ollama37/docs/capabilities/thinking.mdx

---
title: Thinking
---

Thinking-capable models emit a `thinking` field that separates their reasoning trace from the final answer. 

Use this capability to audit model steps, animate the model *thinking* in a UI, or hide the trace entirely when you only need the final response.

## Supported models

- [Qwen 3](https://ollama.com/library/qwen3)
- [GPT-OSS](https://ollama.com/library/gpt-oss) *(use `think` levels: `low`, `medium`, `high` — the trace cannot be fully disabled)*
- [DeepSeek-v3.1](https://ollama.com/library/deepseek-v3.1)
- [DeepSeek R1](https://ollama.com/library/deepseek-r1)
- Browse the latest additions under [thinking models](https://ollama.com/search?c=thinking)

## Enable thinking in API calls

Set the `think` field on chat or generate requests. Most models accept booleans (`true`/`false`).

GPT-OSS instead expects one of `low`, `medium`, or `high` to tune the trace length. 

The `message.thinking` (chat endpoint) or `thinking` (generate endpoint) field contains the reasoning trace while `message.content` / `response` holds the final answer.

<Tabs>
  <Tab title="cURL">
    ```shell
    curl http://localhost:11434/api/chat -d '{
      "model": "qwen3",
      "messages": [{
        "role": "user",
        "content": "How many letter r are in strawberry?"
      }],
      "think": true,
      "stream": false
    }'
    ```
  </Tab>
  <Tab title="Python">
    ```python
    from ollama import chat

    response = chat(
      model='qwen3',
      messages=[{'role': 'user', 'content': 'How many letter r are in strawberry?'}],
      think=True,
      stream=False,
    )

    print('Thinking:\n', response.message.thinking)
    print('Answer:\n', response.message.content)
    ```
  </Tab>
  <Tab title="JavaScript">
    ```javascript
    import ollama from 'ollama'

    const response = await ollama.chat({
      model: 'deepseek-r1',
      messages: [{ role: 'user', content: 'How many letter r are in strawberry?' }],
      think: true,
      stream: false,
    })

    console.log('Thinking:\n', response.message.thinking)
    console.log('Answer:\n', response.message.content)
    ```
  </Tab>
</Tabs>

<Note>
  GPT-OSS requires `think` to be set to `"low"`, `"medium"`, or `"high"`. Passing `true`/`false` is ignored for that model.
</Note>

## Stream the reasoning trace

Thinking streams interleave reasoning tokens before answer tokens. Detect the first `thinking` chunk to render a "thinking" section, then switch to the final reply once `message.content` arrives.

<Tabs>
  <Tab title="Python">
    ```python
    from ollama import chat

    stream = chat(
      model='qwen3',
      messages=[{'role': 'user', 'content': 'What is 17 × 23?'}],
      think=True,
      stream=True,
    )

    in_thinking = False

    for chunk in stream:
      if chunk.message.thinking and not in_thinking:
        in_thinking = True
        print('Thinking:\n', end='')

      if chunk.message.thinking:
        print(chunk.message.thinking, end='')
      elif chunk.message.content:
        if in_thinking:
          print('\n\nAnswer:\n', end='')
          in_thinking = False
        print(chunk.message.content, end='')

    ```
  </Tab>
  <Tab title="JavaScript">
    ```javascript
    import ollama from 'ollama'

    async function main() {
      const stream = await ollama.chat({
        model: 'qwen3',
        messages: [{ role: 'user', content: 'What is 17 × 23?' }],
        think: true,
        stream: true,
      })

      let inThinking = false

      for await (const chunk of stream) {
        if (chunk.message.thinking && !inThinking) {
          inThinking = true
          process.stdout.write('Thinking:\n')
        }

        if (chunk.message.thinking) {
          process.stdout.write(chunk.message.thinking)
        } else if (chunk.message.content) {
          if (inThinking) {
            process.stdout.write('\n\nAnswer:\n')
            inThinking = false
          }
          process.stdout.write(chunk.message.content)
        }
      }
    }

    main()
    ```
  </Tab>
</Tabs>

## CLI quick reference

- Enable thinking for a single run: `ollama run deepseek-r1 --think "Where should I visit in Lisbon?"`
- Disable thinking: `ollama run deepseek-r1 --think=false "Summarize this article"`
- Hide the trace while still using a thinking model: `ollama run deepseek-r1 --hidethinking "Is 9.9 bigger or 9.11?"`
- Inside interactive sessions, toggle with `/set think` or `/set nothink`.
- GPT-OSS only accepts levels: `ollama run gpt-oss --think=low "Draft a headline"` (replace `low` with `medium` or `high` as needed).

<Note>Thinking is enabled by default in the CLI and API for supported models.</Note>