100644
--- a/kvcache/causal.go
+++ b/kvcache/causal.go
@@ -119,10 +119,10 @@ func (c *Causal) Init(backend ml.Backend, dtype ml.DType, maxSequences, capacity
 	}
 
 	var cacheSize int
-	if c.windowSize == math.MaxInt32 || capacity < int(c.windowSize)+maxBatch {
+	if c.windowSize == math.MaxInt32 || capacity < int(c.windowSize) {
 		cacheSize = maxSequences * capacity
 	} else {
-		cacheSize = maxSequences * (int(c.windowSize) + maxBatch)
+		cacheSize = (maxSequences * int(c.windowSize)) + maxBatch
 	}
 	cacheSize = roundUp(cacheSize, c.config.CachePadding)
 	c.cells = make([]cacheCell, cacheSize)

From f4f0992b6ea5d651eff609461c24ece936bd5708 Mon Sep 17 00:00:00 2001
From: Jesse Gross <jesse@ollama.com>
Date: Tue, 25 Mar 2025 11:41:26 -0700
Subject: [PATCH 132/157] llm: Fix debug logging for memory estimates

---
 llm/memory.go | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/llm/memory.go b/llm/memory.go
index ac830ee8..86694d06 100644
--- a/llm/memory.go
+++ b/llm/memory.go
@@ -374,7 +374,7 @@ func (m MemoryEstimate) LogValue() slog.Value {
 			slog.Group(
 				"weights",
 				// memory of the weights
-				"total", format.HumanBytes2(m.memoryWeights),
+				"total", format.HumanBytes2(m.memoryWeights+m.memoryLayerOutput),
 				// memory of repeating layers
 				"repeating", format.HumanBytes2(m.memoryWeights),
 				// memory of non-repeating layers

From f66216e3990b73869341c58ac9561b26c468c558 Mon Sep 17 00:00:00 2001
From: Jesse Gross <jesse@ollama.com>
Date: Mon, 24 Mar 2025 13:39:07 -0700
Subject: [PATCH 133/157] ggml: Support heterogeneous KV cache layer sizes in
 memory estimation

Gemma3 uses sliding windows for its context on 5/6 layers, significantly
reducing memory usage but leading to uneven usage across layers,
which makes allocation to the correct GPU difficult. We currently
estimate very conservatively by assuming all layers are consistent
at the max size.

Llama3.2-vision is also inconsistent between self attention and cross
attention layers - at moment, we calculate the correct total size
and then average this across layers. In some cases, this may lead
to crashes if a large layer is placed on a GPU sized by the average.

This allows memory estimation to calculate per-layer KV cache size
and take this account when placing layers onto GPUs. We already do
this for weights that vary per-tensor, so this is a logical extension.

Fixes #9730
Fixes #9890
---
 fs/ggml/ggml.go    | 39 +++++++++++++++++++++++++++------------
 llm/memory.go      | 24 +++++++++++++++---------
 llm/memory_test.go |  4 ++--
 llm/server.go      |  2 +-
 server/sched.go    |  8 ++++----
 5 files changed, 49 insertions(+), 28 deletions(-)

diff --git a/fs/ggml/ggml.go b/fs/ggml/ggml.go
index 0be69e82..c88583fb 100644
--- a/fs/ggml/ggml.go
+++ b/fs/ggml/ggml.go
@@ -413,7 +413,7 @@ func Decode(rs io.ReadSeeker, maxArraySize int) (*GGML, int64, error) {
 	}, offset, nil
 }
 
-func (f GGML) GraphSize(context, batch uint64, kvCacheType string) (kv, partialOffload, fullOffload uint64) {
+func (f GGML) GraphSize(context, batch uint64, numParallel int, kvCacheType string) (kv []uint64, partialOffload, fullOffload uint64) {
 	embedding := f.KV().EmbeddingLength()
 	heads := f.KV().HeadCount()
 	headsKV := f.KV().HeadCountKV()
@@ -426,7 +426,10 @@ func (f GGML) GraphSize(context, batch uint64, kvCacheType string) (kv, partialO
 	layers := f.Tensors().GroupLayers()
 
 	bytesPerElement := kvCacheBytesPerElement(kvCacheType)
-	kv = uint64(float64(context*f.KV().BlockCount()*(embeddingHeadsK+embeddingHeadsV)*headsKV) * bytesPerElement)
+	kv = make([]uint64, f.KV().BlockCount())
+	for i := range kv {
+		kv[i] = uint64(float64(context*(embeddingHeadsK+embeddingHeadsV)*headsKV) * bytesPerElement)
+	}
 
 	switch f.KV().Architecture() {
 	case "llama":
@@ -460,16 +463,14 @@ func (f GGML) GraphSize(context, batch uint64, kvCacheType string) (kv, partialO
 	case "mllama":
 		var visionTokens, tiles uint64 = 1601, 4
 
-		if crossAttentionLayers, ok := f.KV()["mllama.attention.cross_attention_layers"].(*array); ok {
-			kv = headsKV *
-				(embeddingHeadsK + embeddingHeadsV) * // one for K, one for V
-				(2* // sizeof(float16)
-					(f.KV().BlockCount()-uint64(crossAttentionLayers.size))* // num non-cross attention layers
-					context +
-					4* // sizeof(float32)
-						uint64(crossAttentionLayers.size)* // num cross attention layers
-						visionTokens*
-						tiles)
+		crossAttentionLayers := f.KV().Uints("attention.cross_attention_layers")
+		for i := range kv {
+			if slices.Contains(crossAttentionLayers, uint32(i)) {
+				kv[i] = headsKV * (embeddingHeadsK + embeddingHeadsV) *
+					4 * // sizeof(float32)
+					visionTokens *
+					tiles
+			}
 		}
 
 		fullOffload = max(
@@ -505,6 +506,20 @@ func (f GGML) GraphSize(context, batch uint64, kvCacheType string) (kv, partialO
 				4*embeddingHeadsK*context*8+
 				embedding*embeddingHeadsK*heads*9/16,
 		)
+
+		// Gemma2 also has sliding window attention but we only have an optimized implementation in the Ollama
+		// engine. Gemma3 always uses the Ollama engine.
+		if f.KV().Architecture() == "gemma3" {
+			const gemma3GlobalCacheCount = 6
+			slidingWindow := (uint64(numParallel) * uint64(f.KV().Uint("attention.sliding_window"))) + batch
+			for i := range kv {
+				// Every 6th layer is a global layer, which is the full context size that has already been set. The other
+				// layers are the smaller local (sliding) layers.
+				if (i+1)%gemma3GlobalCacheCount != 0 {
+					kv[i] = uint64(float64(slidingWindow*(embeddingHeadsK+embeddingHeadsV)*headsKV) * bytesPerElement)
+				}
+			}
+		}
 	case "command-r":
 		fullOffload = max(
 			4*batch*(embedding+vocab),
diff --git a/llm/memory.go b/llm/memory.go
index 86694d06..85a0fabd 100644
--- a/llm/memory.go
+++ b/llm/memory.go
@@ -15,12 +15,12 @@ import (
 )
 
 // This algorithm looks for a complete fit to determine if we need to unload other models
-func PredictServerFit(allGpus discover.GpuInfoList, f *ggml.GGML, adapters, projectors []string, opts api.Options) (bool, uint64) {
+func PredictServerFit(allGpus discover.GpuInfoList, f *ggml.GGML, adapters, projectors []string, opts api.Options, numParallel int) (bool, uint64) {
 	// Split up the GPUs by type and try them
 	var estimatedVRAM uint64
 	for _, gpus := range allGpus.ByLibrary() {
 		var layerCount int
-		estimate := EstimateGPULayers(gpus, f, projectors, opts)
+		estimate := EstimateGPULayers(gpus, f, projectors, opts, numParallel)
 		layerCount, estimatedVRAM = estimate.Layers, estimate.VRAMSize
 		if opts.NumGPU < 0 {
 			if layerCount > 0 && layerCount >= int(f.KV().BlockCount()+1) {
@@ -71,7 +71,7 @@ type MemoryEstimate struct {
 
 // Given a model and one or more GPU targets, predict how many layers and bytes we can load, and the total size
 // The GPUs provided must all be the same Library
-func EstimateGPULayers(gpus []discover.GpuInfo, f *ggml.GGML, projectors []string, opts api.Options) MemoryEstimate {
+func EstimateGPULayers(gpus []discover.GpuInfo, f *ggml.GGML, projectors []string, opts api.Options, numParallel int) MemoryEstimate {
 	// Graph size for a partial offload, applies to all GPUs
 	var graphPartialOffload uint64
 
@@ -137,13 +137,19 @@ func EstimateGPULayers(gpus []discover.GpuInfo, f *ggml.GGML, projectors []strin
 		}
 	}
 
-	kv, graphPartialOffload, graphFullOffload := f.GraphSize(uint64(opts.NumCtx), uint64(min(opts.NumCtx, opts.NumBatch)), kvct)
+	kv, graphPartialOffload, graphFullOffload := f.GraphSize(uint64(opts.NumCtx), uint64(min(opts.NumCtx, opts.NumBatch)), numParallel, kvct)
 
-	// KV is proportional to the number of layers
-	layerSize += kv / f.KV().BlockCount()
+	if len(kv) > 0 {
+		layerSize += kv[0]
+	}
+
+	var kvTotal uint64
+	for _, kvLayer := range kv {
+		kvTotal += kvLayer
+	}
 
 	if graphPartialOffload == 0 {
-		graphPartialOffload = f.KV().GQA() * kv / 6
+		graphPartialOffload = f.KV().GQA() * kvTotal / 6
 	}
 	if graphFullOffload == 0 {
 		graphFullOffload = graphPartialOffload
@@ -217,7 +223,7 @@ func EstimateGPULayers(gpus []discover.GpuInfo, f *ggml.GGML, projectors []strin
 		// Some models have inconsistent layer sizes
 		if blk, ok := layers[fmt.Sprintf("blk.%d", i)]; ok {
 			layerSize = blk.Size()
-			layerSize += kv / f.KV().BlockCount()
+			layerSize += kv[i]
 			memoryWeights += blk.Size()
 		}
 
@@ -315,7 +321,7 @@ func EstimateGPULayers(gpus []discover.GpuInfo, f *ggml.GGML, projectors []strin
 		layersRequested:     opts.NumGPU,
 		layersModel:         int(f.KV().BlockCount()) + 1,
 		availableList:       availableList,
-		kv:                  kv,
+		kv:                  kvTotal,
 		allocationsList:     allocationsList,
 		memoryWeights:       memoryWeights,
 		memoryLayerOutput:   memoryLayerOutput,
diff --git a/llm/memory_test.go b/llm/memory_test.go
index 40cc01df..213784a0 100644
--- a/llm/memory_test.go
+++ b/llm/memory_test.go
@@ -61,7 +61,7 @@ func TestEstimateGPULayers(t *testing.T) {
 	projectors := []string{}
 	opts := api.DefaultOptions()
 	t.Run("cpu", func(t *testing.T) {
-		estimate := EstimateGPULayers(gpus, ggml, projectors, opts)
+		estimate := EstimateGPULayers(gpus, ggml, projectors, opts, 1)
 		assert.Equal(t, 0, estimate.Layers)
 		assert.Equal(t, uint64(0), estimate.Graph)
 	})
@@ -112,7 +112,7 @@ func TestEstimateGPULayers(t *testing.T) {
 			gpus[1].FreeMemory += gpuMinimumMemory + layerSize + s.layer1*layerSize + 1
 			gpus[0].FreeMemory += max(graphFullOffload, graphPartialOffload)
 			gpus[1].FreeMemory += max(graphFullOffload, graphPartialOffload)
-			estimate := EstimateGPULayers(gpus, ggml, projectors, opts)
+			estimate := EstimateGPULayers(gpus, ggml, projectors, opts, 1)
 			assert.Equal(t, int(s.expect0+s.expect1), estimate.Layers, "scenario %d: %v", i, s)
 			assert.Equal(t, fmt.Sprintf("%d,%d", s.expect0, s.expect1), estimate.TensorSplit, "scenario %d: %v", i, s)
 			var layerSums uint64
diff --git a/llm/server.go b/llm/server.go
index adc11aae..e6046db6 100644
--- a/llm/server.go
+++ b/llm/server.go
@@ -109,7 +109,7 @@ func NewLlamaServer(gpus discover.GpuInfoList, modelPath string, f *ggml.GGML, a
 		gpus = discover.GetCPUInfo()
 	}
 
-	estimate := EstimateGPULayers(gpus, f, projectors, opts)
+	estimate := EstimateGPULayers(gpus, f, projectors, opts, numParallel)
 	if len(gpus) > 1 || gpus[0].Library != "cpu" {
 		switch {
 		case gpus[0].Library == "metal" && estimate.VRAMSize > systemTotalMemory:
diff --git a/server/sched.go b/server/sched.go
index b4600dbf..9126c296 100644
--- a/server/sched.go
+++ b/server/sched.go
@@ -711,7 +711,7 @@ func pickBestFullFitByLibrary(req *LlmRequest, f *ggml.GGML, gpus discover.GpuIn
 			req.opts.NumCtx = req.origNumCtx * p
 			if !envconfig.SchedSpread() {
 				for _, g := range sgl {
-					if ok, estimatedVRAM = llm.PredictServerFit([]discover.GpuInfo{g}, f, req.model.AdapterPaths, req.model.ProjectorPaths, req.opts); ok {
+					if ok, estimatedVRAM = llm.PredictServerFit([]discover.GpuInfo{g}, f, req.model.AdapterPaths, req.model.ProjectorPaths, req.opts, p); ok {
 						slog.Info("new model will fit in available VRAM in single GPU, loading", "model", req.model.ModelPath, "gpu", g.ID, "parallel", p, "available", g.FreeMemory, "required", format.HumanBytes2(estimatedVRAM))
 						*numParallel = p
 						return []discover.GpuInfo{g}
@@ -727,7 +727,7 @@ func pickBestFullFitByLibrary(req *LlmRequest, f *ggml.GGML, gpus discover.GpuIn
 		// Now try all the GPUs
 		for _, p := range numParallelToTry {
 			req.opts.NumCtx = req.origNumCtx * p
-			if ok, estimatedVRAM = llm.PredictServerFit(sgl, f, req.model.AdapterPaths, req.model.ProjectorPaths, req.opts); ok {
+			if ok, estimatedVRAM = llm.PredictServerFit(sgl, f, req.model.AdapterPaths, req.model.ProjectorPaths, req.opts, p); ok {
 				slog.Info("new model will fit in available VRAM, loading", "model", req.model.ModelPath, "library", sgl[0].Library, "parallel", p, "required", format.HumanBytes2(estimatedVRAM))
 				*numParallel = p
 				return sgl
@@ -750,7 +750,7 @@ func pickBestPartialFitByLibrary(req *LlmRequest, f *ggml.GGML, gpus discover.Gp
 	var bestEstimate uint64
 	var bestFit int
 	for i, gl := range byLibrary {
-		_, estimatedVRAM := llm.PredictServerFit(gl, f, req.model.AdapterPaths, req.model.ProjectorPaths, req.opts)
+		_, estimatedVRAM := llm.PredictServerFit(gl, f, req.model.AdapterPaths, req.model.ProjectorPaths, req.opts, *numParallel)
 		if estimatedVRAM > bestEstimate {
 			bestEstimate = estimatedVRAM
 			bestFit = i
@@ -825,7 +825,7 @@ func (s *Scheduler) expireRunner(model *Model) {
 // If not, pick a runner to unload, else return nil and the request can be loaded
 func (s *Scheduler) maybeFindCPURunnerToUnload(req *LlmRequest, f *ggml.GGML, gpus discover.GpuInfoList) *runnerRef {
 	slog.Debug("evaluating if CPU model load will fit in available system memory")
-	estimate := llm.EstimateGPULayers(gpus, f, req.model.ProjectorPaths, req.opts)
+	estimate := llm.EstimateGPULayers(gpus, f, req.model.ProjectorPaths, req.opts, req.opts.NumCtx/req.origNumCtx)
 	if estimate.TotalSize <= gpus[0].FreeMemory {
 		slog.Debug("cpu inference mode, model fits in available system memory", "model", format.HumanBytes2(estimate.TotalSize), "available", format.HumanBytes2(gpus[0].FreeMemory))
 		return nil

From dd66712e3159161c1de9c39a12fb83edf8813d39 Mon Sep 17 00:00:00 2001
From: Hengky Steen <hengkysteen@gmail.com>
Date: Thu, 27 Mar 2025 03:38:05 +0700
Subject: [PATCH 134/157] docs: add ollamb to community projects

---
 README.md | 1 +
 1 file changed, 1 insertion(+)

diff --git a/README.md b/README.md
index 50e8dba0..d0aecaef 100644
--- a/README.md
+++ b/README.md
@@ -394,6 +394,7 @@ See the [API documentation](./docs/api.md) for all endpoints.
 - [Reins](https://github.com/ibrahimcetin/reins) (Easily tweak parameters, customize system prompts per chat, and enhance your AI experiments with reasoning model support.)
 - [Ellama](https://github.com/zeozeozeo/ellama) (Friendly native app to chat with an Ollama instance)
 - [screenpipe](https://github.com/mediar-ai/screenpipe) Build agents powered by your screen history
+- [Ollamb](https://github.com/hengkysteen/ollamb) (Simple yet rich in features, cross-platform built with Flutter and designed for Ollama. Try the [web demo](https://hengkysteen.github.io/demo/ollamb/).)
 
 ### Cloud
 

From e5d84fb90b21d71f8eb816656ca0b34191425216 Mon Sep 17 00:00:00 2001
From: molbal <molbal@outlook.com>
Date: Wed, 26 Mar 2025 21:39:01 +0100
Subject: [PATCH 135/157] docs: add molbal/orca-cli to community integrations
 (#9909)

---
 README.md | 1 +
 1 file changed, 1 insertion(+)

diff --git a/README.md b/README.md
index d0aecaef..3afd83c3 100644
--- a/README.md
+++ b/README.md
@@ -435,6 +435,7 @@ See the [API documentation](./docs/api.md) for all endpoints.
 - [aichat](https://github.com/sigoden/aichat) All-in-one LLM CLI tool featuring Shell Assistant, Chat-REPL, RAG, AI tools & agents, with access to OpenAI, Claude, Gemini, Ollama, Groq, and more.
 - [PowershAI](https://github.com/rrg92/powershai) PowerShell module that brings AI to terminal on Windows, including support for Ollama
 - [orbiton](https://github.com/xyproto/orbiton) Configuration-free text editor and IDE with support for tab completion with Ollama.
+- [orca-cli](https://github.com/molbal/orca-cli) Ollama Registry CLI Application - Browse, pull and download models from Ollama Registry in your terminal.
 
 ### Apple Vision Pro
 

From b816ff86c923e0290f58f2275e831fc17c29ba37 Mon Sep 17 00:00:00 2001
From: Parth Sareen <parth.sareen@ollama.com>
Date: Wed, 26 Mar 2025 17:34:18 -0700
Subject: [PATCH 136/157] docs: make context length faq readable (#10006)

---
 docs/faq.md | 8 +++++++-
 1 file changed, 7 insertions(+), 1 deletion(-)

diff --git a/docs/faq.md b/docs/faq.md
index 66959cca..f418da47 100644
--- a/docs/faq.md
+++ b/docs/faq.md
@@ -20,7 +20,13 @@ Please refer to the [GPU docs](./gpu.md).
 
 ## How can I specify the context window size?
 
-By default, Ollama uses a context window size of 2048 tokens. This can be overridden with the `OLLAMA_CONTEXT_LENGTH` environment variable. For example, to set the default context length to 8K, use: `OLLAMA_CONTEXT_LENGTH=8192 ollama serve`.
+By default, Ollama uses a context window size of 2048 tokens. 
+
+This can be overridden with the `OLLAMA_CONTEXT_LENGTH` environment variable. For example, to set the default context window to 8K, use: 
+
+```shell
+OLLAMA_CONTEXT_LENGTH=8192 ollama serve
+```
 
 To change this when using `ollama run`, use `/set parameter`:
 

From ead27aa9fe85b4a1e1c434080d5e005e3cd68a16 Mon Sep 17 00:00:00 2001
From: saman-amd <saman.khatir@amd.com>
Date: Thu, 27 Mar 2025 07:35:19 -0700
Subject: [PATCH 137/157] Add gfx1200 & gfx1201 support on linux (#9878)

---
 CMakeLists.txt                                |   6 +-
 CMakePresets.json                             |   2 +-
 llama/patches/0022-add-rdna4-support.patch    | 103 ++++++++++++++++++
 ml/backend/ggml/ggml/src/ggml-cuda/common.cuh |   6 +-
 ml/backend/ggml/ggml/src/ggml-cuda/mmq.cu     |   2 +-
 ml/backend/ggml/ggml/src/ggml-cuda/mmq.cuh    |   4 +-
 ml/backend/ggml/ggml/src/ggml-cuda/mmvq.cu    |   4 +-
 .../ggml/ggml/src/ggml-cuda/vendors/hip.h     |   4 +
 8 files changed, 120 insertions(+), 11 deletions(-)
 create mode 100644 llama/patches/0022-add-rdna4-support.patch

diff --git a/CMakeLists.txt b/CMakeLists.txt
index 034fc7d7..e2447f32 100644
--- a/CMakeLists.txt
+++ b/CMakeLists.txt
@@ -86,9 +86,9 @@ if(CMAKE_CUDA_COMPILER)
     )
 endif()
 
-set(WINDOWS_AMDGPU_TARGETS_EXCLUDE_REGEX "^gfx(906|908|90a):xnack[+-]$"
+set(WINDOWS_AMDGPU_TARGETS_EXCLUDE_REGEX "^gfx(906|908|90a|1200|1201):xnack[+-]$"
     CACHE STRING
-    "Regular expression describing AMDGPU_TARGETS not supported on Windows. Override to force building these targets. Default \"^gfx(906|908|90a):xnack[+-]$\"."
+    "Regular expression describing AMDGPU_TARGETS not supported on Windows. Override to force building these targets. Default \"^gfx(906|908|90a|1200|1201):xnack[+-]$\"."
 )
 
 check_language(HIP)
@@ -97,7 +97,7 @@ if(CMAKE_HIP_COMPILER)
 
     find_package(hip REQUIRED)
     if(NOT AMDGPU_TARGETS)
-        list(FILTER AMDGPU_TARGETS INCLUDE REGEX "^gfx(900|94[012]|101[02]|1030|110[012])$")
+        list(FILTER AMDGPU_TARGETS INCLUDE REGEX "^gfx(900|94[012]|101[02]|1030|110[012]|120[01])$")
     elseif(WIN32 AND WINDOWS_AMDGPU_TARGETS_EXCLUDE_REGEX)
         list(FILTER AMDGPU_TARGETS EXCLUDE REGEX ${WINDOWS_AMDGPU_TARGETS_EXCLUDE_REGEX})
     endif()
diff --git a/CMakePresets.json b/CMakePresets.json
index f3507e3f..bf99917f 100644
--- a/CMakePresets.json
+++ b/CMakePresets.json
@@ -56,7 +56,7 @@
       "name": "ROCm 6",
       "inherits": [ "ROCm" ],
       "cacheVariables": {
-        "AMDGPU_TARGETS": "gfx900;gfx940;gfx941;gfx942;gfx1010;gfx1012;gfx1030;gfx1100;gfx1101;gfx1102;gfx1151;gfx906:xnack-;gfx908:xnack-;gfx90a:xnack+;gfx90a:xnack-"
+        "AMDGPU_TARGETS": "gfx900;gfx940;gfx941;gfx942;gfx1010;gfx1012;gfx1030;gfx1100;gfx1101;gfx1102;gfx1151;gfx1200;gfx1201;gfx906:xnack-;gfx908:xnack-;gfx90a:xnack+;gfx90a:xnack-"
       }
     }
   ],
diff --git a/llama/patches/0022-add-rdna4-support.patch b/llama/patches/0022-add-rdna4-support.patch
new file mode 100644
index 00000000..9b77ae84
--- /dev/null
+++ b/llama/patches/0022-add-rdna4-support.patch
@@ -0,0 +1,103 @@
+From 0000000000000000000000000000000000000000 Mon Sep 17 00:00:00 2001
+From: Saman <saman.khatir@amd.com>
+Date: Wed, 19 Mar 2025 14:02:26 -0700
+Subject: [PATCH] add rdna4 support
+
+---
+ ggml/src/ggml-cuda/common.cuh    | 6 ++++--
+ ggml/src/ggml-cuda/mmq.cu        | 2 +-
+ ggml/src/ggml-cuda/mmq.cuh       | 4 ++--
+ ggml/src/ggml-cuda/mmvq.cu       | 4 ++--
+ ggml/src/ggml-cuda/vendors/hip.h | 4 ++++
+ 5 files changed, 13 insertions(+), 7 deletions(-)
+
+diff --git a/ggml/src/ggml-cuda/common.cuh b/ggml/src/ggml-cuda/common.cuh
+index adf0d3ec..b24593fc 100644
+--- a/ggml/src/ggml-cuda/common.cuh
++++ b/ggml/src/ggml-cuda/common.cuh
+@@ -61,11 +61,13 @@
+ #define GGML_CUDA_CC_RDNA1      (GGML_CUDA_CC_OFFSET_AMD + 0x1010) // RX 5000
+ #define GGML_CUDA_CC_RDNA2      (GGML_CUDA_CC_OFFSET_AMD + 0x1030) // RX 6000, minimum for dp4a
+ #define GGML_CUDA_CC_RDNA3      (GGML_CUDA_CC_OFFSET_AMD + 0x1100) // RX 7000, minimum for WMMA
++#define GGML_CUDA_CC_RDNA4      (GGML_CUDA_CC_OFFSET_AMD + 0x1200) // RX 9000
+ 
+ #define GGML_CUDA_CC_IS_RDNA(cc)  (cc >= GGML_CUDA_CC_RDNA1)
+ #define GGML_CUDA_CC_IS_RDNA1(cc) (cc >= GGML_CUDA_CC_RDNA1 && cc < GGML_CUDA_CC_RDNA2)
+ #define GGML_CUDA_CC_IS_RDNA2(cc) (cc >= GGML_CUDA_CC_RDNA2 && cc < GGML_CUDA_CC_RDNA3)
+-#define GGML_CUDA_CC_IS_RDNA3(cc) (cc >= GGML_CUDA_CC_RDNA3)
++#define GGML_CUDA_CC_IS_RDNA3(cc) (cc >= GGML_CUDA_CC_RDNA3 && cc < GGML_CUDA_CC_RDNA4)
++#define GGML_CUDA_CC_IS_RDNA4(cc) (cc >= GGML_CUDA_CC_RDNA4)
+ #define GGML_CUDA_CC_IS_GCN(cc)   (cc > GGML_CUDA_CC_OFFSET_AMD && cc < GGML_CUDA_CC_CDNA)
+ #define GGML_CUDA_CC_IS_CDNA(cc)  (cc >= GGML_CUDA_CC_CDNA && cc < GGML_CUDA_CC_RDNA1)
+ 
+@@ -386,7 +388,7 @@ static __device__ __forceinline__ int ggml_cuda_dp4a(const int a, const int b, i
+ #if defined(GGML_USE_HIP) && defined(__HIP_PLATFORM_AMD__)
+ #if defined(__gfx906__) || defined(__gfx908__) || defined(__gfx90a__) || defined(RDNA2)
+     c = __builtin_amdgcn_sdot4(a, b, c, false);
+-#elif defined(RDNA3)
++#elif defined(RDNA3) || defined(RDNA4)
+     c = __builtin_amdgcn_sudot4( true, a, true, b, c, false);
+ #elif defined(__gfx1010__) || defined(__gfx900__)
+     int tmp1;
+diff --git a/ggml/src/ggml-cuda/mmq.cu b/ggml/src/ggml-cuda/mmq.cu
+index 10f2ebb1..933d945c 100644
+--- a/ggml/src/ggml-cuda/mmq.cu
++++ b/ggml/src/ggml-cuda/mmq.cu
+@@ -149,5 +149,5 @@ bool ggml_cuda_should_use_mmq(enum ggml_type type, int cc, int64_t ne11) {
+         return !fp16_mma_hardware_available(cc) || ne11 < MMQ_DP4A_MAX_BATCH_SIZE;
+     }
+ 
+-    return (!GGML_CUDA_CC_IS_RDNA3(cc) && !GGML_CUDA_CC_IS_CDNA(cc)) || ne11 < MMQ_DP4A_MAX_BATCH_SIZE;
++    return (!GGML_CUDA_CC_IS_RDNA4(cc) && !GGML_CUDA_CC_IS_RDNA3(cc) && !GGML_CUDA_CC_IS_CDNA(cc)) || ne11 < MMQ_DP4A_MAX_BATCH_SIZE;
+ }
+diff --git a/ggml/src/ggml-cuda/mmq.cuh b/ggml/src/ggml-cuda/mmq.cuh
+index 0451c65f..66ce2bc9 100644
+--- a/ggml/src/ggml-cuda/mmq.cuh
++++ b/ggml/src/ggml-cuda/mmq.cuh
+@@ -2577,9 +2577,9 @@ static __device__ void mul_mat_q_process_tile(
+ 
+ template <ggml_type type, int mmq_x, int nwarps, bool need_check>
+ #if defined(GGML_USE_HIP) && defined(__HIP_PLATFORM_AMD__)
+-#if defined(RDNA3) || defined(RDNA2) || defined(CDNA) || defined(GCN)
++#if defined(RDNA4) || defined(RDNA3) || defined(RDNA2) || defined(CDNA) || defined(GCN)
+     __launch_bounds__(WARP_SIZE*nwarps, 2)
+-#endif // defined(RDNA3) || defined(RDNA2) || defined(CDNA) || defined(GCN)
++#endif // defined(RDNA4) || defined(RDNA3) || defined(RDNA2) || defined(CDNA) || defined(GCN)
+ #else
+ #if __CUDA_ARCH__ >= GGML_CUDA_CC_VOLTA
+     __launch_bounds__(WARP_SIZE*nwarps, 1)
+diff --git a/ggml/src/ggml-cuda/mmvq.cu b/ggml/src/ggml-cuda/mmvq.cu
+index 4fb466ca..23ae7abc 100644
+--- a/ggml/src/ggml-cuda/mmvq.cu
++++ b/ggml/src/ggml-cuda/mmvq.cu
+@@ -62,13 +62,13 @@ static __global__ void mul_mat_vec_q(
+ 
+     constexpr vec_dot_q_cuda_t vec_dot_q_cuda = get_vec_dot_q_cuda(type);
+ 
+-#if defined(GGML_USE_HIP) && defined(__HIP_PLATFORM_AMD__) && (defined(RDNA2) || defined(RDNA3))
++#if defined(GGML_USE_HIP) && defined(__HIP_PLATFORM_AMD__) && (defined(RDNA2) || defined(RDNA3) || defined(RDNA4))
+     constexpr int nwarps              = 1;
+     constexpr int rows_per_cuda_block = 1;
+ #else
+     constexpr int nwarps              = ncols_y <= 4 ? 4 : 2;
+     constexpr int rows_per_cuda_block = ncols_y == 1 ? 1 : 2;
+-#endif // defined(GGML_USE_HIP) && defined(__HIP_PLATFORM_AMD__) && !defined(RDNA2) && !defined(RDNA3)
++#endif // defined(GGML_USE_HIP) && defined(__HIP_PLATFORM_AMD__) && !defined(RDNA2) && !defined(RDNA3) && !defined(RDNA4)
+ 
+     const     int tid = WARP_SIZE*threadIdx.y + threadIdx.x;
+     const     int row0 = rows_per_cuda_block*blockIdx.x;
+diff --git a/ggml/src/ggml-cuda/vendors/hip.h b/ggml/src/ggml-cuda/vendors/hip.h
+index 81964611..a62544b5 100644
+--- a/ggml/src/ggml-cuda/vendors/hip.h
++++ b/ggml/src/ggml-cuda/vendors/hip.h
+@@ -150,6 +150,10 @@
+ #define CDNA
+ #endif
+ 
++#if defined(__gfx1200__) || defined(__gfx1201__)
++#define RDNA4
++#endif
++
+ #if defined(__gfx1100__) || defined(__gfx1101__) || defined(__gfx1102__) || defined(__gfx1103__) || \
+     defined(__gfx1150__) || defined(__gfx1151__)
+ #define RDNA3
diff --git a/ml/backend/ggml/ggml/src/ggml-cuda/common.cuh b/ml/backend/ggml/ggml/src/ggml-cuda/common.cuh
index adf0d3ec..b24593fc 100644
--- a/ml/backend/ggml/ggml/src/ggml-cuda/common.cuh
+++ b/ml/backend/ggml/ggml/src/ggml-cuda/common.cuh
@@ -61,11 +61,13 @@
 #define GGML_CUDA_CC_RDNA1      (GGML_CUDA_CC_OFFSET_AMD + 0x1010) // RX 5000
 #define GGML_CUDA_CC_RDNA2      (GGML_CUDA_CC_OFFSET_AMD + 0x1030) // RX 6000, minimum for dp4a
 #define GGML_CUDA_CC_RDNA3      (GGML_CUDA_CC_OFFSET_AMD + 0x1100) // RX 7000, minimum for WMMA
+#define GGML_CUDA_CC_RDNA4      (GGML_CUDA_CC_OFFSET_AMD + 0x1200) // RX 9000
 
 #define GGML_CUDA_CC_IS_RDNA(cc)  (cc >= GGML_CUDA_CC_RDNA1)
 #define GGML_CUDA_CC_IS_RDNA1(cc) (cc >= GGML_CUDA_CC_RDNA1 && cc < GGML_CUDA_CC_RDNA2)
 #define GGML_CUDA_CC_IS_RDNA2(cc) (cc >= GGML_CUDA_CC_RDNA2 && cc < GGML_CUDA_CC_RDNA3)
-#define GGML_CUDA_CC_IS_RDNA3(cc) (cc >= GGML_CUDA_CC_RDNA3)
+#define GGML_CUDA_CC_IS_RDNA3(cc) (cc >= GGML_CUDA_CC_RDNA3 && cc < GGML_CUDA_CC_RDNA4)
+#define GGML_CUDA_CC_IS_RDNA4(cc) (cc >= GGML_CUDA_CC_RDNA4)
 #define GGML_CUDA_CC_IS_GCN(cc)   (cc > GGML_CUDA_CC_OFFSET_AMD && cc < GGML_CUDA_CC_CDNA)
 #define GGML_CUDA_CC_IS_CDNA(cc)  (cc >= GGML_CUDA_CC_CDNA && cc < GGML_CUDA_CC_RDNA1)
 
@@ -386,7 +388,7 @@ static __device__ __forceinline__ int ggml_cuda_dp4a(const int a, const int b, i
 #if defined(GGML_USE_HIP) && defined(__HIP_PLATFORM_AMD__)
 #if defined(__gfx906__) || defined(__gfx908__) || defined(__gfx90a__) || defined(RDNA2)
     c = __builtin_amdgcn_sdot4(a, b, c, false);
-#elif defined(RDNA3)
+#elif defined(RDNA3) || defined(RDNA4)
     c = __builtin_amdgcn_sudot4( true, a, true, b, c, false);
 #elif defined(__gfx1010__) || defined(__gfx900__)
     int tmp1;
diff --git a/ml/backend/ggml/ggml/src/ggml-cuda/mmq.cu b/ml/backend/ggml/ggml/src/ggml-cuda/mmq.cu
index 10f2ebb1..933d945c 100644
--- a/ml/backend/ggml/ggml/src/ggml-cuda/mmq.cu
+++ b/ml/backend/ggml/ggml/src/ggml-cuda/mmq.cu
@@ -149,5 +149,5 @@ bool ggml_cuda_should_use_mmq(enum ggml_type type, int cc, int64_t ne11) {
         return !fp16_mma_hardware_available(cc) || ne11 < MMQ_DP4A_MAX_BATCH_SIZE;
     }
 
-    return (!GGML_CUDA_CC_IS_RDNA3(cc) && !GGML_CUDA_CC_IS_CDNA(cc)) || ne11 < MMQ_DP4A_MAX_BATCH_SIZE;
+    return (!GGML_CUDA_CC_IS_RDNA4(cc) && !GGML_CUDA_CC_IS_RDNA3(cc) && !GGML_CUDA_CC_IS_CDNA(cc)) || ne11 < MMQ_DP4A_MAX_BATCH_SIZE;
 }
diff --git a/ml/backend/ggml/ggml/src/ggml-cuda/mmq.cuh b/ml/backend/ggml/ggml/src/ggml-cuda/mmq.cuh
index 0451c65f..66ce2bc9 100644
--- a/ml/backend/ggml/ggml/src/ggml-cuda/mmq.cuh
+++ b/ml/backend/ggml/ggml/src/ggml-cuda/mmq.cuh
@@ -2577,9 +2577,9 @@ static __device__ void mul_mat_q_process_tile(
 
 template <ggml_type type, int mmq_x, int nwarps, bool need_check>
 #if defined(GGML_USE_HIP) && defined(__HIP_PLATFORM_AMD__)
-#if defined(RDNA3) || defined(RDNA2) || defined(CDNA) || defined(GCN)
+#if defined(RDNA4) || defined(RDNA3) || defined(RDNA2) || defined(CDNA) || defined(GCN)
     __launch_bounds__(WARP_SIZE*nwarps, 2)
-#endif // defined(RDNA3) || defined(RDNA2) || defined(CDNA) || defined(GCN)
+#endif // defined(RDNA4) || defined(RDNA3) || defined(RDNA2) || defined(CDNA) || defined(GCN)
 #else
 #if __CUDA_ARCH__ >= GGML_CUDA_CC_VOLTA
     __launch_bounds__(WARP_SIZE*nwarps, 1)
diff --git a/ml/backend/ggml/ggml/src/ggml-cuda/mmvq.cu b/ml/backend/ggml/ggml/src/ggml-cuda/mmvq.cu
index 4fb466ca..23ae7abc 100644
--- a/ml/backend/ggml/ggml/src/ggml-cuda/mmvq.cu
+++ b/ml/backend/ggml/ggml/src/ggml-cuda/mmvq.cu
@@ -62,13 +62,13 @@ static __global__ void mul_mat_vec_q(
 
     constexpr vec_dot_q_cuda_t vec_dot_q_cuda = get_vec_dot_q_cuda(type);
 
-#if defined(GGML_USE_HIP) && defined(__HIP_PLATFORM_AMD__) && (defined(RDNA2) || defined(RDNA3))
+#if defined(GGML_USE_HIP) && defined(__HIP_PLATFORM_AMD__) && (defined(RDNA2) || defined(RDNA3) || defined(RDNA4))
     constexpr int nwarps              = 1;
     constexpr int rows_per_cuda_block = 1;
 #else
     constexpr int nwarps              = ncols_y <= 4 ? 4 : 2;
     constexpr int rows_per_cuda_block = ncols_y == 1 ? 1 : 2;
-#endif // defined(GGML_USE_HIP) && defined(__HIP_PLATFORM_AMD__) && !defined(RDNA2) && !defined(RDNA3)
+#endif // defined(GGML_USE_HIP) && defined(__HIP_PLATFORM_AMD__) && !defined(RDNA2) && !defined(RDNA3) && !defined(RDNA4)
 
     const     int tid = WARP_SIZE*threadIdx.y + threadIdx.x;
     const     int row0 = rows_per_cuda_block*blockIdx.x;
diff --git a/ml/backend/ggml/ggml/src/ggml-cuda/vendors/hip.h b/ml/backend/ggml/ggml/src/ggml-cuda/vendors/hip.h
index 81964611..a62544b5 100644
--- a/ml/backend/ggml/ggml/src/ggml-cuda/vendors/hip.h
+++ b/ml/backend/ggml/ggml/src/ggml-cuda/vendors/hip.h
@@ -150,6 +150,10 @@
 #define CDNA
 #endif
 
+#if defined(__gfx1200__) || defined(__gfx1201__)
+#define RDNA4
+#endif
+
 #if defined(__gfx1100__) || defined(__gfx1101__) || defined(__gfx1102__) || defined(__gfx1103__) || \
     defined(__gfx1150__) || defined(__gfx1151__)
 #define RDNA3

From 01aa7887221e7bd286ebcb14a088c94ba1c22a99 Mon Sep 17 00:00:00 2001
From: Jesse Gross <jesse@ollama.com>
Date: Thu, 27 Mar 2025 11:52:09 -0700
Subject: [PATCH 138/157] ml: Remove Output from Context interface

Model implementations should use Input for all of their tensors
supplied to the model. This includes tensors that relate to the
outputs, which is confusing since there is also an Output funciton.

