GRPO (Group Relative Policy Optimization) is one of the foundational technologies behind the success of DeepSeek-R1, and we have reported on this technology multiple times before.
In simple terms, the GRPO algorithm discards the critic model and abandons value function approximation, instead computing the policy gradient by performing relative comparisons among samples within a group. This effectively reduces training instability while improving learning efficiency.
Since GRPO is so effective, do you know how to implement GRPO from scratch?
