GeneBench-Pro
Research-level computational-biology benchmark for AI agents performing judgment-heavy, multistage scientific analyses in genomics, quantitative biology, and translational biomedicine. The suite contains 129 synthetically constructed problems across 10 primary domains and 21 subdomains, with known causal structure and deterministic grading against decision-relevant target estimands.
Models ranked
25
tracked on this benchmark
Score band
31.5 – 0.6
best → lowest tracked
Snapshot trend
+24.08
Jun 30 → Jul 9 · 1 models
Leaderboard
Tracked models ranked by Pass rate (higher is better).
Notes: Keeps the higher Pro-mode score (31.5) per thinking-model rules; GA launch table also cites 28.7% in standard mode.
How to read this benchmark
This benchmark scores models where higher is better. Use scores for directional filtering and shortlisting, not universal quality ranking; then validate pricing, context window, provider availability, and fit for your workload.
Trust this score when
- There is a fresh timestamped snapshot (or multiple snapshots) for this benchmark.
- The model list covers the same version family you can actually deploy today.
- Top candidates overlap with your required routing and feature requirements.
Be cautious when
- There is only one benchmark snapshot or the dataset appears stale.
- The benchmark metric direction is opposite of your decision objective.
- The score difference between options is narrow and likely within implementation variance.
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Last reviewed: Jul 2, 2026