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
• GPT-OSS (use think levels: low, medium, high — the trace cannot be fully disabled)
• DeepSeek-v3.1
• DeepSeek R1
• Browse the latest additions under thinking models

Enable thinking in API calls

Set the think field on chat or generate requests. Most models accept booleans (true/false) or levels (low, medium, high, max), where max requests the highest thinking level.

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.

cURL

    curl http://localhost:11434/api/chat -d '{
      "model": "qwen3",
      "messages": [{
        "role": "user",
        "content": "How many letter r are in strawberry?"
      }],
      "think": true,
      "stream": false
    }'

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)

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)

Note

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

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.

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='')

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()

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.