RLVRAfter RL with verifiable rewards, your model's pass@1 on a math benchmark is well above the base model's. Sampling many answers per problem, the base model catches up and at pass@256 solves more problems.
The problems the RL model solves are almost all ones the base model can also solve given enough samples.