Reinforcement Learning · advanced · concept 131 of 176
GRPO (Group Relative Policy Optimization)
A reinforcement learning algorithm that simplifies PPO by dropping the value network: it samples a group of responses per prompt and scores each one against the group average. Introduced in DeepSeekMath and used to train DeepSeek-R1, it became a standard recipe for training reasoning models on verifiable rewards like math and unit tests.
Key terms
Group baselineNo value networkVerifiable rewardPolicy gradientRollouts
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Where you meet it in the real world
Training reasoning models, math and code post-training, open-weight R1 replications
Videos
▶ Stanford CME295 Transformers & LLMs | Autumn 2025 | Lecture 6 - LLM Reasoning ↗
Stanford Online · YouTube
Guides and articles
GRPO Trainer · Hugging Face ↗
Hugging Face
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