BixBench
BixBench is a benchmark for real-world bioinformatics and computational biology data analysis. It evaluates AI models on multi-step scientific workflows that require code execution, statistical reasoning, and biological domain knowledge to interpret experimental data.
GPT-5.5 from OpenAI currently leads the BixBench leaderboard with a score of 0.805 across 1 evaluated AI models.
What BixBench measures
BixBench is a text benchmark that evaluates large language models on science, reasoning, and agents tasks. LLM Stats tracks 1 model on this benchmark, with a maximum possible score of 1. Current average across reported models is 0.8, with the leader reaching 0.8.
Compare leaders on the best AI for science, best AI for reasoning and best AI for agents leaderboards.
Publication
- Paper
- BixBench: a Comprehensive Benchmark for LLM-based Agents in Computational Biology
- Authors
- Ludovico Mitchener, Jon M Laurent, Alex Andonian, Benjamin Tenmann, and 5 others
- Published
- arXiv
- 2503.00096
Abstract
Large Language Models (LLMs) and LLM-based agents show great promise in accelerating scientific research. Existing benchmarks for measuring this potential and guiding future development continue to evolve from pure recall and rote knowledge tasks, towards more practical work such as literature review and experimental planning. Bioinformatics is a domain where fully autonomous AI-driven discovery may be near, but no extensive benchmarks for measuring progress have been introduced to date. We therefore present the Bioinformatics Benchmark (BixBench), a dataset comprising over 50 real-world scenarios of practical biological data analysis with nearly 300 associated open-answer questions designed to measure the ability of LLM-based agents to explore biological datasets, perform long, multi-step analytical trajectories, and interpret the nuanced results of those analyses. We evaluate the performance of two frontier LLMs (GPT-4o and Claude 3.5 Sonnet) using a custom agent framework we open source. We find that even the latest frontier models only achieve 17% accuracy in the open-answer regime, and no better than random in a multiple-choice setting. By exposing the current limitations of frontier models, we hope BixBench can spur the development of agents capable of conducting rigorous bioinformatic analysis and accelerate scientific discovery.
GPT-5.5 leads with 80.5%.
Progress Over Time
Interactive timeline showing model performance evolution on BixBench
BixBench Leaderboard
| Context | Cost | License | ||||
|---|---|---|---|---|---|---|
| 1 | OpenAI | — | 1.1M | $5.00 / $30.00 |
FAQ
Common questions about BixBench.
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