Meta AI has introduced a significant advancement in coding large language models (LLMs) with the development of Reinforcement Learning with Execution Feedback (RLEF). This technique integrates execution feedback at training time to enhance performance at inference time. The approach has been successfully applied to fine-tune Llama 3.1 models, with the 8B model surpassing GPT-4 on DeepMind’s CodeContests and the 70B model achieving state-of-the-art results. Additionally, the method has been validated through extensive evaluations, including on SWE-bench, demonstrating its effectiveness in improving LLMs for code generation tasks. The evaluations were conducted using a cloud-based infrastructure that speeds up evaluations by 30x.