How do you reconcile the differing results between Deep...

DeepSeekMath’s reliance on PRMs was necessary because their smaller base model solved too few problems to receive useful signal from outcome rewards. At the scale of R1, the model possesses stronger priors, allowing enough problems to receive non-zero outcome rewards for GRPO to function effectively. Therefore, the marginal value of a PRM decreases as model capability and problem filtering improve.