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reasoning benchmark

GeneBench

GeneBench is an evaluation focused on multi-stage scientific data analysis in genetics and quantitative biology. Tasks require reasoning about ambiguous or noisy data with minimal supervisory guidance, addressing realistic obstacles such as hidden confounders or QC failures, and correctly implementing and interpreting modern statistical methods.

Updated Aug 11, 2026

Models2
Model coverage2
MetricScore
EvidenceB

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  • Ranking
  • Distribution
  • Highlights
  • About
  • FAQ

GeneBench Ranking

Higher score ranks better on this benchmark.

2 rows
Columns

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1OPGPT-5.5 ProOpenAI33.2%100.0%2CAug 11, 2026
2OPGPT-5.5OpenAI25.0%0.0%2CAug 11, 2026

GeneBench Score Distribution

A closer view of the leading scores on this benchmark.

GeneBench

GeneBench Highlights

The leading models and scores on this benchmark.

Rank #1GPT-5.5 Pro33.2%Rank #2GPT-5.525.0%

What is GeneBench?

What GeneBench measures and how its scores work.

GeneBench is an evaluation focused on multi-stage scientific data analysis in genetics and quantitative biology. Tasks require reasoning about ambiguous or noisy data with minimal supervisory guidance, addressing realistic obstacles such as hidden confounders or QC failures, and correctly implementing and interpreting modern statistical methods.

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

Family
GeneBench
Modality
text
Primary category
reasoning
Score direction
higher
LLMBoard eligible
No
Evaluation key
genebench|llm-stats-current

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

FAQ

Common questions about GeneBench.

Which model scores highest on GeneBench?

GPT-5.5 Pro is currently ranked first with 33.2%.

What does GeneBench measure?

GeneBench is an evaluation focused on multi-stage scientific data analysis in genetics and quantitative biology. Tasks require reasoning about ambiguous or noisy data with minimal supervisory guidance, addressing realistic obstacles such as hidden confounders or QC failures, and correctly implementing and interpreting modern statistical methods.

Is a higher score better?

Yes. Higher values rank better for this benchmark.

How many models are compared?

2 model results are currently shown.

Does this benchmark affect the overall score?

No. This benchmark is shown for reference but does not contribute to the overall score.

Rankings

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Modalities

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Benchmarks

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