Hard-negative protein binding prediction
Can the model reason accurately about difficult scientific material?
Science3 ranked models5 reported values1 reportsHigher is better
Top rankings
One row per model, using its best reported score across effort settings.
| Rank | Model | Best score | Best reported setting |
|---|---|---|---|
| 1 | GPT-5.6 SolOpenAI | 7.60% | Reported configurationOpenAI report2 values · 1 reportAug 6, 2026 · source |
| 2 | GPT-5.4OpenAI | 3.50% | Reported configurationOpenAI report1 value · 1 reportAug 6, 2026 · source |
| 3 | GPT-5.5OpenAI | 0.40% | Reported configurationOpenAI report2 values · 1 reportAug 6, 2026 · source |
Effort curve
Every sourced cost-linked effort value for this exact version. Lines connect complete sweeps only.
No cost-linked effort sweep for this version.
Definition and comparison boundaryinternal methodology
Can the model reason accurately about difficult scientific material?
Scientific knowledge and reasoning under the benchmark's published question set. Higher is better. The value is the percentage reported in this lab's table.
This is a publisher-defined internal evaluation. The task set or grading details are not fully public, so treat it as directional evidence.
Proprietary, non-contaminated dataset with browser and computer access; 43 protein targets and 492 hotspots.
Method / source