Inference
Reasoning Effort
An API setting that tells a reasoning model how much work to put into a response, trading answer quality against latency and token cost.
In depth
An API setting that tells a reasoning model how much work to put into a response, trading answer quality against latency and token cost. OpenAI exposes it as reasoning.effort with levels such as low, medium, and high, and some models add none, minimal, xhigh, or max. Anthropic's equivalent is the effort parameter, which shapes all output tokens including thinking, text, and tool calls. Defaults vary by model, so check the model page before relying on one.
Primary source: developers.openai.com
Example
OpenAI exposes it as reasoning.effort with levels such as low, medium, and high, and some models add none, minimal, xhigh, or max.
Go deeper at Developers Digest
Hands-on guides, comparisons, and tutorials that cover Inference.
FAQ
Common questions
What is Reasoning Effort?
An API setting that tells a reasoning model how much work to put into a response, trading answer quality against latency and token cost.
Why does Reasoning Effort matter for AI developers?
Reasoning Effort sits in the Inference part of the AI stack. Understanding it helps you make better decisions when building, debugging, and shipping AI features.
Where can I learn more about Reasoning Effort?
Developers Digest publishes tutorials and videos that cover Inference topics including Reasoning Effort. Check the blog and YouTube channel for hands-on walkthroughs.
Related
Related terms
Inference
Thinking Tokens
The tokens a reasoning model generates while working through a problem before it writes its final answer.
Inference
Rate Limits (RPM and TPM)
Caps on how much traffic an organization can send to a model API, measured in requests per minute (RPM) and tokens per minute (TPM).
Inference
Tokens per Second
A throughput measure of how many output tokens a model or serving system produces each second.
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