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Reasoning Effort

reasoning_effort caps how much a model thinks before it answers. On models that reason without a bound by default it is the single largest cost lever - and what it does depends entirely on which upstream your model runs on.

Values

Send one of these on the request body. Higher effort means more reasoning tokens billed and slower replies:

minimal · low · medium · high

Example request

curl https://synthorai.io/v1/chat/completions \
  -H "Authorization: Bearer $SYNTHORAI_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "glm-5.2",
    "messages": [{"role": "user", "content": "Refactor this function."}],
    "reasoning_effort": "low"
  }'

What happens per upstream

The gateway speaks one protocol to you and another to each provider. This table states what the parameter becomes on the way out - including the case where it is dropped.

You call Upstream Behaviour 說明
/v1/chat/completions OpenAI-compatible (GPT, GLM, DeepSeek, Qwen, Kimi…) 透傳 Forwarded to the provider as sent - the gateway neither validates the value nor guarantees the provider honours it. Commonly minimal, low, medium and high, but the accepted set is the provider's: OpenAI also takes none, GLM takes up to max.
/v1/chat/completions Google Vertex - Gemini 3.x 對應 Becomes Gemini's thinkingLevel: none and minimal both map to minimal, low/medium/high map straight across. An explicit google.thinking_config in the request wins over this mapping.
/v1/chat/completions Google Vertex - Gemini 2.5 丟棄 Gemini 2.5 only understands thinkingBudget and rejects thinkingLevel outright, so the gateway sends neither and leaves the model at its default thinking behaviour. Use google.thinking_config with thinking_budget to control 2.5.
/v1/chat/completions Anthropic (Claude) 對應 Becomes Anthropic thinking. none and minimal turn thinking off ({"type":"disabled"}); low/medium/high/xhigh/max become a budget of 2,048 / 8,192 / 16,384 / 32,768 tokens - the inverse of the bucket mapping used in the other direction. A derived budget is clamped to stay below max_tokens, and is skipped entirely when max_tokens cannot fit Anthropic's 1,024-token minimum, so asking for effort never turns a working request into an upstream 400.
/v1/messages OpenAI-compatible (GPT, GLM, DeepSeek, Qwen, Kimi…) 對應 Derived from thinking.budget_tokens by bucket, when extended thinking is enabled and the budget is above zero: up to 2,048 tokens becomes low, up to 8,192 becomes medium, above that becomes high. A zero or absent budget sends nothing.
/v1/responses OpenAI-compatible (GPT, GLM, DeepSeek, Qwen, Kimi…) 對應 Read out of the Responses-API reasoning.effort object and sent as the flat reasoning_effort field.

Each row is transcribed from the converter that implements it and pinned by a Go test, so this table cannot drift from the running gateway without a build failing.

Cost impact

Reasoning tokens are billed as output tokens. On a model that reasons unbounded by default, setting an explicit effort is usually the difference between a few cents and a few dollars for the same answer - measure it on your own prompts before choosing a default.

Models that reason

These models document a reasoning mode. Check the model page for how its upstream handles the parameter:

ByteDance-Seed-1.8 · Dola-Seed-2.0-lite · Dola-Seed-2.0-mini · Dola-Seed-2.0-pro · claude-fable-5 · claude-fable-5-1 · claude-haiku-4-5 · claude-opus-4-5 · claude-opus-4-6 · claude-opus-4-7 · claude-opus-4-8 · claude-opus-5 · claude-sonnet-4-5 · claude-sonnet-4-6 · claude-sonnet-5 · deepseek-v4-flash · deepseek-v4-flash-0731 · deepseek-v4-pro · deepseek-v4-pro-0813 · gemini-2.5-flash · gemini-2.5-flash-lite · gemini-2.5-flash-native-audio · gemini-2.5-pro · gemini-3-flash-preview · gemini-3-pro-image-preview · gemini-3.1-flash-image · gemini-3.1-flash-image-preview · gemini-3.1-flash-lite-image · gemini-3.1-flash-lite-preview · gemini-3.1-flash-live · gemini-3.1-pro-preview · gemini-3.5-flash · gemini-3.5-flash-lite · gemini-3.6-flash · gemini-3.7-flash · gemini-3.8-flash · glm-5 · glm-5-turbo · glm-5.1 · glm-5.2 · glm-5.3 · glm-5.3-flash · gpt-5.2 · gpt-5.2-codex · gpt-5.3-codex · gpt-5.4 · gpt-5.4-mini · gpt-5.4-nano · gpt-5.4-pro · gpt-5.5 · gpt-5.5-pro · gpt-5.6 · gpt-5.6-luna · gpt-5.6-sol · gpt-5.6-terra · gpt-6-astra · kimi-k2.5 · kimi-k2.7-code · kimi-k3 · minimax-m3 · qwen3-max · qwen3-vl-flash · qwen3-vl-plus · qwen3.5-flash · qwen3.5-plus · qwen3.6-35b-a3b · qwen3.6-flash · qwen3.7-max · qwen3.7-plus · qwen3.8-max

Full request body reference: Chat Completions