Reported in recent model launches
These model reports include this benchmark. Their harnesses, task subsets, scoring policies, and resource budgets can differ; follow each report’s evaluation notes before joining the numbers.
What it measures
OpenAI’s internal medicinal-chemistry evaluation measures a specialist slice of scientific reasoning.
How to read the result
Read this as a measurement under the reporting lab’s task selection and grading rather than a public, universally reproducible leaderboard.
Limits and comparison traps
The launch labels this evaluation internal. Missing public items and detailed scoring limit independent reproduction and broad claims.
Benchmark reference notes
Medicinal chemistry, SAR optimization, and molecular property reasoning benchmark reported in GPT-6 Astra.
Where this fits in an evaluation suite
A correct multiple-choice answer and a supported scientific contribution demand different evidence. Check whether the score rewards a proposal, an executed experiment, or a completed research target.
Start with a capability hypothesis, then choose a second test with a different failure mode. Keep the checkpoint, reasoning effort, agent tools, sampling policy, and scoring procedure fixed when measuring a training intervention. Record failures and missing outputs in the denominator.
A reproducible comparison
Pin the benchmark release, task split, model configuration, tools, sampling budget, and evaluation harness described by the primary source.
Publish the exact run configuration, item coverage, score units, and available uncertainty. If a source supplies only an aggregate or a single run, preserve that limit. A new model name or a rounded score alone does not establish a capability improvement.
PRIMARY EVIDENCE & FURTHER READING
Reviewed 2026-10-26. Explanation and interpretation by RLTasks. Benchmark ownership remains with its original authors.