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safety benchmark

FigQA

FigQA is a multiple-choice benchmark on interpreting scientific figures from biology papers. It evaluates dual-use biological knowledge and multimodal reasoning relevant to bioweapons development.

Updated Aug 11, 2026

Models3
Model coverage3
MetricScore
EvidenceB

On this page

  • Ranking
  • Distribution
  • Highlights
  • About
  • FAQ

FigQA Ranking

Higher score ranks better on this benchmark.

3 rows
Columns

Show columns

01ANClaude Mythos PreviewAnthropic89.0%100.0%3CAug 11, 2026
02ANClaude Opus 4.6Anthropic78.3%50.0%3CAug 11, 2026
03XAGrok-4.1 ThinkingxAI34.0%0.0%3CAug 11, 2026

FigQA Score Distribution

A closer view of the leading scores on this benchmark.

FigQA

FigQA Highlights

The leading models and scores on this benchmark.

Rank #1Claude Mythos Preview89.0%Rank #2Claude Opus 4.678.3%Rank #3Grok-4.1 Thinking34.0%

What is FigQA?

What FigQA measures and how its scores work.

FigQA is a multiple-choice benchmark on interpreting scientific figures from biology papers. It evaluates dual-use biological knowledge and multimodal reasoning relevant to bioweapons development.

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

Family
FigQA
Modality
multimodal
Primary category
safety
Score direction
higher
LLMBoard eligible
Yes
Evaluation key
figqa|llm-stats-current

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

FAQ

Common questions about FigQA.

Which model scores highest on FigQA?

Claude Mythos Preview is currently ranked first with 89.0%.

What does FigQA measure?

FigQA is a multiple-choice benchmark on interpreting scientific figures from biology papers. It evaluates dual-use biological knowledge and multimodal reasoning relevant to bioweapons development.

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.