OpenCodeInterpreter is an open-source code generation system that seamlessly combines code creation, execution, and iterative optimization. Trained using a dataset of 68,000 interactive Code-Feedback samples, it dynamically optimizes code based on execution outputs and human feedback. Its exceptional performance in code generation is highlighted by evaluations in benchmark tests like HumanEval and MBPP, where it achieves an average accuracy of 83.2% on OpenCodeInterpreter, which is comparable to the 84.2% of GPT-4 with an Improvement strategy and can be enhanced by human feedback to an accuracy of 91.6%. OpenCodeInterpreter narrows the gap between open-source code generation models and proprietary systems like GPT-4.