math benchmark
PolyMATH
Polymath is a challenging multi-modal mathematical reasoning benchmark designed to evaluate the general cognitive reasoning abilities of Multi-modal Large Language Models (MLLMs). The benchmark comprises 5,000 manually collected high-quality images of cognitive textual and visual challenges across 10 distinct categories, including pattern recognition, spatial reasoning, and relative reasoning.
Updated Aug 11, 2026
Models23
Model coverage23
MetricScore
EvidenceB
PolyMATH Ranking
Higher score ranks better on this benchmark.
PolyMATH Score Distribution
A closer view of the leading scores on this benchmark.
PolyMATH Highlights
The leading models and scores on this benchmark.
What is PolyMATH?
What PolyMATH measures and how its scores work.
Polymath is a challenging multi-modal mathematical reasoning benchmark designed to evaluate the general cognitive reasoning abilities of Multi-modal Large Language Models (MLLMs). The benchmark comprises 5,000 manually collected high-quality images of cognitive textual and visual challenges across 10 distinct categories, including pattern recognition, spatial reasoning, and relative reasoning.
Scores are shown in ratio. This benchmark is not independently verified and has an evidence level of B.
- Family
- PolyMATH
- Modality
- multimodal
- Primary category
- math
- Score direction
- higher
- LLMBoard eligible
- Yes
- Evaluation key
- polymath|llm-stats-current
Benchmark scores retain their original unit. Overall score eligibility is shown separately.
FAQ
Common questions about PolyMATH.
Which model scores highest on PolyMATH?
Qwen3.7 Max is currently ranked first with 86.5%.
What does PolyMATH measure?
Polymath is a challenging multi-modal mathematical reasoning benchmark designed to evaluate the general cognitive reasoning abilities of Multi-modal Large Language Models (MLLMs). The benchmark comprises 5,000 manually collected high-quality images of cognitive textual and visual challenges across 10 distinct categories, including pattern recognition, spatial reasoning, and relative reasoning.
Is a higher score better?
Yes. Higher values rank better for this benchmark.
How many models are compared?
23 model results are currently shown.
Does this benchmark affect the overall score?
Yes. This benchmark can contribute to the current LLMBoard capability score.