math benchmark
MATH-Vision is a dataset designed to measure multimodal mathematical reasoning capabilities. It focuses on evaluating how well models can solve mathematical problems that require both visual understanding and mathematical reasoning, bridging the gap between visual and mathematical domains.
Updated Aug 11, 2026
Higher score ranks better on this benchmark.
A closer view of the leading scores on this benchmark.
The leading models and scores on this benchmark.
What MathVision measures and how its scores work.
MATH-Vision is a dataset designed to measure multimodal mathematical reasoning capabilities. It focuses on evaluating how well models can solve mathematical problems that require both visual understanding and mathematical reasoning, bridging the gap between visual and mathematical domains.
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 MathVision.
Kimi K3 is currently ranked first with 97.8%.
MATH-Vision is a dataset designed to measure multimodal mathematical reasoning capabilities. It focuses on evaluating how well models can solve mathematical problems that require both visual understanding and mathematical reasoning, bridging the gap between visual and mathematical domains.
Yes. Higher values rank better for this benchmark.
32 model results are currently shown.
Yes. This benchmark can contribute to the current LLMBoard capability score.