Since Output is only used internally in GGML and not used by any
model implementations, we can remove it from the interface to
reduce confusion.
---
 kvcache/causal_test.go  |  1 -
 ml/backend.go           |  6 ++----
 ml/backend/ggml/ggml.go | 19 +------------------
 3 files changed, 3 insertions(+), 23 deletions(-)

diff --git a/kvcache/causal_test.go b/kvcache/causal_test.go
index 617f5363..b1dc7d77 100644
--- a/kvcache/causal_test.go
+++ b/kvcache/causal_test.go
@@ -362,7 +362,6 @@ func (c *testContext) FromIntSlice(s []int32, shape ...int) (ml.Tensor, error) {
 }
 
 func (c *testContext) Input() ml.Context    { return c }
-func (c *testContext) Output() ml.Context   { return c }
 func (c *testContext) Layer(int) ml.Context { return c }
 
 func (c *testContext) Forward(...ml.Tensor) ml.Context { return c }
diff --git a/ml/backend.go b/ml/backend.go
index 354faf43..cfb18d6a 100644
--- a/ml/backend.go
+++ b/ml/backend.go
@@ -110,12 +110,10 @@ type Context interface {
 	MaxGraphNodes() int
 	Close()
 
-	// Input returns a context appropriate for creating input tensors
+	// Input returns a context appropriate for creating tensors that are
+	// inputs to the model (which includes things like output locations)
 	Input() Context
 
-	// Output returns a context appropriate for creating output tensors
-	Output() Context
-
 	// Layer returns a context appropriate for creating intermediate tensors
 	Layer(int) Context
 }
diff --git a/ml/backend/ggml/ggml.go b/ml/backend/ggml/ggml.go
index f6b01774..b6f59ae0 100644
--- a/ml/backend/ggml/ggml.go
+++ b/ml/backend/ggml/ggml.go
@@ -48,9 +48,6 @@ type Backend struct {
 	// input is the backend used for inputs
 	input *C.struct_ggml_backend_buffer_type
 
-	// output is the backend used for outputs
-	output *C.struct_ggml_backend_buffer_type
-
 	// layers is the backend used for repeating layers
 	layers map[int]*C.struct_ggml_backend_buffer_type
 
@@ -400,8 +397,7 @@ func New(ctx context.Context, r *os.File, params ml.BackendParams) (ml.Backend,
 			C.size_t(maxGraphNodes),
 			C._Bool(len(gpus) > 1 && slices.Contains(gpus, output.d)),
 		),
-		input:  deviceBufferTypes[input.d],
-		output: deviceBufferTypes[output.d],
+		input: deviceBufferTypes[input.d],
 		layers: func() map[int]*C.struct_ggml_backend_buffer_type {
 			m := make(map[int]*C.struct_ggml_backend_buffer_type)
 			for i, layer := range layers {
@@ -482,19 +478,6 @@ func (c Context) Input() ml.Context {
 	return &c
 }
 
-func (c Context) Output() ml.Context {
-	if c.b.output != nil {
-		return &Context{
-			b:             c.b,
-			ctx:           c.ctx,
-			buft:          c.b.output,
-			maxGraphNodes: c.maxGraphNodes,
-		}
-	}
-
-	return &c
-}
-
 func (c Context) Layer(i int) ml.Context {
 	if buft, ok := c.b.layers[i]; ok {
 		return &Context{

From 0bd0454ea7f51b1ddf527b4ebdaf1e614df211bc Mon Sep 17 00:00:00 2001
From: CYJiang <86391540+googs1025@users.noreply.github.com>
Date: Sat, 29 Mar 2025 02:50:22 +0800
Subject: [PATCH 139/157] server: organize error types (#9465)

Co-authored-by: Bruce MacDonald <brucewmacdonald@gmail.com>
---
 server/download.go  | 7 ++++---
 server/images.go    | 5 +++--
 server/modelpath.go | 5 ++---
 server/routes.go    | 2 +-
 4 files changed, 10 insertions(+), 9 deletions(-)

diff --git a/server/download.go b/server/download.go
index 8f49351e..6f79fd2d 100644
--- a/server/download.go
+++ b/server/download.go
@@ -29,8 +29,9 @@ import (
 const maxRetries = 6
 
 var (
-	errMaxRetriesExceeded = errors.New("max retries exceeded")
-	errPartStalled        = errors.New("part stalled")
+	errMaxRetriesExceeded   = errors.New("max retries exceeded")
+	errPartStalled          = errors.New("part stalled")
+	errMaxRedirectsExceeded = errors.New("maximum redirects exceeded (10) for directURL")
 )
 
 var blobDownloadManager sync.Map
@@ -236,7 +237,7 @@ func (b *blobDownload) run(ctx context.Context, requestURL *url.URL, opts *regis
 
 			newOpts.CheckRedirect = func(req *http.Request, via []*http.Request) error {
 				if len(via) > 10 {
-					return errors.New("maximum redirects exceeded (10) for directURL")
+					return errMaxRedirectsExceeded
 				}
 
 				// if the hostname is the same, allow the redirect
diff --git a/server/images.go b/server/images.go
index 0c37613a..290e68ba 100644
--- a/server/images.go
+++ b/server/images.go
@@ -35,6 +35,7 @@ var (
 	errCapabilityCompletion = errors.New("completion")
 	errCapabilityTools      = errors.New("tools")
 	errCapabilityInsert     = errors.New("insert")
+	errInsecureProtocol     = errors.New("insecure protocol http")
 )
 
 type Capability string
@@ -479,7 +480,7 @@ func PushModel(ctx context.Context, name string, regOpts *registryOptions, fn fu
 	fn(api.ProgressResponse{Status: "retrieving manifest"})
 
 	if mp.ProtocolScheme == "http" && !regOpts.Insecure {
-		return errors.New("insecure protocol http")
+		return errInsecureProtocol
 	}
 
 	manifest, _, err := GetManifest(mp)
@@ -543,7 +544,7 @@ func PullModel(ctx context.Context, name string, regOpts *registryOptions, fn fu
 	}
 
 	if mp.ProtocolScheme == "http" && !regOpts.Insecure {
-		return errors.New("insecure protocol http")
+		return errInsecureProtocol
 	}
 
 	fn(api.ProgressResponse{Status: "pulling manifest"})
diff --git a/server/modelpath.go b/server/modelpath.go
index 5a96dec5..d1bcae93 100644
--- a/server/modelpath.go
+++ b/server/modelpath.go
@@ -31,9 +31,10 @@ const (
 
 var (
 	ErrInvalidImageFormat  = errors.New("invalid image format")
+	ErrInvalidDigestFormat = errors.New("invalid digest format")
 	ErrInvalidProtocol     = errors.New("invalid protocol scheme")
 	ErrInsecureProtocol    = errors.New("insecure protocol http")
-	ErrInvalidDigestFormat = errors.New("invalid digest format")
+	ErrModelPathInvalid    = errors.New("invalid model path")
 )
 
 func ParseModelPath(name string) ModelPath {
@@ -73,8 +74,6 @@ func ParseModelPath(name string) ModelPath {
 	return mp
 }
 
-var errModelPathInvalid = errors.New("invalid model path")
-
 func (mp ModelPath) GetNamespaceRepository() string {
 	return fmt.Sprintf("%s/%s", mp.Namespace, mp.Repository)
 }
diff --git a/server/routes.go b/server/routes.go
index 05993624..92336af0 100644
--- a/server/routes.go
+++ b/server/routes.go
@@ -777,7 +777,7 @@ func (s *Server) ShowHandler(c *gin.Context) {
 func GetModelInfo(req api.ShowRequest) (*api.ShowResponse, error) {
 	name := model.ParseName(req.Model)
 	if !name.IsValid() {
-		return nil, errModelPathInvalid
+		return nil, ErrModelPathInvalid
 	}
 	name, err := getExistingName(name)
 	if err != nil {

From 071a9872cb76f07d09dc8a3c65046d35d921f4e6 Mon Sep 17 00:00:00 2001
From: Leandro Borges Ferreira <lehen01@gmail.com>
Date: Mon, 31 Mar 2025 02:28:06 +0200
Subject: [PATCH 140/157] readme: add Writeopia to community integrations
 (#10042)

---
 README.md | 1 +
 1 file changed, 1 insertion(+)

diff --git a/README.md b/README.md
index 3afd83c3..c3d49105 100644
--- a/README.md
+++ b/README.md
@@ -395,6 +395,7 @@ See the [API documentation](./docs/api.md) for all endpoints.
 - [Ellama](https://github.com/zeozeozeo/ellama) (Friendly native app to chat with an Ollama instance)
 - [screenpipe](https://github.com/mediar-ai/screenpipe) Build agents powered by your screen history
 - [Ollamb](https://github.com/hengkysteen/ollamb) (Simple yet rich in features, cross-platform built with Flutter and designed for Ollama. Try the [web demo](https://hengkysteen.github.io/demo/ollamb/).)
+- [Writeopia](https://github.com/Writeopia/Writeopia) (Text editor with integration with Ollama)
 
 ### Cloud
 

From 5d097277ef8b08c86f354b54596976869998257d Mon Sep 17 00:00:00 2001
From: Jesse Gross <jesse@ollama.com>
Date: Thu, 27 Mar 2025 14:00:05 -0700
Subject: [PATCH 141/157] ollamarunner: Ensure batch size limits are not
 exceeded

With the llama runner, we can generate up to NUM_PARALLEL batches
at once, which will then get broken up to into individual batches
to get executed by llama.cpp (i.e. we add up to 2048 tokens and
this gets split into 4 batches of 512 tokens at default settings).

This splitting can improve parallelism on multi-GPU systems because
the individual batches can move though the pipeline without blocking
on the first one to fully complete. However, we don't yet support
this in the Ollama runner, partially because it makes it hard to
enforce model-specified batch constraints, which didn't exist
previously.

The result is that we will try to execute the full, unsplit batch.
This could result in out of memory or insufficient KV cache space
errors.

This triggers batch breaking when the total inputs from all sequences
exceeds the batch size, rather than per-sequence. In order to ensure
fairness, it also reintroduces round-robinning around sequences so
that we don't let one busy sequence starve the others.
---
 runner/ollamarunner/runner.go | 33 +++++++++++++++++++++++++++------
 1 file changed, 27 insertions(+), 6 deletions(-)

diff --git a/runner/ollamarunner/runner.go b/runner/ollamarunner/runner.go
index 31d20db8..6d20fa85 100644
--- a/runner/ollamarunner/runner.go
+++ b/runner/ollamarunner/runner.go
@@ -267,6 +267,9 @@ type Server struct {
 	// KV cache
 	cache *InputCache
 
+	// next sequence for prompt processing to avoid starvation
+	nextSeq int
+
 	// multimodalHash generates hashes for comparing equality
 	// of non-text data
 	multimodalHash maphash.Hash
@@ -351,14 +354,19 @@ func (s *Server) processBatch() error {
 	var batchInputs []int32
 	var batch input.Batch
 
-	for i, seq := range s.seqs {
+	resumeSeq := -1
+	seqIdx := s.nextSeq - 1
+	for range s.seqs {
+		seqIdx = (seqIdx + 1) % len(s.seqs)
+		seq := s.seqs[seqIdx]
+
 		if seq == nil {
 			continue
 		}
 
 		// if past the num predict limit
 		if seq.numPredict > 0 && seq.numPredicted >= seq.numPredict {
-			s.removeSequence(i, "limit")
+			s.removeSequence(seqIdx, "limit")
 			continue
 		}
 
@@ -369,16 +377,23 @@ func (s *Server) processBatch() error {
 
 		batchSize := s.batchSize
 
-		for j, inp := range seq.inputs {
+		for i, inp := range seq.inputs {
 			// If we are required to put following inputs into a single batch then extend the
 			// batch size. Since we are only extending the size the minimum amount possible, this
-			// will cause a break if we have pending inputs.
+			// will cause a break if we have existing inputs.
 			minBatch := 1 + inp.SameBatch
 			if minBatch > batchSize {
 				batchSize = minBatch
 			}
 
-			if len(seq.pendingInputs)+minBatch > batchSize {
+			// Stop if the required batch would put us over the total batch size (including tokens
+			// added by other sequences). If we haven't been able to add anything yet then pick up
+			// here again for the next batch to avoid starvation, though we can opportunistically
+			// check if other sequences can still squeeze something in.
+			if len(batchInputs)+minBatch > batchSize {
+				if len(seq.pendingInputs) == 0 && resumeSeq == -1 {
+					resumeSeq = seqIdx
+				}
 				break
 			}
 
@@ -405,7 +420,7 @@ func (s *Server) processBatch() error {
 			batch.Sequences = append(batch.Sequences, seq.cache.Id)
 
 			seq.iBatch = len(batch.Outputs)
-			if j+1 == len(seq.inputs) {
+			if i+1 == len(seq.inputs) {
 				batch.Outputs = append(batch.Outputs, int32(len(batchInputs)-1))
 			}
 			seq.pendingInputs = append(seq.pendingInputs, inp)
@@ -414,6 +429,12 @@ func (s *Server) processBatch() error {
 		seq.inputs = seq.inputs[len(seq.pendingInputs):]
 	}
 
+	if resumeSeq != -1 {
+		s.nextSeq = resumeSeq
+	} else {
+		s.nextSeq = seqIdx + 1
+	}
+
 	if len(batchInputs) == 0 {
 		return nil
 	}

From b2a465296d7131ca440fd81c1bee888f4103a585 Mon Sep 17 00:00:00 2001
From: Jesse Gross <jesse@ollama.com>
Date: Fri, 14 Mar 2025 17:24:46 -0700
Subject: [PATCH 142/157] runner: Release semaphore and improve error messages
 on failures

If we have an error after creating a new sequence but before
finding a slot for it, we return without releasing the semaphore.
This reduces our parallel sequences and eventually leads to deadlock.

In practice this should never happen because once we have acquired
the semaphore, we should always be able to find a slot. However, the
code is clearly not correct.
---
 runner/llamarunner/runner.go  | 8 ++++++--
 runner/ollamarunner/runner.go | 4 +++-
 2 files changed, 9 insertions(+), 3 deletions(-)

diff --git a/runner/llamarunner/runner.go b/runner/llamarunner/runner.go
index 83802d60..ee5d47f6 100644
--- a/runner/llamarunner/runner.go
+++ b/runner/llamarunner/runner.go
@@ -599,7 +599,7 @@ func (s *Server) completion(w http.ResponseWriter, r *http.Request) {
 		if errors.Is(err, context.Canceled) {
 			slog.Info("aborting completion request due to client closing the connection")
 		} else {
-			slog.Error("Failed to acquire semaphore", "error", err)
+			http.Error(w, fmt.Sprintf("Failed to acquire semaphore: %v", err), http.StatusInternalServerError)
 		}
 		return
 	}
@@ -611,6 +611,7 @@ func (s *Server) completion(w http.ResponseWriter, r *http.Request) {
 			seq.cache, seq.inputs, err = s.cache.LoadCacheSlot(seq.inputs, true)
 			if err != nil {
 				s.mu.Unlock()
+				s.seqsSem.Release(1)
 				http.Error(w, fmt.Sprintf("Failed to load cache: %v", err), http.StatusInternalServerError)
 				return
 			}
@@ -626,6 +627,7 @@ func (s *Server) completion(w http.ResponseWriter, r *http.Request) {
 	s.mu.Unlock()
 
 	if !found {
+		s.seqsSem.Release(1)
 		http.Error(w, "could not find an available sequence", http.StatusInternalServerError)
 		return
 	}
@@ -691,7 +693,7 @@ func (s *Server) embeddings(w http.ResponseWriter, r *http.Request) {
 		if errors.Is(err, context.Canceled) {
 			slog.Info("aborting embeddings request due to client closing the connection")
 		} else {
-			slog.Error("Failed to acquire semaphore", "error", err)
+			http.Error(w, fmt.Sprintf("Failed to acquire semaphore: %v", err), http.StatusInternalServerError)
 		}
 		return
 	}
@@ -703,6 +705,7 @@ func (s *Server) embeddings(w http.ResponseWriter, r *http.Request) {
 			seq.cache, seq.inputs, err = s.cache.LoadCacheSlot(seq.inputs, false)
 			if err != nil {
 				s.mu.Unlock()
+				s.seqsSem.Release(1)
 				http.Error(w, fmt.Sprintf("Failed to load cache: %v", err), http.StatusInternalServerError)
 				return
 			}
@@ -715,6 +718,7 @@ func (s *Server) embeddings(w http.ResponseWriter, r *http.Request) {
 	s.mu.Unlock()
 
 	if !found {
+		s.seqsSem.Release(1)
 		http.Error(w, "could not find an available sequence", http.StatusInternalServerError)
 		return
 	}
diff --git a/runner/ollamarunner/runner.go b/runner/ollamarunner/runner.go
index 6d20fa85..bc7a07ed 100644
--- a/runner/ollamarunner/runner.go
+++ b/runner/ollamarunner/runner.go
@@ -609,7 +609,7 @@ func (s *Server) completion(w http.ResponseWriter, r *http.Request) {
 		if errors.Is(err, context.Canceled) {
 			slog.Info("aborting completion request due to client closing the connection")
 		} else {
-			slog.Error("Failed to acquire semaphore", "error", err)
+			http.Error(w, fmt.Sprintf("Failed to acquire semaphore: %v", err), http.StatusInternalServerError)
 		}
 		return
 	}
@@ -621,6 +621,7 @@ func (s *Server) completion(w http.ResponseWriter, r *http.Request) {
 			seq.cache, seq.inputs, err = s.cache.LoadCacheSlot(seq.inputs)
 			if err != nil {
 				s.mu.Unlock()
+				s.seqsSem.Release(1)
 				http.Error(w, fmt.Sprintf("Failed to load cache: %v", err), http.StatusInternalServerError)
 				return
 			}
@@ -634,6 +635,7 @@ func (s *Server) completion(w http.ResponseWriter, r *http.Request) {
 	s.mu.Unlock()
 
 	if !found {
+		s.seqsSem.Release(1)
 		http.Error(w, "could not find an available sequence", http.StatusInternalServerError)
 		return
 	}

From ef27d52e7957e00fe664e7dc73cff2714f85468f Mon Sep 17 00:00:00 2001
From: Blake Mizerany <blake.mizerany@gmail.com>
Date: Sun, 30 Mar 2025 23:54:54 -0700
Subject: [PATCH 143/157] server/internal/client/ollama: cache completed chunks
 (#9933)

This change adds tracking of download chunks during the pull process so
that subsequent pulls can skip downloading already completed chunks.
This works across restarts of ollama.

Currently, download state will be lost if a prune is triggered during a
pull (e.g. restart or remove). This issue should be addressed in a
follow-up PR.
---
 server/internal/client/ollama/registry.go     |  95 ++-
 .../internal/client/ollama/registry_test.go   | 651 ++++++++++--------
 2 files changed, 443 insertions(+), 303 deletions(-)

diff --git a/server/internal/client/ollama/registry.go b/server/internal/client/ollama/registry.go
index 665defd5..409932bf 100644
--- a/server/internal/client/ollama/registry.go
+++ b/server/internal/client/ollama/registry.go
@@ -421,14 +421,6 @@ func (r *Registry) Push(ctx context.Context, name string, p *PushParams) error {
 	return err
 }
 
-func canRetry(err error) bool {
-	var re *Error
-	if !errors.As(err, &re) {
-		return false
-	}
-	return re.Status >= 500
-}
-
 // trackingReader is an io.Reader that tracks the number of bytes read and
 // calls the update function with the layer, the number of bytes read.
 //
@@ -514,13 +506,40 @@ func (r *Registry) Pull(ctx context.Context, name string) error {
 				break
 			}
 
+			cacheKey := fmt.Sprintf(
+				"v1 pull chunksum %s %s %d-%d",
+				l.Digest,
+				cs.Digest,
+				cs.Chunk.Start,
+				cs.Chunk.End,
+			)
+			cacheKeyDigest := blob.DigestFromBytes(cacheKey)
+			_, err := c.Get(cacheKeyDigest)
+			if err == nil {
+				received.Add(cs.Chunk.Size())
+				t.update(l, cs.Chunk.Size(), ErrCached)
+				continue
+			}
+
 			wg.Add(1)
 			g.Go(func() (err error) {
 				defer func() {
 					if err == nil {
+						// Ignore cache key write errors for now. We've already
+						// reported to trace that the chunk is complete.
+						//
+						// Ideally, we should only report completion to trace
+						// after successful cache commit. This current approach
+						// works but could trigger unnecessary redownloads if
+						// the checkpoint key is missing on next pull.
+						//
+						// Not incorrect, just suboptimal - fix this in a
+						// future update.
+						_ = blob.PutBytes(c, cacheKeyDigest, cacheKey)
+
 						received.Add(cs.Chunk.Size())
 					} else {
-						err = fmt.Errorf("error downloading %s: %w", cs.Digest.Short(), err)
+						t.update(l, 0, err)
 					}
 					wg.Done()
 				}()
@@ -563,7 +582,7 @@ func (r *Registry) Pull(ctx context.Context, name string) error {
 		return err
 	}
 	if received.Load() != expected {
-		return fmt.Errorf("%w: received %d/%d", ErrIncomplete, received.Load(), expected)
+		return fmt.Errorf("%w: received %d/%d bytes", ErrIncomplete, received.Load(), expected)
 	}
 
 	md := blob.DigestFromBytes(m.Data)
@@ -608,6 +627,30 @@ func (m *Manifest) Layer(d blob.Digest) *Layer {
 	return nil
 }
 
+func (m *Manifest) All() iter.Seq[*Layer] {
+	return func(yield func(*Layer) bool) {
+		if !yield(m.Config) {
+			return
+		}
+		for _, l := range m.Layers {
+			if !yield(l) {
+				return
+			}
+		}
+	}
+}
+
+func (m *Manifest) Size() int64 {
+	var size int64
+	if m.Config != nil {
+		size += m.Config.Size
+	}
+	for _, l := range m.Layers {
+		size += l.Size
+	}
+	return size
+}
+
 // MarshalJSON implements json.Marshaler.
 //
 // NOTE: It adds an empty config object to the manifest, which is required by
@@ -750,20 +793,32 @@ func (r *Registry) chunksums(ctx context.Context, name string, l *Layer) iter.Se
 			return
 		}
 
-		// A chunksums response is a sequence of chunksums in a
-		// simple, easy to parse line-oriented format.
+		// The response is a sequence of chunksums.
 		//
-		// Example:
+		// Chunksums are chunks of a larger blob that can be
+		// downloaded and verified independently.
 		//
-		//     >> GET /v2/<namespace>/<model>/chunksums/<digest>
+		// The chunksums endpoint is a GET request that returns a
+		// sequence of chunksums in the following format:
 		//
-		//     << HTTP/1.1 200 OK
-		//     << Content-Location: <blobURL>
-		//     <<
-		//     << <digest> <start>-<end>
-		//     << ...
+		//     > GET /v2/<namespace>/<model>/chunksums/<digest>
 		//
-		// The blobURL is the URL to download the chunks from.
+		//     < HTTP/1.1 200 OK
+		//     < Content-Location: <blobURL>
+		//     <
+		//     < <digest> <start>-<end>
+		//     < ...
+		//
+		// The <blobURL> is the URL to download the chunks from and
+		// each <digest> is the digest of the chunk, and <start>-<end>
+		// is the range the chunk in the blob.
+		//
+		// Ranges may be used directly in Range headers like
+		// "bytes=<start>-<end>".
+		//
+		// The chunksums returned are guaranteed to be contiguous and
+		// include all bytes of the layer. If the stream is cut short,
+		// clients should retry.
 
 		chunksumsURL := fmt.Sprintf("%s://%s/v2/%s/%s/chunksums/%s",
 			scheme,
diff --git a/server/internal/client/ollama/registry_test.go b/server/internal/client/ollama/registry_test.go
index f8136c06..80d39b76 100644
--- a/server/internal/client/ollama/registry_test.go
+++ b/server/internal/client/ollama/registry_test.go
@@ -9,17 +9,14 @@ import (
 	"fmt"
 	"io"
 	"io/fs"
-	"math/rand/v2"
+	"net"
 	"net/http"
 	"net/http/httptest"
 	"os"
-	"path"
 	"reflect"
-	"slices"
 	"strings"
-	"sync"
+	"sync/atomic"
 	"testing"
-	"time"
 
 	"github.com/ollama/ollama/server/internal/cache/blob"
 	"github.com/ollama/ollama/server/internal/testutil"
@@ -338,15 +335,8 @@ func TestPushCommitRoundtripError(t *testing.T) {
 	}
 }
 
-func checkNotExist(t *testing.T, err error) {
-	t.Helper()
-	if !errors.Is(err, fs.ErrNotExist) {
-		t.Fatalf("err = %v; want fs.ErrNotExist", err)
-	}
-}
-
 func TestRegistryPullInvalidName(t *testing.T) {
-	rc, _ := newClient(t, nil)
+	rc, _ := newRegistryClient(t, nil)
 	err := rc.Pull(t.Context(), "://")
 	if !errors.Is(err, ErrNameInvalid) {
 		t.Errorf("err = %v; want %v", err, ErrNameInvalid)
@@ -362,197 +352,16 @@ func TestRegistryPullInvalidManifest(t *testing.T) {
 	}
 
 	for _, resp := range cases {
-		rc, _ := newClient(t, func(w http.ResponseWriter, r *http.Request) {
+		rc, _ := newRegistryClient(t, func(w http.ResponseWriter, r *http.Request) {
 			io.WriteString(w, resp)
 		})
-		err := rc.Pull(t.Context(), "x")
+		err := rc.Pull(t.Context(), "http://example.com/a/b")
 		if !errors.Is(err, ErrManifestInvalid) {
 			t.Errorf("err = %v; want invalid manifest", err)
 		}
 	}
 }
 
-func TestRegistryPullNotCached(t *testing.T) {
-	check := testutil.Checker(t)
-
-	var c *blob.DiskCache
-	var rc *Registry
-
-	d := blob.DigestFromBytes("some data")
-	rc, c = newClient(t, func(w http.ResponseWriter, r *http.Request) {
-		if strings.Contains(r.URL.Path, "/blobs/") {
-			io.WriteString(w, "some data")
-			return
-		}
-		fmt.Fprintf(w, `{"layers":[{"digest":%q,"size":9}]}`, d)
-	})
-
-	// Confirm that the layer does not exist locally
-	_, err := rc.ResolveLocal("model")
-	checkNotExist(t, err)
-
-	_, err = c.Get(d)
-	checkNotExist(t, err)
-
-	err = rc.Pull(t.Context(), "model")
-	check(err)
-
-	mw, err := rc.Resolve(t.Context(), "model")
-	check(err)
-	mg, err := rc.ResolveLocal("model")
-	check(err)
-	if !reflect.DeepEqual(mw, mg) {
-		t.Errorf("mw = %v; mg = %v", mw, mg)
-	}
-
-	// Confirm successful download
-	info, err := c.Get(d)
-	check(err)
-	if info.Digest != d {
-		t.Errorf("info.Digest = %v; want %v", info.Digest, d)
-	}
-	if info.Size != 9 {
-		t.Errorf("info.Size = %v; want %v", info.Size, 9)
-	}
-
-	data, err := os.ReadFile(c.GetFile(d))
-	check(err)
-	if string(data) != "some data" {
-		t.Errorf("data = %q; want %q", data, "exists")
-	}
-}
-
-func TestRegistryPullCached(t *testing.T) {
-	cached := blob.DigestFromBytes("exists")
-	rc, _ := newClient(t, func(w http.ResponseWriter, r *http.Request) {
-		if strings.Contains(r.URL.Path, "/blobs/") {
-			w.WriteHeader(499) // should not be called
-			return
-		}
-		if strings.Contains(r.URL.Path, "/manifests/") {
-			fmt.Fprintf(w, `{"layers":[{"digest":%q,"size":6}]}`, cached)
-		}
-	})
-
-	var errs []error
-	var reads []int64
-	ctx := WithTrace(t.Context(), &Trace{
-		Update: func(d *Layer, n int64, err error) {
-			t.Logf("update %v %d %v", d, n, err)
-			reads = append(reads, n)
-			errs = append(errs, err)
-		},
-	})
-
-	ctx, cancel := context.WithTimeout(ctx, 3*time.Second)
-	defer cancel()
-
-	err := rc.Pull(ctx, "single")
-	testutil.Check(t, err)
-
-	want := []int64{0, 6}
-	if !errors.Is(errors.Join(errs...), ErrCached) {
-		t.Errorf("errs = %v; want %v", errs, ErrCached)
-	}
-	if !slices.Equal(reads, want) {
-		t.Errorf("pairs = %v; want %v", reads, want)
-	}
-}
-
-func TestRegistryPullManifestNotFound(t *testing.T) {
-	rc, _ := newClient(t, func(w http.ResponseWriter, r *http.Request) {
-		w.WriteHeader(http.StatusNotFound)
-	})
-	err := rc.Pull(t.Context(), "notfound")
-	checkErrCode(t, err, 404, "")
-}
-
-func TestRegistryPullResolveRemoteError(t *testing.T) {
-	rc, _ := newClient(t, func(w http.ResponseWriter, r *http.Request) {
-		w.WriteHeader(http.StatusInternalServerError)
-		io.WriteString(w, `{"errors":[{"code":"an_error"}]}`)
-	})
-	err := rc.Pull(t.Context(), "single")
-	checkErrCode(t, err, 500, "an_error")
-}
-
-func TestRegistryPullResolveRoundtripError(t *testing.T) {
-	rc, _ := newClient(t, func(w http.ResponseWriter, r *http.Request) {
-		if strings.Contains(r.URL.Path, "/manifests/") {
-			w.WriteHeader(499) // force RoundTrip error
-			return
-		}
-	})
-	err := rc.Pull(t.Context(), "single")
-	if !errors.Is(err, errRoundTrip) {
-		t.Errorf("err = %v; want %v", err, errRoundTrip)
-	}
-}
-
-// TestRegistryPullMixedCachedNotCached tests that cached layers do not
-// interfere with pulling layers that are not cached
-func TestRegistryPullMixedCachedNotCached(t *testing.T) {
-	x := blob.DigestFromBytes("xxxxxx")
-	e := blob.DigestFromBytes("exists")
-	y := blob.DigestFromBytes("yyyyyy")
-
-	for i := range 10 {
-		t.Logf("iteration %d", i)
-
-		digests := []blob.Digest{x, e, y}
-
-		rand.Shuffle(len(digests), func(i, j int) {
-			digests[i], digests[j] = digests[j], digests[i]
-		})
-
-		manifest := fmt.Sprintf(`{
-			"layers": [
-				{"digest":"%s","size":6},
-				{"digest":"%s","size":6},
-				{"digest":"%s","size":6}
-			]
-		}`, digests[0], digests[1], digests[2])
-
-		rc, c := newClient(t, func(w http.ResponseWriter, r *http.Request) {
-			switch path.Base(r.URL.Path) {
-			case "latest":
-				io.WriteString(w, manifest)
-			case x.String():
-				io.WriteString(w, "xxxxxx")
-			case e.String():
-				io.WriteString(w, "exists")
-			case y.String():
-				io.WriteString(w, "yyyyyy")
-			default:
-				panic(fmt.Sprintf("unexpected request: %v", r))
-			}
-		})
-
-		ctx := WithTrace(t.Context(), &Trace{
-			Update: func(l *Layer, n int64, err error) {
-				t.Logf("update %v %d %v", l, n, err)
-			},
-		})
-
-		// Check that we pull all layers that we can.
-
-		err := rc.Pull(ctx, "mixed")
-		if err != nil {
-			t.Fatal(err)
-		}
-
-		for _, d := range digests {
-			info, err := c.Get(d)
-			if err != nil {
-				t.Fatalf("Get(%v): %v", d, err)
-			}
-			if info.Size != 6 {
-				t.Errorf("info.Size = %v; want %v", info.Size, 6)
-			}
-		}
-	}
-}
-
 func TestRegistryResolveByDigest(t *testing.T) {
 	check := testutil.Checker(t)
 
@@ -590,26 +399,6 @@ func TestInsecureSkipVerify(t *testing.T) {
 	testutil.Check(t, err)
 }
 
-func TestCanRetry(t *testing.T) {
-	cases := []struct {
-		err  error
-		want bool
-	}{
-		{nil, false},
-		{errors.New("x"), false},
-		{ErrCached, false},
-		{ErrManifestInvalid, false},
-		{ErrNameInvalid, false},
-		{&Error{Status: 100}, false},
-		{&Error{Status: 500}, true},
-	}
-	for _, tt := range cases {
-		if got := canRetry(tt.err); got != tt.want {
-			t.Errorf("CanRetry(%v) = %v; want %v", tt.err, got, tt.want)
-		}
-	}
-}
-
 func TestErrorUnmarshal(t *testing.T) {
 	cases := []struct {
 		name    string
@@ -761,17 +550,23 @@ func TestParseNameExtended(t *testing.T) {
 
 func TestUnlink(t *testing.T) {
 	t.Run("found by name", func(t *testing.T) {
-		rc, _ := newClient(t, nil)
+		check := testutil.Checker(t)
+
+		rc, _ := newRegistryClient(t, nil)
+		// make a blob and link it
+		d := blob.DigestFromBytes("{}")
+		err := blob.PutBytes(rc.Cache, d, "{}")
+		check(err)
+		err = rc.Cache.Link("registry.ollama.ai/library/single:latest", d)
+		check(err)
 
 		// confirm linked
-		_, err := rc.ResolveLocal("single")
-		if err != nil {
-			t.Errorf("unexpected error: %v", err)
-		}
+		_, err = rc.ResolveLocal("single")
+		check(err)
 
 		// unlink
 		_, err = rc.Unlink("single")
-		testutil.Check(t, err)
+		check(err)
 
 		// confirm unlinked
 		_, err = rc.ResolveLocal("single")
@@ -780,7 +575,7 @@ func TestUnlink(t *testing.T) {
 		}
 	})
 	t.Run("not found by name", func(t *testing.T) {
-		rc, _ := newClient(t, nil)
+		rc, _ := newRegistryClient(t, nil)
 		ok, err := rc.Unlink("manifestNotFound")
 		if err != nil {
 			t.Fatal(err)
@@ -791,78 +586,368 @@ func TestUnlink(t *testing.T) {
 	})
 }
 
-func TestPullChunksums(t *testing.T) {
-	check := testutil.Checker(t)
+// Many tests from here out, in this file are based on a single blob, "abc",
+// with the checksum of its sha256 hash. The checksum is:
+//
+//	"abc" -> sha256:ba7816bf8f01cfea414140de5dae2223b00361a396177a9cb410ff61f20015ad
+//
+// Using the literal value instead of a constant with fmt.Xprintf calls proved
+// to be the most readable and maintainable approach. The sum is consistently
+// used in the tests and unique so searches do not yield false positives.
 
-	content := "hello"
-	var chunksums string
-	contentDigest := func() blob.Digest {
-		return blob.DigestFromBytes(content)
+func checkRequest(t *testing.T, req *http.Request, method, path string) {
+	t.Helper()
+	if got := req.URL.Path; got != path {
+		t.Errorf("URL = %q, want %q", got, path)
 	}
-	rc, c := newClient(t, func(w http.ResponseWriter, r *http.Request) {
-		switch {
-		case strings.Contains(r.URL.Path, "/manifests/latest"):
-			fmt.Fprintf(w, `{"layers":[{"digest":%q,"size":%d}]}`, contentDigest(), len(content))
-		case strings.HasSuffix(r.URL.Path, "/chunksums/"+contentDigest().String()):
-			loc := fmt.Sprintf("http://blob.store/v2/library/test/blobs/%s", contentDigest())
-			w.Header().Set("Content-Location", loc)
-			io.WriteString(w, chunksums)
-		case strings.Contains(r.URL.Path, "/blobs/"+contentDigest().String()):
-			http.ServeContent(w, r, contentDigest().String(), time.Time{}, strings.NewReader(content))
-		default:
-			t.Errorf("unexpected request: %v", r)
-			http.NotFound(w, r)
-		}
-	})
+	if req.Method != method {
+		t.Errorf("Method = %q, want %q", req.Method, method)
+	}
+}
 
-	rc.MaxStreams = 1        // prevent concurrent chunk downloads
-	rc.ChunkingThreshold = 1 // for all blobs to be chunked
+func newRegistryClient(t *testing.T, h http.HandlerFunc) (*Registry, context.Context) {
+	s := httptest.NewServer(h)
+	t.Cleanup(s.Close)
+	cache, err := blob.Open(t.TempDir())
+	if err != nil {
+		t.Fatal(err)
+	}
 
-	var mu sync.Mutex
-	var reads []int64
 	ctx := WithTrace(t.Context(), &Trace{
 		Update: func(l *Layer, n int64, err error) {
-			t.Logf("Update: %v %d %v", l, n, err)
-			mu.Lock()
-			reads = append(reads, n)
-			mu.Unlock()
+			t.Log("trace:", l.Digest.Short(), n, err)
 		},
 	})
 
-	chunksums = fmt.Sprintf("%s 0-2\n%s 3-4\n",
-		blob.DigestFromBytes("hel"),
-		blob.DigestFromBytes("lo"),
-	)
-	err := rc.Pull(ctx, "test")
-	check(err)
-	wantReads := []int64{
-		0, // initial signaling of layer pull starting
-		3, // first chunk read
-		2, // second chunk read
-	}
-	if !slices.Equal(reads, wantReads) {
-		t.Errorf("reads = %v; want %v", reads, wantReads)
+	rc := &Registry{
+		Cache: cache,
+		HTTPClient: &http.Client{Transport: &http.Transport{
+			Dial: func(network, addr string) (net.Conn, error) {
+				return net.Dial(network, s.Listener.Addr().String())
+			},
+		}},
 	}
+	return rc, ctx
+}
 
-	mw, err := rc.Resolve(t.Context(), "test")
-	check(err)
-	mg, err := rc.ResolveLocal("test")
-	check(err)
-	if !reflect.DeepEqual(mw, mg) {
-		t.Errorf("mw = %v; mg = %v", mw, mg)
-	}
-	for i := range mg.Layers {
-		_, err = c.Get(mg.Layers[i].Digest)
-		if err != nil {
-			t.Errorf("Get(%v): %v", mg.Layers[i].Digest, err)
+func TestPullChunked(t *testing.T) {
+	var steps atomic.Int64
+	c, ctx := newRegistryClient(t, func(w http.ResponseWriter, r *http.Request) {
+		switch steps.Add(1) {
+		case 1:
+			checkRequest(t, r, "GET", "/v2/library/abc/manifests/latest")
+			io.WriteString(w, `{"layers":[{"size":3,"digest":"sha256:ba7816bf8f01cfea414140de5dae2223b00361a396177a9cb410ff61f20015ad"}]}`)
+		case 2:
+			checkRequest(t, r, "GET", "/v2/library/abc/chunksums/sha256:ba7816bf8f01cfea414140de5dae2223b00361a396177a9cb410ff61f20015ad")
+			w.Header().Set("Content-Location", "http://blob.store/v2/library/abc/blobs/sha256:ba7816bf8f01cfea414140de5dae2223b00361a396177a9cb410ff61f20015ad")
+			fmt.Fprintf(w, "%s 0-1\n", blob.DigestFromBytes("ab"))
+			fmt.Fprintf(w, "%s 2-2\n", blob.DigestFromBytes("c"))
+		case 3, 4:
+			checkRequest(t, r, "GET", "/v2/library/abc/blobs/sha256:ba7816bf8f01cfea414140de5dae2223b00361a396177a9cb410ff61f20015ad")
+			switch rng := r.Header.Get("Range"); rng {
+			case "bytes=0-1":
+				io.WriteString(w, "ab")
+			case "bytes=2-2":
+				t.Logf("writing c")
+				io.WriteString(w, "c")
+			default:
+				t.Errorf("unexpected range %q", rng)
+			}
+		default:
+			t.Errorf("unexpected steps %d: %v", steps.Load(), r)
+			http.Error(w, "unexpected steps", http.StatusInternalServerError)
 		}
-	}
+	})
 
