multimodal benchmark
ScienceQA Visual is a multimodal science question answering benchmark consisting of 21,208 multiple-choice questions from elementary and high school science curricula. The dataset covers 3 subjects (natural science, language science, social science), 26 topics, 127 categories, and 379 skills. 48.7% of questions include image context requiring multimodal reasoning. Questions are annotated with lectures (83.9%) and explanations (90.5%) to support chain-of-thought reasoning for science question answering.
Updated Aug 11, 2026
Higher score ranks better on this benchmark.
| 01 | MI | 97.5% | 100.0% | 1 | C |
The leading models and scores on this benchmark.
What ScienceQA Visual measures and how its scores work.
ScienceQA Visual is a multimodal science question answering benchmark consisting of 21,208 multiple-choice questions from elementary and high school science curricula. The dataset covers 3 subjects (natural science, language science, social science), 26 topics, 127 categories, and 379 skills. 48.7% of questions include image context requiring multimodal reasoning. Questions are annotated with lectures (83.9%) and explanations (90.5%) to support chain-of-thought reasoning for science question answering.
Scores are shown in ratio. This benchmark is not independently verified and has an evidence level of B.
Benchmark scores retain their original unit. Overall score eligibility is shown separately.
Common questions about ScienceQA Visual.
Phi-4-multimodal-instruct is currently ranked first with 97.5%.
ScienceQA Visual is a multimodal science question answering benchmark consisting of 21,208 multiple-choice questions from elementary and high school science curricula. The dataset covers 3 subjects (natural science, language science, social science), 26 topics, 127 categories, and 379 skills. 48.7% of questions include image context requiring multimodal reasoning. Questions are annotated with lectures (83.9%) and explanations (90.5%) to support chain-of-thought reasoning for science question answering.
Yes. Higher values rank better for this benchmark.
1 model results are currently shown.
No. This benchmark is shown for reference but does not contribute to the overall score.