Reasoning · Docs

Models marked Reasoning produce internal reasoning before the final answer.

completion = client.chat.completions.create(
    model="deepseek-ai/DeepSeek-V4.1-Flash",
    messages=[{"role": "user", "content": "How many primes are below 100?"}],
    reasoning_effort="medium",
)
message = completion.choices[0].message
print(message.content)

What to know

Billing. Reasoning tokens are billed at the output rate and reported in usage.completion_tokens_details.reasoning_tokens.
max_tokens includes reasoning. Leave enough headroom, or the answer may be cut off before it starts.
Effort. Where supported, reasoning_effort (low, medium, high) trades latency and cost for depth.
Reasoning content. Some models return their reasoning in a reasoning_content field alongside content. It is processed like any other output — not stored.
Keep-alives. While a model reasons, streaming responses may include SSE comment lines; ignore them.