-	// missing chunks
-	content = "llama"
-	chunksums = fmt.Sprintf("%s 0-1\n", blob.DigestFromBytes("ll"))
-	err = rc.Pull(ctx, "missingchunks")
-	if err == nil {
-		t.Error("expected error because of missing chunks")
+	c.ChunkingThreshold = 1 // force chunking
+
+	err := c.Pull(ctx, "http://o.com/library/abc")
+	testutil.Check(t, err)
+
+	_, err = c.Cache.Resolve("o.com/library/abc:latest")
+	testutil.Check(t, err)
+
+	if g := steps.Load(); g != 4 {
+		t.Fatalf("got %d steps, want 4", g)
+	}
+}
+
+func TestPullCached(t *testing.T) {
+	c, ctx := newRegistryClient(t, func(w http.ResponseWriter, r *http.Request) {
+		checkRequest(t, r, "GET", "/v2/library/abc/manifests/latest")
+		io.WriteString(w, `{"layers":[{"size":3,"digest":"sha256:ba7816bf8f01cfea414140de5dae2223b00361a396177a9cb410ff61f20015ad"}]}`)
+	})
+
+	check := testutil.Checker(t)
+
+	// Premeptively cache the blob
+	d, err := blob.ParseDigest("sha256:ba7816bf8f01cfea414140de5dae2223b00361a396177a9cb410ff61f20015ad")
+	check(err)
+	err = blob.PutBytes(c.Cache, d, []byte("abc"))
+	check(err)
+
+	// Pull only the manifest, which should be enough to resolve the cached blob
+	err = c.Pull(ctx, "http://o.com/library/abc")
+	check(err)
+}
+
+func TestPullManifestError(t *testing.T) {
+	c, ctx := newRegistryClient(t, func(w http.ResponseWriter, r *http.Request) {
+		checkRequest(t, r, "GET", "/v2/library/abc/manifests/latest")
+		w.WriteHeader(http.StatusNotFound)
+		io.WriteString(w, `{"errors":[{"code":"MANIFEST_UNKNOWN"}]}`)
+	})
+
+	err := c.Pull(ctx, "http://o.com/library/abc")
+	if err == nil {
+		t.Fatalf("expected error")
+	}
+	var got *Error
+	if !errors.Is(err, ErrModelNotFound) {
+		t.Fatalf("err = %v, want %v", got, ErrModelNotFound)
+	}
+}
+
+func TestPullLayerError(t *testing.T) {
+	c, ctx := newRegistryClient(t, func(w http.ResponseWriter, r *http.Request) {
+		checkRequest(t, r, "GET", "/v2/library/abc/manifests/latest")
+		io.WriteString(w, `!`)
+	})
+
+	err := c.Pull(ctx, "http://o.com/library/abc")
+	if err == nil {
+		t.Fatalf("expected error")
+	}
+	var want *json.SyntaxError
+	if !errors.As(err, &want) {
+		t.Fatalf("err = %T, want %T", err, want)
+	}
+}
+
+func TestPullLayerChecksumError(t *testing.T) {
+	var step atomic.Int64
+	c, _ := newRegistryClient(t, func(w http.ResponseWriter, r *http.Request) {
+		switch step.Add(1) {
+		case 1:
+			checkRequest(t, r, "GET", "/v2/library/abc/manifests/latest")
+			io.WriteString(w, `{"layers":[{"size":3,"digest":"sha256:ba7816bf8f01cfea414140de5dae2223b00361a396177a9cb410ff61f20015ad"}]}`)
+		case 2:
+			checkRequest(t, r, "GET", "/v2/library/abc/chunksums/sha256:ba7816bf8f01cfea414140de5dae2223b00361a396177a9cb410ff61f20015ad")
+			w.Header().Set("Content-Location", "http://blob.store/v2/library/abc/blobs/sha256:ba7816bf8f01cfea414140de5dae2223b00361a396177a9cb410ff61f20015ad")
+			fmt.Fprintf(w, "%s 0-1\n", blob.DigestFromBytes("ab"))
+			fmt.Fprintf(w, "%s 2-2\n", blob.DigestFromBytes("c"))
+		case 3:
+			w.WriteHeader(http.StatusNotFound)
+			io.WriteString(w, `{"errors":[{"code":"BLOB_UNKNOWN"}]}`)
+		case 4:
+			io.WriteString(w, "c")
+		default:
+			t.Errorf("unexpected steps %d: %v", step.Load(), r)
+			http.Error(w, "unexpected steps", http.StatusInternalServerError)
+		}
+	})
+
+	c.MaxStreams = 1
+	c.ChunkingThreshold = 1 // force chunking
+
+	var written atomic.Int64
+	ctx := WithTrace(t.Context(), &Trace{
+		Update: func(l *Layer, n int64, err error) {
+			t.Log("trace:", l.Digest.Short(), n, err)
+			written.Add(n)
+		},
+	})
+
+	err := c.Pull(ctx, "http://o.com/library/abc")
+	var got *Error
+	if !errors.As(err, &got) || got.Code != "BLOB_UNKNOWN" {
+		t.Fatalf("err = %v, want %v", err, got)
+	}
+
+	if g := written.Load(); g != 1 {
+		t.Fatalf("wrote %d bytes, want 1", g)
+	}
+}
+
+func TestPullChunksumStreamError(t *testing.T) {
+	var step atomic.Int64
+	c, ctx := newRegistryClient(t, func(w http.ResponseWriter, r *http.Request) {
+		switch step.Add(1) {
+		case 1:
+			checkRequest(t, r, "GET", "/v2/library/abc/manifests/latest")
+			io.WriteString(w, `{"layers":[{"size":3,"digest":"sha256:ba7816bf8f01cfea414140de5dae2223b00361a396177a9cb410ff61f20015ad"}]}`)
+		case 2:
+			w.Header().Set("Content-Location", "http://blob.store/v2/library/abc/blobs/sha256:ba7816bf8f01cfea414140de5dae2223b00361a396177a9cb410ff61f20015ad")
+
+			// Write one valid chunksum and one invalid chunksum
+			fmt.Fprintf(w, "%s 0-1\n", blob.DigestFromBytes("ab")) // valid
+			fmt.Fprint(w, "sha256:!")                              // invalid
+		case 3:
+			io.WriteString(w, "ab")
+		default:
+			t.Errorf("unexpected steps %d: %v", step.Load(), r)
+			http.Error(w, "unexpected steps", http.StatusInternalServerError)
+		}
+	})
+
+	c.ChunkingThreshold = 1 // force chunking
+
+	got := c.Pull(ctx, "http://o.com/library/abc")
+	if !errors.Is(got, ErrIncomplete) {
+		t.Fatalf("err = %v, want %v", got, ErrIncomplete)
+	}
+}
+
+type flushAfterWriter struct {
+	w io.Writer
+}
+
+func (f *flushAfterWriter) Write(p []byte) (n int, err error) {
+	n, err = f.w.Write(p)
+	f.w.(http.Flusher).Flush() // panic if not a flusher
+	return
+}
+
+func TestPullChunksumStreaming(t *testing.T) {
+	csr, csw := io.Pipe()
+	defer csw.Close()
+
+	var step atomic.Int64
+	c, _ := newRegistryClient(t, func(w http.ResponseWriter, r *http.Request) {
+		switch step.Add(1) {
+		case 1:
+			checkRequest(t, r, "GET", "/v2/library/abc/manifests/latest")
+			io.WriteString(w, `{"layers":[{"size":3,"digest":"sha256:ba7816bf8f01cfea414140de5dae2223b00361a396177a9cb410ff61f20015ad"}]}`)
+		case 2:
+			w.Header().Set("Content-Location", "http://blob.store/v2/library/abc/blobs/sha256:ba7816bf8f01cfea414140de5dae2223b00361a396177a9cb410ff61f20015ad")
+			fw := &flushAfterWriter{w} // ensure client gets data as it arrives by aggressively flushing
+			_, err := io.Copy(fw, csr)
+			if err != nil {
+				t.Errorf("copy: %v", err)
+			}
+		case 3:
+			io.WriteString(w, "ab")
+		case 4:
+			io.WriteString(w, "c")
+		default:
+			t.Errorf("unexpected steps %d: %v", step.Load(), r)
+			http.Error(w, "unexpected steps", http.StatusInternalServerError)
+		}
+	})
+
+	c.ChunkingThreshold = 1 // force chunking
+
+	update := make(chan int64, 1)
+	ctx := WithTrace(t.Context(), &Trace{
+		Update: func(l *Layer, n int64, err error) {
+			t.Log("trace:", l.Digest.Short(), n, err)
+			if n > 0 {
+				update <- n
+			}
+		},
+	})
+
+	errc := make(chan error, 1)
+	go func() {
+		errc <- c.Pull(ctx, "http://o.com/library/abc")
+	}()
+
+	// Send first chunksum and ensure it kicks off work immediately
+	fmt.Fprintf(csw, "%s 0-1\n", blob.DigestFromBytes("ab"))
+	if g := <-update; g != 2 {
+		t.Fatalf("got %d, want 2", g)
+	}
+
+	// now send the second chunksum and ensure it kicks off work immediately
+	fmt.Fprintf(csw, "%s 2-2\n", blob.DigestFromBytes("c"))
+	if g := <-update; g != 1 {
+		t.Fatalf("got %d, want 1", g)
+	}
+	csw.Close()
+	testutil.Check(t, <-errc)
+}
+
+func TestPullChunksumsCached(t *testing.T) {
+	var step atomic.Int64
+	c, _ := newRegistryClient(t, func(w http.ResponseWriter, r *http.Request) {
+		switch step.Add(1) {
+		case 1:
+			checkRequest(t, r, "GET", "/v2/library/abc/manifests/latest")
+			io.WriteString(w, `{"layers":[{"size":3,"digest":"sha256:ba7816bf8f01cfea414140de5dae2223b00361a396177a9cb410ff61f20015ad"}]}`)
+		case 2:
+			w.Header().Set("Content-Location", "http://blob.store/v2/library/abc/blobs/sha256:ba7816bf8f01cfea414140de5dae2223b00361a396177a9cb410ff61f20015ad")
+			fmt.Fprintf(w, "%s 0-1\n", blob.DigestFromBytes("ab"))
+			fmt.Fprintf(w, "%s 2-2\n", blob.DigestFromBytes("c"))
+		case 3, 4:
+			switch rng := r.Header.Get("Range"); rng {
+			case "bytes=0-1":
+				io.WriteString(w, "ab")
+			case "bytes=2-2":
+				io.WriteString(w, "c")
+			default:
+				t.Errorf("unexpected range %q", rng)
+			}
+		default:
+			t.Errorf("unexpected steps %d: %v", step.Load(), r)
+			http.Error(w, "unexpected steps", http.StatusInternalServerError)
+		}
+	})
+
+	c.MaxStreams = 1        // force serial processing of chunksums
+	c.ChunkingThreshold = 1 // force chunking
+
+	ctx, cancel := context.WithCancel(t.Context())
+	defer cancel()
+
+	// Cancel the pull after the first chunksum is processed, but before
+	// the second chunksum is processed (which is waiting because
+	// MaxStreams=1). This should cause the second chunksum to error out
+	// leaving the blob incomplete.
+	ctx = WithTrace(ctx, &Trace{
+		Update: func(l *Layer, n int64, err error) {
+			if n > 0 {
+				cancel()
+			}
+		},
+	})
+	err := c.Pull(ctx, "http://o.com/library/abc")
+	if !errors.Is(err, context.Canceled) {
+		t.Fatalf("err = %v, want %v", err, context.Canceled)
+	}
+
+	_, err = c.Cache.Resolve("o.com/library/abc:latest")
+	if !errors.Is(err, fs.ErrNotExist) {
+		t.Fatalf("err = %v, want nil", err)
+	}
+
+	// Reset state and pull again to ensure the blob chunks that should
+	// have been cached are, and the remaining chunk was downloaded, making
+	// the blob complete.
+	step.Store(0)
+	var written atomic.Int64
+	var cached atomic.Int64
+	ctx = WithTrace(t.Context(), &Trace{
+		Update: func(l *Layer, n int64, err error) {
+			t.Log("trace:", l.Digest.Short(), n, err)
+			if errors.Is(err, ErrCached) {
+				cached.Add(n)
+			}
+			written.Add(n)
+		},
+	})
+
+	check := testutil.Checker(t)
+
+	err = c.Pull(ctx, "http://o.com/library/abc")
+	check(err)
+
+	_, err = c.Cache.Resolve("o.com/library/abc:latest")
+	check(err)
+
+	if g := written.Load(); g != 3 {
+		t.Fatalf("wrote %d bytes, want 3", g)
+	}
+	if g := cached.Load(); g != 2 { // "ab" should have been cached
+		t.Fatalf("cached %d bytes, want 3", g)
 	}
 }

From 66b253923891d41a31d28531e9db5efccf53e1d0 Mon Sep 17 00:00:00 2001
From: Bruce MacDonald <brucewmacdonald@gmail.com>
Date: Mon, 31 Mar 2025 12:54:45 -0700
Subject: [PATCH 144/157] runner: clear cache when shift is not possible
 (#9433)

Clear KV cache when shift operation is not supported by model.
Added KvCacheCanShift() check to handle models that can't perform cache shifts,
falling back to full cache clear while preserving logical token history to
maintain expected behavior when context window fills up.
---
 llama/llama.go                    |  4 ++
 runner/llamarunner/cache.go       | 55 +++++++++++++++----
 runner/llamarunner/runner.go      | 10 +++-
 runner/ollamarunner/cache.go      | 24 +++++++-
 runner/ollamarunner/cache_test.go | 91 +++++++++++++++++++++++++++++++
 runner/ollamarunner/runner.go     | 10 +++-
 6 files changed, 180 insertions(+), 14 deletions(-)

diff --git a/llama/llama.go b/llama/llama.go
index a026bee2..e8cdafe7 100644
--- a/llama/llama.go
+++ b/llama/llama.go
@@ -166,6 +166,10 @@ func (c *Context) KvCacheDefrag() {
 	C.llama_kv_cache_defrag(c.c)
 }
 
+func (c *Context) KvCacheCanShift() bool {
+	return bool(C.llama_kv_cache_can_shift(c.c))
+}
+
 // Get the embeddings for a sequence id
 func (c *Context) GetEmbeddingsSeq(seqId int) []float32 {
 	e := unsafe.Pointer(C.llama_get_embeddings_seq(c.c, C.int(seqId)))
diff --git a/runner/llamarunner/cache.go b/runner/llamarunner/cache.go
index d29e94b6..2e55b09d 100644
--- a/runner/llamarunner/cache.go
+++ b/runner/llamarunner/cache.go
@@ -213,8 +213,16 @@ func (c *InputCache) ShiftDiscard(inputLen int, numKeep int) int {
 	return discard
 }
 
-// Frees up space in the KV cache by deleting the oldest half of history and shifting
-// the newest half into that space (saving numKeep inputs at the beginning).
+type ErrReprocessInputs struct {
+	Inputs []input
+}
+
+func (e *ErrReprocessInputs) Error() string {
+	return fmt.Sprintf("kv cache shift not supported, inputs need reprocessing (input count: %v)", len(e.Inputs))
+}
+
+// ShiftCacheSlot frees up space in the KV cache by deleting the oldest half of history
+// and shifting the newest half into that space (saving numKeep inputs at the beginning).
 //
 // Assumes that at least 1 entry can be freed up by shifting (i.e. numKeep < numCtx)
 func (c *InputCache) ShiftCacheSlot(slot *InputCacheSlot, numKeep int) error {
@@ -222,7 +230,8 @@ func (c *InputCache) ShiftCacheSlot(slot *InputCacheSlot, numKeep int) error {
 		return fmt.Errorf("unable to shift context - keep exceeds context (keep: %v context: %v)", numKeep, c.numCtx)
 	}
 
-	discard := c.ShiftDiscard(len(slot.Inputs), numKeep)
+	inputLen := len(slot.Inputs)
+	discard := c.ShiftDiscard(inputLen, numKeep)
 
 	if discard <= 0 {
 		return nil
@@ -231,16 +240,42 @@ func (c *InputCache) ShiftCacheSlot(slot *InputCacheSlot, numKeep int) error {
 	slog.Debug("context limit hit - shifting", "id", slot.Id, "limit", c.numCtx, "input", len(slot.Inputs),
 		"keep", numKeep, "discard", discard)
 
-	// TODO (jessegross): KV cache removal can fail for certain types of models
-	if !c.lc.KvCacheSeqRm(slot.Id, numKeep, numKeep+discard) {
-		return fmt.Errorf("unable to remove old kv cache entries (id: %v, keep: %v discard: %v)", slot.Id, numKeep, discard)
-	}
-	c.lc.KvCacheSeqAdd(slot.Id, numKeep+discard, len(slot.Inputs), -discard)
+	var shiftFailed bool
 
-	for i := numKeep + discard; i < len(slot.Inputs); i++ {
+	if c.lc.KvCacheCanShift() {
+		// For models that support shifting, attempt to shift the KV cache
+		if !c.lc.KvCacheSeqRm(slot.Id, numKeep, numKeep+discard) {
+			shiftFailed = true
+			slog.Debug("kv cache removal not supported, clearing cache and returning inputs for reprocessing", "id", slot.Id)
+		} else {
+			c.lc.KvCacheSeqAdd(slot.Id, numKeep+discard, inputLen, -discard)
+		}
+	} else {
+		// For models that don't support shifting
+		shiftFailed = true
+		slog.Debug("kv cache cannot shift, clearing cache and returning inputs for reprocessing", "id", slot.Id)
+	}
+
+	if shiftFailed {
+		// Create new input slice with preserved tokens (numKeep + remaining tokens after discard)
+		newInputs := make([]input, numKeep+inputLen-(numKeep+discard))
+		copy(newInputs[:numKeep], slot.Inputs[:numKeep])
+		copy(newInputs[numKeep:], slot.Inputs[numKeep+discard:])
+
+		// Clear the entire KV cache
+		_ = c.lc.KvCacheSeqRm(slot.Id, 0, -1)
+		// Reset the slot inputs since we've cleared the cache
+		slot.Inputs = []input{}
+
+		// Return error with inputs that need to be reprocessed
+		return &ErrReprocessInputs{Inputs: newInputs}
+	}
+
+	// Standard shift succeeded - update input array
+	for i := numKeep + discard; i < inputLen; i++ {
 		slot.Inputs[i-discard] = slot.Inputs[i]
 	}
-	slot.Inputs = slot.Inputs[:len(slot.Inputs)-discard]
+	slot.Inputs = slot.Inputs[:inputLen-discard]
 
 	return nil
 }
diff --git a/runner/llamarunner/runner.go b/runner/llamarunner/runner.go
index ee5d47f6..a4264f5f 100644
--- a/runner/llamarunner/runner.go
+++ b/runner/llamarunner/runner.go
@@ -389,7 +389,15 @@ func (s *Server) processBatch(tokenBatch *llama.Batch, embedBatch *llama.Batch)
 				if len(seq.pendingInputs) == 0 {
 					err := s.cache.ShiftCacheSlot(seq.cache, seq.numKeep)
 					if err != nil {
-						return err
+						var reprocess *ErrReprocessInputs
+						if errors.As(err, &reprocess) {
+							// Prepend these inputs to the sequence's inputs queue for reprocessing
+							seq.inputs = append(reprocess.Inputs, seq.inputs...)
+							// Continue processing as normal
+							continue
+						} else {
+							return err
+						}
 					}
 				} else {
 					break
diff --git a/runner/ollamarunner/cache.go b/runner/ollamarunner/cache.go
index aa56c982..af48ff22 100644
--- a/runner/ollamarunner/cache.go
+++ b/runner/ollamarunner/cache.go
@@ -239,6 +239,14 @@ func (c *InputCache) ShiftDiscard(inputLen int32, numKeep int32) int32 {
 	return discard
 }
 
+type ErrReprocessInputs struct {
+	Inputs []input.Input
+}
+
+func (e *ErrReprocessInputs) Error() string {
+	return fmt.Sprintf("kv cache shift not supported, inputs need reprocessing (input count: %v)", len(e.Inputs))
+}
+
 // Frees up space in the KV cache by deleting the oldest half of history and shifting
 // the newest half into that space (saving numKeep inputs at the beginning).
 //
@@ -258,11 +266,23 @@ func (c *InputCache) ShiftCacheSlot(slot *InputCacheSlot, numKeep int32) error {
 	slog.Debug("context limit hit - shifting", "id", slot.Id, "limit", c.numCtx, "input", len(slot.Inputs),
 		"keep", numKeep, "discard", discard)
 
-	// TODO (jessegross): KV cache removal can fail for certain types of models
 	if c.cache != nil {
 		err := c.cache.Remove(slot.Id, numKeep, numKeep+discard)
 		if err != nil {
-			return fmt.Errorf("unable to remove old kv cache entries (id: %v, keep: %v discard: %v): %w", slot.Id, numKeep, discard, err)
+			slog.Debug("kv cache removal unsupported, clearing cache and returning inputs for reprocessing",
+				"id", slot.Id, "error", err)
+
+			// Create new input slice with preserved tokens (numKeep + remaining tokens after discard)
+			newInputs := make([]input.Input, numKeep+inputLen-(numKeep+discard))
+			copy(newInputs[:numKeep], slot.Inputs[:numKeep])
+			copy(newInputs[numKeep:], slot.Inputs[numKeep+discard:])
+
+			// Reset the cache
+			_ = c.cache.Remove(slot.Id, 0, -1)
+			slot.Inputs = []input.Input{}
+
+			// Return error with inputs that need to be reprocessed
+			return &ErrReprocessInputs{Inputs: newInputs}
 		}
 	}
 
diff --git a/runner/ollamarunner/cache_test.go b/runner/ollamarunner/cache_test.go
index f8925d11..6a8d8a6a 100644
--- a/runner/ollamarunner/cache_test.go
+++ b/runner/ollamarunner/cache_test.go
@@ -1,10 +1,13 @@
 package ollamarunner
 
 import (
+	"errors"
+	"fmt"
 	"image"
 	"testing"
 	"time"
 
+	"github.com/ollama/ollama/ml"
 	"github.com/ollama/ollama/model/input"
 )
 
@@ -425,3 +428,91 @@ func TestLoadCacheSlot(t *testing.T) {
 		})
 	}
 }
+
+// Mock implementation of the Cache interface
+type mockCache struct {
+	shouldFail bool
+}
+
+// Implement only the methods needed for the test
+func (m *mockCache) Remove(seq int, beginIndex, endIndex int32) error {
+	if m.shouldFail {
+		return fmt.Errorf("mock cache removal error")
+	}
+	return nil
+}
+
+// Stub implementations for other interface methods
+func (m *mockCache) SetLayer(layer int)                                                            {}
+func (m *mockCache) Get(ctx ml.Context) (ml.Tensor, ml.Tensor, ml.Tensor)                          { return nil, nil, nil }
+func (m *mockCache) Put(ctx ml.Context, key, value ml.Tensor)                                      {}
+func (m *mockCache) Init(backend ml.Backend, dtype ml.DType, maxSequences, capacity, maxBatch int) {}
+func (m *mockCache) Close()                                                                        {}
+func (m *mockCache) StartForward(ctx ml.Context, batch input.Batch) error                          { return nil }
+func (m *mockCache) CopyPrefix(srcSeq, dstSeq int, len int32)                                      {}
+func (m *mockCache) SetConfig(ml.CacheConfig)                                                      {}
+
+func TestShiftCacheSlot(t *testing.T) {
+	tests := []struct {
+		name          string
+		numCtx        int32
+		inputs        []input.Input
+		numKeep       int32
+		cacheErr      bool
+		wantErr       any
+		wantInputsLen int
+	}{
+		{
+			name:          "Normal shift",
+			numCtx:        10,
+			inputs:        []input.Input{{Token: 1}, {Token: 2}, {Token: 3}, {Token: 4}, {Token: 5}, {Token: 6}, {Token: 7}, {Token: 8}, {Token: 9}, {Token: 10}},
+			numKeep:       2,
+			cacheErr:      false, // No error
+			wantErr:       nil,
+			wantInputsLen: 6, // After discarding 4 tokens
+		},
+		{
+			name:          "Cache removal fails",
+			numCtx:        10,
+			inputs:        []input.Input{{Token: 1}, {Token: 2}, {Token: 3}, {Token: 4}, {Token: 5}, {Token: 6}, {Token: 7}, {Token: 8}, {Token: 9}, {Token: 10}},
+			numKeep:       2,
+			cacheErr:      true,
+			wantErr:       &ErrReprocessInputs{},
+			wantInputsLen: 0, // Original inputs should be cleared
+		},
+	}
+
+	for _, tt := range tests {
+		t.Run(tt.name, func(t *testing.T) {
+			mock := &mockCache{shouldFail: tt.cacheErr}
+			c := InputCache{
+				numCtx: tt.numCtx,
+				cache:  mock,
+			}
+			slot := &InputCacheSlot{
+				Id:     123,
+				Inputs: make([]input.Input, len(tt.inputs)),
+			}
+			copy(slot.Inputs, tt.inputs)
+
+			err := c.ShiftCacheSlot(slot, tt.numKeep)
+
+			if tt.wantErr != nil {
+				if err == nil {
+					t.Errorf("Expected error but got nil")
+					return
+				}
+
+				if !errors.As(err, &tt.wantErr) {
+					t.Errorf("Expected error of type %T but got %T: %v", tt.wantErr, err, err)
+				}
+			} else if err != nil {
+				t.Errorf("Unexpected error: %v", err)
+			}
+
+			if len(slot.Inputs) != tt.wantInputsLen {
+				t.Errorf("Slot inputs length after operation: got %v, want %v", len(slot.Inputs), tt.wantInputsLen)
+			}
+		})
+	}
+}
diff --git a/runner/ollamarunner/runner.go b/runner/ollamarunner/runner.go
index bc7a07ed..45838718 100644
--- a/runner/ollamarunner/runner.go
+++ b/runner/ollamarunner/runner.go
@@ -407,7 +407,15 @@ func (s *Server) processBatch() error {
 
 				err := s.cache.ShiftCacheSlot(seq.cache, seq.numKeep)
 				if err != nil {
-					return err
+					var reprocess *ErrReprocessInputs
+					if errors.As(err, &reprocess) {
+						// Prepend these inputs to the sequence's inputs queue for reprocessing
+						seq.inputs = append(reprocess.Inputs, seq.inputs...)
+						// Skip this sequence but continue processing the rest
+						continue
+					} else {
+						return err
+					}
 				}
 			}
 

From 4059a297a6d95ce94f3619eac0536fda666d58f1 Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?=E6=B9=9B=E9=9C=B2=E5=85=88=E7=94=9F?=
 <zhanluxianshen@163.com>
Date: Tue, 1 Apr 2025 08:07:42 +0800
Subject: [PATCH 145/157] discover: /proc/cpuinfo file open and close. (#9950)

Signed-off-by: zhanluxianshen <zhanluxianshen@163.com>
---
 discover/gpu_linux.go | 5 ++---
 1 file changed, 2 insertions(+), 3 deletions(-)

diff --git a/discover/gpu_linux.go b/discover/gpu_linux.go
index d636a54e..44c53b44 100644
--- a/discover/gpu_linux.go
+++ b/discover/gpu_linux.go
@@ -111,6 +111,7 @@ func GetCPUDetails() ([]CPU, error) {
 	if err != nil {
 		return nil, err
 	}
+	defer file.Close()
 	return linuxCPUDetails(file)
 }
 
@@ -168,13 +169,11 @@ func linuxCPUDetails(file io.Reader) ([]CPU, error) {
 	for id, s := range socketByID {
 		s.CoreCount = len(coreBySocket[id])
 		s.ThreadCount = 0
-		for _, tc := range threadsByCoreBySocket[id] {
-			s.ThreadCount += tc
-		}
 
 		// This only works if HT is enabled, consider a more reliable model, maybe cache size comparisons?
 		efficiencyCoreCount := 0
 		for _, threads := range threadsByCoreBySocket[id] {
+			s.ThreadCount += threads
 			if threads == 1 {
 				efficiencyCoreCount++
 			}

From 23fc8e92eb01ddd1cf06b34ff270926ec7edd4b8 Mon Sep 17 00:00:00 2001
From: Abyss-c0re <dev@abyss-core.com>
Date: Tue, 1 Apr 2025 03:23:04 +0300
Subject: [PATCH 146/157] docs: add DeepShell to community projects (#9955)

Co-authored-by: Bruce MacDonald <brucewmacdonald@gmail.com>
---
 README.md | 1 +
 1 file changed, 1 insertion(+)

diff --git a/README.md b/README.md
index c3d49105..24391caf 100644
--- a/README.md
+++ b/README.md
@@ -435,6 +435,7 @@ See the [API documentation](./docs/api.md) for all endpoints.
 - [SwollamaCLI](https://github.com/marcusziade/Swollama) bundled with the Swollama Swift package. [Demo](https://github.com/marcusziade/Swollama?tab=readme-ov-file#cli-usage)
 - [aichat](https://github.com/sigoden/aichat) All-in-one LLM CLI tool featuring Shell Assistant, Chat-REPL, RAG, AI tools & agents, with access to OpenAI, Claude, Gemini, Ollama, Groq, and more.
 - [PowershAI](https://github.com/rrg92/powershai) PowerShell module that brings AI to terminal on Windows, including support for Ollama
+- [DeepShell](https://github.com/Abyss-c0re/deepshell) Your self-hosted AI assistant. Interactive Shell, Files and Folders analysis.
 - [orbiton](https://github.com/xyproto/orbiton) Configuration-free text editor and IDE with support for tab completion with Ollama.
 - [orca-cli](https://github.com/molbal/orca-cli) Ollama Registry CLI Application - Browse, pull and download models from Ollama Registry in your terminal.
 

From c001b98087e45b7b60509127d4d2e9d9ba809444 Mon Sep 17 00:00:00 2001
From: Ilian <ilian@tagspaces.org>
Date: Tue, 1 Apr 2025 02:28:59 +0200
Subject: [PATCH 147/157] docs: add TagSpaces to community integrations (#9983)

---
 README.md | 1 +
 1 file changed, 1 insertion(+)

diff --git a/README.md b/README.md
index 24391caf..aca00a87 100644
--- a/README.md
+++ b/README.md
@@ -285,6 +285,7 @@ See the [API documentation](./docs/api.md) for all endpoints.
 - [Bionic GPT](https://github.com/bionic-gpt/bionic-gpt)
 - [HTML UI](https://github.com/rtcfirefly/ollama-ui)
 - [Saddle](https://github.com/jikkuatwork/saddle)
+- [TagSpaces](https://www.tagspaces.org) (A platform for file based apps, [utilizing Ollama](https://docs.tagspaces.org/ai/) for the generation of tags and descriptions)
 - [Chatbot UI](https://github.com/ivanfioravanti/chatbot-ollama)
 - [Chatbot UI v2](https://github.com/mckaywrigley/chatbot-ui)
 - [Typescript UI](https://github.com/ollama-interface/Ollama-Gui?tab=readme-ov-file)

From e172f095ba4af2c98d7744ce4ffcf4cd3a8e123c Mon Sep 17 00:00:00 2001
From: Bruce MacDonald <brucewmacdonald@gmail.com>
Date: Tue, 1 Apr 2025 15:21:46 -0700
Subject: [PATCH 148/157] api: return model capabilities from the show endpoint
  (#10066)

With support for multimodal models becoming more varied and common it is important for clients to be able to easily see what capabilities a model has. Retuning these from the show endpoint will allow clients to easily see what a model can do.
---
 api/types.go              |  24 +--
 cmd/cmd.go                |  15 ++
 cmd/cmd_test.go           |  29 +++
 docs/api.md               |   8 +-
 server/images.go          | 101 +++++++----
 server/images_test.go     | 360 ++++++++++++++++++++++++++++++++++++++
 server/routes.go          |  35 ++--
 server/sched.go           |   3 +-
 types/model/capability.go |  15 ++
 9 files changed, 521 insertions(+), 69 deletions(-)
 create mode 100644 server/images_test.go
 create mode 100644 types/model/capability.go

diff --git a/api/types.go b/api/types.go
index a38b335b..b4a65fe5 100644
--- a/api/types.go
+++ b/api/types.go
@@ -12,6 +12,7 @@ import (
 	"time"
 
 	"github.com/ollama/ollama/envconfig"
+	"github.com/ollama/ollama/types/model"
 )
 
 // StatusError is an error with an HTTP status code and message.
@@ -340,17 +341,18 @@ type ShowRequest struct {
 
 // ShowResponse is the response returned from [Client.Show].
 type ShowResponse struct {
-	License       string         `json:"license,omitempty"`
-	Modelfile     string         `json:"modelfile,omitempty"`
-	Parameters    string         `json:"parameters,omitempty"`
-	Template      string         `json:"template,omitempty"`
-	System        string         `json:"system,omitempty"`
-	Details       ModelDetails   `json:"details,omitempty"`
-	Messages      []Message      `json:"messages,omitempty"`
-	ModelInfo     map[string]any `json:"model_info,omitempty"`
-	ProjectorInfo map[string]any `json:"projector_info,omitempty"`
-	Tensors       []Tensor       `json:"tensors,omitempty"`
-	ModifiedAt    time.Time      `json:"modified_at,omitempty"`
+	License       string             `json:"license,omitempty"`
+	Modelfile     string             `json:"modelfile,omitempty"`
+	Parameters    string             `json:"parameters,omitempty"`
+	Template      string             `json:"template,omitempty"`
+	System        string             `json:"system,omitempty"`
+	Details       ModelDetails       `json:"details,omitempty"`
+	Messages      []Message          `json:"messages,omitempty"`
+	ModelInfo     map[string]any     `json:"model_info,omitempty"`
+	ProjectorInfo map[string]any     `json:"projector_info,omitempty"`
+	Tensors       []Tensor           `json:"tensors,omitempty"`
+	Capabilities  []model.Capability `json:"capabilities,omitempty"`
+	ModifiedAt    time.Time          `json:"modified_at,omitempty"`
 }
 
 // CopyRequest is the request passed to [Client.Copy].
diff --git a/cmd/cmd.go b/cmd/cmd.go
index abb4806b..36d7e6cf 100644
--- a/cmd/cmd.go
+++ b/cmd/cmd.go
@@ -18,6 +18,7 @@ import (
 	"os/signal"
 	"path/filepath"
 	"runtime"
+	"slices"
 	"sort"
 	"strconv"
 	"strings"
@@ -339,6 +340,11 @@ func RunHandler(cmd *cobra.Command, args []string) error {
 		return err
 	}
 
+	opts.MultiModal = slices.Contains(info.Capabilities, model.CapabilityVision)
+
+	// TODO: remove the projector info and vision info checks below,
+	// these are left in for backwards compatibility with older servers
+	// that don't have the capabilities field in the model info
 	if len(info.ProjectorInfo) != 0 {
 		opts.MultiModal = true
 	}
@@ -669,6 +675,15 @@ func showInfo(resp *api.ShowResponse, verbose bool, w io.Writer) error {
 		return
 	})
 
+	if len(resp.Capabilities) > 0 {
+		tableRender("Capabilities", func() (rows [][]string) {
+			for _, capability := range resp.Capabilities {
+				rows = append(rows, []string{"", capability.String()})
+			}
+			return
+		})
+	}
+
 	if resp.ProjectorInfo != nil {
 		tableRender("Projector", func() (rows [][]string) {
 			arch := resp.ProjectorInfo["general.architecture"].(string)
diff --git a/cmd/cmd_test.go b/cmd/cmd_test.go
index ea3bdffe..e6a542d0 100644
--- a/cmd/cmd_test.go
+++ b/cmd/cmd_test.go
@@ -16,6 +16,7 @@ import (
 	"github.com/spf13/cobra"
 
 	"github.com/ollama/ollama/api"
+	"github.com/ollama/ollama/types/model"
 )
 
 func TestShowInfo(t *testing.T) {
@@ -260,6 +261,34 @@ Weigh anchor!
 			t.Errorf("unexpected output (-want +got):\n%s", diff)
 		}
 	})
+
+	t.Run("capabilities", func(t *testing.T) {
+		var b bytes.Buffer
+		if err := showInfo(&api.ShowResponse{
+			Details: api.ModelDetails{
+				Family:            "test",
+				ParameterSize:     "7B",
+				QuantizationLevel: "FP16",
+			},
+			Capabilities: []model.Capability{model.CapabilityVision, model.CapabilityTools},
+		}, false, &b); err != nil {
+			t.Fatal(err)
+		}
+
+		expect := "  Model\n" +
+			"    architecture    test    \n" +
+			"    parameters      7B      \n" +
+			"    quantization    FP16    \n" +
+			"\n" +
+			"  Capabilities\n" +
+			"    vision    \n" +
+			"    tools     \n" +
+			"\n"
+
+		if diff := cmp.Diff(expect, b.String()); diff != "" {
+			t.Errorf("unexpected output (-want +got):\n%s", diff)
+		}
+	})
 }
 
 func TestDeleteHandler(t *testing.T) {
diff --git a/docs/api.md b/docs/api.md
index fe044d79..04ee299d 100644
--- a/docs/api.md
+++ b/docs/api.md
@@ -1217,7 +1217,7 @@ Show information about a model including details, modelfile, template, parameter
 
 ```shell
 curl http://localhost:11434/api/show -d '{
-  "model": "llama3.2"
+  "model": "llava"
 }'
 ```
 
