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. To view the list of models that support reasoning, see the Supported models page. 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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Inference

Administration

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