A visual mathematics benchmark that tests whether a model can solve math problems grounded in diagrams, equations, figures, and other visual inputs.
BenchLM mirrors the published score view for MathVision. Qwen3.5 397B leads the public snapshot at 88.6% , followed by Qwen3.6 Plus (88.0%) and Kimi K2.6 (87.4%). BenchLM does not use these results to rank models overall.
Qwen3.5 397B
Alibaba
Qwen3.6 Plus
Alibaba
Kimi K2.6
Moonshot AI
The published MathVision snapshot is tightly clustered at the top: Qwen3.5 397B sits at 88.6%, while the third row is only 1.2 points behind. The broader top-10 spread is 14.3 points, so the benchmark still separates strong models even when the leaders cluster.
9 models have been evaluated on MathVision. The benchmark falls in the Multimodal & Grounded category. This category carries a 12% weight in BenchLM.ai's overall scoring system. MathVision is currently displayed for reference but excluded from the scoring formula, so it does not directly affect overall rankings.
Year
2026
Tasks
Visually grounded math problems
Format
Image + math reasoning
Difficulty
Advanced multimodal mathematics
MathVision matters because text-only math ability does not guarantee strong performance when the relevant information is embedded in images, geometry diagrams, or formatted equations.
Version
MathVision 2026
Refresh cadence
Quarterly
Staleness state
Current
Question availability
Public benchmark set
BenchLM uses freshness metadata to decide whether a benchmark should still be treated as a strong differentiator, a benchmark to watch, or a display-only reference. For the full scoring policy, see the BenchLM methodology page.
A visual mathematics benchmark that tests whether a model can solve math problems grounded in diagrams, equations, figures, and other visual inputs.
Qwen3.5 397B by Alibaba currently leads with a score of 88.6% on MathVision.
9 AI models have been evaluated on MathVision on BenchLM.
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