Reasoning

Reasoning lets a large language model (LLM) think through a problem step by step before responding. When reasoning is enabled, the model generates chain-of-thought text and returns that text separately from the answer. Reasoning only works for models that support it.

The `reasoning` parameter

To enable or disable reasoning, pass a reasoning parameter in the request body of the chat completions API. Some models reason by default and don’t require the reasoning parameter. Omit the reasoning parameter in a request to see if the model returns reasoning by default or not.

The chat completions API also accepts a thinking parameter as an alternative to reasoning. Use whichever format your client or model expects.

Send a reasoning request

Here’s an example that shows how to send a request with reasoning enabled. Be sure to create an API key before you run it.

import os
from openai import OpenAI

client = OpenAI(
    base_url="https://api.modular.com/v1",
    api_key=os.environ.get("MODULAR_API_KEY"),
)

completion = client.chat.completions.create(
    model="google/gemma-4-31b-it",
    messages=[
        {"role": "user", "content": "How many r's are in the word strawberry?"}
    ],
    extra_body={"reasoning": {"enabled": True}}
)

print(completion.to_json(indent=2))

curl -X POST https://api.modular.com/v1/chat/completions \
    -H "Authorization: Bearer $MODULAR_API_KEY" \
    -H "Content-Type: application/json" \
    -d '{
        "model": "google/gemma-4-31b-it",
        "messages": [
            {"role": "user", "content": "How many r'\''s are in the word strawberry?"}
        ],
        "reasoning": {"enabled": true}
    }'

You should receive a response similar to this:

{
  "choices": [
    {
      "finish_reason": "stop",
      "index": 0,
      "message": {
        "content": "There are 3 \"r\"s in strawberry.",
        "role": "assistant",
        "reasoning": "The user is asking for the number of letter 'r's in the word \"strawberry\".\n\n    *   S-T-R-A-W-B-E-R-R-Y\n    *   R (1)\n    *   R (2)\n    *   R (3)\n\nThere are 3 'r's."
      }
    }
  ],
  "model": "google/gemma-4-31b-it",
  "usage": {
    "completion_tokens": 144,
    "prompt_tokens": 27,
    "total_tokens": 171,
    "completion_tokens_details": {
      "reasoning_tokens": 132
    }
  }
}

Understand the response

When reasoning is enabled, the reasoning response field contains the model’s chain-of-thought text. When reasoning is disabled or the model doesn’t support it, reasoning is null. Some models return a reasoning_content field instead; this is equivalent to reasoning and contains the same information. The usage field in the response reports reasoning_tokens, which counts the tokens used for chain-of-thought. This way, you know how many additional tokens the model uses when reasoning is enabled. When reasoning is disabled or not supported, the request returns 0 on this field.

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The `reasoning` parameter

Send a reasoning request

Understand the response

​The reasoning parameter

​Send a reasoning request

​Understand the response

The `reasoning` parameter

Send a reasoning request

Understand the response