Training and post-training

Reasoning and test-time compute

Post-training that teaches a model to produce a long reasoning trace before answering, and to spend more compute at inference when a problem is harder. Reinforcement learning with verifiable rewards — where a checkable answer supplies the training signal — is what made the approach reproducible outside closed labs. The trade is worth stating plainly: accuracy bought with generation length rather than with a larger model, and paid for in latency and serving cost.

Reference period

2024 / 2025

Last reviewed

2026-08-30