@@ -1260,7 +1260,11 @@ curl http://localhost:11434/api/show -d '{
     "tokenizer.ggml.pre": "llama-bpe",
     "tokenizer.ggml.token_type": [],        // populates if `verbose=true`
     "tokenizer.ggml.tokens": []             // populates if `verbose=true`
-  }
+  },
+  "capabilities": [
+    "completion",
+    "vision"
+  ],
 }
 ```
 
diff --git a/server/images.go b/server/images.go
index 290e68ba..2ef9e5d0 100644
--- a/server/images.go
+++ b/server/images.go
@@ -35,17 +35,11 @@ var (
 	errCapabilityCompletion = errors.New("completion")
 	errCapabilityTools      = errors.New("tools")
 	errCapabilityInsert     = errors.New("insert")
+	errCapabilityVision     = errors.New("vision")
+	errCapabilityEmbedding  = errors.New("embedding")
 	errInsecureProtocol     = errors.New("insecure protocol http")
 )
 
-type Capability string
-
-const (
-	CapabilityCompletion = Capability("completion")
-	CapabilityTools      = Capability("tools")
-	CapabilityInsert     = Capability("insert")
-)
-
 type registryOptions struct {
 	Insecure bool
 	Username string
@@ -72,46 +66,77 @@ type Model struct {
 	Template *template.Template
 }
 
+// Capabilities returns the capabilities that the model supports
+func (m *Model) Capabilities() []model.Capability {
+	capabilities := []model.Capability{}
+
+	// Check for completion capability
+	r, err := os.Open(m.ModelPath)
+	if err == nil {
+		defer r.Close()
+
+		f, _, err := ggml.Decode(r, 0)
+		if err == nil {
+			if _, ok := f.KV()[fmt.Sprintf("%s.pooling_type", f.KV().Architecture())]; ok {
+				capabilities = append(capabilities, model.CapabilityEmbedding)
+			} else {
+				capabilities = append(capabilities, model.CapabilityCompletion)
+			}
+			if _, ok := f.KV()[fmt.Sprintf("%s.vision.block_count", f.KV().Architecture())]; ok {
+				capabilities = append(capabilities, model.CapabilityVision)
+			}
+		} else {
+			slog.Error("couldn't decode ggml", "error", err)
+		}
+	} else {
+		slog.Error("couldn't open model file", "error", err)
+	}
+
+	if m.Template == nil {
+		return capabilities
+	}
+
+	// Check for tools capability
+	if slices.Contains(m.Template.Vars(), "tools") {
+		capabilities = append(capabilities, model.CapabilityTools)
+	}
+
+	// Check for insert capability
+	if slices.Contains(m.Template.Vars(), "suffix") {
+		capabilities = append(capabilities, model.CapabilityInsert)
+	}
+
+	return capabilities
+}
+
 // CheckCapabilities checks if the model has the specified capabilities returning an error describing
 // any missing or unknown capabilities
-func (m *Model) CheckCapabilities(caps ...Capability) error {
+func (m *Model) CheckCapabilities(want ...model.Capability) error {
+	available := m.Capabilities()
 	var errs []error
-	for _, cap := range caps {
-		switch cap {
-		case CapabilityCompletion:
-			r, err := os.Open(m.ModelPath)
-			if err != nil {
-				slog.Error("couldn't open model file", "error", err)
-				continue
-			}
-			defer r.Close()
 
-			// TODO(mxyng): decode the GGML into model to avoid doing this multiple times
-			f, _, err := ggml.Decode(r, 0)
-			if err != nil {
-				slog.Error("couldn't decode ggml", "error", err)
-				continue
-			}
+	// Map capabilities to their corresponding error
+	capToErr := map[model.Capability]error{
+		model.CapabilityCompletion: errCapabilityCompletion,
+		model.CapabilityTools:      errCapabilityTools,
+		model.CapabilityInsert:     errCapabilityInsert,
+		model.CapabilityVision:     errCapabilityVision,
+		model.CapabilityEmbedding:  errCapabilityEmbedding,
+	}
 
-			if _, ok := f.KV()[fmt.Sprintf("%s.pooling_type", f.KV().Architecture())]; ok {
-				errs = append(errs, errCapabilityCompletion)
-			}
-		case CapabilityTools:
-			if !slices.Contains(m.Template.Vars(), "tools") {
-				errs = append(errs, errCapabilityTools)
-			}
-		case CapabilityInsert:
-			vars := m.Template.Vars()
-			if !slices.Contains(vars, "suffix") {
-				errs = append(errs, errCapabilityInsert)
-			}
-		default:
+	for _, cap := range want {
+		err, ok := capToErr[cap]
+		if !ok {
 			slog.Error("unknown capability", "capability", cap)
 			return fmt.Errorf("unknown capability: %s", cap)
 		}
+
+		if !slices.Contains(available, cap) {
+			errs = append(errs, err)
+		}
 	}
 
-	if err := errors.Join(errs...); err != nil {
+	if len(errs) > 0 {
 		return fmt.Errorf("%w %w", errCapabilities, errors.Join(errs...))
 	}
 
diff --git a/server/images_test.go b/server/images_test.go
new file mode 100644
index 00000000..22e5b7e6
--- /dev/null
+++ b/server/images_test.go
@@ -0,0 +1,360 @@
+package server
+
+import (
+	"bytes"
+	"encoding/binary"
+	"os"
+	"path/filepath"
+	"strings"
+	"testing"
+
+	"github.com/ollama/ollama/template"
+	"github.com/ollama/ollama/types/model"
+)
+
+// Constants for GGUF magic bytes and version
+var (
+	ggufMagic = []byte{0x47, 0x47, 0x55, 0x46} // "GGUF"
+	ggufVer   = uint32(3)                      // Version 3
+)
+
+// Helper function to create mock GGUF data
+func createMockGGUFData(architecture string, vision bool) []byte {
+	var buf bytes.Buffer
+
+	// Write GGUF header
+	buf.Write(ggufMagic)
+	binary.Write(&buf, binary.LittleEndian, ggufVer)
+
+	// Write tensor count (0 for our test)
+	var numTensors uint64 = 0
+	binary.Write(&buf, binary.LittleEndian, numTensors)
+
+	// Calculate number of metadata entries
+	numMetaEntries := uint64(1) // architecture entry
+	if vision {
+		numMetaEntries++
+	}
+	// Add embedding entry if architecture is "bert"
+	if architecture == "bert" {
+		numMetaEntries++
+	}
+	binary.Write(&buf, binary.LittleEndian, numMetaEntries)
+
+	// Write architecture metadata
+	archKey := "general.architecture"
+	keyLen := uint64(len(archKey))
+	binary.Write(&buf, binary.LittleEndian, keyLen)
+	buf.WriteString(archKey)
+
+	// String type (8)
+	var strType uint32 = 8
+	binary.Write(&buf, binary.LittleEndian, strType)
+
+	// String length
+	strLen := uint64(len(architecture))
+	binary.Write(&buf, binary.LittleEndian, strLen)
+	buf.WriteString(architecture)
+
+	if vision {
+		visionKey := architecture + ".vision.block_count"
+		keyLen = uint64(len(visionKey))
+		binary.Write(&buf, binary.LittleEndian, keyLen)
+		buf.WriteString(visionKey)
+
+		// uint32 type (4)
+		var uint32Type uint32 = 4
+		binary.Write(&buf, binary.LittleEndian, uint32Type)
+
+		// uint32 value (1)
+		var countVal uint32 = 1
+		binary.Write(&buf, binary.LittleEndian, countVal)
+	}
+	// Write embedding metadata if architecture is "bert"
+	if architecture == "bert" {
+		poolKey := architecture + ".pooling_type"
+		keyLen = uint64(len(poolKey))
+		binary.Write(&buf, binary.LittleEndian, keyLen)
+		buf.WriteString(poolKey)
+
+		// uint32 type (4)
+		var uint32Type uint32 = 4
+		binary.Write(&buf, binary.LittleEndian, uint32Type)
+
+		// uint32 value (1)
+		var poolingVal uint32 = 1
+		binary.Write(&buf, binary.LittleEndian, poolingVal)
+	}
+
+	return buf.Bytes()
+}
+
+func TestModelCapabilities(t *testing.T) {
+	// Create a temporary directory for test files
+	tempDir, err := os.MkdirTemp("", "model_capabilities_test")
+	if err != nil {
+		t.Fatalf("Failed to create temp directory: %v", err)
+	}
+	defer os.RemoveAll(tempDir)
+
+	// Create different types of mock model files
+	completionModelPath := filepath.Join(tempDir, "model.bin")
+	visionModelPath := filepath.Join(tempDir, "vision_model.bin")
+	embeddingModelPath := filepath.Join(tempDir, "embedding_model.bin")
+	// Create a simple model file for tests that don't depend on GGUF content
+	simpleModelPath := filepath.Join(tempDir, "simple_model.bin")
+
+	err = os.WriteFile(completionModelPath, createMockGGUFData("llama", false), 0o644)
+	if err != nil {
+		t.Fatalf("Failed to create completion model file: %v", err)
+	}
+	err = os.WriteFile(visionModelPath, createMockGGUFData("llama", true), 0o644)
+	if err != nil {
+		t.Fatalf("Failed to create completion model file: %v", err)
+	}
+	err = os.WriteFile(embeddingModelPath, createMockGGUFData("bert", false), 0o644)
+	if err != nil {
+		t.Fatalf("Failed to create embedding model file: %v", err)
+	}
+	err = os.WriteFile(simpleModelPath, []byte("dummy model data"), 0o644)
+	if err != nil {
+		t.Fatalf("Failed to create simple model file: %v", err)
+	}
+
+	toolsInsertTemplate, err := template.Parse("{{ .prompt }}{{ if .tools }}{{ .tools }}{{ end }}{{ if .suffix }}{{ .suffix }}{{ end }}")
+	if err != nil {
+		t.Fatalf("Failed to parse template: %v", err)
+	}
+	chatTemplate, err := template.Parse("{{ .prompt }}")
+	if err != nil {
+		t.Fatalf("Failed to parse template: %v", err)
+	}
+	toolsTemplate, err := template.Parse("{{ .prompt }}{{ if .tools }}{{ .tools }}{{ end }}")
+	if err != nil {
+		t.Fatalf("Failed to parse template: %v", err)
+	}
+
+	testModels := []struct {
+		name         string
+		model        Model
+		expectedCaps []model.Capability
+	}{
+		{
+			name: "model with completion capability",
+			model: Model{
+				ModelPath: completionModelPath,
+				Template:  chatTemplate,
+			},
+			expectedCaps: []model.Capability{model.CapabilityCompletion},
+		},
+
+		{
+			name: "model with completion, tools, and insert capability",
+			model: Model{
+				ModelPath: completionModelPath,
+				Template:  toolsInsertTemplate,
+			},
+			expectedCaps: []model.Capability{model.CapabilityCompletion, model.CapabilityTools, model.CapabilityInsert},
+		},
+		{
+			name: "model with tools and insert capability",
+			model: Model{
+				ModelPath: simpleModelPath,
+				Template:  toolsInsertTemplate,
+			},
+			expectedCaps: []model.Capability{model.CapabilityTools, model.CapabilityInsert},
+		},
+		{
+			name: "model with tools capability",
+			model: Model{
+				ModelPath: simpleModelPath,
+				Template:  toolsTemplate,
+			},
+			expectedCaps: []model.Capability{model.CapabilityTools},
+		},
+		{
+			name: "model with vision capability",
+			model: Model{
+				ModelPath: visionModelPath,
+				Template:  chatTemplate,
+			},
+			expectedCaps: []model.Capability{model.CapabilityCompletion, model.CapabilityVision},
+		},
+		{
+			name: "model with vision, tools, and insert capability",
+			model: Model{
+				ModelPath: visionModelPath,
+				Template:  toolsInsertTemplate,
+			},
+			expectedCaps: []model.Capability{model.CapabilityCompletion, model.CapabilityVision, model.CapabilityTools, model.CapabilityInsert},
+		},
+		{
+			name: "model with embedding capability",
+			model: Model{
+				ModelPath: embeddingModelPath,
+				Template:  chatTemplate,
+			},
+			expectedCaps: []model.Capability{model.CapabilityEmbedding},
+		},
+	}
+
+	// compare two slices of model.Capability regardless of order
+	compareCapabilities := func(a, b []model.Capability) bool {
+		if len(a) != len(b) {
+			return false
+		}
+
+		aCount := make(map[model.Capability]int)
+		for _, cap := range a {
+			aCount[cap]++
+		}
+
+		bCount := make(map[model.Capability]int)
+		for _, cap := range b {
+			bCount[cap]++
+		}
+
+		for cap, count := range aCount {
+			if bCount[cap] != count {
+				return false
+			}
+		}
+
+		return true
+	}
+
+	for _, tt := range testModels {
+		t.Run(tt.name, func(t *testing.T) {
+			// Test Capabilities method
+			caps := tt.model.Capabilities()
+			if !compareCapabilities(caps, tt.expectedCaps) {
+				t.Errorf("Expected capabilities %v, got %v", tt.expectedCaps, caps)
+			}
+		})
+	}
+}
+
+func TestModelCheckCapabilities(t *testing.T) {
+	// Create a temporary directory for test files
+	tempDir, err := os.MkdirTemp("", "model_check_capabilities_test")
+	if err != nil {
+		t.Fatalf("Failed to create temp directory: %v", err)
+	}
+	defer os.RemoveAll(tempDir)
+
+	visionModelPath := filepath.Join(tempDir, "vision_model.bin")
+	simpleModelPath := filepath.Join(tempDir, "model.bin")
+	embeddingModelPath := filepath.Join(tempDir, "embedding_model.bin")
+
+	err = os.WriteFile(simpleModelPath, []byte("dummy model data"), 0o644)
+	if err != nil {
+		t.Fatalf("Failed to create simple model file: %v", err)
+	}
+	err = os.WriteFile(visionModelPath, createMockGGUFData("llama", true), 0o644)
+	if err != nil {
+		t.Fatalf("Failed to create vision model file: %v", err)
+	}
+	err = os.WriteFile(embeddingModelPath, createMockGGUFData("bert", false), 0o644)
+	if err != nil {
+		t.Fatalf("Failed to create embedding model file: %v", err)
+	}
+
+	toolsInsertTemplate, err := template.Parse("{{ .prompt }}{{ if .tools }}{{ .tools }}{{ end }}{{ if .suffix }}{{ .suffix }}{{ end }}")
+	if err != nil {
+		t.Fatalf("Failed to parse template: %v", err)
+	}
+	chatTemplate, err := template.Parse("{{ .prompt }}")
+	if err != nil {
+		t.Fatalf("Failed to parse template: %v", err)
+	}
+	toolsTemplate, err := template.Parse("{{ .prompt }}{{ if .tools }}{{ .tools }}{{ end }}")
+	if err != nil {
+		t.Fatalf("Failed to parse template: %v", err)
+	}
+
+	tests := []struct {
+		name           string
+		model          Model
+		checkCaps      []model.Capability
+		expectedErrMsg string
+	}{
+		{
+			name: "completion model without tools capability",
+			model: Model{
+				ModelPath: simpleModelPath,
+				Template:  chatTemplate,
+			},
+			checkCaps:      []model.Capability{model.CapabilityTools},
+			expectedErrMsg: "does not support tools",
+		},
+		{
+			name: "model with all needed capabilities",
+			model: Model{
+				ModelPath: simpleModelPath,
+				Template:  toolsInsertTemplate,
+			},
+			checkCaps: []model.Capability{model.CapabilityTools, model.CapabilityInsert},
+		},
+		{
+			name: "model missing insert capability",
+			model: Model{
+				ModelPath: simpleModelPath,
+				Template:  toolsTemplate,
+			},
+			checkCaps:      []model.Capability{model.CapabilityInsert},
+			expectedErrMsg: "does not support insert",
+		},
+		{
+			name: "model missing vision capability",
+			model: Model{
+				ModelPath: simpleModelPath,
+				Template:  toolsTemplate,
+			},
+			checkCaps:      []model.Capability{model.CapabilityVision},
+			expectedErrMsg: "does not support vision",
+		},
+		{
+			name: "model with vision capability",
+			model: Model{
+				ModelPath: visionModelPath,
+				Template:  chatTemplate,
+			},
+			checkCaps: []model.Capability{model.CapabilityVision},
+		},
+		{
+			name: "model with embedding capability",
+			model: Model{
+				ModelPath: embeddingModelPath,
+				Template:  chatTemplate,
+			},
+			checkCaps: []model.Capability{model.CapabilityEmbedding},
+		},
+		{
+			name: "unknown capability",
+			model: Model{
+				ModelPath: simpleModelPath,
+				Template:  chatTemplate,
+			},
+			checkCaps:      []model.Capability{"unknown"},
+			expectedErrMsg: "unknown capability",
+		},
+	}
+
+	for _, tt := range tests {
+		t.Run(tt.name, func(t *testing.T) {
+			// Test CheckCapabilities method
+			err := tt.model.CheckCapabilities(tt.checkCaps...)
+			if tt.expectedErrMsg == "" {
+				if err != nil {
+					t.Errorf("Expected no error, got: %v", err)
+				}
+			} else {
+				if err == nil {
+					t.Errorf("Expected error containing %q, got nil", tt.expectedErrMsg)
+				} else if !strings.Contains(err.Error(), tt.expectedErrMsg) {
+					t.Errorf("Expected error containing %q, got: %v", tt.expectedErrMsg, err)
+				}
+			}
+		})
+	}
+}
diff --git a/server/routes.go b/server/routes.go
index 92336af0..95e49820 100644
--- a/server/routes.go
+++ b/server/routes.go
@@ -87,7 +87,7 @@ func modelOptions(model *Model, requestOpts map[string]interface{}) (api.Options
 
 // scheduleRunner schedules a runner after validating inputs such as capabilities and model options.
 // It returns the allocated runner, model instance, and consolidated options if successful and error otherwise.
-func (s *Server) scheduleRunner(ctx context.Context, name string, caps []Capability, requestOpts map[string]any, keepAlive *api.Duration) (llm.LlamaServer, *Model, *api.Options, error) {
+func (s *Server) scheduleRunner(ctx context.Context, name string, caps []model.Capability, requestOpts map[string]any, keepAlive *api.Duration) (llm.LlamaServer, *Model, *api.Options, error) {
 	if name == "" {
 		return nil, nil, nil, fmt.Errorf("model %w", errRequired)
 	}
@@ -144,7 +144,7 @@ func (s *Server) GenerateHandler(c *gin.Context) {
 		return
 	}
 
-	model, err := GetModel(name.String())
+	m, err := GetModel(name.String())
 	if err != nil {
 		switch {
 		case errors.Is(err, fs.ErrNotExist):
@@ -159,7 +159,7 @@ func (s *Server) GenerateHandler(c *gin.Context) {
 
 	// expire the runner
 	if req.Prompt == "" && req.KeepAlive != nil && int(req.KeepAlive.Seconds()) == 0 {
-		s.sched.expireRunner(model)
+		s.sched.expireRunner(m)
 
 		c.JSON(http.StatusOK, api.GenerateResponse{
 			Model:      req.Model,
@@ -176,9 +176,9 @@ func (s *Server) GenerateHandler(c *gin.Context) {
 		return
 	}
 
-	caps := []Capability{CapabilityCompletion}
+	caps := []model.Capability{model.CapabilityCompletion}
 	if req.Suffix != "" {
-		caps = append(caps, CapabilityInsert)
+		caps = append(caps, model.CapabilityInsert)
 	}
 
 	r, m, opts, err := s.scheduleRunner(c.Request.Context(), name.String(), caps, req.Options, req.KeepAlive)
@@ -203,7 +203,7 @@ func (s *Server) GenerateHandler(c *gin.Context) {
 		return
 	}
 
-	isMllama := checkMllamaModelFamily(model)
+	isMllama := checkMllamaModelFamily(m)
 	if isMllama && len(req.Images) > 1 {
 		c.AbortWithStatusJSON(http.StatusBadRequest, gin.H{"error": "this model only supports one image: more than one image sent"})
 		return
@@ -211,7 +211,7 @@ func (s *Server) GenerateHandler(c *gin.Context) {
 
 	images := make([]llm.ImageData, len(req.Images))
 	for i := range req.Images {
-		if isMllama && len(model.ProjectorPaths) > 0 {
+		if isMllama && len(m.ProjectorPaths) > 0 {
 			data, opts, err := mllama.Preprocess(bytes.NewReader(req.Images[i]))
 			if err != nil {
 				c.AbortWithStatusJSON(http.StatusInternalServerError, gin.H{"error": "error processing image"})
@@ -422,7 +422,7 @@ func (s *Server) EmbedHandler(c *gin.Context) {
 		return
 	}
 
-	r, m, opts, err := s.scheduleRunner(c.Request.Context(), name.String(), []Capability{}, req.Options, req.KeepAlive)
+	r, m, opts, err := s.scheduleRunner(c.Request.Context(), name.String(), []model.Capability{}, req.Options, req.KeepAlive)
 	if err != nil {
 		handleScheduleError(c, req.Model, err)
 		return
@@ -530,7 +530,7 @@ func (s *Server) EmbeddingsHandler(c *gin.Context) {
 		return
 	}
 
-	r, _, _, err := s.scheduleRunner(c.Request.Context(), name.String(), []Capability{}, req.Options, req.KeepAlive)
+	r, _, _, err := s.scheduleRunner(c.Request.Context(), name.String(), []model.Capability{}, req.Options, req.KeepAlive)
 	if err != nil {
 		handleScheduleError(c, req.Model, err)
 		return
@@ -813,12 +813,13 @@ func GetModelInfo(req api.ShowRequest) (*api.ShowResponse, error) {
 	}
 
 	resp := &api.ShowResponse{
-		License:    strings.Join(m.License, "\n"),
-		System:     m.System,
-		Template:   m.Template.String(),
-		Details:    modelDetails,
-		Messages:   msgs,
-		ModifiedAt: manifest.fi.ModTime(),
+		License:      strings.Join(m.License, "\n"),
+		System:       m.System,
+		Template:     m.Template.String(),
+		Details:      modelDetails,
+		Messages:     msgs,
+		Capabilities: m.Capabilities(),
+		ModifiedAt:   manifest.fi.ModTime(),
 	}
 
 	var params []string
@@ -1468,9 +1469,9 @@ func (s *Server) ChatHandler(c *gin.Context) {
 		return
 	}
 
-	caps := []Capability{CapabilityCompletion}
+	caps := []model.Capability{model.CapabilityCompletion}
 	if len(req.Tools) > 0 {
-		caps = append(caps, CapabilityTools)
+		caps = append(caps, model.CapabilityTools)
 	}
 
 	name := model.ParseName(req.Model)
diff --git a/server/sched.go b/server/sched.go
index 9126c296..e6cefa5a 100644
--- a/server/sched.go
+++ b/server/sched.go
@@ -20,6 +20,7 @@ import (
 	"github.com/ollama/ollama/format"
 	"github.com/ollama/ollama/fs/ggml"
 	"github.com/ollama/ollama/llm"
+	"github.com/ollama/ollama/types/model"
 )
 
 type LlmRequest struct {
@@ -195,7 +196,7 @@ func (s *Scheduler) processPending(ctx context.Context) {
 					}
 
 					// Embedding models should always be loaded with parallel=1
-					if pending.model.CheckCapabilities(CapabilityCompletion) != nil {
+					if pending.model.CheckCapabilities(model.CapabilityCompletion) != nil {
 						numParallel = 1
 					}
 
diff --git a/types/model/capability.go b/types/model/capability.go
new file mode 100644
index 00000000..fb868940
--- /dev/null
+++ b/types/model/capability.go
@@ -0,0 +1,15 @@
+package model
+
+type Capability string
+
+const (
+	CapabilityCompletion = Capability("completion")
+	CapabilityTools      = Capability("tools")
+	CapabilityInsert     = Capability("insert")
+	CapabilityVision     = Capability("vision")
+	CapabilityEmbedding  = Capability("embedding")
+)
+
+func (c Capability) String() string {
+	return string(c)
+}

From 4e415029b30b2dc8a666491fdbe6254536e5d810 Mon Sep 17 00:00:00 2001
From: IsAurora6 <85173010+IsAurora6@users.noreply.github.com>
Date: Wed, 2 Apr 2025 16:27:16 +0800
Subject: [PATCH 149/157] readme: add Casibase to community integrations
 (#10057)

---
 README.md | 1 +
 1 file changed, 1 insertion(+)

diff --git a/README.md b/README.md
index aca00a87..e472fbc5 100644
--- a/README.md
+++ b/README.md
@@ -325,6 +325,7 @@ See the [API documentation](./docs/api.md) for all endpoints.
 - [RWKV-Runner](https://github.com/josStorer/RWKV-Runner) (RWKV offline LLM deployment tool, also usable as a client for ChatGPT and Ollama)
 - [Ollama Grid Search](https://github.com/dezoito/ollama-grid-search) (app to evaluate and compare models)
 - [Olpaka](https://github.com/Otacon/olpaka) (User-friendly Flutter Web App for Ollama)
+- [Casibase](https://casibase.org) (An open source AI knowledge base and dialogue system combining the latest RAG, SSO, ollama support and multiple large language models.)
 - [OllamaSpring](https://github.com/CrazyNeil/OllamaSpring) (Ollama Client for macOS)
 - [LLocal.in](https://github.com/kartikm7/llocal) (Easy to use Electron Desktop Client for Ollama)
 - [Shinkai Desktop](https://github.com/dcSpark/shinkai-apps) (Two click install Local AI using Ollama + Files + RAG)

From 9876c9faa41c7dd7143fa47727520d353559f81b Mon Sep 17 00:00:00 2001
From: Bruce MacDonald <brucewmacdonald@gmail.com>
Date: Wed, 2 Apr 2025 09:44:27 -0700
Subject: [PATCH 150/157] chore(all): replace instances of interface with any
 (#10067)

Both interface{} and any (which is just an alias for interface{} introduced in Go 1.18) represent the empty interface that all types satisfy.
---
 api/types.go                                  | 22 +++++++++----------
 api/types_test.go                             |  2 +-
 benchmark/server_benchmark_test.go            |  4 ++--
 cmd/cmd.go                                    |  4 ++--
 .../sentencepiece/sentencepiece_model.pb.go   | 14 ++++++------
 discover/cpu_common.go                        |  2 +-
 format/time_test.go                           |  2 +-
 integration/basic_test.go                     |  8 +++----
 integration/concurrency_test.go               |  4 ++--
 integration/context_test.go                   |  4 ++--
 integration/llm_image_test.go                 |  6 ++---
 integration/llm_test.go                       |  4 ++--
 integration/max_queue_test.go                 |  2 +-
 integration/utils_test.go                     | 10 ++++-----
 openai/openai.go                              | 10 ++++-----
 openai/openai_test.go                         |  2 +-
 server/images.go                              |  2 +-
 server/routes.go                              |  6 ++---
 server/sched.go                               |  8 +++----
 19 files changed, 58 insertions(+), 58 deletions(-)

diff --git a/api/types.go b/api/types.go
index b4a65fe5..a70fb120 100644
--- a/api/types.go
+++ b/api/types.go
@@ -82,7 +82,7 @@ type GenerateRequest struct {
 
 	// Options lists model-specific options. For example, temperature can be
 	// set through this field, if the model supports it.
-	Options map[string]interface{} `json:"options"`
+	Options map[string]any `json:"options"`
 }
 
 // ChatRequest describes a request sent by [Client.Chat].
@@ -107,7 +107,7 @@ type ChatRequest struct {
 	Tools `json:"tools,omitempty"`
 
 	// Options lists model-specific options.
-	Options map[string]interface{} `json:"options"`
+	Options map[string]any `json:"options"`
 }
 
 type Tools []Tool
@@ -261,7 +261,7 @@ type EmbedRequest struct {
 	Truncate *bool `json:"truncate,omitempty"`
 
 	// Options lists model-specific options.
-	Options map[string]interface{} `json:"options"`
+	Options map[string]any `json:"options"`
 }
 
 // EmbedResponse is the response from [Client.Embed].
@@ -287,7 +287,7 @@ type EmbeddingRequest struct {
 	KeepAlive *Duration `json:"keep_alive,omitempty"`
 
 	// Options lists model-specific options.
-	Options map[string]interface{} `json:"options"`
+	Options map[string]any `json:"options"`
 }
 
 // EmbeddingResponse is the response from [Client.Embeddings].
@@ -333,7 +333,7 @@ type ShowRequest struct {
 	Template string `json:"template"`
 	Verbose  bool   `json:"verbose"`
 
-	Options map[string]interface{} `json:"options"`
+	Options map[string]any `json:"options"`
 
 	// Deprecated: set the model name with Model instead
 	Name string `json:"name"`
@@ -505,7 +505,7 @@ func (m *Metrics) Summary() {
 	}
 }
 
-func (opts *Options) FromMap(m map[string]interface{}) error {
+func (opts *Options) FromMap(m map[string]any) error {
 	valueOpts := reflect.ValueOf(opts).Elem() // names of the fields in the options struct
 	typeOpts := reflect.TypeOf(opts).Elem()   // types of the fields in the options struct
 
@@ -562,12 +562,12 @@ func (opts *Options) FromMap(m map[string]interface{}) error {
 				}
 				field.SetString(val)
 			case reflect.Slice:
-				// JSON unmarshals to []interface{}, not []string
-				val, ok := val.([]interface{})
+				// JSON unmarshals to []any, not []string
+				val, ok := val.([]any)
 				if !ok {
 					return fmt.Errorf("option %q must be of type array", key)
 				}
-				// convert []interface{} to []string
+				// convert []any to []string
 				slice := make([]string, len(val))
 				for i, item := range val {
 					str, ok := item.(string)
@@ -674,7 +674,7 @@ func (d *Duration) UnmarshalJSON(b []byte) (err error) {
 }
 
 // FormatParams converts specified parameter options to their correct types
-func FormatParams(params map[string][]string) (map[string]interface{}, error) {
+func FormatParams(params map[string][]string) (map[string]any, error) {
 	opts := Options{}
 	valueOpts := reflect.ValueOf(&opts).Elem() // names of the fields in the options struct
 	typeOpts := reflect.TypeOf(opts)           // types of the fields in the options struct
@@ -688,7 +688,7 @@ func FormatParams(params map[string][]string) (map[string]interface{}, error) {
 		}
 	}
 
-	out := make(map[string]interface{})
+	out := make(map[string]any)
 	// iterate params and set values based on json struct tags
 	for key, vals := range params {
 		if opt, ok := jsonOpts[key]; !ok {
diff --git a/api/types_test.go b/api/types_test.go
index a9de5a9a..b28d4249 100644
--- a/api/types_test.go
+++ b/api/types_test.go
@@ -134,7 +134,7 @@ func TestUseMmapParsingFromJSON(t *testing.T) {
 
 	for _, test := range tests {
 		t.Run(test.name, func(t *testing.T) {
-			var oMap map[string]interface{}
+			var oMap map[string]any
 			err := json.Unmarshal([]byte(test.req), &oMap)
 			require.NoError(t, err)
 			opts := DefaultOptions()
diff --git a/benchmark/server_benchmark_test.go b/benchmark/server_benchmark_test.go
index b27aa630..672b8b17 100644
--- a/benchmark/server_benchmark_test.go
+++ b/benchmark/server_benchmark_test.go
@@ -92,7 +92,7 @@ func BenchmarkColdStart(b *testing.B) {
 				req := &api.GenerateRequest{
 					Model:   m,
 					Prompt:  tt.prompt,
-					Options: map[string]interface{}{"num_predict": tt.maxTokens, "temperature": 0.1},
+					Options: map[string]any{"num_predict": tt.maxTokens, "temperature": 0.1},
 				}
 
 				runGenerateBenchmark(b, ctx, client, req)
@@ -155,7 +155,7 @@ func warmup(client *api.Client, model string, prompt string, b *testing.B) {
 			&api.GenerateRequest{
 				Model:   model,
 				Prompt:  prompt,
-				Options: map[string]interface{}{"num_predict": 50, "temperature": 0.1},
+				Options: map[string]any{"num_predict": 50, "temperature": 0.1},
 			},
 			func(api.GenerateResponse) error { return nil },
 		)
diff --git a/cmd/cmd.go b/cmd/cmd.go
index 36d7e6cf..84727862 100644
--- a/cmd/cmd.go
+++ b/cmd/cmd.go
@@ -268,7 +268,7 @@ func RunHandler(cmd *cobra.Command, args []string) error {
 	opts := runOptions{
 		Model:    args[0],
 		WordWrap: os.Getenv("TERM") == "xterm-256color",
-		Options:  map[string]interface{}{},
+		Options:  map[string]any{},
 	}
 
 	format, err := cmd.Flags().GetString("format")
@@ -852,7 +852,7 @@ type runOptions struct {
 	Format      string
 	System      string
 	Images      []api.ImageData
-	Options     map[string]interface{}
+	Options     map[string]any
 	MultiModal  bool
 	KeepAlive   *api.Duration
 }
diff --git a/convert/sentencepiece/sentencepiece_model.pb.go b/convert/sentencepiece/sentencepiece_model.pb.go
index 6bf66891..76d136e8 100644
--- a/convert/sentencepiece/sentencepiece_model.pb.go
+++ b/convert/sentencepiece/sentencepiece_model.pb.go
@@ -1360,7 +1360,7 @@ func file_sentencepiece_model_proto_rawDescGZIP() []byte {
 
 var file_sentencepiece_model_proto_enumTypes = make([]protoimpl.EnumInfo, 2)
 var file_sentencepiece_model_proto_msgTypes = make([]protoimpl.MessageInfo, 6)
-var file_sentencepiece_model_proto_goTypes = []interface{}{
+var file_sentencepiece_model_proto_goTypes = []any{
 	(TrainerSpec_ModelType)(0),         // 0: sentencepiece.TrainerSpec.ModelType
 	(ModelProto_SentencePiece_Type)(0), // 1: sentencepiece.ModelProto.SentencePiece.Type
 	(*TrainerSpec)(nil),                // 2: sentencepiece.TrainerSpec
@@ -1392,7 +1392,7 @@ func file_sentencepiece_model_proto_init() {
 		return
 	}
 	if !protoimpl.UnsafeEnabled {
-		file_sentencepiece_model_proto_msgTypes[0].Exporter = func(v interface{}, i int) interface{} {
+		file_sentencepiece_model_proto_msgTypes[0].Exporter = func(v any, i int) any {
 			switch v := v.(*TrainerSpec); i {
 			case 0:
 				return &v.state
@@ -1406,7 +1406,7 @@ func file_sentencepiece_model_proto_init() {
 				return nil
 			}
 		}
-		file_sentencepiece_model_proto_msgTypes[1].Exporter = func(v interface{}, i int) interface{} {
+		file_sentencepiece_model_proto_msgTypes[1].Exporter = func(v any, i int) any {
 			switch v := v.(*NormalizerSpec); i {
 			case 0:
 				return &v.state
@@ -1420,7 +1420,7 @@ func file_sentencepiece_model_proto_init() {
 				return nil
 			}
 		}
-		file_sentencepiece_model_proto_msgTypes[2].Exporter = func(v interface{}, i int) interface{} {
+		file_sentencepiece_model_proto_msgTypes[2].Exporter = func(v any, i int) any {
 			switch v := v.(*SelfTestData); i {
 			case 0:
 				return &v.state
@@ -1434,7 +1434,7 @@ func file_sentencepiece_model_proto_init() {
 				return nil
 			}
 		}
-		file_sentencepiece_model_proto_msgTypes[3].Exporter = func(v interface{}, i int) interface{} {
+		file_sentencepiece_model_proto_msgTypes[3].Exporter = func(v any, i int) any {
 			switch v := v.(*ModelProto); i {
 			case 0:
 				return &v.state
@@ -1448,7 +1448,7 @@ func file_sentencepiece_model_proto_init() {
 				return nil
 			}
 		}
-		file_sentencepiece_model_proto_msgTypes[4].Exporter = func(v interface{}, i int) interface{} {
+		file_sentencepiece_model_proto_msgTypes[4].Exporter = func(v any, i int) any {
 			switch v := v.(*SelfTestData_Sample); i {
 			case 0:
 				return &v.state
@@ -1460,7 +1460,7 @@ func file_sentencepiece_model_proto_init() {
 				return nil
 			}
 		}
-		file_sentencepiece_model_proto_msgTypes[5].Exporter = func(v interface{}, i int) interface{} {
+		file_sentencepiece_model_proto_msgTypes[5].Exporter = func(v any, i int) any {
 			switch v := v.(*ModelProto_SentencePiece); i {
 			case 0:
 				return &v.state
diff --git a/discover/cpu_common.go b/discover/cpu_common.go
index 242e4879..2b9f7292 100644
--- a/discover/cpu_common.go
+++ b/discover/cpu_common.go
@@ -12,7 +12,7 @@ func IsNUMA() bool {
 		// numa support in llama.cpp is linux only
 		return false
 	}
-	ids := map[string]interface{}{}
+	ids := map[string]any{}
 	packageIds, _ := filepath.Glob("/sys/devices/system/cpu/cpu*/topology/physical_package_id")
 	for _, packageId := range packageIds {
 		id, err := os.ReadFile(packageId)
diff --git a/format/time_test.go b/format/time_test.go
index bd0ba9a8..d0f8934d 100644
--- a/format/time_test.go
+++ b/format/time_test.go
@@ -5,7 +5,7 @@ import (
 	"time"
 )
 
-func assertEqual(t *testing.T, a interface{}, b interface{}) {
+func assertEqual(t *testing.T, a any, b any) {
 	if a != b {
 		t.Errorf("Assert failed, expected %v, got %v", b, a)
 	}
diff --git a/integration/basic_test.go b/integration/basic_test.go
index 88d3530e..09e62259 100644
--- a/integration/basic_test.go
+++ b/integration/basic_test.go
@@ -22,7 +22,7 @@ func TestOrcaMiniBlueSky(t *testing.T) {
 		Model:  "orca-mini",
 		Prompt: "why is the sky blue?",
 		Stream: &stream,
-		Options: map[string]interface{}{
+		Options: map[string]any{
 			"temperature": 0,
 			"seed":        123,
 		},
@@ -39,7 +39,7 @@ func TestUnicode(t *testing.T) {
 		Model:  "deepseek-coder-v2:16b-lite-instruct-q2_K",
 		Prompt: "天空为什么是蓝色的?",
 		Stream: &stream,
-		Options: map[string]interface{}{
+		Options: map[string]any{
 			"temperature": 0,
 			"seed":        123,
 			// Workaround deepseek context shifting bug
@@ -61,7 +61,7 @@ func TestExtendedUnicodeOutput(t *testing.T) {
 		Model:  "gemma2:2b",
 		Prompt: "Output some smily face emoji",
 		Stream: &stream,
-		Options: map[string]interface{}{
+		Options: map[string]any{
 			"temperature": 0,
 			"seed":        123,
 		},
@@ -96,7 +96,7 @@ func TestUnicodeModelDir(t *testing.T) {
 		Model:  "orca-mini",
 		Prompt: "why is the sky blue?",
 		Stream: &stream,
-		Options: map[string]interface{}{
+		Options: map[string]any{
 			"temperature": 0,
 			"seed":        123,
 		},
diff --git a/integration/concurrency_test.go b/integration/concurrency_test.go
index 78e3b5ab..5f7f289e 100644
--- a/integration/concurrency_test.go
+++ b/integration/concurrency_test.go
@@ -25,7 +25,7 @@ func TestMultiModelConcurrency(t *testing.T) {
