MASEval is a new framework designed for the comprehensive evaluation of multi-agent systems based on large language models (LLM). Unlike existing benchmarks, which primarily focus on model capabilities, MASEval considers the entire system as the unit of analysis, including topology, orchestration logic, and error handling.

System-Level Evaluation

The framework aims to address a significant gap in the current landscape of evaluation tools, where implementation decisions at the system level can significantly impact performance. MASEval allows for the systematic comparison of different frameworks (such as smolagents, LangGraph, and AutoGen) across various benchmarks and models, highlighting how the choice of framework can have a comparable impact to that of the model itself.

Flexibility and License

MASEval is distributed under the MIT license and is available on GitHub, offering researchers and developers a flexible tool to explore and improve multi-agent systems. This holistic approach allows for the identification of the most suitable implementations for specific use cases and the development of more efficient and performant systems.