Reasoning Models & Test-Time Compute

Models trained to reason at length, and methods that improve answers by spending more computation at inference time.

Definitions

Extended Thinking: Extended thinking is a model mode in which the model generates a separate block of reasoning before its final response, with a developer-controlled setting that trades latency and cost for answer quality.
Reasoning Model: A reasoning model is a language model trained, typically with reinforcement learning, to produce an extended internal chain of thought before answering, so that it improves with more thinking time on math, coding, and planning tasks.
Self-Taught Reasoner: The Self-Taught Reasoner (STaR) bootstraps reasoning ability by having a model generate rationales, keeping those that lead to correct answers, and fine-tuning on them in repeated rounds.
Test-Time Compute Scaling: Test-time compute scaling improves a model's answers by spending more computation at inference, through longer reasoning, more samples, search, or verification, rather than by training a larger model.