 				Prompt:    "why is the ocean blue?",
 				Stream:    &stream,
 				KeepAlive: &api.Duration{Duration: 10 * time.Second},
-				Options: map[string]interface{}{
+				Options: map[string]any{
 					"seed":        42,
 					"temperature": 0.0,
 				},
@@ -34,7 +34,7 @@ func TestMultiModelConcurrency(t *testing.T) {
 				Prompt:    "what is the origin of the us thanksgiving holiday?",
 				Stream:    &stream,
 				KeepAlive: &api.Duration{Duration: 10 * time.Second},
-				Options: map[string]interface{}{
+				Options: map[string]any{
 					"seed":        42,
 					"temperature": 0.0,
 				},
diff --git a/integration/context_test.go b/integration/context_test.go
index add41a76..409d913a 100644
--- a/integration/context_test.go
+++ b/integration/context_test.go
@@ -23,7 +23,7 @@ func TestLongInputContext(t *testing.T) {
 		Model:  "llama2",
 		Prompt: "Oh, don’t speak to me of Austria. Perhaps I don’t understand things, but Austria never has wished, and does not wish, for war. She is betraying us! Russia alone must save Europe. Our gracious sovereign recognizes his high vocation and will be true to it. That is the one thing I have faith in! Our good and wonderful sovereign has to perform the noblest role on earth, and he is so virtuous and noble that God will not forsake him. He will fulfill his vocation and crush the hydra of revolution, which has become more terrible than ever in the person of this murderer and villain! We alone must avenge the blood of the just one.... Whom, I ask you, can we rely on?... England with her commercial spirit will not and cannot understand the Emperor Alexander’s loftiness of soul. She has refused to evacuate Malta. She wanted to find, and still seeks, some secret motive in our actions. What answer did Novosíltsev get? None. The English have not understood and cannot understand the self-abnegation of our Emperor who wants nothing for himself, but only desires the good of mankind. And what have they promised? Nothing! And what little they have promised they will not perform! Prussia has always declared that Buonaparte is invincible, and that all Europe is powerless before him.... And I don’t believe a word that Hardenburg says, or Haugwitz either. This famous Prussian neutrality is just a trap. I have faith only in God and the lofty destiny of our adored monarch. He will save Europe! What country is this referring to?",
 		Stream: &stream,
-		Options: map[string]interface{}{
+		Options: map[string]any{
 			"temperature": 0,
 			"seed":        123,
 			"num_ctx":     128,
@@ -50,7 +50,7 @@ func TestContextExhaustion(t *testing.T) {
 		Model:  "llama2",
 		Prompt: "Write me a story with a ton of emojis?",
 		Stream: &stream,
-		Options: map[string]interface{}{
+		Options: map[string]any{
 			"temperature": 0,
 			"seed":        123,
 			"num_ctx":     128,
diff --git a/integration/llm_image_test.go b/integration/llm_image_test.go
index fbbd9d5c..51a16fc7 100644
--- a/integration/llm_image_test.go
+++ b/integration/llm_image_test.go
@@ -19,7 +19,7 @@ func TestIntegrationLlava(t *testing.T) {
 		Model:  "llava:7b",
 		Prompt: "what does the text in this image say?",
 		Stream: &stream,
-		Options: map[string]interface{}{
+		Options: map[string]any{
 			"seed":        42,
 			"temperature": 0.0,
 		},
@@ -47,7 +47,7 @@ func TestIntegrationMllama(t *testing.T) {
 		Model:  "x/llama3.2-vision",
 		Prompt: "what does the text in this image say?",
 		Stream: &stream,
-		Options: map[string]interface{}{
+		Options: map[string]any{
 			"seed":        42,
 			"temperature": 0.0,
 		},
@@ -75,7 +75,7 @@ func TestIntegrationSplitBatch(t *testing.T) {
 		System: "Lorem ipsum dolor sit amet, consectetur adipiscing elit. Sed aliquet, justo in malesuada lobortis, odio ligula volutpat quam, quis faucibus ipsum magna quis sapien. Aliquam in venenatis diam, eu viverra magna. Phasellus imperdiet hendrerit volutpat. Vivamus sem ex, facilisis placerat felis non, dictum elementum est. Phasellus aliquam imperdiet lacus, eget placerat ligula sodales vel. Pellentesque nec auctor mi. Curabitur arcu nisi, faucibus eget nunc id, viverra interdum mi. Curabitur ornare ipsum ex, ac euismod ex aliquam in. Vestibulum id magna at purus accumsan fermentum. Proin scelerisque posuere nunc quis interdum. Maecenas sed mollis nisl. Etiam vitae ipsum interdum, placerat est quis, tincidunt velit. Nullam tempor nibh non lorem volutpat efficitur. Cras laoreet diam imperdiet ipsum auctor bibendum. Suspendisse ultrices urna sed metus sagittis suscipit. Quisque ullamcorper aliquam nibh ut mollis. Aenean dapibus mauris pharetra, venenatis elit ac, hendrerit odio. Cras vestibulum erat tempor, lobortis justo eu, lobortis ipsum. Nam laoreet dapibus sem. Proin vel diam ultrices, elementum ante et, ornare lectus. Proin eu accumsan nisl. Praesent ac ex vitae ipsum vulputate tristique facilisis sit amet lacus. Nullam faucibus magna a pellentesque pretium. Nunc lacinia ullamcorper sollicitudin. Donec vitae accumsan turpis, sed porttitor est. Donec porttitor mi vitae augue faucibus, vel mollis diam tincidunt.",
 		Prompt: "what does the text in this image say?",
 		Stream: &stream,
-		Options: map[string]interface{}{
+		Options: map[string]any{
 			"seed":        42,
 			"temperature": 0.0,
 		},
diff --git a/integration/llm_test.go b/integration/llm_test.go
index 398e0a03..f897fdd9 100644
--- a/integration/llm_test.go
+++ b/integration/llm_test.go
@@ -20,7 +20,7 @@ var (
 			Model:  "orca-mini",
 			Prompt: "why is the ocean blue?",
 			Stream: &stream,
-			Options: map[string]interface{}{
+			Options: map[string]any{
 				"seed":        42,
 				"temperature": 0.0,
 			},
@@ -28,7 +28,7 @@ var (
 			Model:  "orca-mini",
 			Prompt: "what is the origin of the us thanksgiving holiday?",
 			Stream: &stream,
-			Options: map[string]interface{}{
+			Options: map[string]any{
 				"seed":        42,
 				"temperature": 0.0,
 			},
diff --git a/integration/max_queue_test.go b/integration/max_queue_test.go
index 1878d0da..c316aa62 100644
--- a/integration/max_queue_test.go
+++ b/integration/max_queue_test.go
@@ -32,7 +32,7 @@ func TestMaxQueue(t *testing.T) {
 	req := api.GenerateRequest{
 		Model:  "orca-mini",
 		Prompt: "write a long historical fiction story about christopher columbus.  use at least 10 facts from his actual journey",
-		Options: map[string]interface{}{
+		Options: map[string]any{
 			"seed":        42,
 			"temperature": 0.0,
 		},
diff --git a/integration/utils_test.go b/integration/utils_test.go
index e76b63f2..71304cd0 100644
--- a/integration/utils_test.go
+++ b/integration/utils_test.go
@@ -291,7 +291,7 @@ func GenerateRequests() ([]api.GenerateRequest, [][]string) {
 				Prompt:    "why is the ocean blue?",
 				Stream:    &stream,
 				KeepAlive: &api.Duration{Duration: 10 * time.Second},
-				Options: map[string]interface{}{
+				Options: map[string]any{
 					"seed":        42,
 					"temperature": 0.0,
 				},
@@ -300,7 +300,7 @@ func GenerateRequests() ([]api.GenerateRequest, [][]string) {
 				Prompt:    "why is the color of dirt brown?",
 				Stream:    &stream,
 				KeepAlive: &api.Duration{Duration: 10 * time.Second},
-				Options: map[string]interface{}{
+				Options: map[string]any{
 					"seed":        42,
 					"temperature": 0.0,
 				},
@@ -309,7 +309,7 @@ func GenerateRequests() ([]api.GenerateRequest, [][]string) {
 				Prompt:    "what is the origin of the us thanksgiving holiday?",
 				Stream:    &stream,
 				KeepAlive: &api.Duration{Duration: 10 * time.Second},
-				Options: map[string]interface{}{
+				Options: map[string]any{
 					"seed":        42,
 					"temperature": 0.0,
 				},
@@ -318,7 +318,7 @@ func GenerateRequests() ([]api.GenerateRequest, [][]string) {
 				Prompt:    "what is the origin of independence day?",
 				Stream:    &stream,
 				KeepAlive: &api.Duration{Duration: 10 * time.Second},
-				Options: map[string]interface{}{
+				Options: map[string]any{
 					"seed":        42,
 					"temperature": 0.0,
 				},
@@ -327,7 +327,7 @@ func GenerateRequests() ([]api.GenerateRequest, [][]string) {
 				Prompt:    "what is the composition of air?",
 				Stream:    &stream,
 				KeepAlive: &api.Duration{Duration: 10 * time.Second},
-				Options: map[string]interface{}{
+				Options: map[string]any{
 					"seed":        42,
 					"temperature": 0.0,
 				},
diff --git a/openai/openai.go b/openai/openai.go
index 214801fa..012189d2 100644
--- a/openai/openai.go
+++ b/openai/openai.go
@@ -23,10 +23,10 @@ import (
 var finishReasonToolCalls = "tool_calls"
 
 type Error struct {
-	Message string      `json:"message"`
-	Type    string      `json:"type"`
-	Param   interface{} `json:"param"`
-	Code    *string     `json:"code"`
+	Message string  `json:"message"`
+	Type    string  `json:"type"`
+	Param   any     `json:"param"`
+	Code    *string `json:"code"`
 }
 
 type ErrorResponse struct {
@@ -465,7 +465,7 @@ func fromChatRequest(r ChatCompletionRequest) (*api.ChatRequest, error) {
 		}
 	}
 
-	options := make(map[string]interface{})
+	options := make(map[string]any)
 
 	switch stop := r.Stop.(type) {
 	case string:
diff --git a/openai/openai_test.go b/openai/openai_test.go
index d8c821d3..a6acfcac 100644
--- a/openai/openai_test.go
+++ b/openai/openai_test.go
@@ -219,7 +219,7 @@ func TestChatMiddleware(t *testing.T) {
 							{
 								Function: api.ToolCallFunction{
 									Name: "get_current_weather",
-									Arguments: map[string]interface{}{
+									Arguments: map[string]any{
 										"location": "Paris, France",
 										"format":   "celsius",
 									},
diff --git a/server/images.go b/server/images.go
index 2ef9e5d0..bd6d92a6 100644
--- a/server/images.go
+++ b/server/images.go
@@ -60,7 +60,7 @@ type Model struct {
 	System         string
 	License        []string
 	Digest         string
-	Options        map[string]interface{}
+	Options        map[string]any
 	Messages       []api.Message
 
 	Template *template.Template
diff --git a/server/routes.go b/server/routes.go
index 95e49820..eee34033 100644
--- a/server/routes.go
+++ b/server/routes.go
@@ -72,7 +72,7 @@ var (
 	errBadTemplate = errors.New("template error")
 )
 
-func modelOptions(model *Model, requestOpts map[string]interface{}) (api.Options, error) {
+func modelOptions(model *Model, requestOpts map[string]any) (api.Options, error) {
 	opts := api.DefaultOptions()
 	if err := opts.FromMap(model.Options); err != nil {
 		return api.Options{}, err
@@ -826,7 +826,7 @@ func GetModelInfo(req api.ShowRequest) (*api.ShowResponse, error) {
 	cs := 30
 	for k, v := range m.Options {
 		switch val := v.(type) {
-		case []interface{}:
+		case []any:
 			for _, nv := range val {
 				params = append(params, fmt.Sprintf("%-*s %#v", cs, k, nv))
 			}
@@ -1336,7 +1336,7 @@ func Serve(ln net.Listener) error {
 	return nil
 }
 
-func waitForStream(c *gin.Context, ch chan interface{}) {
+func waitForStream(c *gin.Context, ch chan any) {
 	c.Header("Content-Type", "application/json")
 	for resp := range ch {
 		switch r := resp.(type) {
diff --git a/server/sched.go b/server/sched.go
index e6cefa5a..8082680b 100644
--- a/server/sched.go
+++ b/server/sched.go
@@ -38,7 +38,7 @@ type Scheduler struct {
 	pendingReqCh  chan *LlmRequest
 	finishedReqCh chan *LlmRequest
 	expiredCh     chan *runnerRef
-	unloadedCh    chan interface{}
+	unloadedCh    chan any
 
 	loaded   map[string]*runnerRef
 	loadedMu sync.Mutex
@@ -68,7 +68,7 @@ func InitScheduler(ctx context.Context) *Scheduler {
 		pendingReqCh:  make(chan *LlmRequest, maxQueue),
 		finishedReqCh: make(chan *LlmRequest, maxQueue),
 		expiredCh:     make(chan *runnerRef, maxQueue),
-		unloadedCh:    make(chan interface{}, maxQueue),
+		unloadedCh:    make(chan any, maxQueue),
 		loaded:        make(map[string]*runnerRef),
 		newServerFn:   llm.NewLlamaServer,
 		getGpuFn:      discover.GetGPUInfo,
@@ -618,8 +618,8 @@ func (runner *runnerRef) needsReload(ctx context.Context, req *LlmRequest) bool
 // a before and after GPU memory allocation.  The returned channel
 // will be notified when we're done waiting, or have timed out and should
 // proceed anyway
-func (runner *runnerRef) waitForVRAMRecovery() chan interface{} {
-	finished := make(chan interface{}, 1)
+func (runner *runnerRef) waitForVRAMRecovery() chan any {
+	finished := make(chan any, 1)
 
 	// CPU or Metal don't need checking, so no waiting required
 	// windows can page VRAM, only cuda currently can report accurate used vram usage

From 493385eb3e811ebbb49c6a23d6db7c39885bbb89 Mon Sep 17 00:00:00 2001
From: Jesse Gross <jesse@ollama.com>
Date: Tue, 1 Apr 2025 15:01:23 -0700
Subject: [PATCH 151/157] ollamarunner: Don't truncate a SameBatch

When truncating inputs to the the context window at the beginning of
a sequence, we remove the minimum amount possible. However, this
may cause us to truncate to the middle of a set of inputs that
the model specified should not be split up. To avoid this, we
need to remove the rest of the partial batch.
---
 runner/ollamarunner/cache.go  |  2 ++
 runner/ollamarunner/runner.go | 33 +++++++++++++++++++++++++++++----
 2 files changed, 31 insertions(+), 4 deletions(-)

diff --git a/runner/ollamarunner/cache.go b/runner/ollamarunner/cache.go
index af48ff22..30292f64 100644
--- a/runner/ollamarunner/cache.go
+++ b/runner/ollamarunner/cache.go
@@ -225,6 +225,8 @@ func countCommonPrefix(a []input.Input, b []input.Input) int32 {
 	return count
 }
 
+// TODO(jessegross): If we need to reprocess the inputs we should ensure that
+// we don't split up a SameBatch
 func (c *InputCache) ShiftDiscard(inputLen int32, numKeep int32) int32 {
 	targetFree := (c.numCtx - numKeep) / 2
 	targetFree = max(targetFree, 1)
diff --git a/runner/ollamarunner/runner.go b/runner/ollamarunner/runner.go
index 45838718..f3286aba 100644
--- a/runner/ollamarunner/runner.go
+++ b/runner/ollamarunner/runner.go
@@ -115,16 +115,41 @@ func (s *Server) NewSequence(prompt string, images []llm.ImageData, params NewSe
 		params.numKeep = int32(len(inputs))
 	}
 
-	// TODO(jessegross): We should ensure that we always leave minBatch of context space to shift,
-	// otherwise we might truncate or split the batch against the model's wishes
-
 	// Ensure that at least 1 input can be discarded during shift
 	params.numKeep = min(params.numKeep, s.cache.numCtx-1)
 
 	if int32(len(inputs)) > s.cache.numCtx {
 		discard := int32(len(inputs)) - s.cache.numCtx
+		promptStart := params.numKeep + discard
+
+		// If we need to truncate in the middle of a unbreakable batch, remove the entire batch
+		sameBatch := 0
+		for i, inp := range inputs {
+			if sameBatch > 0 {
+				sameBatch--
+
+				if promptStart == int32(i) {
+					promptStart++
+				}
+			} else if promptStart == int32(i) {
+				break
+			}
+
+			if inp.SameBatch != 0 {
+				if int32(i) < params.numKeep {
+					return nil, fmt.Errorf("SameBatch may not be specified within numKeep (index: %v numKeep: %v SameBatch: %v)", i, params.numKeep, inp.SameBatch)
+				}
+
+				sameBatch = inp.SameBatch
+			}
+		}
+
+		if promptStart >= int32(len(inputs)) {
+			return nil, errors.New("entire prompt removed by truncation")
+		}
+
 		newInputs := inputs[:params.numKeep]
-		newInputs = append(newInputs, inputs[params.numKeep+discard:]...)
+		newInputs = append(newInputs, inputs[promptStart:]...)
 
 		slog.Warn("truncating input prompt", "limit", s.cache.numCtx, "prompt", len(inputs), "keep", params.numKeep, "new", len(newInputs))
 		inputs = newInputs

From b42970063d8f05c47dd6d9a6b71f1e14cc4805c9 Mon Sep 17 00:00:00 2001
From: jmorganca <jmorganca@gmail.com>
Date: Sun, 30 Mar 2025 16:05:40 -0700
Subject: [PATCH 152/157] kvcache: Add check for values that fall out of
 sliding window cache

The sliding window cache trims entries that are outside the window for
the latest token. This works when we are extending the cache, such as
when the conversation continues. However, if we have a partial overlap
in conversation (including the BOS tokens), then we resume from a past
point in the conversation and the needed tokens are no longer stored
in memory. This verifies that the new window overlaps with the old one
before reusing the cache.

Co-authored-by: Jesse Gross <jesse@ollama.com>
---
 kvcache/cache.go                  |  5 +++
 kvcache/causal.go                 | 38 ++++++++++++++++-
 kvcache/causal_test.go            | 71 +++++++++++++++++++++++++++++++
 kvcache/encoder.go                |  4 ++
 kvcache/wrapper.go                | 10 +++++
 runner/ollamarunner/cache.go      |  4 ++
 runner/ollamarunner/cache_test.go |  1 +
 7 files changed, 131 insertions(+), 2 deletions(-)

diff --git a/kvcache/cache.go b/kvcache/cache.go
index 18aec800..07015b9e 100644
--- a/kvcache/cache.go
+++ b/kvcache/cache.go
@@ -62,6 +62,11 @@ type Cache interface {
 	// CopyPrefix copies tokens in the range [0, len) from srcSeq to dstSeq
 	CopyPrefix(srcSeq, dstSeq int, len int32)
 
+	// CanResume returns true if the cache can continue with the next token at
+	// the given position and sequence. Assumes that the caller has already
+	// verified the contents of the cache.
+	CanResume(seq int, pos int32) bool
+
 	// Remove deletes tokens in the range [beginIndex, endIndex) from seq. Set
 	// endIndex to math.MaxInt32 to remove everything starting at beginIndex.
 	//
diff --git a/kvcache/causal.go b/kvcache/causal.go
index fb4f0f74..4fc18d88 100644
--- a/kvcache/causal.go
+++ b/kvcache/causal.go
@@ -581,6 +581,35 @@ func (c *Causal) CopyPrefix(srcSeq, dstSeq int, len int32) {
 	c.cellRanges[dstSeq] = seqRange
 }
 
+func (c *Causal) CanResume(seq int, pos int32) bool {
+	if c.windowSize == math.MaxInt32 {
+		return true
+	}
+
+	seqRange, ok := c.cellRanges[seq]
+	if !ok {
+		return false
+	}
+
+	// for sliding window, check that the window of the new sequence is contained in
+	// the window of what we are storing
+	var last int32 = -1
+	for i := seqRange.min; i <= seqRange.max; i++ {
+		if slices.Contains(c.cells[i].sequences, seq) {
+			last = max(last, c.cells[i].pos)
+		}
+	}
+
+	if last == -1 {
+		return false
+	}
+
+	lastWindowStart := max(0, last-c.windowSize)
+	posWindowStart := max(0, pos-c.windowSize)
+
+	return posWindowStart >= lastWindowStart
+}
+
 func (c *Causal) shift(seq int, beginIndex, offset int32) error {
 	if c.shiftFn == nil {
 		return ErrNotSupported
@@ -635,6 +664,12 @@ func (c *Causal) shift(seq int, beginIndex, offset int32) error {
 }
 
 func (c *Causal) Remove(seq int, beginIndex, endIndex int32) error {
+	// TODO(jessegross): We should check to see if removing the middle of the sequence will
+	// cause the sliding window to encompass tokens that we no longer have. If so, then we
+	// should return an error, which will trigger the runner to evaluate the full history and
+	// rebuild the window. However, if we have multimodal inputs in our history, this reuse
+	// results in use after free, so we don't do it for now.
+
 	var offset int32
 	if endIndex != math.MaxInt32 {
 		offset = beginIndex - endIndex
@@ -649,8 +684,7 @@ func (c *Causal) Remove(seq int, beginIndex, endIndex int32) error {
 			} else {
 				if c.cells[i].pos >= endIndex {
 					if slices.ContainsFunc(c.cells[i].sequences, func(s int) bool { return s != seq }) {
-						// TODO(jessegross): Need to be careful about data shared between sequences
-						return errors.New("shifting on cells shared by multiple sequences not yet implemented")
+						return errors.New("shifting cells shared by multiple sequences not supported")
 					}
 
 					c.cells[i].pos += offset
diff --git a/kvcache/causal_test.go b/kvcache/causal_test.go
index b1dc7d77..bf98abef 100644
--- a/kvcache/causal_test.go
+++ b/kvcache/causal_test.go
@@ -300,6 +300,77 @@ func testCache(t *testing.T, backend ml.Backend, cache Cache, tests []testCase)
 	}
 }
 
+func TestCanResume(t *testing.T) {
+	backend := &testBackend{}
+	windowSize := int32(4)
+	cache := NewSWACache(windowSize, nil)
+	defer cache.Close()
+
+	cache.Init(backend, ml.DTypeF16, 1, 16, 16)
+
+	context := backend.NewContext()
+	defer context.Close()
+
+	err := cache.StartForward(context, input.Batch{
+		Positions: []int32{0, 1, 2, 3},
+		Sequences: []int{0, 0, 0, 0},
+	})
+	if err != nil {
+		t.Fatalf("StartForward failed: %v", err)
+	}
+
+	cache.SetLayer(0)
+	tensor, _ := context.FromFloatSlice([]float32{1, 2, 3, 4}, 1, 1, 4)
+	cache.Put(context, tensor, tensor)
+
+	// with window size 4, nothing has slid out of the window yet
+	if !cache.CanResume(0, 0) {
+		t.Errorf("CanResume(0, 0) = false, want true (within window)")
+	}
+	if !cache.CanResume(0, 1) {
+		t.Errorf("CanResume(0, 1) = false, want true (within window)")
+	}
+	if !cache.CanResume(0, 2) {
+		t.Errorf("CanResume(0, 2) = false, want true (within window)")
+	}
+	if !cache.CanResume(0, 3) {
+		t.Errorf("CanResume(0, 3) = false, want true (latest position)")
+	}
+
+	// shift window by adding position 4
+	err = cache.StartForward(context, input.Batch{
+		Positions: []int32{4, 5},
+		Sequences: []int{0, 0},
+	})
+	if err != nil {
+		t.Fatalf("StartForward failed: %v", err)
+	}
+
+	cache.SetLayer(0)
+	tensor, _ = context.FromFloatSlice([]float32{5, 6}, 1, 1, 2)
+	cache.Put(context, tensor, tensor)
+
+	// only the latest position has overlapping windows
+	if cache.CanResume(0, 0) {
+		t.Errorf("after shift: CanResume(0, 0) = true, want false (outside window)")
+	}
+	if cache.CanResume(0, 1) {
+		t.Errorf("after shift: CanResume(0, 1) = true, want false (outside window)")
+	}
+	if cache.CanResume(0, 2) {
+		t.Errorf("after shift: CanResume(0, 2) = true, want false (outside window)")
+	}
+	if cache.CanResume(0, 3) {
+		t.Errorf("after shift: CanResume(0, 3) = true, want false (outside window)")
+	}
+	if cache.CanResume(0, 4) {
+		t.Errorf("after shift: CanResume(0, 4) = true, want false (outside window)")
+	}
+	if !cache.CanResume(0, 5) {
+		t.Errorf("after shift: CanResume(0, 5) = false, want true (latest position)")
+	}
+}
+
 type testBackend struct{}
 
 func (b *testBackend) Config() ml.Config {
diff --git a/kvcache/encoder.go b/kvcache/encoder.go
index 07ff4291..03d650a3 100644
--- a/kvcache/encoder.go
+++ b/kvcache/encoder.go
@@ -134,6 +134,10 @@ func (c *EncoderCache) CopyPrefix(srcSeq, dstSeq int, len int32) {
 	panic("encoder cache does not support multiple sequences")
 }
 
+func (c *EncoderCache) CanResume(seq int, pos int32) bool {
+	return true
+}
+
 func (c *EncoderCache) Remove(seq int, beginIndex, endIndex int32) error {
 	if c.encoderPos >= beginIndex && c.encoderPos < endIndex {
 		c.encoderCached = false
diff --git a/kvcache/wrapper.go b/kvcache/wrapper.go
index 0e8ff1f3..926bc2d4 100644
--- a/kvcache/wrapper.go
+++ b/kvcache/wrapper.go
@@ -87,6 +87,16 @@ func (c *WrapperCache) CopyPrefix(srcSeq, dstSeq int, len int32) {
 	}
 }
 
+func (c *WrapperCache) CanResume(seq int, pos int32) bool {
+	for _, cache := range c.caches {
+		if !cache.CanResume(seq, pos) {
+			return false
+		}
+	}
+
+	return true
+}
+
 func (c *WrapperCache) Remove(seq int, beginIndex, endIndex int32) error {
 	// If the one of these fails, the caller is supposed to retry with endIndex set to math.MaxInt32, which should not fail
 	for _, cache := range c.caches {
diff --git a/runner/ollamarunner/cache.go b/runner/ollamarunner/cache.go
index 30292f64..01f435e4 100644
--- a/runner/ollamarunner/cache.go
+++ b/runner/ollamarunner/cache.go
@@ -118,6 +118,10 @@ func (c *InputCache) LoadCacheSlot(prompt []input.Input) (*InputCacheSlot, []inp
 	}
 
 	if c.cache != nil {
+		if numPast > 0 && !c.cache.CanResume(slot.Id, numPast) {
+			numPast = 0
+		}
+
 		err = c.cache.Remove(slot.Id, numPast, math.MaxInt32)
 		if err != nil {
 			// Some models don't support partial erasure
diff --git a/runner/ollamarunner/cache_test.go b/runner/ollamarunner/cache_test.go
index 6a8d8a6a..543b4b2f 100644
--- a/runner/ollamarunner/cache_test.go
+++ b/runner/ollamarunner/cache_test.go
@@ -451,6 +451,7 @@ func (m *mockCache) Close()
 func (m *mockCache) StartForward(ctx ml.Context, batch input.Batch) error                          { return nil }
 func (m *mockCache) CopyPrefix(srcSeq, dstSeq int, len int32)                                      {}
 func (m *mockCache) SetConfig(ml.CacheConfig)                                                      {}
+func (m *mockCache) CanResume(seq int, pos int32) bool                                             { return true }
 
 func TestShiftCacheSlot(t *testing.T) {
 	tests := []struct {

From b51e0f397ced70bbfa7f22e9b3c94953967cb8e5 Mon Sep 17 00:00:00 2001
From: Jeffrey Morgan <jmorganca@gmail.com>
Date: Wed, 2 Apr 2025 13:22:56 -0700
Subject: [PATCH 153/157] model: fix issues with spm tokenizer for Gemma 3
 (#10081)

---
 model/models/gemma2/model.go      |   1 -
 model/models/gemma3/model.go      |   1 -
 model/models/gemma3/model_text.go |   1 -
 model/process_text_spm.go         | 225 ++++++++++++++++--------------
 model/process_text_spm_test.go    |  60 +++++++-
 5 files changed, 175 insertions(+), 113 deletions(-)

diff --git a/model/models/gemma2/model.go b/model/models/gemma2/model.go
index 67c69ee8..b8f5f066 100644
--- a/model/models/gemma2/model.go
+++ b/model/models/gemma2/model.go
@@ -38,7 +38,6 @@ const (
 func New(c ml.Config) (model.Model, error) {
 	m := Model{
 		SentencePieceModel: model.NewSentencePieceModel(
-			c.String("tokenizer.ggml.pretokenizer", `(?i:'s|'t|'re|'ve|'m|'ll|'d)|[^\r\n\p{L}\p{N}]?\p{L}+|\p{N}{1,3}| ?[^\s\p{L}\p{N}]+[\r\n]*|\s*[\r\n]+|\s+(?!\S)|\s+`),
 			&model.Vocabulary{
 				Values: c.Strings("tokenizer.ggml.tokens"),
 				Scores: c.Floats("tokenizer.ggml.scores"),
diff --git a/model/models/gemma3/model.go b/model/models/gemma3/model.go
index 567ad1a4..f9c53343 100644
--- a/model/models/gemma3/model.go
+++ b/model/models/gemma3/model.go
@@ -55,7 +55,6 @@ func (p *MultiModalProjector) Forward(ctx ml.Context, visionOutputs ml.Tensor, i
 func New(c ml.Config) (model.Model, error) {
 	m := Model{
 		SentencePieceModel: model.NewSentencePieceModel(
-			c.String("tokenizer.ggml.pretokenizer", `(?i:'s|'t|'re|'ve|'m|'ll|'d)|[^\r\n\p{L}\p{N}]?\p{L}+|\p{N}{1,3}| ?[^\s\p{L}\p{N}]+[\r\n]*|\s*[\r\n]+|\s+(?!\S)|\s+`),
 			&model.Vocabulary{
 				Values: c.Strings("tokenizer.ggml.tokens"),
 				Scores: c.Floats("tokenizer.ggml.scores"),
diff --git a/model/models/gemma3/model_text.go b/model/models/gemma3/model_text.go
index 7d8b6577..7b2b83c0 100644
--- a/model/models/gemma3/model_text.go
+++ b/model/models/gemma3/model_text.go
@@ -45,7 +45,6 @@ func newTextModel(c ml.Config) *TextModel {
 
 	m := TextModel{
 		SentencePieceModel: model.NewSentencePieceModel(
-			c.String("tokenizer.ggml.pretokenizer", `(?i:'s|'t|'re|'ve|'m|'ll|'d)|[^\r\n\p{L}\p{N}]?\p{L}+|\p{N}{1,3}| ?[^\s\p{L}\p{N}]+[\r\n]*|\s*[\r\n]+|\s+(?!\S)|\s+`),
 			&model.Vocabulary{
 				Values: c.Strings("tokenizer.ggml.tokens"),
 				Scores: c.Floats("tokenizer.ggml.scores"),
diff --git a/model/process_text_spm.go b/model/process_text_spm.go
index 68e3ed01..c6e08dbd 100644
--- a/model/process_text_spm.go
+++ b/model/process_text_spm.go
@@ -1,29 +1,23 @@
 package model
 
 import (
-	"iter"
+	"container/heap"
+	"fmt"
 	"log/slog"
+	"strconv"
 	"strings"
-
-	"github.com/dlclark/regexp2"
-	queue "github.com/emirpasic/gods/v2/queues/priorityqueue"
 )
 
 const spmWhitespaceSep = "▁"
 
-func replaceWhitespaceBySeperator(s string) string {
-	return strings.ReplaceAll(s, " ", spmWhitespaceSep)
-}
-
 type SentencePieceModel struct {
 	maxTokenLen int
-	pre         *regexp2.Regexp
 	vocab       *Vocabulary
 }
 
 var _ TextProcessor = (*SentencePieceModel)(nil)
 
-func NewSentencePieceModel(pre string, vocab *Vocabulary) SentencePieceModel {
+func NewSentencePieceModel(vocab *Vocabulary) SentencePieceModel {
 	slog.Debug("Tokens", "num tokens", len(vocab.Values), "vals", vocab.Values[:5], "scores", vocab.Scores[:5], "types", vocab.Types[:5])
 
 	counter := map[int]int{}
@@ -44,7 +38,6 @@ func NewSentencePieceModel(pre string, vocab *Vocabulary) SentencePieceModel {
 
 	return SentencePieceModel{
 		maxTokenLen: maxTokenLen,
-		pre:         regexp2.MustCompile(pre, regexp2.Unicode|regexp2.RE2),
 		vocab:       vocab,
 	}
 }
@@ -53,20 +46,9 @@ func (spm SentencePieceModel) Is(id int32, special Special) bool {
 	return spm.vocab.Is(id, special)
 }
 
-func (spm *SentencePieceModel) split(s string) iter.Seq[string] {
-	return func(yield func(string) bool) {
-		for m, _ := spm.pre.FindStringMatch(s); m != nil; m, _ = spm.pre.FindNextMatch(m) {
-			if !yield(m.String()) {
-				break
-			}
-		}
-	}
-}
-
 func (spm SentencePieceModel) Encode(s string, addSpecial bool) ([]int32, error) {
 	fragments := []fragment{{value: s}}
 	for _, special := range spm.vocab.SpecialVocabulary() {
-		// TODO: process special tokens concurrently
 		id := spm.vocab.Encode(special)
 		for i := 0; i < len(fragments); i++ {
 			frag := fragments[i]
@@ -91,7 +73,6 @@ func (spm SentencePieceModel) Encode(s string, addSpecial bool) ([]int32, error)
 			fragments = append(fragments[:i], append(middle, fragments[i+1:]...)...)
 		}
 	}
-	slog.Debug("fragments", "frags", fragments)
 
 	var ids []int32
 	for _, frag := range fragments {
@@ -100,105 +81,96 @@ func (spm SentencePieceModel) Encode(s string, addSpecial bool) ([]int32, error)
 			continue
 		}
 
-		for split := range spm.split(frag.value) {
-			split = replaceWhitespaceBySeperator(split)
+		text := strings.ReplaceAll(frag.value, " ", spmWhitespaceSep)
 
-			var sb strings.Builder
-			sb.Write([]byte(split))
-			if id := spm.vocab.Encode(sb.String()); id >= 0 {
-				ids = append(ids, id)
-				continue
+		if id := spm.vocab.Encode(text); id >= 0 {
+			ids = append(ids, id)
+			continue
+		}
+
+		q := &queue{}
+		heap.Init(q)
+
+		runes := []rune(text)
+		merges := make([]merge, len(runes))
+		for r := range runes {
+			merges[r] = merge{
+				p:     r - 1,
+				n:     r + 1,
+				runes: []rune{runes[r]},
 			}
+		}
 
-			runes := []rune(sb.String())
-			pq := queue.NewWith(func(a, b any) int {
-				priA := a.(*candidate)
-				priB := b.(*candidate)
-				if priA.score > priB.score || (priA.score == priB.score && priA.a < priB.a) {
-					return -1
-				}
-				return 1
-			})
-
-			merges := make([]merge, len(runes))
-			for r := range runes {
-				merges[r] = merge{
-					p:     r - 1,
-					n:     r + 1,
-					runes: []rune{runes[r]},
-				}
-			}
-
-			slog.Debug("tokenizer", "merges", merges)
-
-			pairwise := func(a, b int) *candidate {
-				if a < 0 || b >= len(runes) {
-					return nil
-				}
-
-				left, right := string(merges[a].runes), string(merges[b].runes)
-				if id := spm.vocab.Encode(left + right); id >= 0 {
-					return &candidate{
-						a:     a,
-						b:     b,
-						score: spm.vocab.Scores[id],
-					}
-				}
+		pairwise := func(a, b int) *candidate {
+			if a < 0 || b >= len(runes) {
 				return nil
 			}
 
-			for i := range len(runes) - 1 {
-				if pair := pairwise(i, i+1); pair != nil {
-					pq.Enqueue(pair)
+			left, right := string(merges[a].runes), string(merges[b].runes)
+			if id := spm.vocab.Encode(left + right); id >= 0 {
+				return &candidate{
+					a:     a,
+					b:     b,
+					score: spm.vocab.Scores[id],
+					size:  len(left) + len(right),
 				}
 			}
 
-			pqv := pq.Values()
-			for _, v := range pqv {
-				e := v.(*candidate)
-				slog.Debug("candidate", "candidate", e)
+			return nil
+		}
+
+		for i := range len(runes) - 1 {
+			if pair := pairwise(i, i+1); pair != nil {
+				heap.Push(q, pair)
+			}
+		}
+
+		for q.Len() > 0 {
+			pair := heap.Pop(q).(*candidate)
+			left, right := merges[pair.a], merges[pair.b]
+
+			if string(left.runes) == "" || string(right.runes) == "" || len(string(left.runes))+len(string(right.runes)) != pair.size {
+				continue
 			}
 
-			for !pq.Empty() {
-				v, _ := pq.Dequeue()
-				pair := v.(*candidate)
-				left, right := merges[pair.a], merges[pair.b]
+			merges[pair.a].runes = append(left.runes, right.runes...)
+			merges[pair.b].runes = nil
+			merges[pair.a].n = right.n
+			if right.n < len(merges) {
+				merges[right.n].p = pair.a
+			}
 
-				slog.Debug("pair", "left", left, "right", right)
-				if len(left.runes) == 0 || len(right.runes) == 0 {
+			if pair := pairwise(merges[pair.a].p, pair.a); pair != nil {
+				heap.Push(q, pair)
+			}
+
+			if pair := pairwise(pair.a, merges[pair.a].n); pair != nil {
+				heap.Push(q, pair)
+			}
+		}
+
+		for _, merge := range merges {
+			if token := string(merge.runes); token != "" {
+				id := spm.vocab.Encode(token)
+
+				if id >= 0 {
+					ids = append(ids, id)
 					continue
 				}
 
-				if id := spm.vocab.Encode(string(left.runes) + string(right.runes)); id < 0 {
-					continue
-				}
-
-				merges[pair.a].runes = append(left.runes, right.runes...)
-				merges[pair.b].runes = nil
-				merges[pair.a].n = right.n
-				if right.n < len(merges) {
-					merges[right.n].p = pair.a
-				}
-
-				if pair := pairwise(merges[pair.a].p, pair.a); pair != nil {
-					pq.Enqueue(pair)
-				}
-
-				if pair := pairwise(pair.a, merges[pair.a].n); pair != nil {
-					pq.Enqueue(pair)
-				}
-			}
-
-			slog.Debug("merges", "merges", merges)
-
-			for _, merge := range merges {
-				if len(merge.runes) > 0 {
-					if id := spm.vocab.Encode(string(merge.runes)); id >= 0 {
-						ids = append(ids, id)
+				// Fallback to byte tokenization
+				var result []int32
+				for _, b := range []byte(token) {
+					byteToken := fmt.Sprintf("<0x%02X>", b)
+					unknownID := spm.vocab.Encode(byteToken)
+					if unknownID >= 0 {
+						result = append(result, unknownID)
 					} else {
-						slog.Debug("missing token", "token", string(merge.runes))
+						slog.Debug("unknown byte token", "byte", b, "token", byteToken)
 					}
 				}
+
+				ids = append(ids, result...)
 			}
 		}
 	}
@@ -229,6 +201,30 @@ func (spm SentencePieceModel) Encode(s string, addSpecial bool) ([]int32, error)
 type candidate struct {
 	a, b  int
 	score float32
+	size  int
+}
+
+type queue []*candidate
+
+func (q queue) Len() int { return len(q) }
+
+func (q queue) Less(i, j int) bool {
+	return (q[i].score > q[j].score) || (q[i].score == q[j].score && q[i].a < q[j].a)
+}
+
+func (q queue) Swap(i, j int) { q[i], q[j] = q[j], q[i] }
