Prompting
Reasoning Summaries
Readable digests of a reasoning model's internal chain of thought, returned in place of the raw reasoning.
In depth
Readable digests of a reasoning model's internal chain of thought, returned in place of the raw reasoning. OpenAI returns them when you set the reasoning summary parameter (auto picks the most detailed summarizer a model supports), and Claude returns them with display set to summarized. You are still billed for the full thinking tokens, not the shorter summary. Newer Claude models default to omitted, which returns an empty thinking field unless you ask for the summary.
Primary source: developers.openai.com
Example
In practice, developers reach for Reasoning Summaries when they need the capability described above as part of an AI feature or workflow.
Go deeper at Developers Digest
Hands-on guides, comparisons, and tutorials that cover Prompting.
FAQ
Common questions
What is Reasoning Summaries?
Readable digests of a reasoning model's internal chain of thought, returned in place of the raw reasoning.
Why does Reasoning Summaries matter for AI developers?
Reasoning Summaries sits in the Prompting 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 Summaries?
Developers Digest publishes tutorials and videos that cover Prompting topics including Reasoning Summaries. Check the blog and YouTube channel for hands-on walkthroughs.
Related
Related terms
Prompting
Chain-of-Thought Monitoring
Chain-of-thought monitoring uses an automated monitor, often another language model, to read a reasoning model's chain of thought and flag signs that it intends to misbehave, such as reward hacking, sabotage, or deceiving the user.
Prompting
Reinforcement Fine-Tuning (RFT)
Fine-tuning a model with reinforcement learning against a grader you define, instead of on fixed correct answers.
Prompting
Reward Model
A model trained to give a response a single score that predicts how much a human would prefer it.
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