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reasoning benchmark

MedChemBench (Internal)

MedChemBench is an internal OpenAI evaluation of medicinal-chemistry reasoning, testing whether models can support drug-discovery-relevant chemistry analysis and decision-making.

Updated Aug 11, 2026

Models3
Model coverage3
MetricScore
EvidenceB

On this page

  • Ranking
  • Distribution
  • Highlights
  • About
  • FAQ

MedChemBench (Internal) Ranking

Higher score ranks better on this benchmark.

3 rows
Columns

Show columns

01OPGPT-5.6 SolOpenAI48.3%100.0%3CAug 11, 2026
02OPGPT-5.6 TerraOpenAI35.0%50.0%3CAug 11, 2026
03OPGPT-5.6 LunaOpenAI30.4%0.0%3CAug 11, 2026

MedChemBench (Internal) Score Distribution

A closer view of the leading scores on this benchmark.

MedChemBench (Internal)

MedChemBench (Internal) Highlights

The leading models and scores on this benchmark.

Rank #1GPT-5.6 Sol48.3%Rank #2GPT-5.6 Terra35.0%Rank #3GPT-5.6 Luna30.4%

What is MedChemBench (Internal)?

What MedChemBench (Internal) measures and how its scores work.

MedChemBench is an internal OpenAI evaluation of medicinal-chemistry reasoning, testing whether models can support drug-discovery-relevant chemistry analysis and decision-making.

Scores are shown in ratio. This benchmark is not independently verified and has an evidence level of B.

Family
MedChemBench (Internal)
Modality
text
Primary category
reasoning
Score direction
higher
LLMBoard eligible
Yes
Evaluation key
medchembench|llm-stats-current

Benchmark scores retain their original unit. Overall score eligibility is shown separately.

FAQ

Common questions about MedChemBench (Internal).

Which model scores highest on MedChemBench (Internal)?

GPT-5.6 Sol is currently ranked first with 48.3%.

What does MedChemBench (Internal) measure?

MedChemBench is an internal OpenAI evaluation of medicinal-chemistry reasoning, testing whether models can support drug-discovery-relevant chemistry analysis and decision-making.

Is a higher score better?

Yes. Higher values rank better for this benchmark.

How many models are compared?

3 model results are currently shown.

Does this benchmark affect the overall score?

Yes. This benchmark can contribute to the current LLMBoard capability score.