Reinforcement Learning (RL) techniques, particularly the Group Relative Policy Optimization (GRPO) algorithm, have been utilized to significantly improve the mathematical reasoning capabilities of language models. The study highlights how proper infrastructure, data diversity, and effective training practices can enhance performance, while also addressing challenges like model collapse and advantage estimation bias.