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Use reasoning effort to adjust how much work a supported model does before answering. Higher effort can increase latency and output-token cost. Omit the control to use the model’s default.
Chat Completions accepts none, minimal, low, medium, high, and xhigh. The gateway translates the value for the model and serving route: a supported effort level, a reasoning-token budget, or an on/off control. Models without a working reasoning control may ignore it; none is not a universal guarantee of zero reasoning tokens. Keep enough output budget for both reasoning and the visible answer. A small budget can end in finish_reason: "length" with little or no answer text.
Send reasoning.effort and max_output_tokens instead. Responses forwards effort on OpenAI-shaped backends; it does not provide the same cross-provider translation as Chat Completions:
reasoning.summary accepts auto, concise, or detailed and is forwarded to backends that support it. It does not guarantee a summary in the gateway response. reasoning.context is accepted for client compatibility but has no effect. Responses remains stateless; send conversation history in input.
When reported by the backend, Chat Completions includes usage.completion_tokens_details.reasoning_tokens. It is a subset of completion_tokens; do not add it again when calculating usage.Some backends return reasoning_content with the assistant message or streaming delta. Keep the complete assistant message when sending tool results back: reasoning content and opaque signatures can be required for the next turn. See tool calling.