+
+func (q *queue) Push(x interface{}) {
+	item := x.(*candidate)
+	*q = append(*q, item)
+}
+
+func (q *queue) Pop() interface{} {
+	old := *q
+	n := len(old)
+	item := old[n-1]
+	*q = old[0 : n-1]
+	return item
 }
 
 func (spm SentencePieceModel) Decode(ids []int32) (string, error) {
@@ -236,11 +232,26 @@ func (spm SentencePieceModel) Decode(ids []int32) (string, error) {
 	for _, id := range ids {
 		data := spm.vocab.Decode(id)
 		data = strings.ReplaceAll(data, spmWhitespaceSep, " ")
-		if _, err := sb.WriteString(data); err != nil {
-			return "", err
+
+		// For tokenizers that use byte tokens like "<0xEA>"
+		// convert them to the partial unicode character
+		// so they are buffered correctly by the runner instead
+		// of being sent back to the api as "<0xEA>"
+		if len(data) == 6 && strings.HasPrefix(data, "<0x") && strings.HasSuffix(data, ">") {
+			byteVal, err := strconv.ParseUint(data[1:5], 0, 8)
+			if err != nil {
+				return "", fmt.Errorf("failed to parse hex byte: %v", err)
+			}
+
+			if err := sb.WriteByte(byte(byteVal)); err != nil {
+				return "", err
+			}
+		} else {
+			if _, err := sb.WriteString(data); err != nil {
+				return "", err
+			}
 		}
 	}
 
-	slog.Debug("decoded", "ids", ids, "text", sb.String())
 	return sb.String(), nil
 }
diff --git a/model/process_text_spm_test.go b/model/process_text_spm_test.go
index a43004db..4813333e 100644
--- a/model/process_text_spm_test.go
+++ b/model/process_text_spm_test.go
@@ -25,8 +25,6 @@ func loadSentencePieceVocab(t *testing.T) SentencePieceModel {
 		t.Fatal(err)
 	}
 
-	preTokenizer := `(?i:'s|'t|'re|'ve|'m|'ll|'d)|[^\r\n\p{L}\p{N}]?\p{L}+|\p{N}{1,3}| ?[^\s\p{L}\p{N}]+[\r\n]*|\s*[\r\n]+|\s+(?!\S)|\s+`
-
 	var v Vocabulary
 
 	for _, piece := range spm.GetPieces() {
@@ -47,7 +45,7 @@ func loadSentencePieceVocab(t *testing.T) SentencePieceModel {
 		}
 	}
 
-	return NewSentencePieceModel(preTokenizer, &v)
+	return NewSentencePieceModel(&v)
 }
 
 func TestSentencePieceEncode(t *testing.T) {
@@ -116,3 +114,59 @@ func TestSentencePieceEncode(t *testing.T) {
 		}
 	})
 }
+
+func TestSentencePieceModelDecodeByteTokens(t *testing.T) {
+	vocab := &Vocabulary{
+		Values: []string{
+			"normal",
+			"<0xEA>",
+			"<0x41>",
+			"<0xC3>",
+			"<0xA3>",
+		},
+		Types: []uint32{
+			TOKEN_TYPE_NORMAL,
+			TOKEN_TYPE_BYTE,
+			TOKEN_TYPE_BYTE,
+			TOKEN_TYPE_BYTE,
+			TOKEN_TYPE_BYTE,
+		},
+		Scores: []float32{0, 0, 0, 0, 0},
+	}
+
+	spm := NewSentencePieceModel(vocab)
+
+	tests := []struct {
+		name     string
+		ids      []int32
+		expected string
+	}{
+		{
+			name:     "single byte token",
+			ids:      []int32{1},
+			expected: "\xea",
+		},
+		{
+			name:     "ASCII byte token",
+			ids:      []int32{2},
+			expected: "A",
+		},
+		{
+			name:     "multiple byte tokens forming UTF-8 character",
+			ids:      []int32{3, 4},
+			expected: "ã",
+		},
+	}
+
+	for _, tt := range tests {
+		t.Run(tt.name, func(t *testing.T) {
+			result, err := spm.Decode(tt.ids)
+			if err != nil {
+				t.Errorf("failed to decode token IDs %v: %v", tt.ids, err)
+			}
+			if result != tt.expected {
+				t.Errorf("got %q, want %q", result, tt.expected)
+			}
+		})
+	}
+}

From e53b3cbd0c3f08eb692a318c8eaf687a01c2e8c0 Mon Sep 17 00:00:00 2001
From: Bruce MacDonald <brucewmacdonald@gmail.com>
Date: Thu, 3 Apr 2025 10:19:24 -0700
Subject: [PATCH 154/157] llm: set done reason at server level (#9830)

No functional change. Many different done reasons can be set at the runner
level, so rather than obsuring them we should return them to the server
process and let it choose what to do with the done reason. This separates
the API concerns from the runner.
---
 llm/server.go                  | 26 ++++++++++++++++++++++++--
 runner/llamarunner/runner.go   | 21 ++++++++-------------
 runner/ollamarunner/runner.go  | 21 ++++++++-------------
 server/routes.go               | 20 ++++++++++----------
 server/routes_generate_test.go |  8 ++++----
 5 files changed, 54 insertions(+), 42 deletions(-)

diff --git a/llm/server.go b/llm/server.go
index e6046db6..a2bc1548 100644
--- a/llm/server.go
+++ b/llm/server.go
@@ -675,9 +675,32 @@ type CompletionRequest struct {
 	Grammar string // set before sending the request to the subprocess
 }
 
+// DoneReason represents the reason why a completion response is done
+type DoneReason int
+
+const (
+	// DoneReasonStop indicates the completion stopped naturally
+	DoneReasonStop DoneReason = iota
+	// DoneReasonLength indicates the completion stopped due to length limits
+	DoneReasonLength
+	// DoneReasonConnectionClosed indicates the completion stopped due to the connection being closed
+	DoneReasonConnectionClosed
+)
+
+func (d DoneReason) String() string {
+	switch d {
+	case DoneReasonLength:
+		return "length"
+	case DoneReasonStop:
+		return "stop"
+	default:
+		return "" // closed
+	}
+}
+
 type CompletionResponse struct {
 	Content            string        `json:"content"`
-	DoneReason         string        `json:"done_reason"`
+	DoneReason         DoneReason    `json:"done_reason"`
 	Done               bool          `json:"done"`
 	PromptEvalCount    int           `json:"prompt_eval_count"`
 	PromptEvalDuration time.Duration `json:"prompt_eval_duration"`
@@ -786,7 +809,6 @@ func (s *llmServer) Completion(ctx context.Context, req CompletionRequest, fn fu
 				continue
 			}
 
-			// slog.Debug("got line", "line", string(line))
 			evt, ok := bytes.CutPrefix(line, []byte("data: "))
 			if !ok {
 				evt = line
diff --git a/runner/llamarunner/runner.go b/runner/llamarunner/runner.go
index a4264f5f..d8169be4 100644
--- a/runner/llamarunner/runner.go
+++ b/runner/llamarunner/runner.go
@@ -83,7 +83,7 @@ type Sequence struct {
 	// true if an embedding are to be returned instead of text generation
 	embeddingOnly bool
 
-	doneReason string
+	doneReason llm.DoneReason
 
 	// Metrics
 	startProcessingTime time.Time
@@ -301,7 +301,7 @@ func flushPending(seq *Sequence) bool {
 	}
 }
 
-func (s *Server) removeSequence(seqIndex int, reason string) {
+func (s *Server) removeSequence(seqIndex int, reason llm.DoneReason) {
 	seq := s.seqs[seqIndex]
 
 	flushPending(seq)
@@ -380,7 +380,7 @@ func (s *Server) processBatch(tokenBatch *llama.Batch, embedBatch *llama.Batch)
 
 		// if past the num predict limit
 		if seq.numPredict > 0 && seq.numPredicted >= seq.numPredict {
-			s.removeSequence(seqIdx, "limit")
+			s.removeSequence(seqIdx, llm.DoneReasonLength)
 			continue
 		}
 
@@ -482,7 +482,7 @@ func (s *Server) processBatch(tokenBatch *llama.Batch, embedBatch *llama.Batch)
 			}
 
 			seq.embedding <- embed
-			s.removeSequence(i, "")
+			s.removeSequence(i, llm.DoneReasonStop)
 			continue
 		}
 
@@ -499,7 +499,7 @@ func (s *Server) processBatch(tokenBatch *llama.Batch, embedBatch *llama.Batch)
 			// as it's important for the /api/generate context
 			// seq.responses <- piece
 
-			s.removeSequence(i, "stop")
+			s.removeSequence(i, llm.DoneReasonStop)
 			continue
 		}
 
@@ -530,7 +530,7 @@ func (s *Server) processBatch(tokenBatch *llama.Batch, embedBatch *llama.Batch)
 			}
 			seq.cache.Inputs = seq.cache.Inputs[:tokenLen]
 
-			s.removeSequence(i, "stop")
+			s.removeSequence(i, llm.DoneReasonStop)
 			continue
 		}
 
@@ -543,7 +543,7 @@ func (s *Server) processBatch(tokenBatch *llama.Batch, embedBatch *llama.Batch)
 		}
 
 		if !flushPending(seq) {
-			s.removeSequence(i, "connection")
+			s.removeSequence(i, llm.DoneReasonConnectionClosed)
 		}
 	}
 
@@ -657,14 +657,9 @@ func (s *Server) completion(w http.ResponseWriter, r *http.Request) {
 
 				flusher.Flush()
 			} else {
-				// Send the final response
-				doneReason := "stop"
-				if seq.doneReason == "limit" {
-					doneReason = "length"
-				}
 				if err := json.NewEncoder(w).Encode(&llm.CompletionResponse{
 					Done:               true,
-					DoneReason:         doneReason,
+					DoneReason:         seq.doneReason,
 					PromptEvalCount:    seq.numPromptInputs,
 					PromptEvalDuration: seq.startGenerationTime.Sub(seq.startProcessingTime),
 					EvalCount:          seq.numDecoded,
diff --git a/runner/ollamarunner/runner.go b/runner/ollamarunner/runner.go
index f3286aba..7b7e0940 100644
--- a/runner/ollamarunner/runner.go
+++ b/runner/ollamarunner/runner.go
@@ -82,7 +82,7 @@ type Sequence struct {
 	// true if an embedding are to be returned instead of text generation
 	embeddingOnly bool
 
-	doneReason string
+	doneReason llm.DoneReason
 
 	// Metrics
 	startProcessingTime time.Time
@@ -341,7 +341,7 @@ func flushPending(seq *Sequence) bool {
 	}
 }
 
-func (s *Server) removeSequence(seqIndex int, reason string) {
+func (s *Server) removeSequence(seqIndex int, reason llm.DoneReason) {
 	seq := s.seqs[seqIndex]
 
 	flushPending(seq)
@@ -391,7 +391,7 @@ func (s *Server) processBatch() error {
 
 		// if past the num predict limit
 		if seq.numPredict > 0 && seq.numPredicted >= seq.numPredict {
-			s.removeSequence(seqIdx, "limit")
+			s.removeSequence(seqIdx, llm.DoneReasonLength)
 			continue
 		}
 
@@ -510,7 +510,7 @@ func (s *Server) processBatch() error {
 		if seq.embeddingOnly {
 			// TODO(jessegross): Embedding support
 			slog.Warn("generation of embedding outputs not yet supported")
-			s.removeSequence(i, "")
+			s.removeSequence(i, llm.DoneReasonStop)
 			continue
 		}
 
@@ -528,7 +528,7 @@ func (s *Server) processBatch() error {
 			// as it's important for the /api/generate context
 			// seq.responses <- piece
 
-			s.removeSequence(i, "stop")
+			s.removeSequence(i, llm.DoneReasonStop)
 			continue
 		}
 
@@ -564,7 +564,7 @@ func (s *Server) processBatch() error {
 			}
 			seq.cache.Inputs = seq.cache.Inputs[:tokenLen]
 
-			s.removeSequence(i, "stop")
+			s.removeSequence(i, llm.DoneReasonStop)
 			continue
 		}
 
@@ -577,7 +577,7 @@ func (s *Server) processBatch() error {
 		}
 
 		if !flushPending(seq) {
-			s.removeSequence(i, "connection")
+			s.removeSequence(i, llm.DoneReasonConnectionClosed)
 		}
 	}
 
@@ -690,14 +690,9 @@ func (s *Server) completion(w http.ResponseWriter, r *http.Request) {
 
 				flusher.Flush()
 			} else {
-				// Send the final response
-				doneReason := "stop"
-				if seq.doneReason == "limit" {
-					doneReason = "length"
-				}
 				if err := json.NewEncoder(w).Encode(&llm.CompletionResponse{
 					Done:               true,
-					DoneReason:         doneReason,
+					DoneReason:         seq.doneReason,
 					PromptEvalCount:    seq.numPromptInputs,
 					PromptEvalDuration: seq.startGenerationTime.Sub(seq.startProcessingTime),
 					EvalCount:          seq.numPredicted,
diff --git a/server/routes.go b/server/routes.go
index eee34033..906426b1 100644
--- a/server/routes.go
+++ b/server/routes.go
@@ -308,11 +308,10 @@ func (s *Server) GenerateHandler(c *gin.Context) {
 			Options: opts,
 		}, func(cr llm.CompletionResponse) {
 			res := api.GenerateResponse{
-				Model:      req.Model,
-				CreatedAt:  time.Now().UTC(),
-				Response:   cr.Content,
-				Done:       cr.Done,
-				DoneReason: cr.DoneReason,
+				Model:     req.Model,
+				CreatedAt: time.Now().UTC(),
+				Response:  cr.Content,
+				Done:      cr.Done,
 				Metrics: api.Metrics{
 					PromptEvalCount:    cr.PromptEvalCount,
 					PromptEvalDuration: cr.PromptEvalDuration,
@@ -326,6 +325,7 @@ func (s *Server) GenerateHandler(c *gin.Context) {
 			}
 
 			if cr.Done {
+				res.DoneReason = cr.DoneReason.String()
 				res.TotalDuration = time.Since(checkpointStart)
 				res.LoadDuration = checkpointLoaded.Sub(checkpointStart)
 
@@ -1533,11 +1533,10 @@ func (s *Server) ChatHandler(c *gin.Context) {
 			Options: opts,
 		}, func(r llm.CompletionResponse) {
 			res := api.ChatResponse{
-				Model:      req.Model,
-				CreatedAt:  time.Now().UTC(),
-				Message:    api.Message{Role: "assistant", Content: r.Content},
-				Done:       r.Done,
-				DoneReason: r.DoneReason,
+				Model:     req.Model,
+				CreatedAt: time.Now().UTC(),
+				Message:   api.Message{Role: "assistant", Content: r.Content},
+				Done:      r.Done,
 				Metrics: api.Metrics{
 					PromptEvalCount:    r.PromptEvalCount,
 					PromptEvalDuration: r.PromptEvalDuration,
@@ -1547,6 +1546,7 @@ func (s *Server) ChatHandler(c *gin.Context) {
 			}
 
 			if r.Done {
+				res.DoneReason = r.DoneReason.String()
 				res.TotalDuration = time.Since(checkpointStart)
 				res.LoadDuration = checkpointLoaded.Sub(checkpointStart)
 			}
diff --git a/server/routes_generate_test.go b/server/routes_generate_test.go
index aa263bf9..f219387c 100644
--- a/server/routes_generate_test.go
+++ b/server/routes_generate_test.go
@@ -58,7 +58,7 @@ func TestGenerateChat(t *testing.T) {
 	mock := mockRunner{
 		CompletionResponse: llm.CompletionResponse{
 			Done:               true,
-			DoneReason:         "stop",
+			DoneReason:         llm.DoneReasonStop,
 			PromptEvalCount:    1,
 			PromptEvalDuration: 1,
 			EvalCount:          1,
@@ -401,7 +401,7 @@ func TestGenerateChat(t *testing.T) {
 		mock.CompletionResponse = llm.CompletionResponse{
 			Content:            `{"name":"get_weather","arguments":{"location":"Seattle, WA","unit":"celsius"}}`,
 			Done:               true,
-			DoneReason:         "done",
+			DoneReason:         llm.DoneReasonStop,
 			PromptEvalCount:    1,
 			PromptEvalDuration: 1,
 			EvalCount:          1,
@@ -519,7 +519,7 @@ func TestGenerateChat(t *testing.T) {
 				{
 					Content:            `, WA","unit":"celsius"}}`,
 					Done:               true,
-					DoneReason:         "tool_call",
+					DoneReason:         llm.DoneReasonStop,
 					PromptEvalCount:    3,
 					PromptEvalDuration: 1,
 				},
@@ -594,7 +594,7 @@ func TestGenerate(t *testing.T) {
 	mock := mockRunner{
 		CompletionResponse: llm.CompletionResponse{
 			Done:               true,
-			DoneReason:         "stop",
+			DoneReason:         llm.DoneReasonStop,
 			PromptEvalCount:    1,
 			PromptEvalDuration: 1,
 			EvalCount:          1,

From 3b96a93672377129f2a2aafc447e79ef1ca48c5f Mon Sep 17 00:00:00 2001
From: Michael Yang <mxyng@pm.me>
Date: Tue, 18 Mar 2025 14:38:44 -0700
Subject: [PATCH 155/157] fs: move ml.Config to fs package

---
 fs/config.go                         | 13 +++++++++++++
 kvcache/causal_test.go               |  3 ++-
 ml/backend.go                        | 16 +++-------------
 ml/backend/ggml/ggml.go              | 11 ++++++-----
 model/model.go                       | 11 ++++++-----
 model/model_test.go                  |  9 +++++----
 model/models/gemma2/model.go         |  3 ++-
 model/models/gemma3/model.go         |  3 ++-
 model/models/gemma3/model_text.go    |  3 ++-
 model/models/gemma3/model_vision.go  |  3 ++-
 model/models/gemma3/process_image.go |  4 ++--
 model/models/llama/model.go          |  3 ++-
 model/models/mllama/model.go         |  3 ++-
 model/models/mllama/model_text.go    |  3 ++-
 model/models/mllama/model_vision.go  |  3 ++-
 model/models/mllama/process_image.go |  4 ++--
 16 files changed, 55 insertions(+), 40 deletions(-)
 create mode 100644 fs/config.go

diff --git a/fs/config.go b/fs/config.go
new file mode 100644
index 00000000..bc5bfa55
--- /dev/null
+++ b/fs/config.go
@@ -0,0 +1,13 @@
+package fs
+
+type Config interface {
+	Architecture() string
+	String(string, ...string) string
+	Uint(string, ...uint32) uint32
+	Float(string, ...float32) float32
+	Bool(string, ...bool) bool
+
+	Strings(string, ...[]string) []string
+	Uints(string, ...[]uint32) []uint32
+	Floats(string, ...[]float32) []float32
+}
diff --git a/kvcache/causal_test.go b/kvcache/causal_test.go
index bf98abef..517e3726 100644
--- a/kvcache/causal_test.go
+++ b/kvcache/causal_test.go
@@ -5,6 +5,7 @@ import (
 	"slices"
 	"testing"
 
+	"github.com/ollama/ollama/fs"
 	"github.com/ollama/ollama/ml"
 	"github.com/ollama/ollama/model/input"
 )
@@ -373,7 +374,7 @@ func TestCanResume(t *testing.T) {
 
 type testBackend struct{}
 
-func (b *testBackend) Config() ml.Config {
+func (b *testBackend) Config() fs.Config {
 	panic("not implemented")
 }
 
diff --git a/ml/backend.go b/ml/backend.go
index cfb18d6a..b22ba795 100644
--- a/ml/backend.go
+++ b/ml/backend.go
@@ -9,22 +9,12 @@ import (
 	"slices"
 	"strconv"
 	"strings"
+
+	"github.com/ollama/ollama/fs"
 )
 
-type Config interface {
-	Architecture() string
-	String(string, ...string) string
-	Uint(string, ...uint32) uint32
-	Float(string, ...float32) float32
-	Bool(string, ...bool) bool
-
-	Strings(string, ...[]string) []string
-	Uints(string, ...[]uint32) []uint32
-	Floats(string, ...[]float32) []float32
-}
-
 type Backend interface {
-	Config() Config
+	Config() fs.Config
 	Get(name string) Tensor
 	NewContext() Context
 	NewContextSize(size int) Context
diff --git a/ml/backend/ggml/ggml.go b/ml/backend/ggml/ggml.go
index b6f59ae0..17f06384 100644
--- a/ml/backend/ggml/ggml.go
+++ b/ml/backend/ggml/ggml.go
@@ -24,7 +24,8 @@ import (
 	"unsafe"
 
 	"github.com/ollama/ollama/format"
-	fs "github.com/ollama/ollama/fs/ggml"
+	"github.com/ollama/ollama/fs"
+	fsggml "github.com/ollama/ollama/fs/ggml"
 	"github.com/ollama/ollama/ml"
 	ggml "github.com/ollama/ollama/ml/backend/ggml/ggml/src"
 	"golang.org/x/sync/errgroup"
@@ -41,7 +42,7 @@ func devices() []*C.struct_ggml_backend_device {
 }
 
 type Backend struct {
-	meta    *fs.GGML
+	meta    *fsggml.GGML
 	sched   *C.struct_ggml_backend_sched
 	tensors map[string]*C.struct_ggml_tensor
 
@@ -58,7 +59,7 @@ type Backend struct {
 }
 
 func New(ctx context.Context, r *os.File, params ml.BackendParams) (ml.Backend, error) {
-	meta, n, err := fs.Decode(r, -1)
+	meta, n, err := fsggml.Decode(r, -1)
 	if err != nil {
 		return nil, err
 	}
@@ -182,7 +183,7 @@ func New(ctx context.Context, r *os.File, params ml.BackendParams) (ml.Backend,
 	maxTensors += blocks * 2
 
 	type tensor struct {
-		source *fs.Tensor
+		source *fsggml.Tensor
 		target string
 	}
 
@@ -413,7 +414,7 @@ func init() {
 	ml.RegisterBackend("ggml", New)
 }
 
-func (b *Backend) Config() ml.Config {
+func (b *Backend) Config() fs.Config {
 	return b.meta.KV()
 }
 
diff --git a/model/model.go b/model/model.go
index 8355a55a..bc8944d2 100644
--- a/model/model.go
+++ b/model/model.go
@@ -16,7 +16,8 @@ import (
 	_ "golang.org/x/image/tiff"
 	_ "golang.org/x/image/webp"
 
-	fs "github.com/ollama/ollama/fs/ggml"
+	"github.com/ollama/ollama/fs"
+	fsggml "github.com/ollama/ollama/fs/ggml"
 	"github.com/ollama/ollama/kvcache"
 	"github.com/ollama/ollama/ml"
 	_ "github.com/ollama/ollama/ml/backend"
@@ -83,10 +84,10 @@ func (m *Base) Config() config {
 	return m.config
 }
 
-var models = make(map[string]func(ml.Config) (Model, error))
+var models = make(map[string]func(fs.Config) (Model, error))
 
 // Register registers a model constructor for the given architecture
-func Register(name string, f func(ml.Config) (Model, error)) {
+func Register(name string, f func(fs.Config) (Model, error)) {
 	if _, ok := models[name]; ok {
 		panic("model: model already registered")
 	}
@@ -131,14 +132,14 @@ func NewTextProcessor(s string) (TextProcessor, error) {
 		return nil, err
 	}
 	defer r.Close()
-	meta, _, err := fs.Decode(r, -1)
+	meta, _, err := fsggml.Decode(r, -1)
 	if err != nil {
 		return nil, err
 	}
 	return getTextProcessor(meta.KV())
 }
 
-func getTextProcessor(kv fs.KV) (TextProcessor, error) {
+func getTextProcessor(kv fsggml.KV) (TextProcessor, error) {
 	arch := kv.Architecture()
 	f, ok := models[arch]
 	if !ok {
diff --git a/model/model_test.go b/model/model_test.go
index 0b1ea08e..717c425e 100644
--- a/model/model_test.go
+++ b/model/model_test.go
@@ -7,7 +7,8 @@ import (
 	"testing"
 
 	"github.com/google/go-cmp/cmp"
-	fs "github.com/ollama/ollama/fs/ggml"
+	"github.com/ollama/ollama/fs"
+	fsggml "github.com/ollama/ollama/fs/ggml"
 	"github.com/ollama/ollama/ml"
 	"github.com/ollama/ollama/ml/backend/ggml"
 	"github.com/ollama/ollama/ml/nn"
@@ -139,7 +140,7 @@ func TestPopulateFieldsAlternateName(t *testing.T) {
 }
 
 func TestGetTextProcessor(t *testing.T) {
-	tp, err := getTextProcessor(fs.KV{})
+	tp, err := getTextProcessor(fsggml.KV{})
 	if err == nil {
 		t.Error("expected error")
 	} else if !strings.Contains(err.Error(), "unsupported model architecture") {
@@ -148,10 +149,10 @@ func TestGetTextProcessor(t *testing.T) {
 		t.Error("expected nil tp")
 	}
 
-	models["dummy"] = func(ml.Config) (Model, error) {
+	models["dummy"] = func(fs.Config) (Model, error) {
 		return notTextProcessorModel{}, nil
 	}
-	tp, err = getTextProcessor(fs.KV{"general.architecture": "dummy"})
+	tp, err = getTextProcessor(fsggml.KV{"general.architecture": "dummy"})
 	if err == nil {
 		t.Error("expected error")
 	} else if !strings.Contains(err.Error(), "not a TextProcessor") {
diff --git a/model/models/gemma2/model.go b/model/models/gemma2/model.go
index b8f5f066..752cb5cc 100644
--- a/model/models/gemma2/model.go
+++ b/model/models/gemma2/model.go
@@ -3,6 +3,7 @@ package gemma2
 import (
 	"math"
 
+	"github.com/ollama/ollama/fs"
 	"github.com/ollama/ollama/kvcache"
 	"github.com/ollama/ollama/ml"
 	"github.com/ollama/ollama/ml/nn"
@@ -35,7 +36,7 @@ const (
 	gemma27BLayerCount = 46
 )
 
-func New(c ml.Config) (model.Model, error) {
+func New(c fs.Config) (model.Model, error) {
 	m := Model{
 		SentencePieceModel: model.NewSentencePieceModel(
 			&model.Vocabulary{
diff --git a/model/models/gemma3/model.go b/model/models/gemma3/model.go
index f9c53343..cef058e2 100644
--- a/model/models/gemma3/model.go
+++ b/model/models/gemma3/model.go
@@ -6,6 +6,7 @@ import (
 	"math"
 	"slices"
 
+	"github.com/ollama/ollama/fs"
 	"github.com/ollama/ollama/kvcache"
 	"github.com/ollama/ollama/ml"
 	"github.com/ollama/ollama/ml/nn"
@@ -52,7 +53,7 @@ func (p *MultiModalProjector) Forward(ctx ml.Context, visionOutputs ml.Tensor, i
 	return visionOutputs
 }
 
-func New(c ml.Config) (model.Model, error) {
+func New(c fs.Config) (model.Model, error) {
 	m := Model{
 		SentencePieceModel: model.NewSentencePieceModel(
 			&model.Vocabulary{
diff --git a/model/models/gemma3/model_text.go b/model/models/gemma3/model_text.go
index 7b2b83c0..3b640a96 100644
--- a/model/models/gemma3/model_text.go
+++ b/model/models/gemma3/model_text.go
@@ -3,6 +3,7 @@ package gemma3
 import (
 	"math"
 
+	"github.com/ollama/ollama/fs"
 	"github.com/ollama/ollama/kvcache"
 	"github.com/ollama/ollama/ml"
 	"github.com/ollama/ollama/ml/nn"
@@ -40,7 +41,7 @@ const (
 	cacheTypeCausal
 )
 
-func newTextModel(c ml.Config) *TextModel {
+func newTextModel(c fs.Config) *TextModel {
 	numBlocks := int(c.Uint("block_count"))
 
 	m := TextModel{
diff --git a/model/models/gemma3/model_vision.go b/model/models/gemma3/model_vision.go
index 94aa27bd..636a363d 100644
--- a/model/models/gemma3/model_vision.go
+++ b/model/models/gemma3/model_vision.go
@@ -3,6 +3,7 @@ package gemma3
 import (
 	"math"
 
+	"github.com/ollama/ollama/fs"
 	"github.com/ollama/ollama/ml"
 	"github.com/ollama/ollama/ml/nn"
 )
@@ -111,7 +112,7 @@ func (m *VisionModel) Forward(ctx ml.Context, pixelValues ml.Tensor) ml.Tensor {
 	return hiddenState
 }
 
-func newVisionModel(c ml.Config) *VisionModel {
+func newVisionModel(c fs.Config) *VisionModel {
 	return &VisionModel{
 		Layers: make([]VisionEncoderLayer, c.Uint("vision.block_count")),
 		VisionModelOptions: &VisionModelOptions{
diff --git a/model/models/gemma3/process_image.go b/model/models/gemma3/process_image.go
index fe8269a3..611a17bd 100644
--- a/model/models/gemma3/process_image.go
+++ b/model/models/gemma3/process_image.go
@@ -3,7 +3,7 @@ package gemma3
 import (
 	"image"
 
-	"github.com/ollama/ollama/ml"
+	"github.com/ollama/ollama/fs"
 	"github.com/ollama/ollama/model/imageproc"
 )
 
@@ -11,7 +11,7 @@ type ImageProcessor struct {
 	imageSize, patchSize, numChannels int
 }
 
-func newImageProcessor(c ml.Config) ImageProcessor {
+func newImageProcessor(c fs.Config) ImageProcessor {
 	return ImageProcessor{
 		imageSize:   int(c.Uint("vision.image_size")),
 		patchSize:   int(c.Uint("vision.patch_size")),
diff --git a/model/models/llama/model.go b/model/models/llama/model.go
index 5c173997..68980dd7 100644
--- a/model/models/llama/model.go
+++ b/model/models/llama/model.go
@@ -5,6 +5,7 @@ import (
 	"math"
 	"strings"
 
+	"github.com/ollama/ollama/fs"
 	"github.com/ollama/ollama/kvcache"
 	"github.com/ollama/ollama/ml"
 	"github.com/ollama/ollama/ml/nn"
@@ -30,7 +31,7 @@ type Model struct {
 	*Options
 }
 
-func New(c ml.Config) (model.Model, error) {
+func New(c fs.Config) (model.Model, error) {
 	if !strings.EqualFold(c.String("tokenizer.ggml.model"), "gpt2") {
 		return nil, fmt.Errorf("tokenizer %s not yet supported", c.String("tokenizer.ggml.model"))
 	}
diff --git a/model/models/mllama/model.go b/model/models/mllama/model.go
index 988a189d..e53eb184 100644
--- a/model/models/mllama/model.go
+++ b/model/models/mllama/model.go
@@ -8,6 +8,7 @@ import (
 	"image"
 	"slices"
 
+	"github.com/ollama/ollama/fs"
 	"github.com/ollama/ollama/kvcache"
 	"github.com/ollama/ollama/ml"
 	"github.com/ollama/ollama/ml/nn"
@@ -32,7 +33,7 @@ const (
 	selfAttentionLayer
 )
 
-func New(c ml.Config) (model.Model, error) {
+func New(c fs.Config) (model.Model, error) {
 	// Verify unified config
 	if c.Uint("vision.block_count") == 0 {
 		return nil, fmt.Errorf("non-unified vision model not supported")
diff --git a/model/models/mllama/model_text.go b/model/models/mllama/model_text.go
index 1cf30d89..261897c3 100644
--- a/model/models/mllama/model_text.go
+++ b/model/models/mllama/model_text.go
@@ -4,6 +4,7 @@ import (
 	"math"
 	"slices"
 
+	"github.com/ollama/ollama/fs"
 	"github.com/ollama/ollama/kvcache"
 	"github.com/ollama/ollama/ml"
 	"github.com/ollama/ollama/ml/nn"
@@ -220,7 +221,7 @@ func (m *TextModel) Forward(ctx ml.Context, inputIDs, positionIDs, outputs, mask
 	return m.Output.Forward(ctx, hiddenState)
 }
 
-func newTextModel(c ml.Config) *TextModel {
+func newTextModel(c fs.Config) *TextModel {
 	var decoderLayers []TextDecoderLayer
 	for i := range c.Uint("block_count") {
 		var textDecoderLayer TextDecoderLayer
diff --git a/model/models/mllama/model_vision.go b/model/models/mllama/model_vision.go
index ac777f05..2f7d26ca 100644
--- a/model/models/mllama/model_vision.go
+++ b/model/models/mllama/model_vision.go
@@ -4,6 +4,7 @@ import (
 	"math"
 	"slices"
 
+	"github.com/ollama/ollama/fs"
 	"github.com/ollama/ollama/ml"
 	"github.com/ollama/ollama/ml/nn"
 )
@@ -213,7 +214,7 @@ func (m *VisionModel) Forward(ctx ml.Context, pixelValues, positionIDs, aspectRa
 	return hiddenState.Concat(ctx, hiddenStates, 0)
 }
 
-func newVisionModel(c ml.Config) *VisionModel {
+func newVisionModel(c fs.Config) *VisionModel {
 	return &VisionModel{
 		Transformer:       &VisionEncoder{Layers: make([]VisionEncoderLayer, c.Uint("vision.block_count"))},
 		GlobalTransformer: &VisionEncoder{Layers: make([]VisionEncoderLayer, c.Uint("vision.global.block_count"))},
diff --git a/model/models/mllama/process_image.go b/model/models/mllama/process_image.go
index c94d14a6..1b0506d3 100644
--- a/model/models/mllama/process_image.go
+++ b/model/models/mllama/process_image.go
@@ -8,14 +8,14 @@ import (
 
 	"golang.org/x/image/draw"
 
-	"github.com/ollama/ollama/ml"
+	"github.com/ollama/ollama/fs"
 )
 
 type ImageProcessor struct {
 	imageSize, numChannels, maxNumTiles int
 }
 
-func newImageProcessor(c ml.Config) ImageProcessor {
+func newImageProcessor(c fs.Config) ImageProcessor {
 	return ImageProcessor{
 		imageSize:   int(c.Uint("vision.image_size")),
 		numChannels: int(c.Uint("vision.num_channels")),

From 6bd0a983cd2cf74f27df2e5a5c80f1794a2ed7ef Mon Sep 17 00:00:00 2001
From: Bruce MacDonald <brucewmacdonald@gmail.com>
Date: Fri, 14 Mar 2025 16:56:32 -0700
Subject: [PATCH 156/157] model: support for mistral-small in the ollama runner

Mistral is a popular research lab making open source models. This updates
the forward pass of llama architecture models to support both llama models
and mistral models by accounting for additional metadata present in mistral
models, and finding the correct dimensions for the output projection.
---
 convert/convert.go                            |   4 +-
 convert/convert_mistral.go                    | 190 +++++++++++++++
 convert/reader.go                             |   5 +-
 fs/ggml/ggml.go                               |   7 +-
 kvcache/causal_test.go                        |  26 ++-
 llama/llama.cpp/src/llama-arch.cpp            |  17 ++
 llama/llama.cpp/src/llama-arch.h              |   1 +
 llama/llama.cpp/src/llama-model.cpp           |   3 +
 llama/llama.cpp/src/llama-quant.cpp           |   9 +-
 ...tch => 0021-add-model-quantizations.patch} | 102 ++++++--
 llama/patches/0022-metal-add-op_neg.patch     |  75 ++++++
 ml/backend.go                                 |  10 +-
 ml/backend/ggml/ggml.go                       |  56 +++++
 .../src/ggml-metal/ggml-metal-embed.metal     |   7 +
 .../ggml/ggml/src/ggml-metal/ggml-metal.m     |  15 ++
 .../ggml/ggml/src/ggml-metal/ggml-metal.metal |   7 +
 model/models/gemma3/model_text.go             |  22 +-
 model/models/mistral3/imageproc.go            |  56 +++++
 model/models/mistral3/model.go                | 189 +++++++++++++++
 model/models/mistral3/model_text.go           | 177 ++++++++++++++
 model/models/mistral3/model_vision.go         | 186 +++++++++++++++
 model/models/mllama/model_vision.go           |   2 +-
 model/models/models.go                        |   1 +
 model/models/pixtral/imageproc.go             |  68 ------
 model/models/pixtral/imageproc_test.go        | 219 ------------------
 model/process_text.go                         |   4 +
 parser/parser.go                              |   8 +-
 27 files changed, 1116 insertions(+), 350 deletions(-)
 create mode 100644 convert/convert_mistral.go
 rename llama/patches/{0021-gemma3-quantization.patch => 0021-add-model-quantizations.patch} (52%)
 create mode 100644 llama/patches/0022-metal-add-op_neg.patch
 create mode 100644 model/models/mistral3/imageproc.go
 create mode 100644 model/models/mistral3/model.go
 create mode 100644 model/models/mistral3/model_text.go
 create mode 100644 model/models/mistral3/model_vision.go
 delete mode 100644 model/models/pixtral/imageproc.go
 delete mode 100644 model/models/pixtral/imageproc_test.go

diff --git a/convert/convert.go b/convert/convert.go
index a31b0d6c..26bc72cc 100644
--- a/convert/convert.go
+++ b/convert/convert.go
@@ -182,8 +182,10 @@ func ConvertModel(fsys fs.FS, ws io.WriteSeeker) error {
 
 	var conv ModelConverter
 	switch p.Architectures[0] {
-	case "LlamaForCausalLM", "MistralForCausalLM":
+	case "LlamaForCausalLM":
 		conv = &llamaModel{}
+	case "Mistral3ForConditionalGeneration":
+		conv = &mistral3Model{}
 	case "MixtralForCausalLM":
 		conv = &mixtralModel{}
 	case "GemmaForCausalLM":
diff --git a/convert/convert_mistral.go b/convert/convert_mistral.go
new file mode 100644
index 00000000..6c224ae4
--- /dev/null
+++ b/convert/convert_mistral.go
@@ -0,0 +1,190 @@
+package convert
+
+import (
+	"cmp"
+	"fmt"
+	"strings"
+
+	"github.com/pdevine/tensor"
+	"github.com/pdevine/tensor/native"
+
+	"github.com/ollama/ollama/fs/ggml"
+)
+
+type mistral3Model struct {
+	ModelParameters
+	ImageTokenIndex    uint32 `json:"image_token_index"`
+	SpatialMergeSize   uint32 `json:"spatial_merge_size"`
+	VisionFeatureLayer int32  `json:"vision_feature_layer"`
+	TextModel          struct {
+		NumHiddenLayers       uint32  `json:"num_hidden_layers"`
+		MaxPositionEmbeddings uint32  `json:"max_position_embeddings"`
+		HiddenSize            uint32  `json:"hidden_size"`
+		IntermediateSize      uint32  `json:"intermediate_size"`
+		NumAttentionHeads     uint32  `json:"num_attention_heads"`
+		NumKeyValueHeads      uint32  `json:"num_key_value_heads"`
+		RopeTheta             float32 `json:"rope_theta"`
+		RMSNormEPS            float32 `json:"rms_norm_eps"`
+		HeadDim               uint32  `json:"head_dim"`
+		SlidingWindow         *uint32 `json:"sliding_window"`
+		HiddenAct             string  `json:"hidden_act"`
+		VocabSize             uint32  `json:"vocab_size"`
+	} `json:"text_config"`
+	VisionModel struct {
+		NumAttentionHeads uint32  `json:"num_attention_heads"`
+		NumHiddenLayers   uint32  `json:"num_hidden_layers"`
+		HiddenSize        uint32  `json:"hidden_size"`
+		IntermediateSize  uint32  `json:"intermediate_size"`
+		ImageSize         uint32  `json:"image_size"`
+		NumChannels       uint32  `json:"num_channels"`
+		PatchSize         uint32  `json:"patch_size"`
+		HeadDim           uint32  `json:"head_dim"`
+		HiddenAct         string  `json:"hidden_act"`
+		RopeTheta         float32 `json:"rope_theta"`
+	} `json:"vision_config"`
+	MultiModalProjectorBias bool   `json:"multimodal_projector_bias"`
+	ProjectorHiddenAct      string `json:"projector_hidden_act"`
+}
+
+func (p *mistral3Model) KV(t *Tokenizer) ggml.KV {
+	kv := p.ModelParameters.KV(t)
+	kv["general.architecture"] = "mistral3"
+	kv["mistral3.vocab_size"] = p.TextModel.VocabSize
+
+	// Text configuration
+	kv["mistral3.block_count"] = p.TextModel.NumHiddenLayers
+	kv["mistral3.context_length"] = p.TextModel.MaxPositionEmbeddings
+	kv["mistral3.embedding_length"] = p.TextModel.HiddenSize
+	kv["mistral3.feed_forward_length"] = p.TextModel.IntermediateSize
+	kv["mistral3.attention.head_count"] = p.TextModel.NumAttentionHeads
+	kv["mistral3.attention.head_count_kv"] = p.TextModel.NumKeyValueHeads
+	kv["mistral3.attention.layer_norm_rms_epsilon"] = p.TextModel.RMSNormEPS
+	kv["mistral3.attention.key_length"] = p.TextModel.HeadDim
+	kv["mistral3.attention.value_length"] = p.TextModel.HeadDim
+	kv["mistral3.rope.dimension_count"] = p.TextModel.HiddenSize / p.TextModel.NumHiddenLayers
+	kv["mistral3.rope.freq_base"] = p.TextModel.RopeTheta
+
+	// Vision configuration
+	kv["mistral3.vision.block_count"] = p.VisionModel.NumHiddenLayers
+	kv["mistral3.vision.embedding_length"] = p.VisionModel.HiddenSize
+	kv["mistral3.vision.feed_forward_length"] = p.VisionModel.IntermediateSize
+	kv["mistral3.vision.attention.head_count"] = p.VisionModel.NumAttentionHeads
+	kv["mistral3.vision.attention.key_length"] = p.VisionModel.HeadDim
+	kv["mistral3.vision.image_size"] = p.VisionModel.ImageSize
+	kv["mistral3.vision.patch_size"] = p.VisionModel.PatchSize
