Reasoning Model
A Reasoning Model (or o1-style model) is an artificial intelligence model trained to perform reinforcement learning and execute chain-of-thought steps internally before returning an answer. This allows the model to deliberate, correct mistakes, and evaluate strategies.
Frequently Asked Questions
How do reasoning models differ from standard LLMs?▼
Standard LLMs output text instantly on a token-by-token basis. Reasoning models generate internal 'thinking tokens' to plan and check their work before writing the final output.
Do thinking tokens count toward API costs?▼
Yes, thinking tokens require computation during inference and are typically charged as input/output tokens.
Quick Facts
- CategoryFoundational AI
- Key ApplicationComplex code generation, advanced mathematics solving, and scientific research analysis.
Coverage Trend12 Weeks
Related AI Terms
Reasoning Model Media Coverage & Intelligence
Using AI to help physicians diagnose rare genetic diseases affecting children
Researchers used an OpenAI reasoning model to help diagnose rare diseases, identifying 18 new diagnoses in previously unsolved cases.
Forecasting Future Behavior as a Learning Task
Trust in an AI system is often anchored by explanations of how it works, which one then uses to forecast its behavior on new inputs. For large reasoning models
Not All Errors Are Equal: Consequence-Aware Reasoning Compute Allocation
Modern reasoning models can allocate different amounts of test-time computation, such as thinking tokens, model