Synthorai
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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 Descrizione
/v1/chat/completions OpenAI-compatible (GPT, GLM, DeepSeek, Qwen, Kimi…) inoltrato Forwarded to the provider as sent, with one exception: when a model's catalog entry lists the effort levels it accepts, a value below the lowest is raised to it and one above the highest steps down (GPT-6.1 Sol cannot turn reasoning off, so none and minimal run at low). Otherwise 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 on most models, GLM takes up to max. Check the provider's own reference for its range.
/v1/chat/completions Google Vertex - Gemini 4 convertito Becomes Gemini's thinkingLevel, kept inside the three levels Gemini 4 Argon accepts: none and minimal run at low (the model cannot turn thinking off), low/medium/high map straight across, xhigh and max run at high. An explicit google.thinking_config in the request wins over this mapping.
/v1/chat/completions Google Vertex - Gemini 3.x convertito 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 scartato 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) convertito Diventa il thinking di Anthropic, nella forma che il modello accetta. Sui modelli Claude che accettano solo il ragionamento adattivo (Claude Opus 4.7 e successivi, Sonnet 5 e successivi, Haiku 5.5), low/medium/high/xhigh/max diventano thinking:{"type":"adaptive"} con output_config.effort allo stesso livello, e minimal gira come low. none disattiva il ragionamento nella forma propria del modello: {"type":"disabled"} sulla maggior parte, {"type":"between_tools"} su Sonnet 5.5, e adattivo a low su Opus 5.5, che non può disattivare il ragionamento. Qualsiasi altro valore non viene inoltrato. Sui modelli Claude precedenti diventa invece un budget: none e minimal disattivano il ragionamento ({"type":"disabled"}); low/medium/high/xhigh/max diventano un budget di 2,048 / 8,192 / 16,384 / 32,768 token, l'inverso della suddivisione usata nella direzione opposta. Un budget derivato resta sotto max_tokens e non viene inviato affatto quando max_tokens non contiene il minimo di 1,024 token di Anthropic, quindi chiedere un livello di effort non trasforma mai una richiesta funzionante in un errore 400 del fornitore.
/v1/messages OpenAI-compatible (GPT, GLM, DeepSeek, Qwen, Kimi…) convertito 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. For a model whose catalog entry lists the effort levels it accepts (GPT-6.1 Sol), the request's intent is followed instead: thinking disabled or between_tools runs at the lowest level (low), even when output_config.effort is also set; otherwise output_config.effort is sent as the effort.
/v1/responses OpenAI-compatible (GPT, GLM, DeepSeek, Qwen, Kimi…) convertito 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-haiku-5-5 · claude-opus-4-5 · claude-opus-4-6 · claude-opus-4-7 · claude-opus-4-8 · claude-opus-5 · claude-opus-5-5 · claude-sonnet-4-5 · claude-sonnet-4-6 · claude-sonnet-5 · claude-sonnet-5-5 · deepseek-v4-flash · deepseek-v4-flash-0731 · deepseek-v4-pro · deepseek-v4-pro-0813 · deepseek-v4.1-flash · deepseek-v4.1-flash-1017 · 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 · 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 · gemini-4-argon · gemini-nano-banana-2.1 · 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 · gpt-6-luna · gpt-6-sol · gpt-6.1-sol · gpt-6.1-terra · 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-flash · qwen3.8-max

Full request body reference: Chat Completions