Hard-negative protein binding predictionBrowse 284 families
Hard-negative protein binding prediction
Can the model reason accurately about difficult scientific material?
- Domain
- Science
- Ranked models
- 2
- Reported values
- 2
- Reports
- 1 · lab
- Direction
- Higher is better
- Status
- Latest stable
Rankings
Best reported score per model across effort settings
| # | Model | Best setting | Score |
|---|---|---|---|
| 1 | GPT-5.6 SolOpenAI | reportedcost n/a1 value · Sep 3 · source | 7.6% |
| 2 | GPT-6 AstraOpenAI | reportedcost n/a1 value · Sep 3 · source | 0.0% |
Effort curve
Score vs. reported cost. Lines connect complete sweeps only.
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. Percentage of protein-binding selections scored correct by OpenAI.
This is a publisher-defined internal evaluation. The task set or grading details are not fully public, so treat it as directional evidence.
OpenAI reports 0.0% for ordinary Astra and 7.6% for GPT-5.6 Sol on a proprietary non-contaminated evaluation with 43 protein targets and 492 hotspots; a helpful-only Astra model is also 0.0%. OpenAI is retiring this evaluation and notes an environment-variable leakage issue.
Method / source ↗