+	kv["mistral3.vision.num_channels"] = p.VisionModel.NumChannels
+	// kv["mistral3.vision.attention.layer_norm_epsilon"] = 1e-05 // Default value
+	kv["mistral3.vision.rope.freq_base"] = p.VisionModel.RopeTheta
+
+	// Multimodal configuration
+	kv["mistral3.image_token_index"] = p.ImageTokenIndex
+	kv["mistral3.spatial_merge_size"] = p.SpatialMergeSize
+
+	kv["mistral3.mm.projector_bias"] = p.MultiModalProjectorBias
+
+	if p.ProjectorHiddenAct != "" {
+		kv["mistral3.mm.projector_hidden_act"] = p.ProjectorHiddenAct
+	}
+
+	return kv
+}
+
+func (p *mistral3Model) Tensors(ts []Tensor) []ggml.Tensor {
+	var out []ggml.Tensor
+
+	for _, t := range ts {
+		if !strings.HasPrefix(t.Name(), "v.") {
+			if strings.HasSuffix(t.Name(), ".attn_q.weight") ||
+				strings.HasSuffix(t.Name(), ".attn_k.weight") {
+				t.SetRepacker(p.repack)
+			}
+		}
+
+		out = append(out, ggml.Tensor{
+			Name:     t.Name(),
+			Kind:     t.Kind(),
+			Shape:    t.Shape(),
+			WriterTo: t,
+		})
+	}
+
+	return out
+}
+
+func (p *mistral3Model) Replacements() []string {
+	return []string{
+		"language_model.model.norm", "output_norm",
+		"language_model.model.", "",
+		"language_model.", "",
+		"layers", "blk",
+		"transformer.layers", "blk",
+		"vision_tower", "v",
+		"ln_pre", "encoder_norm",
+		"input_layernorm", "attn_norm",
+		"post_attention_layernorm", "ffn_norm",
+		"embed_tokens", "token_embd",
+		"self_attn.q_proj", "attn_q",
+		"self_attn.k_proj", "attn_k",
+		"self_attn.v_proj", "attn_v",
+		"self_attn.o_proj", "attn_output",
+		"mlp.down_proj", "ffn_down",
+		"mlp.gate_proj", "ffn_gate",
+		"mlp.up_proj", "ffn_up",
+		"attention.q_proj", "attn_q",
+		"attention.k_proj", "attn_k",
+		"attention.v_proj", "attn_v",
+		"attention.o_proj", "attn_output",
+		"attention_norm", "attn_norm",
+		"feed_forward.gate_proj", "ffn_gate",
+		"feed_forward.down_proj", "ffn_down",
+		"feed_forward.up_proj", "ffn_up",
+		"multi_modal_projector", "mm",
+		"ffn_norm", "ffn_norm",
+		"lm_head", "output",
+	}
+}
+
+func (p *mistral3Model) repack(name string, data []float32, shape []uint64) ([]float32, error) {
+	var dims []int
+	for _, dim := range shape {
+		dims = append(dims, int(dim))
+	}
+
+	var heads uint32
+	if strings.HasSuffix(name, ".attn_q.weight") {
+		heads = p.TextModel.NumAttentionHeads
+	} else if strings.HasSuffix(name, ".attn_k.weight") {
+		heads = cmp.Or(p.TextModel.NumKeyValueHeads, p.TextModel.NumAttentionHeads)
+	} else {
+		return nil, fmt.Errorf("unknown tensor for repack: %s", name)
+	}
+
+	n := tensor.New(tensor.WithShape(dims...), tensor.WithBacking(data))
+	if err := n.Reshape(append([]int{int(heads), 2, dims[0] / int(heads) / 2}, dims[1:]...)...); err != nil {
+		return nil, err
+	}
+
+	if err := n.T(0, 2, 1, 3); err != nil {
+		return nil, err
+	}
+
+	if err := n.Reshape(dims...); err != nil {
+		return nil, err
+	}
+
+	if err := n.Transpose(); err != nil {
+		return nil, err
+	}
+
+	ts, err := native.SelectF32(n, 1)
+	if err != nil {
+		return nil, err
+	}
+
+	var f32s []float32
+	for _, t := range ts {
+		f32s = append(f32s, t...)
+	}
+
+	return f32s, nil
+}
diff --git a/convert/reader.go b/convert/reader.go
index c1218e66..904b13a4 100644
--- a/convert/reader.go
+++ b/convert/reader.go
@@ -62,10 +62,7 @@ func parseTensors(fsys fs.FS, replacer *strings.Replacer) ([]Tensor, error) {
 		Pattern string
 		Func    func(fs.FS, *strings.Replacer, ...string) ([]Tensor, error)
 	}{
-		{"model-*-of-*.safetensors", parseSafetensors},
-		{"model.safetensors", parseSafetensors},
-		{"adapters.safetensors", parseSafetensors},
-		{"adapter_model.safetensors", parseSafetensors},
+		{"*.safetensors", parseSafetensors},
 		{"pytorch_model-*-of-*.bin", parseTorch},
 		{"pytorch_model.bin", parseTorch},
 		{"consolidated.*.pth", parseTorch},
diff --git a/fs/ggml/ggml.go b/fs/ggml/ggml.go
index c88583fb..9431e9cc 100644
--- a/fs/ggml/ggml.go
+++ b/fs/ggml/ggml.go
@@ -134,7 +134,10 @@ func (kv KV) Floats(key string, defaultValue ...[]float32) []float32 {
 }
 
 func (kv KV) OllamaEngineRequired() bool {
-	return kv.Architecture() == "gemma3"
+	return slices.Contains([]string{
+		"gemma3",
+		"mistral3",
+	}, kv.Architecture())
 }
 
 func keyValue[T string | uint32 | uint64 | float32 | *array | bool](kv KV, key string, defaultValue ...T) T {
@@ -638,7 +641,7 @@ func (llm GGML) VisionGraphSize() (weights, graphSize uint64) {
 			embeddingLength*numPatches*maxNumTiles +
 			9*embeddingLength*numPaddedPatches*maxNumTiles +
 			numPaddedPatches*maxNumTiles*numPaddedPatches*maxNumTiles*headCount)
-	case "gemma3":
+	case "gemma3", "mistral3":
 		graphSize = 4 * (imageSize*imageSize*numChannels +
 			embeddingLength*patchSize +
 			numPatches*numPatches*headCount)
diff --git a/kvcache/causal_test.go b/kvcache/causal_test.go
index 517e3726..bd63214c 100644
--- a/kvcache/causal_test.go
+++ b/kvcache/causal_test.go
@@ -484,6 +484,14 @@ func (t *testTensor) Floats() []float32 {
 	return out
 }
 
+func (t *testTensor) Neg(ctx ml.Context) ml.Tensor {
+	out := ctx.Empty(t.DType(), t.Shape()...).(*testTensor)
+	for i := range out.data {
+		out.data[i] = -t.data[i]
+	}
+	return out
+}
+
 func (t *testTensor) Add(ctx ml.Context, t2 ml.Tensor) ml.Tensor {
 	out := ctx.Empty(t.DType(), t.Shape()...).(*testTensor)
 
@@ -538,17 +546,15 @@ func (t *testTensor) RoPE(ctx ml.Context, positionIDs, ropeFactors ml.Tensor, di
 	panic("not implemented")
 }
 
-func (t *testTensor) Tanh(ctx ml.Context) ml.Tensor {
+func (t *testTensor) IM2Col(ctx ml.Context, weight ml.Tensor, s0, s1, p0, p1, d0, d1 int) ml.Tensor {
 	panic("not implemented")
 }
 
-func (t *testTensor) GELU(ctx ml.Context) ml.Tensor {
-	panic("not implemented")
-}
-
-func (t *testTensor) SILU(ctx ml.Context) ml.Tensor {
-	panic("not implemented")
-}
+func (t *testTensor) Cos(ctx ml.Context) ml.Tensor  { panic("not implemented") }
+func (t *testTensor) Sin(ctx ml.Context) ml.Tensor  { panic("not implemented") }
+func (t *testTensor) Tanh(ctx ml.Context) ml.Tensor { panic("not implemented") }
+func (t *testTensor) GELU(ctx ml.Context) ml.Tensor { panic("not implemented") }
+func (t *testTensor) SILU(ctx ml.Context) ml.Tensor { panic("not implemented") }
 
 func (t *testTensor) Reshape(ctx ml.Context, shape ...int) ml.Tensor {
 	panic("not implemented")
@@ -600,6 +606,8 @@ func (t *testTensor) Stack(ctx ml.Context, dim int, s ...ml.Tensor) ml.Tensor {
 	panic("not implemented")
 }
 
+func (t *testTensor) Repeat(ctx ml.Context, dim, n int) ml.Tensor { panic("not implemented") }
+
 func (t *testTensor) Concat(ctx ml.Context, t2 ml.Tensor, dim int) ml.Tensor {
 	panic("not implemented")
 }
@@ -612,3 +620,5 @@ func (t *testTensor) Copy(ctx ml.Context, t2 ml.Tensor) ml.Tensor {
 	copy(t2.(*testTensor).data, t.data)
 	return nil
 }
+
+func (t *testTensor) Duplicate(ctx ml.Context) ml.Tensor { panic("not implemented") }
diff --git a/llama/llama.cpp/src/llama-arch.cpp b/llama/llama.cpp/src/llama-arch.cpp
index b443fcd3..13a0a988 100644
--- a/llama/llama.cpp/src/llama-arch.cpp
+++ b/llama/llama.cpp/src/llama-arch.cpp
@@ -65,6 +65,7 @@ static const std::map<llm_arch, const char *> LLM_ARCH_NAMES = {
     { LLM_ARCH_CHAMELEON,        "chameleon"        },
     { LLM_ARCH_SOLAR,            "solar"            },
     { LLM_ARCH_WAVTOKENIZER_DEC, "wavtokenizer-dec" },
+    { LLM_ARCH_MISTRAL3,         "mistral3"         },
     { LLM_ARCH_UNKNOWN,          "(unknown)"        },
 };
 
@@ -1371,6 +1372,22 @@ static const std::map<llm_arch, std::map<llm_tensor, const char *>> LLM_TENSOR_N
             { LLM_TENSOR_POS_NET_ATTN_OUT,  "posnet.%d.attn_output" },
         },
     },
+    {
+        LLM_ARCH_MISTRAL3,
+        {
+            { LLM_TENSOR_TOKEN_EMBD,  "token_embd" },
+            { LLM_TENSOR_OUTPUT_NORM, "output_norm" },
+            { LLM_TENSOR_ATTN_NORM,   "blk.%d.attn_norm" },
+            { LLM_TENSOR_ATTN_Q,      "blk.%d.attn_q" },
+            { LLM_TENSOR_ATTN_K,      "blk.%d.attn_k" },
+            { LLM_TENSOR_ATTN_V,      "blk.%d.attn_v" },
+            { LLM_TENSOR_ATTN_OUT,    "blk.%d.attn_output" },
+            { LLM_TENSOR_FFN_NORM,    "blk.%d.ffn_norm" },
+            { LLM_TENSOR_FFN_GATE,    "blk.%d.ffn_gate" },
+            { LLM_TENSOR_FFN_UP,      "blk.%d.ffn_up" },
+            { LLM_TENSOR_FFN_DOWN,    "blk.%d.ffn_down" },
+        }
+    },
     {
         LLM_ARCH_UNKNOWN,
         {
diff --git a/llama/llama.cpp/src/llama-arch.h b/llama/llama.cpp/src/llama-arch.h
index aad92a5d..8476ae0a 100644
--- a/llama/llama.cpp/src/llama-arch.h
+++ b/llama/llama.cpp/src/llama-arch.h
@@ -69,6 +69,7 @@ enum llm_arch {
     LLM_ARCH_CHAMELEON,
     LLM_ARCH_SOLAR,
     LLM_ARCH_WAVTOKENIZER_DEC,
+    LLM_ARCH_MISTRAL3,
     LLM_ARCH_UNKNOWN,
 };
 
diff --git a/llama/llama.cpp/src/llama-model.cpp b/llama/llama.cpp/src/llama-model.cpp
index 70183041..db4f2685 100644
--- a/llama/llama.cpp/src/llama-model.cpp
+++ b/llama/llama.cpp/src/llama-model.cpp
@@ -1277,6 +1277,7 @@ void llama_model::load_hparams(llama_model_loader & ml) {
                 ml.get_key(LLM_KV_ATTENTION_GROUPNORM_GROUPS, hparams.n_norm_groups);
                 ml.get_key(LLM_KV_ATTENTION_CAUSAL,           hparams.causal_attn);
             } break;
+        case LLM_ARCH_MISTRAL3: break;
         default: throw std::runtime_error("unsupported model architecture");
     }
 
@@ -3537,6 +3538,7 @@ bool llama_model::load_tensors(llama_model_loader & ml) {
                     output   = create_tensor(tn(LLM_TENSOR_OUTPUT, "weight"), {hparams.convnext.n_embd, n_embd}, 0);
                     output_b = create_tensor(tn(LLM_TENSOR_OUTPUT, "bias"),   {n_embd}, 0);
                 } break;
+            case LLM_ARCH_MISTRAL3: break;
             default:
                 throw std::runtime_error("unknown architecture");
         }
@@ -4015,6 +4017,7 @@ enum llama_rope_type llama_model_rope_type(const struct llama_model * model) {
         case LLM_ARCH_GRANITE_MOE:
         case LLM_ARCH_CHAMELEON:
         case LLM_ARCH_SOLAR:
+        case LLM_ARCH_MISTRAL3:
             return LLAMA_ROPE_TYPE_NORM;
 
         // the pairs of head values are offset by n_rot/2
diff --git a/llama/llama.cpp/src/llama-quant.cpp b/llama/llama.cpp/src/llama-quant.cpp
index d2f3a510..ebcbafa1 100644
--- a/llama/llama.cpp/src/llama-quant.cpp
+++ b/llama/llama.cpp/src/llama-quant.cpp
@@ -738,13 +738,8 @@ static void llama_model_quantize_impl(const std::string & fname_inp, const std::
         bool quantize = name.rfind("weight") == name.size() - 6; // ends with 'weight'?
 
         // don't quantize vision stuff
-        quantize &= name.find("v.blk.") == std::string::npos;
-
-        quantize &= name.find("mm.mm_input_projection.weight") == std::string::npos;
-        quantize &= name.find("mm.mm_soft_emb_norm.weight") == std::string::npos;
-        quantize &= name.find("v.patch_embedding.weight") == std::string::npos;
-        quantize &= name.find("v.position_embedding.weight") == std::string::npos;
-        quantize &= name.find("v.post_layernorm.weight") == std::string::npos;
+        quantize &= name.find("v.") == std::string::npos;
+        quantize &= name.find("mm.") == std::string::npos;
 
         // quantize only 2D and 3D tensors (experts)
         quantize &= (ggml_n_dims(tensor) >= 2);
diff --git a/llama/patches/0021-gemma3-quantization.patch b/llama/patches/0021-add-model-quantizations.patch
similarity index 52%
rename from llama/patches/0021-gemma3-quantization.patch
rename to llama/patches/0021-add-model-quantizations.patch
index 4f6dbc11..cdc35a41 100644
--- a/llama/patches/0021-gemma3-quantization.patch
+++ b/llama/patches/0021-add-model-quantizations.patch
@@ -1,17 +1,19 @@
 From 0000000000000000000000000000000000000000 Mon Sep 17 00:00:00 2001
 From: Patrick Devine <patrick@infrahq.com>
 Date: Fri, 14 Mar 2025 16:33:23 -0700
-Subject: [PATCH] gemma3 quantization
+Subject: [PATCH] add model quantizations
 
+- gemma3
+- mistral3
 ---
- src/llama-arch.cpp  | 19 +++++++++++++++++++
- src/llama-arch.h    |  1 +
- src/llama-model.cpp |  7 +++++++
- src/llama-quant.cpp |  9 +++++++++
- 4 files changed, 36 insertions(+)
+ src/llama-arch.cpp  | 36 ++++++++++++++++++++++++++++++++++++
+ src/llama-arch.h    |  2 ++
+ src/llama-model.cpp | 10 ++++++++++
+ src/llama-quant.cpp |  4 ++++
+ 4 files changed, 52 insertions(+)
 
 diff --git a/src/llama-arch.cpp b/src/llama-arch.cpp
-index b6f20286..b443fcd3 100644
+index b6f20286..13a0a988 100644
 --- a/src/llama-arch.cpp
 +++ b/src/llama-arch.cpp
 @@ -37,6 +37,7 @@ static const std::map<llm_arch, const char *> LLM_ARCH_NAMES = {
@@ -22,7 +24,15 @@ index b6f20286..b443fcd3 100644
      { LLM_ARCH_STARCODER2,       "starcoder2"       },
      { LLM_ARCH_MAMBA,            "mamba"            },
      { LLM_ARCH_XVERSE,           "xverse"           },
-@@ -804,6 +805,24 @@ static const std::map<llm_arch, std::map<llm_tensor, const char *>> LLM_TENSOR_N
+@@ -64,6 +65,7 @@ static const std::map<llm_arch, const char *> LLM_ARCH_NAMES = {
+     { LLM_ARCH_CHAMELEON,        "chameleon"        },
+     { LLM_ARCH_SOLAR,            "solar"            },
+     { LLM_ARCH_WAVTOKENIZER_DEC, "wavtokenizer-dec" },
++    { LLM_ARCH_MISTRAL3,         "mistral3"         },
+     { LLM_ARCH_UNKNOWN,          "(unknown)"        },
+ };
+ 
+@@ -804,6 +806,24 @@ static const std::map<llm_arch, std::map<llm_tensor, const char *>> LLM_TENSOR_N
              { LLM_TENSOR_FFN_POST_NORM,   "blk.%d.post_ffw_norm" },
          },
      },
@@ -47,8 +57,31 @@ index b6f20286..b443fcd3 100644
      {
          LLM_ARCH_STARCODER2,
          {
+@@ -1352,6 +1372,22 @@ static const std::map<llm_arch, std::map<llm_tensor, const char *>> LLM_TENSOR_N
+             { LLM_TENSOR_POS_NET_ATTN_OUT,  "posnet.%d.attn_output" },
+         },
+     },
++    {
++        LLM_ARCH_MISTRAL3,
++        {
++            { LLM_TENSOR_TOKEN_EMBD,  "token_embd" },
++            { LLM_TENSOR_OUTPUT_NORM, "output_norm" },
++            { LLM_TENSOR_ATTN_NORM,   "blk.%d.attn_norm" },
++            { LLM_TENSOR_ATTN_Q,      "blk.%d.attn_q" },
++            { LLM_TENSOR_ATTN_K,      "blk.%d.attn_k" },
++            { LLM_TENSOR_ATTN_V,      "blk.%d.attn_v" },
++            { LLM_TENSOR_ATTN_OUT,    "blk.%d.attn_output" },
++            { LLM_TENSOR_FFN_NORM,    "blk.%d.ffn_norm" },
++            { LLM_TENSOR_FFN_GATE,    "blk.%d.ffn_gate" },
++            { LLM_TENSOR_FFN_UP,      "blk.%d.ffn_up" },
++            { LLM_TENSOR_FFN_DOWN,    "blk.%d.ffn_down" },
++        }
++    },
+     {
+         LLM_ARCH_UNKNOWN,
+         {
 diff --git a/src/llama-arch.h b/src/llama-arch.h
-index ec742224..aad92a5d 100644
+index ec742224..8476ae0a 100644
 --- a/src/llama-arch.h
 +++ b/src/llama-arch.h
 @@ -41,6 +41,7 @@ enum llm_arch {
@@ -59,8 +92,16 @@ index ec742224..aad92a5d 100644
      LLM_ARCH_STARCODER2,
      LLM_ARCH_MAMBA,
      LLM_ARCH_XVERSE,
+@@ -68,6 +69,7 @@ enum llm_arch {
+     LLM_ARCH_CHAMELEON,
+     LLM_ARCH_SOLAR,
+     LLM_ARCH_WAVTOKENIZER_DEC,
++    LLM_ARCH_MISTRAL3,
+     LLM_ARCH_UNKNOWN,
+ };
+ 
 diff --git a/src/llama-model.cpp b/src/llama-model.cpp
-index ab1a07d1..70183041 100644
+index ab1a07d1..db4f2685 100644
 --- a/src/llama-model.cpp
 +++ b/src/llama-model.cpp
 @@ -878,6 +878,9 @@ void llama_model::load_hparams(llama_model_loader & ml) {
@@ -73,7 +114,15 @@ index ab1a07d1..70183041 100644
          case LLM_ARCH_STARCODER2:
              {
                  ml.get_key(LLM_KV_ATTENTION_LAYERNORM_EPS, hparams.f_norm_eps);
-@@ -2537,6 +2540,9 @@ bool llama_model::load_tensors(llama_model_loader & ml) {
+@@ -1274,6 +1277,7 @@ void llama_model::load_hparams(llama_model_loader & ml) {
+                 ml.get_key(LLM_KV_ATTENTION_GROUPNORM_GROUPS, hparams.n_norm_groups);
+                 ml.get_key(LLM_KV_ATTENTION_CAUSAL,           hparams.causal_attn);
+             } break;
++        case LLM_ARCH_MISTRAL3: break;
+         default: throw std::runtime_error("unsupported model architecture");
+     }
+ 
+@@ -2537,6 +2541,9 @@ bool llama_model::load_tensors(llama_model_loader & ml) {
                          layer.ffn_post_norm = create_tensor(tn(LLM_TENSOR_FFN_POST_NORM, "weight", i), {n_embd}, 0);
                      }
                  } break;
@@ -83,7 +132,23 @@ index ab1a07d1..70183041 100644
              case LLM_ARCH_STARCODER2:
                  {
                      tok_embd = create_tensor(tn(LLM_TENSOR_TOKEN_EMBD, "weight"), {n_embd, n_vocab}, 0);
-@@ -4029,6 +4035,7 @@ enum llama_rope_type llama_model_rope_type(const struct llama_model * model) {
+@@ -3531,6 +3538,7 @@ bool llama_model::load_tensors(llama_model_loader & ml) {
+                     output   = create_tensor(tn(LLM_TENSOR_OUTPUT, "weight"), {hparams.convnext.n_embd, n_embd}, 0);
+                     output_b = create_tensor(tn(LLM_TENSOR_OUTPUT, "bias"),   {n_embd}, 0);
+                 } break;
++            case LLM_ARCH_MISTRAL3: break;
+             default:
+                 throw std::runtime_error("unknown architecture");
+         }
+@@ -4009,6 +4017,7 @@ enum llama_rope_type llama_model_rope_type(const struct llama_model * model) {
+         case LLM_ARCH_GRANITE_MOE:
+         case LLM_ARCH_CHAMELEON:
+         case LLM_ARCH_SOLAR:
++        case LLM_ARCH_MISTRAL3:
+             return LLAMA_ROPE_TYPE_NORM;
+ 
+         // the pairs of head values are offset by n_rot/2
+@@ -4029,6 +4038,7 @@ enum llama_rope_type llama_model_rope_type(const struct llama_model * model) {
          case LLM_ARCH_PHIMOE:
          case LLM_ARCH_GEMMA:
          case LLM_ARCH_GEMMA2:
@@ -92,21 +157,16 @@ index ab1a07d1..70183041 100644
          case LLM_ARCH_OPENELM:
          case LLM_ARCH_GPTNEOX:
 diff --git a/src/llama-quant.cpp b/src/llama-quant.cpp
-index 6eb1da08..d2f3a510 100644
+index 6eb1da08..ebcbafa1 100644
 --- a/src/llama-quant.cpp
 +++ b/src/llama-quant.cpp
-@@ -737,6 +737,15 @@ static void llama_model_quantize_impl(const std::string & fname_inp, const std::
+@@ -737,6 +737,10 @@ static void llama_model_quantize_impl(const std::string & fname_inp, const std::
          // This used to be a regex, but <regex> has an extreme cost to compile times.
          bool quantize = name.rfind("weight") == name.size() - 6; // ends with 'weight'?
  
 +        // don't quantize vision stuff
-+        quantize &= name.find("v.blk.") == std::string::npos;
-+
-+        quantize &= name.find("mm.mm_input_projection.weight") == std::string::npos;
-+        quantize &= name.find("mm.mm_soft_emb_norm.weight") == std::string::npos;
-+        quantize &= name.find("v.patch_embedding.weight") == std::string::npos;
-+        quantize &= name.find("v.position_embedding.weight") == std::string::npos;
-+        quantize &= name.find("v.post_layernorm.weight") == std::string::npos;
++        quantize &= name.find("v.") == std::string::npos;
++        quantize &= name.find("mm.") == std::string::npos;
 +
          // quantize only 2D and 3D tensors (experts)
          quantize &= (ggml_n_dims(tensor) >= 2);
diff --git a/llama/patches/0022-metal-add-op_neg.patch b/llama/patches/0022-metal-add-op_neg.patch
new file mode 100644
index 00000000..a903535f
--- /dev/null
+++ b/llama/patches/0022-metal-add-op_neg.patch
@@ -0,0 +1,75 @@
+From 0000000000000000000000000000000000000000 Mon Sep 17 00:00:00 2001
+From: Michael Yang <git@mxy.ng>
+Date: Wed, 2 Apr 2025 15:26:15 -0700
+Subject: [PATCH] metal: add op_neg
+
+---
+ ggml/src/ggml-metal/ggml-metal.m     | 15 +++++++++++++++
+ ggml/src/ggml-metal/ggml-metal.metal |  7 +++++++
+ 2 files changed, 22 insertions(+)
+
+diff --git a/ggml/src/ggml-metal/ggml-metal.m b/ggml/src/ggml-metal/ggml-metal.m
+index e4c093f9..d8422f1b 100644
+--- a/ggml/src/ggml-metal/ggml-metal.m
++++ b/ggml/src/ggml-metal/ggml-metal.m
+@@ -423,6 +423,7 @@ enum ggml_metal_kernel_type {
+     GGML_METAL_KERNEL_TYPE_SQRT,
+     GGML_METAL_KERNEL_TYPE_SIN,
+     GGML_METAL_KERNEL_TYPE_COS,
++    GGML_METAL_KERNEL_TYPE_NEG,
+     GGML_METAL_KERNEL_TYPE_SUM_ROWS,
+     GGML_METAL_KERNEL_TYPE_POOL_2D_AVG_F32,
+     GGML_METAL_KERNEL_TYPE_POOL_2D_MAX_F32,
+@@ -1039,6 +1040,7 @@ static struct ggml_backend_metal_context * ggml_metal_init(ggml_backend_dev_t de
+         GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_SQRT,                          sqrt,                           true);
+         GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_SIN,                           sin,                            true);
+         GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_COS,                           cos,                            true);
++        GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_NEG,                           neg,                            true);
+         GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_SUM_ROWS,                      sum_rows,                       true);
+         GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_ARGMAX,                        argmax,                         true);
+         GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_POOL_2D_AVG_F32,               pool_2d_avg_f32,                true);
+@@ -1202,6 +1204,7 @@ static bool ggml_metal_supports_op(const struct ggml_backend_metal_device_contex
+                 case GGML_UNARY_OP_GELU_QUICK:
+                 case GGML_UNARY_OP_SILU:
+                 case GGML_UNARY_OP_ELU:
++                case GGML_UNARY_OP_NEG:
+                     return ggml_is_contiguous(op->src[0]);
+                 default:
+                     return false;
+@@ -1873,6 +1876,18 @@ static void ggml_metal_encode_node(
+ 
+                     [encoder dispatchThreadgroups:MTLSizeMake(n, 1, 1) threadsPerThreadgroup:MTLSizeMake(1, 1, 1)];
+                 } break;
++                case GGML_UNARY_OP_NEG:
++                {
++                    id<MTLComputePipelineState> pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_NEG].pipeline;
++
++                    [encoder setComputePipelineState:pipeline];
++                    [encoder setBuffer:id_src0 offset:offs_src0 atIndex:0];
++                    [encoder setBuffer:id_dst  offset:offs_dst  atIndex:1];
++
++                    const int64_t n = ggml_nelements(dst);
++
++                    [encoder dispatchThreadgroups:MTLSizeMake(n, 1, 1) threadsPerThreadgroup:MTLSizeMake(1, 1, 1)];
++                } break;
+                 default:
+                 {
+                     GGML_LOG_WARN("%s: node %3d, op = %8s not implemented\n", __func__, idx, ggml_op_name(dst->op));
+diff --git a/ggml/src/ggml-metal/ggml-metal.metal b/ggml/src/ggml-metal/ggml-metal.metal
+index f38909d0..bb0ff668 100644
+--- a/ggml/src/ggml-metal/ggml-metal.metal
++++ b/ggml/src/ggml-metal/ggml-metal.metal
+@@ -945,6 +945,13 @@ kernel void kernel_cos(
+     dst[tpig] = cos(src0[tpig]);
+ }
+ 
++kernel void kernel_neg(
++        device const float * src0,
++        device       float * dst,
++        uint tpig[[thread_position_in_grid]]) {
++    dst[tpig] = -src0[tpig];
++}
++
+ kernel void kernel_sum_rows(
+         device const float * src0,
+         device       float * dst,
diff --git a/ml/backend.go b/ml/backend.go
index b22ba795..fffc04a4 100644
--- a/ml/backend.go
+++ b/ml/backend.go
@@ -118,6 +118,7 @@ type Tensor interface {
 	Bytes() []byte
 	Floats() []float32
 
+	Neg(ctx Context) Tensor
 	Add(ctx Context, t2 Tensor) Tensor
 	Mul(ctx Context, t2 Tensor) Tensor
 	Mulmat(ctx Context, t2 Tensor) Tensor
@@ -132,7 +133,10 @@ type Tensor interface {
 	Conv2D(ctx Context, weight Tensor, s0, s1, p0, p1, d0, d1 int) Tensor
 
 	RoPE(ctx Context, positionIDs, ropeFactors Tensor, dim, ropeType uint32, base, scale float32) Tensor
+	IM2Col(ctx Context, weight Tensor, s0, s1, p0, p1, d0, d1 int) Tensor
 
+	Sin(ctx Context) Tensor
+	Cos(ctx Context) Tensor
 	Tanh(ctx Context) Tensor
 	GELU(ctx Context) Tensor
 	SILU(ctx Context) Tensor
@@ -147,9 +151,13 @@ type Tensor interface {
 	Unpad(ctx Context, shape ...int) Tensor
 
 	Stack(ctx Context, dim int, s ...Tensor) Tensor
+
+	// Repeat repeats the tensor n times along dimension dim
+	Repeat(ctx Context, dim, n int) Tensor
 	Concat(ctx Context, t2 Tensor, dim int) Tensor
 	Rows(ctx Context, t2 Tensor) Tensor
 	Copy(ctx Context, t2 Tensor) Tensor
+	Duplicate(ctx Context) Tensor
 }
 
 // ScaledDotProductAttention implements a fused attention
@@ -214,7 +222,7 @@ func Dump(ctx Context, t Tensor, opts ...DumpOptions) string {
 			return strconv.FormatFloat(float64(f), 'f', opts[0].Precision, 32)
 		})
 	case DTypeF16, DTypeQ80, DTypeQ40:
-		f32 := ctx.Empty(DTypeF32, t.Shape()...)
+		f32 := ctx.Input().Empty(DTypeF32, t.Shape()...)
 		f32 = t.Copy(ctx, f32)
 		return dump[[]float32](ctx, f32, opts[0].Items, func(f float32) string {
 			return strconv.FormatFloat(float64(f), 'f', opts[0].Precision, 32)
diff --git a/ml/backend/ggml/ggml.go b/ml/backend/ggml/ggml.go
index 17f06384..a106fed5 100644
--- a/ml/backend/ggml/ggml.go
+++ b/ml/backend/ggml/ggml.go
@@ -711,6 +711,13 @@ func (t *Tensor) DType() ml.DType {
 	}
 }
 
+func (t *Tensor) Neg(ctx ml.Context) ml.Tensor {
+	return &Tensor{
+		b: t.b,
+		t: C.ggml_neg(ctx.(*Context).ctx, t.t),
+	}
+}
+
 func (t *Tensor) Add(ctx ml.Context, t2 ml.Tensor) ml.Tensor {
 	return &Tensor{
 		b: t.b,
@@ -718,6 +725,27 @@ func (t *Tensor) Add(ctx ml.Context, t2 ml.Tensor) ml.Tensor {
 	}
 }
 
+func (t *Tensor) Repeat(ctx ml.Context, dim, n int) ml.Tensor {
+	if dim < 0 || dim >= C.GGML_MAX_DIMS {
+		panic("invalid dimension")
+	}
+
+	shape := make([]C.int64_t, C.GGML_MAX_DIMS)
+	for i := range C.GGML_MAX_DIMS {
+		if i == dim {
+			shape[i] = C.int64_t(t.Dim(i) * n)
+		} else {
+			shape[i] = C.int64_t(t.Dim(i))
+		}
+	}
+
+	tmpl := C.ggml_new_tensor(ctx.(*Context).ctx, t.t._type, C.int(len(shape)), unsafe.SliceData(shape))
+	return &Tensor{
+		b: t.b,
+		t: C.ggml_repeat(ctx.(*Context).ctx, t.t, tmpl),
+	}
+}
+
 func (t *Tensor) Stack(ctx ml.Context, dim int, s ...ml.Tensor) ml.Tensor {
 	if len(s) > 0 {
 		return t.Concat(ctx, s[0].Stack(ctx, dim, s[1:]...), dim)
@@ -854,6 +882,20 @@ func (t *Tensor) Softmax(ctx ml.Context) ml.Tensor {
 	}
 }
 
+func (t *Tensor) Sin(ctx ml.Context) ml.Tensor {
+	return &Tensor{
+		b: t.b,
+		t: C.ggml_sin(ctx.(*Context).ctx, t.t),
+	}
+}
+
+func (t *Tensor) Cos(ctx ml.Context) ml.Tensor {
+	return &Tensor{
+		b: t.b,
+		t: C.ggml_cos(ctx.(*Context).ctx, t.t),
+	}
+}
+
 func (t *Tensor) Tanh(ctx ml.Context) ml.Tensor {
 	return &Tensor{
 		b: t.b,
@@ -942,6 +984,13 @@ func (t *Tensor) RoPE(ctx ml.Context, positionIDs, ropeFactors ml.Tensor, ropeDi
 	}
 }
 
+func (t *Tensor) IM2Col(ctx ml.Context, t2 ml.Tensor, s0, s1, p0, p1, d0, d1 int) ml.Tensor {
+	return &Tensor{
+		b: t.b,
+		t: C.ggml_im2col(ctx.(*Context).ctx, t.t, t2.(*Tensor).t, C.int(s0), C.int(s1), C.int(p0), C.int(p1), C.int(d0), C.int(d1), true, C.GGML_TYPE_F32),
+	}
+}
+
 func (t *Tensor) GELU(ctx ml.Context) ml.Tensor {
 	return &Tensor{
 		b: t.b,
@@ -1010,3 +1059,10 @@ func (t *Tensor) ScaledDotProductAttention(ctx ml.Context, key, value, mask ml.T
 		return kqv.Permute(ctx, 0, 2, 1, 3).Contiguous(ctx)
 	}
 }
+
+func (t *Tensor) Duplicate(ctx ml.Context) ml.Tensor {
+	return &Tensor{
+		b: t.b,
+		t: C.ggml_dup(ctx.(*Context).ctx, t.t),
+	}
+}
diff --git a/ml/backend/ggml/ggml/src/ggml-metal/ggml-metal-embed.metal b/ml/backend/ggml/ggml/src/ggml-metal/ggml-metal-embed.metal
index c3610ac0..a2f599ce 100644
--- a/ml/backend/ggml/ggml/src/ggml-metal/ggml-metal-embed.metal
+++ b/ml/backend/ggml/ggml/src/ggml-metal/ggml-metal-embed.metal
@@ -3083,6 +3083,13 @@ kernel void kernel_cos(
     dst[tpig] = cos(src0[tpig]);
 }
 
+kernel void kernel_neg(
+        device const float * src0,
+        device       float * dst,
+        uint tpig[[thread_position_in_grid]]) {
+    dst[tpig] = -src0[tpig];
+}
+
 kernel void kernel_sum_rows(
         device const float * src0,
         device       float * dst,
diff --git a/ml/backend/ggml/ggml/src/ggml-metal/ggml-metal.m b/ml/backend/ggml/ggml/src/ggml-metal/ggml-metal.m
index e4c093f9..d8422f1b 100644
--- a/ml/backend/ggml/ggml/src/ggml-metal/ggml-metal.m
+++ b/ml/backend/ggml/ggml/src/ggml-metal/ggml-metal.m
@@ -423,6 +423,7 @@ enum ggml_metal_kernel_type {
     GGML_METAL_KERNEL_TYPE_SQRT,
     GGML_METAL_KERNEL_TYPE_SIN,
     GGML_METAL_KERNEL_TYPE_COS,
+    GGML_METAL_KERNEL_TYPE_NEG,
     GGML_METAL_KERNEL_TYPE_SUM_ROWS,
     GGML_METAL_KERNEL_TYPE_POOL_2D_AVG_F32,
     GGML_METAL_KERNEL_TYPE_POOL_2D_MAX_F32,
@@ -1039,6 +1040,7 @@ static struct ggml_backend_metal_context * ggml_metal_init(ggml_backend_dev_t de
         GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_SQRT,                          sqrt,                           true);
         GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_SIN,                           sin,                            true);
         GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_COS,                           cos,                            true);
+        GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_NEG,                           neg,                            true);
         GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_SUM_ROWS,                      sum_rows,                       true);
         GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_ARGMAX,                        argmax,                         true);
         GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_POOL_2D_AVG_F32,               pool_2d_avg_f32,                true);
@@ -1202,6 +1204,7 @@ static bool ggml_metal_supports_op(const struct ggml_backend_metal_device_contex
                 case GGML_UNARY_OP_GELU_QUICK:
                 case GGML_UNARY_OP_SILU:
                 case GGML_UNARY_OP_ELU:
+                case GGML_UNARY_OP_NEG:
                     return ggml_is_contiguous(op->src[0]);
                 default:
                     return false;
@@ -1873,6 +1876,18 @@ static void ggml_metal_encode_node(
 
                     [encoder dispatchThreadgroups:MTLSizeMake(n, 1, 1) threadsPerThreadgroup:MTLSizeMake(1, 1, 1)];
                 } break;
+                case GGML_UNARY_OP_NEG:
+                {
+                    id<MTLComputePipelineState> pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_NEG].pipeline;
+
+                    [encoder setComputePipelineState:pipeline];
+                    [encoder setBuffer:id_src0 offset:offs_src0 atIndex:0];
+                    [encoder setBuffer:id_dst  offset:offs_dst  atIndex:1];
+
+                    const int64_t n = ggml_nelements(dst);
+
+                    [encoder dispatchThreadgroups:MTLSizeMake(n, 1, 1) threadsPerThreadgroup:MTLSizeMake(1, 1, 1)];
+                } break;
                 default:
                 {
                     GGML_LOG_WARN("%s: node %3d, op = %8s not implemented\n", __func__, idx, ggml_op_name(dst->op));
diff --git a/ml/backend/ggml/ggml/src/ggml-metal/ggml-metal.metal b/ml/backend/ggml/ggml/src/ggml-metal/ggml-metal.metal
index f38909d0..bb0ff668 100644
--- a/ml/backend/ggml/ggml/src/ggml-metal/ggml-metal.metal
+++ b/ml/backend/ggml/ggml/src/ggml-metal/ggml-metal.metal
@@ -945,6 +945,13 @@ kernel void kernel_cos(
     dst[tpig] = cos(src0[tpig]);
 }
 
+kernel void kernel_neg(
+        device const float * src0,
+        device       float * dst,
+        uint tpig[[thread_position_in_grid]]) {
+    dst[tpig] = -src0[tpig];
+}
+
 kernel void kernel_sum_rows(
         device const float * src0,
         device       float * dst,
diff --git a/model/models/gemma3/model_text.go b/model/models/gemma3/model_text.go
index 3b640a96..2d7bb20a 100644
--- a/model/models/gemma3/model_text.go
+++ b/model/models/gemma3/model_text.go
@@ -11,7 +11,7 @@ import (
 	"github.com/ollama/ollama/model/input"
 )
 
-type TextOptions struct {
+type TextConfig struct {
 	hiddenSize, numHeads, numKVHeads int
 	attnKeyLen, attnValLen           int
 	eps, ropeScale                   float32
@@ -28,7 +28,7 @@ type TextModel struct {
 	OutputNorm     *nn.RMSNorm   `gguf:"output_norm"`
 	Output         *nn.Linear    `gguf:"output,alt:token_embd"`
 
-	*TextOptions
+	*TextConfig
 }
 
 const (
@@ -55,7 +55,7 @@ func newTextModel(c fs.Config) *TextModel {
 			},
 		),
 		Layers: make([]TextLayer, numBlocks),
-		TextOptions: &TextOptions{
+		TextConfig: &TextConfig{
 			hiddenSize:     int(c.Uint("embedding_length")),
 			numHeads:       int(c.Uint("attention.head_count")),
 			numKVHeads:     int(c.Uint("attention.head_count_kv")),
@@ -84,7 +84,7 @@ type TextSelfAttention struct {
 	Output    *nn.Linear  `gguf:"attn_output"`
 }
 
-func (sa *TextSelfAttention) Forward(ctx ml.Context, layer int, hiddenState, positionIDs ml.Tensor, cache kvcache.Cache, opts *TextOptions) ml.Tensor {
+func (sa *TextSelfAttention) Forward(ctx ml.Context, layer int, hiddenState, positionIDs ml.Tensor, cache kvcache.Cache, opts *TextConfig) ml.Tensor {
 	batchSize := hiddenState.Dim(1)
 	ropeType := uint32(2)
 
@@ -120,12 +120,12 @@ func (sa *TextSelfAttention) Forward(ctx ml.Context, layer int, hiddenState, pos
 }
 
 func (m *TextModel) Shift(ctx ml.Context, layer int, key, shift ml.Tensor) (ml.Tensor, error) {
-	ropeBase := m.TextOptions.ropeLocalBase
+	ropeBase := m.TextConfig.ropeLocalBase
 	if (layer+1)%gemmaGlobalCacheCount == 0 {
-		ropeBase = m.TextOptions.ropeGlobalBase
+		ropeBase = m.TextConfig.ropeGlobalBase
 	}
 
-	return key.RoPE(ctx, shift, nil, uint32(m.TextOptions.attnKeyLen), uint32(2), ropeBase, m.TextOptions.ropeScale), nil
+	return key.RoPE(ctx, shift, nil, uint32(m.TextConfig.attnKeyLen), uint32(2), ropeBase, m.TextConfig.ropeScale), nil
 }
 
 type TextMLP struct {
@@ -134,7 +134,7 @@ type TextMLP struct {
 	Gate *nn.Linear `gguf:"ffn_gate"`
 }
 
-func (mlp *TextMLP) Forward(ctx ml.Context, hiddenState ml.Tensor, opts *TextOptions) ml.Tensor {
+func (mlp *TextMLP) Forward(ctx ml.Context, hiddenState ml.Tensor, opts *TextConfig) ml.Tensor {
 	hiddenState = mlp.Gate.Forward(ctx, hiddenState).GELU(ctx).Mul(ctx, mlp.Up.Forward(ctx, hiddenState))
 	return mlp.Down.Forward(ctx, hiddenState)
 }
@@ -148,7 +148,7 @@ type TextLayer struct {
