From Parameters to Behaviors: A Survey of Model Fusion for Large Language Models

Model fusion integrates the capabilities from source models into a single target model. As the open-source AI ecosystem matures, Hugging Face has hosted more than 2M models. This growing pool provides a rich base for model reuse and capability integration. Yet existing surveys often cover only separate parts of this space, and they do not provide a unified definition or a systematic taxonomy. This survey defines model fusion and organizes prior work into three levels: parameter-level, representation-level, and behavior-level fusion. We also review related metrics, benchmarks, and applications, summarize current challenges, and identify future directions. Our goal is to provide a clear map of this area and support future work on model fusion.