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Documentation Index

Fetch the complete documentation index at: https://docs.subconscious.dev/llms.txt

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Thinking mode enables the model to reason step by step before producing its final answer. This is useful for complex tasks like math, logic, code generation, and multi-step analysis.

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How It Works

When thinking mode is enabled, the model generates internal reasoning tokens (wrapped in <think> tags) before the final response. These reasoning tokens help the model work through complex problems but are included in your output token usage.

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Enabling Thinking Mode

Pass chat_template_kwargs with enable_thinking: true in the request body. Since this is a Subconscious-specific extension, use the extra_body parameter in the OpenAI SDK: 
from openai import OpenAI

client = OpenAI(
    api_key="your-api-key",
    base_url="https://api.subconscious.dev/v1",
)

response = client.chat.completions.create(
    model="subconscious/tim-qwen3.6-27b",
    messages=[{"role": "user", "content": "What is 127 * 849 + 3621?"}],
    extra_body={
        "chat_template_kwargs": {"enable_thinking": True},
    },
)

print(response.choices[0].message.content)

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Response Format

With thinking mode enabled, the model’s response includes reasoning wrapped in <think> tags followed by the final answer: 
<think>
Let me calculate this step by step.
127 * 849 = 127 * 800 + 127 * 49
127 * 800 = 101,600
127 * 49 = 6,223
101,600 + 6,223 = 107,823
107,823 + 3,621 = 111,444
</think>

The answer is **111,444**.

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Streaming with Thinking

Thinking mode works with streaming. The reasoning tokens stream first, followed by the final answer:
Python
stream = client.chat.completions.create(
    model="subconscious/tim-qwen3.6-27b",
    messages=[{"role": "user", "content": "Solve: If 3x + 7 = 22, what is x?"}],
    stream=True,
    extra_body={
        "chat_template_kwargs": {"enable_thinking": True},
    },
)

for chunk in stream:
    content = chunk.choices[0].delta.content
    if content:
        print(content, end="", flush=True)

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When to Use Thinking Mode

Use thinking mode for:
  • Math and arithmetic problems
  • Logic puzzles and reasoning tasks
  • Complex code generation
  • Multi-step analysis
  • Tasks requiring planning or strategy
Skip thinking mode for:
  • Simple Q&A
  • Creative writing
  • Translation
  • Summarization
  • Tasks where speed matters more than accuracy
Thinking tokens count toward your output token usage. For simple tasks, leaving thinking mode off will be faster and more cost-effective.