BioMedArena: An Open-source Toolkit for Building and Evaluating Biomedical Deep Research Agents
About
Reproducing and comparing deep research agents today is hard: the same backbone evaluated on the same benchmark can report different accuracies across papers because the harness and tool registry differ, and integrating a new model into a comparable evaluation surface costs weeks of model-specific engineering. These are symptoms of a broader reproducibility problem in deep research agent research. Here, we introduce BioMedArena, an open-source toolkit that addresses this reproducibility gap and provides an arena for comparing deep research agents under a shared evaluation environment. BioMedArena decouples six layers of biomedical agent evaluation -- benchmark loading, tool exposure, tool selection, harness mode, context management, and scoring -- and exposes 166 biomedical benchmarks and 75 biomedical tools across 9 functional families. Adding a new model, benchmark, or tool can be accomplished with a few-line provider adapter. Beyond evaluation infrastructure, BioMedArena ships a library of high-quality reference components: 6 agent harnesses (including our proposed Mutual-Evolve) and 6 context-management strategies, any of which can be equipped on any backbone. Equipping these components substantially improves all 12 backbones; on each of 8 representative biomedical benchmarks, the best equipped backbone surpasses prior state-of-the-art (SOTA), by 15.01 percentage points on average. The toolkit, configurations, and per-task traces are available at https://github.com/AI-in-Health/BioMedArena.
Related benchmarks
| Task | Dataset | Result | Rank | |
|---|---|---|---|---|
| Biomedical Intelligence Evaluation | BixBench 205 (Evaluation) | Accuracy85.9 | 25 | |
| Laboratory Science Knowledge Evaluation | LAB-Bench 2 821 (Evaluation) | Accuracy82.3 | 25 | |
| High-Level Expert Knowledge Evaluation | HLE Gold 149 | Accuracy (Bio)55.1 | 25 | |
| Chemical Reasoning | SuperChem 500 (Total) | Accuracy (Text)72.8 | 15 | |
| Medical Knowledge Evaluation | Medbullets op4 4-option 308 | Accuracy92.2 | 13 | |
| Medical Question Answering | MedXpertQA Expert 2450 | Accuracy72 | 13 | |
| Protein Language Modeling Evaluation | ProteinLM Bench 944 | Accuracy77 | 13 | |
| Medical Question Answering | HealthBench Hard 1000 | Accuracy86 | 12 |