 	PostMLPNorm       *nn.RMSNorm `gguf:"post_ffw_norm"`
 }
 
-func (l *TextLayer) Forward(ctx ml.Context, layer int, hiddenState, positionIDs, outputs ml.Tensor, cache kvcache.Cache, opts *TextOptions) ml.Tensor {
+func (l *TextLayer) Forward(ctx ml.Context, layer int, hiddenState, positionIDs, outputs ml.Tensor, cache kvcache.Cache, opts *TextConfig) ml.Tensor {
 	residual := hiddenState
 
 	hiddenState = l.AttentionNorm.Forward(ctx, hiddenState, opts.eps)
@@ -173,7 +173,7 @@ func (l *TextLayer) Forward(ctx ml.Context, layer int, hiddenState, positionIDs,
 
 func (m *TextModel) Forward(ctx ml.Context, inputs, positions, outputs ml.Tensor, batch input.Batch, cache kvcache.Cache) ml.Tensor {
 	hiddenState := m.TokenEmbedding.Forward(ctx, inputs)
-	hiddenState = hiddenState.Scale(ctx, math.Sqrt(float64(m.TextOptions.hiddenSize)))
+	hiddenState = hiddenState.Scale(ctx, math.Sqrt(float64(m.TextConfig.hiddenSize)))
 
 	// set image embeddings
 	var except []int
@@ -206,7 +206,7 @@ func (m *TextModel) Forward(ctx ml.Context, inputs, positions, outputs ml.Tensor
 			lastLayerOutputs = outputs
 		}
 
-		hiddenState = layer.Forward(ctx, i, hiddenState, positions, lastLayerOutputs, cache, m.TextOptions)
+		hiddenState = layer.Forward(ctx, i, hiddenState, positions, lastLayerOutputs, cache, m.TextConfig)
 	}
 
 	hiddenState = m.OutputNorm.Forward(ctx, hiddenState, m.eps)
diff --git a/model/models/mistral3/imageproc.go b/model/models/mistral3/imageproc.go
new file mode 100644
index 00000000..3d464bca
--- /dev/null
+++ b/model/models/mistral3/imageproc.go
@@ -0,0 +1,56 @@
+package mistral3
+
+import (
+	"image"
+	_ "image/jpeg"
+	_ "image/png"
+	"math"
+
+	"github.com/ollama/ollama/fs"
+	"github.com/ollama/ollama/model/imageproc"
+)
+
+type ImageProcessor struct {
+	imageSize   int
+	patchSize   int
+	numChannels int
+	longestEdge int
+}
+
+func newImageProcessor(c fs.Config) ImageProcessor {
+	return ImageProcessor{
+		imageSize:   int(c.Uint("vision.image_size", 1540)),
+		patchSize:   int(c.Uint("vision.patch_size", 14)),
+		numChannels: int(c.Uint("vision.num_channels", 3)),
+		longestEdge: int(c.Uint("vision.longest_edge", 1540)),
+	}
+}
+
+// ProcessImage prepares an image for the vision model by:
+// 1. Compositing transparent images
+// 2. Resizing to fit model constraints while preserving aspect ratio
+// 3. Normalizing pixel values
+// Returns normalized image data and the final size in pixels
+func (p *ImageProcessor) ProcessImage(img image.Image) ([]float32, image.Point, error) {
+	img = imageproc.Composite(img)
+
+	size := img.Bounds().Size()
+	ratio := max(float64(size.Y)/float64(p.longestEdge), float64(size.X)/float64(p.longestEdge))
+	if ratio > 1.0 {
+		size = image.Point{
+			int(math.Floor(float64(size.X) / ratio)),
+			int(math.Floor(float64(size.Y) / ratio)),
+		}
+	}
+
+	patchesX := (size.X-1)/p.patchSize + 1
+	patchesY := (size.Y-1)/p.patchSize + 1
+	size = image.Point{
+		patchesX * p.patchSize,
+		patchesY * p.patchSize,
+	}
+
+	img = imageproc.Resize(img, size, imageproc.ResizeBilinear)
+	data := imageproc.Normalize(img, imageproc.ClipDefaultMean, imageproc.ClipDefaultSTD, true, true)
+	return data, size, nil
+}
diff --git a/model/models/mistral3/model.go b/model/models/mistral3/model.go
new file mode 100644
index 00000000..fca3896c
--- /dev/null
+++ b/model/models/mistral3/model.go
@@ -0,0 +1,189 @@
+package mistral3
+
+import (
+	"bytes"
+	"image"
+	"slices"
+	"sync"
+
+	"github.com/ollama/ollama/fs"
+	"github.com/ollama/ollama/kvcache"
+	"github.com/ollama/ollama/ml"
+	"github.com/ollama/ollama/ml/nn"
+	"github.com/ollama/ollama/model"
+	"github.com/ollama/ollama/model/input"
+)
+
+type Model struct {
+	model.Base
+	*TextModel
+	*VisionModel         `gguf:"v,vision"`
+	*MultiModalProjector `gguf:"mm"`
+
+	ImageProcessor
+}
+
+// Implement MultimodalProcessor interface
+var _ model.MultimodalProcessor = (*Model)(nil)
+
+func New(c fs.Config) (model.Model, error) {
+	textModel, err := NewTextModel(c)
+	if err != nil {
+		return nil, err
+	}
+
+	m := &Model{
+		TextModel:           textModel,
+		VisionModel:         newVisionModel(c),
+		ImageProcessor:      newImageProcessor(c),
+		MultiModalProjector: newMultiModalProjector(c),
+	}
+
+	m.Cache = kvcache.NewCausalCache(m.TextModel.Shift)
+
+	return m, nil
+}
+
+type PatchMerger struct {
+	MergingLayer *nn.Linear `gguf:"merging_layer"`
+}
+
+func (pm *PatchMerger) Forward(ctx ml.Context, visionOutputs ml.Tensor, size image.Point, spatialMergeSize int) ml.Tensor {
+	d := visionOutputs.Dim(0)
+	imageGrid := visionOutputs.Permute(ctx, 1, 0, 2, 3).Contiguous(ctx).Reshape(ctx, size.X, size.Y, d)
+	kernel := ctx.Input().Empty(ml.DTypeF32, spatialMergeSize, spatialMergeSize, d)
+	patches := kernel.IM2Col(ctx, imageGrid, spatialMergeSize, spatialMergeSize, 0, 0, 1, 1)
+	reshaped := patches.Reshape(ctx, d*spatialMergeSize*spatialMergeSize, patches.Dim(1)*patches.Dim(2))
+	return pm.MergingLayer.Forward(ctx, reshaped)
+}
+
+type MultiModalProjector struct {
+	Norm        *nn.RMSNorm  `gguf:"norm"`
+	Linear1     *nn.Linear   `gguf:"linear_1"`
+	Linear2     *nn.Linear   `gguf:"linear_2"`
+	PatchMerger *PatchMerger `gguf:"patch_merger"`
+
+	spatialMergeSize int
+	eps              float32
+	patchSize        int
+}
+
+func (p *MultiModalProjector) Forward(ctx ml.Context, visionOutputs ml.Tensor, size image.Point) (ml.Tensor, image.Point) {
+	visionOutputs = p.Norm.Forward(ctx, visionOutputs, p.eps)
+	patchSizes := image.Point{size.X / p.patchSize, size.Y / p.patchSize}
+	visionOutputs = p.PatchMerger.Forward(ctx, visionOutputs, patchSizes, p.spatialMergeSize)
+	visionOutputs = p.Linear1.Forward(ctx, visionOutputs)
+	visionOutputs = visionOutputs.GELU(ctx)
+	return p.Linear2.Forward(ctx, visionOutputs), image.Point{patchSizes.X / p.spatialMergeSize, patchSizes.Y / p.spatialMergeSize}
+}
+
+func newMultiModalProjector(c fs.Config) *MultiModalProjector {
+	return &MultiModalProjector{
+		spatialMergeSize: int(c.Uint("spatial_merge_size", 2)),
+		eps:              c.Float("text_config.rms_norm_eps", 1e-5),
+		patchSize:        int(c.Uint("vision.patch_size", 14)),
+	}
+}
+
+func (m *Model) EncodeMultimodal(ctx ml.Context, multimodalData []byte) (any, error) {
+	if len(m.VisionModel.Layers) == 0 {
+		return nil, model.ErrNoVisionModel
+	}
+
+	image, _, err := image.Decode(bytes.NewReader(multimodalData))
+	if err != nil {
+		return nil, err
+	}
+
+	f32s, size, err := m.ImageProcessor.ProcessImage(image)
+	if err != nil {
+		return nil, err
+	}
+
+	pixelValues, err := ctx.Input().FromFloatSlice(f32s, size.X, size.Y, m.ImageProcessor.numChannels)
+	if err != nil {
+		return nil, err
+	}
+
+	visionOutputs := m.VisionModel.Forward(ctx, pixelValues)
+	features, size := m.MultiModalProjector.Forward(ctx, visionOutputs, size)
+
+	// split into patches to be sent to the text transformer
+	parent := imageFeatures{tensor: features}
+	rows := make([]*imageRow, size.Y)
+	for i := range rows {
+		rows[i] = &imageRow{parent: &parent, s: i, shape: []int{features.Dim(0), size.X}}
+	}
+
+	return rows, nil
+}
+
+type imageFeatures struct {
+	tensor ml.Tensor
+
+	dataOnce sync.Once
+	data     []float32
+}
+
+type imageRow struct {
+	parent *imageFeatures
+	s      int
+	shape  []int
+}
+
+func (r *imageRow) data() []float32 {
+	n := 1
+	for _, s := range r.shape {
+		n *= s
+	}
+
+	return r.parent.data[r.s*n : (r.s+1)*n]
+}
+
+// PostTokenize arranges Mistral 3's inputs for the forward pass
+// In Mistral 3 and Pixtral, the input patches are arranged as follows:
+// [IMG]...[IMG][IMG_BREAK][IMG]...[IMG][IMG_BREAK][IMG]...[IMG][IMG_END]
+// Each sequence of [IMG]...[IMG] is a set of patches of vision embeddings
+// that can be processed together.
+func (m *Model) PostTokenize(inputs []input.Input) ([]input.Input, error) {
+	var result []input.Input
+	for _, inp := range inputs {
+		if inp.Multimodal == nil {
+			result = append(result, inp)
+		} else {
+			inputMultimodal := inp.Multimodal.([]*imageRow)
+			for i, row := range inputMultimodal {
+				// [IMG]
+				result = append(result, input.Input{Token: 10, Multimodal: row, MultimodalHash: inp.MultimodalHash, SameBatch: row.shape[1]})
+				result = append(result, slices.Repeat([]input.Input{{Token: 10}}, row.shape[1]-1)...)
+				if i == len(inputMultimodal)-1 {
+					// [IMG_END]
+					result = append(result, input.Input{Token: 13})
+				} else {
+					// [IMG_BREAK]
+					result = append(result, input.Input{Token: 12})
+				}
+			}
+		}
+	}
+
+	return result, nil
+}
+
+func (m *Model) Forward(ctx ml.Context, batch input.Batch) (ml.Tensor, error) {
+	positions, err := ctx.Input().FromIntSlice(batch.Positions, len(batch.Positions))
+	if err != nil {
+		return nil, err
+	}
+
+	outputs, err := ctx.Input().FromIntSlice(batch.Outputs, len(batch.Outputs))
+	if err != nil {
+		return nil, err
+	}
+
+	return m.TextModel.Forward(ctx, batch.Inputs, positions, outputs, batch, m.Cache), nil
+}
+
+func init() {
+	model.Register("mistral3", New)
+}
diff --git a/model/models/mistral3/model_text.go b/model/models/mistral3/model_text.go
new file mode 100644
index 00000000..c256cbf1
--- /dev/null
+++ b/model/models/mistral3/model_text.go
@@ -0,0 +1,177 @@
+package mistral3
+
+import (
+	"fmt"
+	"math"
+	"strings"
+
+	"github.com/ollama/ollama/fs"
+	"github.com/ollama/ollama/kvcache"
+	"github.com/ollama/ollama/ml"
+	"github.com/ollama/ollama/ml/nn"
+	"github.com/ollama/ollama/model"
+	"github.com/ollama/ollama/model/input"
+)
+
+type TextOptions struct {
+	hiddenSize, numHeads, numKVHeads, headDim int
+	eps, ropeBase, ropeScale                  float32
+	ropeDim                                   uint32
+}
+
+type TextModel struct {
+	model.Base
+	model.BytePairEncoding
+
+	TokenEmbedding *nn.Embedding `gguf:"token_embd"`
+	Layers         []Layer       `gguf:"blk"`
+	OutputNorm     *nn.RMSNorm   `gguf:"output_norm"`
+	Output         *nn.Linear    `gguf:"output,alt:token_embd"`
+
+	*TextOptions
+}
+
+type SelfAttention struct {
+	Query  *nn.Linear `gguf:"attn_q"`
+	Key    *nn.Linear `gguf:"attn_k"`
+	Value  *nn.Linear `gguf:"attn_v"`
+	Output *nn.Linear `gguf:"attn_output"`
+}
+
+func (sa *SelfAttention) Forward(ctx ml.Context, hiddenState, positionIDs ml.Tensor, cache kvcache.Cache, opts *TextOptions) ml.Tensor {
+	batchSize := hiddenState.Dim(1)
+	ropeType := uint32(0)
+	headDim := opts.headDim
+	if headDim == 0 {
+		headDim = opts.hiddenSize / opts.numHeads
+	}
+
+	q := sa.Query.Forward(ctx, hiddenState)
+	q = q.Reshape(ctx, headDim, opts.numHeads, batchSize)
+	q = q.RoPE(ctx, positionIDs, nil, opts.ropeDim, ropeType, opts.ropeBase, opts.ropeScale)
+
+	k := sa.Key.Forward(ctx, hiddenState)
+	k = k.Reshape(ctx, headDim, opts.numKVHeads, batchSize)
+	k = k.RoPE(ctx, positionIDs, nil, opts.ropeDim, ropeType, opts.ropeBase, opts.ropeScale)
+
+	v := sa.Value.Forward(ctx, hiddenState)
+	v = v.Reshape(ctx, headDim, opts.numKVHeads, batchSize)
+
+	kqv := nn.Attention(ctx, q, k, v, 1.0/math.Sqrt(float64(headDim)), cache)
+	kqv = kqv.Reshape(ctx, headDim*opts.numHeads, batchSize)
+	return sa.Output.Forward(ctx, kqv)
+}
+
+func (m *TextModel) Shift(ctx ml.Context, layer int, key, shift ml.Tensor) (ml.Tensor, error) {
+	return key.RoPE(ctx, shift, nil, uint32(0), m.ropeDim, m.ropeBase, m.ropeScale), nil
+}
+
+type MLP struct {
+	Up   *nn.Linear `gguf:"ffn_up"`
+	Down *nn.Linear `gguf:"ffn_down"`
+	Gate *nn.Linear `gguf:"ffn_gate"`
+}
+
+func (mlp *MLP) Forward(ctx ml.Context, hiddenState ml.Tensor, opts *TextOptions) ml.Tensor {
+	hiddenState = mlp.Gate.Forward(ctx, hiddenState).SILU(ctx).Mul(ctx, mlp.Up.Forward(ctx, hiddenState))
+	return mlp.Down.Forward(ctx, hiddenState)
+}
+
+type Layer struct {
+	AttentionNorm *nn.RMSNorm `gguf:"attn_norm"`
+	SelfAttention *SelfAttention
+	MLPNorm       *nn.RMSNorm `gguf:"ffn_norm"`
+	MLP           *MLP
+}
+
+func (l *Layer) Forward(ctx ml.Context, hiddenState, positionIDs, outputs ml.Tensor, cache kvcache.Cache, opts *TextOptions) ml.Tensor {
+	residual := hiddenState
+
+	hiddenState = l.AttentionNorm.Forward(ctx, hiddenState, opts.eps)
+	hiddenState = l.SelfAttention.Forward(ctx, hiddenState, positionIDs, cache, opts)
+
+	// In the final layer (outputs != nil), optimize by pruning to just the token positions
+	// we need logits for.
+	if outputs != nil {
+		hiddenState = hiddenState.Rows(ctx, outputs)
+		residual = residual.Rows(ctx, outputs)
+	}
+
+	hiddenState = hiddenState.Add(ctx, residual)
+	residual = hiddenState
+
+	hiddenState = l.MLPNorm.Forward(ctx, hiddenState, opts.eps)
+	hiddenState = l.MLP.Forward(ctx, hiddenState, opts)
+	return hiddenState.Add(ctx, residual)
+}
+
+func (m *TextModel) Forward(ctx ml.Context, inputs, positions, outputs ml.Tensor, batch input.Batch, cache kvcache.Cache) ml.Tensor {
+	hiddenState := m.TokenEmbedding.Forward(ctx, inputs).Duplicate(ctx)
+
+	// image embeddings
+	for _, image := range batch.Multimodal {
+		row := image.Multimodal.(*imageRow)
+		row.parent.dataOnce.Do(func() {
+			// use a new, throwaway context so the image tensor is not added to the graph
+			temp := m.Backend().NewContext()
+			temp.Forward(row.parent.tensor).Compute(row.parent.tensor)
+			row.parent.data = row.parent.tensor.Floats()
+			temp.Close()
+		})
+
+		imageFeature, err := ctx.Input().FromFloatSlice(row.data(), row.shape...)
+		if err != nil {
+			panic(err)
+		}
+
+		ctx.Forward(imageFeature.Copy(ctx, hiddenState.View(ctx, image.Index*hiddenState.Stride(1), imageFeature.Dim(0)*imageFeature.Dim(1))))
+	}
+
+	for i, layer := range m.Layers {
+		cache.SetLayer(i)
+
+		var lastLayerOutputs ml.Tensor
+		if i == len(m.Layers)-1 {
+			lastLayerOutputs = outputs
+		}
+
+		hiddenState = layer.Forward(ctx, hiddenState, positions, lastLayerOutputs, cache, m.TextOptions)
+	}
+
+	hiddenState = m.OutputNorm.Forward(ctx, hiddenState, m.eps)
+	return m.Output.Forward(ctx, hiddenState)
+}
+
+func NewTextModel(c fs.Config) (*TextModel, error) {
+	if !strings.EqualFold(c.String("tokenizer.ggml.model"), "gpt2") {
+		return nil, fmt.Errorf("tokenizer %s not yet supported", c.String("tokenizer.ggml.model"))
+	}
+
+	textModel := &TextModel{
+		BytePairEncoding: model.NewBytePairEncoding(
+			c.String("tokenizer.ggml.pretokenizer", `[^\r\n\p{L}\p{N}]?[\p{Lu}\p{Lt}\p{Lm}\p{Lo}\p{M}]*[\p{Ll}\p{Lm}\p{Lo}\p{M}]+|[^\r\n\p{L}\p{N}]?[\p{Lu}\p{Lt}\p{Lm}\p{Lo}\p{M}]+[\p{Ll}\p{Lm}\p{Lo}\p{M}]*|\p{N}| ?[^\s\p{L}\p{N}]+[\r\n/]*|\s*[\r\n]+|\s+(?!\S)|\s+`),
+			&model.Vocabulary{
+				Values: c.Strings("tokenizer.ggml.tokens"),
+				Types:  c.Uints("tokenizer.ggml.token_type"),
+				Merges: c.Strings("tokenizer.ggml.merges"),
+				BOS:    int32(c.Uint("tokenizer.ggml.bos_token_id", 1)),
+				AddBOS: c.Bool("tokenizer.ggml.add_bos_token", true),
+				EOS:    int32(c.Uint("tokenizer.ggml.eos_token_id", 2)),
+				AddEOS: c.Bool("tokenizer.ggml.add_eos_token", false),
+			},
+		),
+		Layers: make([]Layer, c.Uint("block_count")),
+		TextOptions: &TextOptions{
+			hiddenSize: int(c.Uint("embedding_length")),
+			numHeads:   int(c.Uint("attention.head_count")),
+			numKVHeads: int(c.Uint("attention.head_count_kv")),
+			headDim:    int(c.Uint("attention.key_length")),
+			eps:        c.Float("attention.layer_norm_rms_epsilon"),
+			ropeBase:   c.Float("rope.freq_base"),
+			ropeScale:  c.Float("rope.freq_scale", 1),
+			ropeDim:    c.Uint("rope.dimension_count"),
+		},
+	}
+
+	return textModel, nil
+}
diff --git a/model/models/mistral3/model_vision.go b/model/models/mistral3/model_vision.go
new file mode 100644
index 00000000..469dc40c
--- /dev/null
+++ b/model/models/mistral3/model_vision.go
@@ -0,0 +1,186 @@
+package mistral3
+
+import (
+	"math"
+
+	"github.com/ollama/ollama/fs"
+	"github.com/ollama/ollama/ml"
+	"github.com/ollama/ollama/ml/nn"
+)
+
+var batchSize int = 1
+
+func rotateHalf(ctx ml.Context, t ml.Tensor) ml.Tensor {
+	x1 := t.View(ctx, 0, t.Dim(0)/2, t.Stride(1), t.Dim(1), t.Stride(2), t.Dim(2), t.Stride(3), t.Dim(3))
+	x2 := t.View(ctx, t.Stride(0)*t.Dim(0)/2, t.Dim(0)/2, t.Stride(1), t.Dim(1), t.Stride(2), t.Dim(2), t.Stride(3), t.Dim(3)).Contiguous(ctx)
+	return x2.Neg(ctx).Concat(ctx, x1, 0)
+}
+
+func applyRotaryPositionalEmbedding(ctx ml.Context, t, cos, sin ml.Tensor) ml.Tensor {
+	return t.Mul(ctx, cos).Add(ctx, rotateHalf(ctx, t).Mul(ctx, sin))
+}
+
+type VisionSelfAttention struct {
+	Query  *nn.Linear `gguf:"attn_q"`
+	Key    *nn.Linear `gguf:"attn_k"`
+	Value  *nn.Linear `gguf:"attn_v"`
+	Output *nn.Linear `gguf:"attn_output"`
+}
+
+func (sa *VisionSelfAttention) Forward(ctx ml.Context, hiddenStates, cos, sin ml.Tensor, opts *VisionModelOptions) ml.Tensor {
+	query := sa.Query.Forward(ctx, hiddenStates)
+	key := sa.Key.Forward(ctx, hiddenStates)
+	value := sa.Value.Forward(ctx, hiddenStates)
+
+	query = query.Reshape(ctx, opts.headDim, opts.numHeads, query.Dim(1), batchSize)
+	key = key.Reshape(ctx, opts.headDim, opts.numHeads, key.Dim(1), batchSize)
+	value = value.Reshape(ctx, opts.headDim, opts.numHeads, value.Dim(1), batchSize)
+
+	query = applyRotaryPositionalEmbedding(ctx, query, cos, sin)
+	key = applyRotaryPositionalEmbedding(ctx, key, cos, sin)
+
+	attention := nn.Attention(ctx, query, key, value, 1./math.Sqrt(float64(opts.headDim)), nil)
+	attention = attention.Reshape(ctx, opts.hiddenSize, attention.Dim(2), batchSize)
+	return sa.Output.Forward(ctx, attention)
+}
+
+type VisionMLP struct {
+	Gate *nn.Linear `gguf:"ffn_gate"`
+	Up   *nn.Linear `gguf:"ffn_up"`
+	Down *nn.Linear `gguf:"ffn_down"`
+}
+
+func (mlp *VisionMLP) Forward(ctx ml.Context, hiddenStates ml.Tensor, opts *VisionModelOptions) ml.Tensor {
+	hiddenStates = mlp.Gate.Forward(ctx, hiddenStates).SILU(ctx).Mul(ctx, mlp.Up.Forward(ctx, hiddenStates))
+	return mlp.Down.Forward(ctx, hiddenStates)
+}
+
+type VisionEncoderLayer struct {
+	AttentionNorm *nn.RMSNorm `gguf:"attn_norm"`
+	SelfAttention *VisionSelfAttention
+	FFNNorm       *nn.RMSNorm `gguf:"ffn_norm"`
+	MLP           *VisionMLP
+}
+
+func (e *VisionEncoderLayer) Forward(ctx ml.Context, hiddenStates, cos, sin ml.Tensor, opts *VisionModelOptions) ml.Tensor {
+	residual := hiddenStates
+	hiddenStates = e.AttentionNorm.Forward(ctx, hiddenStates, opts.eps)
+	hiddenStates = e.SelfAttention.Forward(ctx, hiddenStates, cos, sin, opts)
+	hiddenStates = hiddenStates.Add(ctx, residual)
+
+	residual = hiddenStates
+	hiddenStates = e.FFNNorm.Forward(ctx, hiddenStates, opts.eps)
+	hiddenStates = e.MLP.Forward(ctx, hiddenStates, opts)
+	return hiddenStates.Add(ctx, residual)
+}
+
+type VisionModelOptions struct {
+	hiddenSize       int
+	numHeads         int
+	headDim          int
+	intermediateSize int
+	imageSize        int
+	patchSize        int
+	numChannels      int
+	eps              float32
+	ropeBase         float32
+}
+
+type VisionModel struct {
+	PatchEmbedding *nn.Conv2D           `gguf:"patch_conv"`
+	EncoderNorm    *nn.RMSNorm          `gguf:"encoder_norm"`
+	Layers         []VisionEncoderLayer `gguf:"blk"`
+
+	*VisionModelOptions
+}
+
+func (m *VisionModel) positionalEmbedding(ctx ml.Context, positionIDs ml.Tensor) ml.Tensor {
+	maxPatchesPerSide := m.imageSize / m.patchSize
+	frequencies := m.headDim / 2
+	frequenciesHeight := make([]float32, frequencies/2*maxPatchesPerSide)
+	frequenciesWidth := make([]float32, frequencies/2*maxPatchesPerSide)
+	for i := range frequencies {
+		for j := range maxPatchesPerSide {
+			frequency := float32(j) / float32(math.Pow(float64(m.ropeBase), float64(i)*2/float64(m.headDim)))
+			if i%2 == 0 {
+				frequenciesHeight[i/2*maxPatchesPerSide+j] = frequency
+			} else {
+				frequenciesWidth[i/2*maxPatchesPerSide+j] = frequency
+			}
+		}
+	}
+
+	h, err := ctx.Input().FromFloatSlice(frequenciesHeight, maxPatchesPerSide, frequencies/2)
+	if err != nil {
+		panic(err)
+	}
+
+	w, err := ctx.Input().FromFloatSlice(frequenciesWidth, maxPatchesPerSide, frequencies/2)
+	if err != nil {
+		panic(err)
+	}
+
+	h = h.Permute(ctx, 1, 0, 2, 3).Contiguous(ctx)
+	w = w.Permute(ctx, 1, 0, 2, 3).Contiguous(ctx)
+
+	h = h.Repeat(ctx, 1, maxPatchesPerSide)
+	h = h.Reshape(ctx, frequencies/2, maxPatchesPerSide, maxPatchesPerSide).Permute(ctx, 0, 2, 1, 3).Contiguous(ctx)
+	w = w.Repeat(ctx, 2, maxPatchesPerSide)
+
+	inverseFrequencies := h.Concat(ctx, w, 0).Reshape(ctx, frequencies, maxPatchesPerSide*maxPatchesPerSide)
+	inverseFrequencies = inverseFrequencies.Concat(ctx, inverseFrequencies, 0)
+	return inverseFrequencies.Rows(ctx, positionIDs)
+}
+
+func (m *VisionModel) Forward(ctx ml.Context, pixelValues ml.Tensor) ml.Tensor {
+	numPatchesW := pixelValues.Dim(0) / m.patchSize
+	numPatchesH := pixelValues.Dim(1) / m.patchSize
+	numPatches := numPatchesW * numPatchesH
+
+	hiddenStates := m.PatchEmbedding.Forward(ctx, pixelValues, m.patchSize, m.patchSize, 0, 0, 1, 1)
+	hiddenStates = hiddenStates.Reshape(ctx, numPatches, m.hiddenSize)
+	hiddenStates = hiddenStates.Permute(ctx, 1, 0, 2, 3).Contiguous(ctx)
+	hiddenStates = m.EncoderNorm.Forward(ctx, hiddenStates, m.VisionModelOptions.eps)
+
+	// Prepare position IDs for 2D rope
+	positions := make([]int32, numPatches)
+	for h := range numPatchesH {
+		for w := range numPatchesW {
+			idx := h*numPatchesW + w
+			positions[idx] = int32(h*m.imageSize/m.patchSize + w)
+		}
+	}
+
+	positionIDs, err := ctx.Input().FromIntSlice(positions, len(positions))
+	if err != nil {
+		panic(err)
+	}
+
+	positionEmbedding := m.positionalEmbedding(ctx, positionIDs)
+	cos, sin := positionEmbedding.Cos(ctx), positionEmbedding.Sin(ctx)
+	cos = cos.Reshape(ctx, cos.Dim(0), 1, cos.Dim(1))
+	sin = sin.Reshape(ctx, sin.Dim(0), 1, sin.Dim(1))
+
+	for _, layer := range m.Layers {
+		hiddenStates = layer.Forward(ctx, hiddenStates, cos, sin, m.VisionModelOptions)
+	}
+
+	return hiddenStates
+}
+
+func newVisionModel(c fs.Config) *VisionModel {
+	return &VisionModel{
+		Layers: make([]VisionEncoderLayer, c.Uint("vision.block_count", 24)),
+		VisionModelOptions: &VisionModelOptions{
+			hiddenSize:       int(c.Uint("vision.embedding_length", 1024)),
+			numHeads:         int(c.Uint("vision.attention.head_count", 16)),
+			headDim:          int(c.Uint("vision.attention.key_length", 64)),
+			intermediateSize: int(c.Uint("vision.feed_forward_length", 4096)),
+			imageSize:        int(c.Uint("vision.image_size", 1540)),
+			patchSize:        int(c.Uint("vision.patch_size", 14)),
+			numChannels:      int(c.Uint("vision.num_channels", 3)),
+			eps:              c.Float("vision.attention.layer_norm_epsilon", 1e-5),
+			ropeBase:         c.Float("vision.rope.freq_base", 10000.0),
+		},
+	}
+}
diff --git a/model/models/mllama/model_vision.go b/model/models/mllama/model_vision.go
index 2f7d26ca..8b10bde8 100644
--- a/model/models/mllama/model_vision.go
+++ b/model/models/mllama/model_vision.go
@@ -186,7 +186,7 @@ func (m *VisionModel) Forward(ctx ml.Context, pixelValues, positionIDs, aspectRa
 	hiddenState = hiddenState.Permute(ctx, 1, 0, 2, 3).Contiguous(ctx)
 
 	hiddenState = m.PreTilePositionEmbedding.Forward(ctx, hiddenState, aspectRatioIDs, m.VisionModelOptions)
-	hiddenState = m.ClassEmbedding.Stack(ctx, 2, slices.Repeat([]ml.Tensor{m.ClassEmbedding}, m.numTiles-1)...).Concat(ctx, hiddenState, 1)
+	hiddenState = m.ClassEmbedding.Repeat(ctx, 2, m.numTiles).Concat(ctx, hiddenState, 1)
 
 	hiddenState = m.PositionEmbedding.Forward(ctx, hiddenState, positionIDs, aspectRatioIDs, numPositions, m.VisionModelOptions)
 	hiddenState = m.PreLayerNorm.Forward(ctx, hiddenState, m.eps)
diff --git a/model/models/models.go b/model/models/models.go
index ce1d2ce0..c5da2894 100644
--- a/model/models/models.go
+++ b/model/models/models.go
@@ -4,5 +4,6 @@ import (
 	_ "github.com/ollama/ollama/model/models/gemma2"
 	_ "github.com/ollama/ollama/model/models/gemma3"
 	_ "github.com/ollama/ollama/model/models/llama"
+	_ "github.com/ollama/ollama/model/models/mistral3"
 	_ "github.com/ollama/ollama/model/models/mllama"
 )
diff --git a/model/models/pixtral/imageproc.go b/model/models/pixtral/imageproc.go
deleted file mode 100644
index 16ec0c41..00000000
--- a/model/models/pixtral/imageproc.go
+++ /dev/null
@@ -1,68 +0,0 @@
-package pixtral
-
-import (
-	"fmt"
-	"image"
-	_ "image/jpeg"
-	_ "image/png"
-	"io"
-	"math"
-
-	"github.com/ollama/ollama/model/imageproc"
-)
-
-func getNumImageTokens(imageSize, patchSize image.Point) image.Point {
-	return image.Point{
-		(imageSize.X-1)/patchSize.X + 1,
-		(imageSize.Y-1)/patchSize.Y + 1,
-	}
-}
-
-func getResizeOutputImageSize(img image.Image, longestEdge int, patchSize image.Point) image.Point {
-	b := img.Bounds()
-	le := float64(longestEdge)
-	ratio := math.Max(float64(b.Max.Y)/le, float64(b.Max.X)/le)
-
-	newSize := img.Bounds().Max
-
-	if ratio > 1.0 {
-		newSize = image.Point{
-			int(math.Ceil(float64(b.Max.X) / ratio)),
-			int(math.Ceil(float64(b.Max.Y) / ratio)),
-		}
-	}
-
-	tokens := getNumImageTokens(newSize, patchSize)
-	return image.Point{
-		tokens.X * patchSize.X,
-		tokens.Y * patchSize.Y,
-	}
-}
-
-func resizeImage(img image.Image, format string, longestEdge int, patchSize image.Point) image.Image {
-	if format == "png" {
-		img = imageproc.Composite(img)
-	}
-
-	newSize := getResizeOutputImageSize(img, longestEdge, patchSize)
-
-	// todo should be ResizeBicubic, but it doesn't exist
-	return imageproc.Resize(img, newSize, imageproc.ResizeBilinear)
-}
-
-func Preprocess(imageData io.Reader) ([]float32, map[string]any, error) {
-	img, format, err := image.Decode(imageData)
-	if err != nil {
-		return nil, nil, fmt.Errorf("failed to decode image: %w", err)
-	}
-
-	longestEdge := 1024
-	patchSize := image.Point{16, 16}
-
-	img = resizeImage(img, format, longestEdge, patchSize)
-
-	data := imageproc.Normalize(img, imageproc.ClipDefaultMean, imageproc.ClipDefaultSTD, true, true)
-
-	opts := map[string]any{}
-	return data, opts, nil
-}
diff --git a/model/models/pixtral/imageproc_test.go b/model/models/pixtral/imageproc_test.go
deleted file mode 100644
index 1d9e4ffe..00000000
--- a/model/models/pixtral/imageproc_test.go
+++ /dev/null
@@ -1,219 +0,0 @@
-package pixtral
-
-import (
-	"bytes"
-	"encoding/binary"
-	"image"
-	"image/png"
-	"math"
-	"os"
-	"testing"
-
-	"github.com/google/go-cmp/cmp"
-)
-
-func TestGetNumImageTokens(t *testing.T) {
-	type numImageTokensCase struct {
-		ImageSize image.Point
-		PatchSize image.Point
-		Expected  image.Point
-	}
-
-	cases := []numImageTokensCase{
-		{
-			ImageSize: image.Point{1024, 764},
-			PatchSize: image.Point{16, 16},
-			Expected:  image.Point{64, 48},
-		},
-		{
-			ImageSize: image.Point{800, 600},
-			PatchSize: image.Point{16, 16},
-			Expected:  image.Point{50, 38},
-		},
-		{
-			ImageSize: image.Point{640, 480},
-			PatchSize: image.Point{16, 16},
-			Expected:  image.Point{40, 30},
-		},
-		{
-			ImageSize: image.Point{320, 200},
-			PatchSize: image.Point{16, 16},
-			Expected:  image.Point{20, 13},
-		},
-		{
-			ImageSize: image.Point{1320, 200},
-			PatchSize: image.Point{16, 16},
-			Expected:  image.Point{83, 13},
-		},
-		{
-			ImageSize: image.Point{2000, 200},
-			PatchSize: image.Point{16, 16},
-			Expected:  image.Point{125, 13},
-		},
-		{
-			ImageSize: image.Point{10000, 200},
-			PatchSize: image.Point{16, 16},
-			Expected:  image.Point{625, 13},
-		},
-		{
-			ImageSize: image.Point{1131, 577},
-			PatchSize: image.Point{16, 16},
-			Expected:  image.Point{71, 37},
-		},
-		{
-			ImageSize: image.Point{16, 16},
-			PatchSize: image.Point{16, 16},
-			Expected:  image.Point{1, 1},
-		},
-	}
-
-	for _, c := range cases {
-		actual := getNumImageTokens(c.ImageSize, c.PatchSize)
-
-		if diff := cmp.Diff(actual, c.Expected); diff != "" {
-			t.Errorf("mismatch (-got +want):\n%s", diff)
-		}
-	}
-}
-
-func TestGetResizeOutputImageSize(t *testing.T) {
-	type resizeCase struct {
-		Image       image.Image
-		LongestEdge int
-		PatchSize   image.Point
-		Expected    image.Point
-	}
-
-	cases := []resizeCase{
-		{
-			Image:       image.NewRGBA(image.Rect(0, 0, 1024, 768)),
-			LongestEdge: 1024,
-			PatchSize:   image.Point{16, 16},
-			Expected:    image.Point{1024, 768},
-		},
-		{
-			Image:       image.NewRGBA(image.Rect(0, 0, 1162, 690)),
-			LongestEdge: 1024,
-			PatchSize:   image.Point{16, 16},
-			Expected:    image.Point{1024, 624},
-		},
-		{
-			Image:       image.NewRGBA(image.Rect(0, 0, 300, 200)),
-			LongestEdge: 1024,
-			PatchSize:   image.Point{16, 16},
-			Expected:    image.Point{304, 208},
-		},
-		{
-			Image:       image.NewRGBA(image.Rect(0, 0, 1862, 522)),
-			LongestEdge: 1024,
-			PatchSize:   image.Point{16, 16},
-			Expected:    image.Point{1024, 288},
-		},
-	}
-
-	for _, c := range cases {
-		actual := getResizeOutputImageSize(c.Image, c.LongestEdge, c.PatchSize)
-
-		if diff := cmp.Diff(actual, c.Expected); diff != "" {
-			t.Errorf("mismatch (-got +want):\n%s", diff)
-		}
-	}
-}
-
-func TestResize(t *testing.T) {
-	type resizeCase struct {
-		Image       image.Image
-		LongestEdge int
-		PatchSize   image.Point
-		Expected    image.Image
-	}
-
-	cases := []resizeCase{
-		{
-			Image:       image.NewRGBA(image.Rect(0, 0, 1862, 522)),
-			LongestEdge: 1024,
-			PatchSize:   image.Point{16, 16},
-			Expected:    image.NewRGBA(image.Rect(0, 0, 1024, 288)),
-		},
-		{
-			Image:       image.NewRGBA(image.Rect(0, 0, 10, 10)),
-			LongestEdge: 1024,
-			PatchSize:   image.Point{16, 16},
-			Expected:    image.NewRGBA(image.Rect(0, 0, 16, 16)),
-		},
-	}
-
-	for _, c := range cases {
-		actual := resizeImage(c.Image, "png", c.LongestEdge, c.PatchSize)
-
-		if actual.Bounds() != c.Expected.Bounds() {
-			t.Errorf("image size incorrect: '%#v': expected: '%#v'", actual.Bounds(), c.Expected.Bounds())
-		}
-	}
-}
-
-func TestPreprocess(t *testing.T) {
-	type preprocessCase struct {
-		TestImage   image.Image
-		ExpectedLen int
-	}
-
-	cases := []preprocessCase{
-		{
-			TestImage:   image.NewRGBA(image.Rect(0, 0, 10, 10)),
-			ExpectedLen: 16 * 16 * 3 * 1,
-		},
-		{
-			TestImage:   image.NewRGBA(image.Rect(0, 0, 2000, 2000)),
-			ExpectedLen: 1024 * 1024 * 3 * 1,
-		},
-	}
-
-	for _, c := range cases {
-		var buf bytes.Buffer
-		err := png.Encode(&buf, c.TestImage)
-		if err != nil {
-			t.Fatal(err)
-		}
-
-		imgData, _, err := Preprocess(&buf)
-		if err != nil {
-			t.Fatalf("error processing: %q", err)
-		}
-
-		switch len(imgData) {
-		case 0:
-			t.Errorf("no image data returned")
-		case c.ExpectedLen:
-			// ok
-		default:
-			t.Errorf("unexpected image data length: %d, expected: %d", len(imgData), c.ExpectedLen)
-		}
-	}
-}
-
-func TestPreprocessImages(t *testing.T) {
-	for _, testFile := range []string{"flight.png", "sportsball.png"} {
-		f, err := os.Open(testFile)
-		if err != nil {
-			t.Skipf("skipping test, no test image found at %s", testFile)
-		}
-		defer f.Close()
-
-		imgData, _, err := Preprocess(f)
-		if err != nil {
-			t.Fatalf("error processing: %q", err)
-		}
-
-		byteData := make([]byte, len(imgData)*4) // float32 is 4 bytes
-		for i, f := range imgData {
-			binary.LittleEndian.PutUint32(byteData[i*4:], math.Float32bits(f))
-		}
-
-		outputPath := "processed_" + testFile + ".bin"
-		err = os.WriteFile(outputPath, byteData, 0o644)
-		if err != nil {
-			t.Fatalf("error writing processed image: %q", err)
-		}
-	}
-}
diff --git a/model/process_text.go b/model/process_text.go
index 01af65b6..f0fb7787 100644
--- a/model/process_text.go
+++ b/model/process_text.go
@@ -263,6 +263,10 @@ func (bpe BytePairEncoding) Encode(s string, addSpecial bool) ([]int32, error) {
 					continue
 				}
 
+				if id := bpe.vocab.Encode(pair.value); id < 0 {
+					continue
+				}
+
 				merges[pair.a].runes = append(left.runes, right.runes...)
 				merges[pair.b].runes = nil
 
diff --git a/parser/parser.go b/parser/parser.go
index 6832351f..9a98c8ea 100644
--- a/parser/parser.go
+++ b/parser/parser.go
@@ -211,16 +211,10 @@ func filesForModel(path string) ([]string, error) {
 	}
 
 	var files []string
-	if st, _ := glob(filepath.Join(path, "model*.safetensors"), "application/octet-stream"); len(st) > 0 {
+	if st, _ := glob(filepath.Join(path, "*.safetensors"), "application/octet-stream"); len(st) > 0 {
 		// safetensors files might be unresolved git lfs references; skip if they are
 		// covers model-x-of-y.safetensors, model.fp32-x-of-y.safetensors, model.safetensors
 		files = append(files, st...)
-	} else if st, _ := glob(filepath.Join(path, "adapters.safetensors"), "application/octet-stream"); len(st) > 0 {
-		// covers adapters.safetensors
-		files = append(files, st...)
-	} else if st, _ := glob(filepath.Join(path, "adapter_model.safetensors"), "application/octet-stream"); len(st) > 0 {
-		// covers adapter_model.safetensors
-		files = append(files, st...)
 	} else if pt, _ := glob(filepath.Join(path, "pytorch_model*.bin"), "application/zip"); len(pt) > 0 {
 		// pytorch files might also be unresolved git lfs references; skip if they are
 		// covers pytorch_model-x-of-y.bin, pytorch_model.fp32-x-of-y.bin, pytorch_model.bin

From 0f3f9e353df96d4cfc40ac19114c782a57fe30f5 Mon Sep 17 00:00:00 2001
From: Daniel Hipke <danhipke@users.noreply.github.com>
Date: Fri, 4 Apr 2025 17:04:24 -0700
Subject: [PATCH 157/157] ml/backend/ggml: create a new file descriptor for
 tensor (#10133)

improves model loading times on network-based filesystems
such as GCS fuse by creating a dedicated file descriptor for each
section of the file being read, reducing seeking
---
 ml/backend/ggml/ggml.go | 9 ++++++++-
 1 file changed, 8 insertions(+), 1 deletion(-)

diff --git a/ml/backend/ggml/ggml.go b/ml/backend/ggml/ggml.go
index a106fed5..7e81e995 100644
--- a/ml/backend/ggml/ggml.go
+++ b/ml/backend/ggml/ggml.go
@@ -319,7 +319,14 @@ func New(ctx context.Context, r *os.File, params ml.BackendParams) (ml.Backend,
 				tts[i] = tt
 			}
 
-			sr := io.NewSectionReader(r, int64(meta.Tensors().Offset+t.Offset), int64(t.Size()))
+			// Create a new FD for each goroutine so that each FD is read sequentially, rather than
+			// seeking around within an FD shared between all goroutines.
+			file, err := os.Open(r.Name())
+			if err != nil {
+				return err
+			}
+			defer file.Close()
+			sr := io.NewSectionReader(file, int64(meta.Tensors().Offset+t.Offset), int64(t.Size()))
 			bts := make([]byte, 128*format.KibiByte)
 
 			var s uint64