math benchmark
PolyMath-en
PolyMath is a multilingual mathematical reasoning benchmark covering 18 languages and 4 difficulty levels from easy to hard, ensuring difficulty comprehensiveness, language diversity, and high-quality translation. The benchmark evaluates mathematical reasoning capabilities of large language models across diverse linguistic contexts, making it a highly discriminative multilingual mathematical benchmark.
Updated Aug 11, 2026
Models2
Model coverage2
MetricScore
EvidenceB
PolyMath-en Ranking
Higher score ranks better on this benchmark.
| 01 | MA | 65.1% | 100.0% | 2 | C | |
| 02 | MA | 65.1% | 0.0% | 2 | C |
PolyMath-en Score Distribution
A closer view of the leading scores on this benchmark.
PolyMath-en Highlights
The leading models and scores on this benchmark.
What is PolyMath-en?
What PolyMath-en measures and how its scores work.
PolyMath is a multilingual mathematical reasoning benchmark covering 18 languages and 4 difficulty levels from easy to hard, ensuring difficulty comprehensiveness, language diversity, and high-quality translation. The benchmark evaluates mathematical reasoning capabilities of large language models across diverse linguistic contexts, making it a highly discriminative multilingual mathematical benchmark.
Scores are shown in ratio. This benchmark is not independently verified and has an evidence level of B.
- Family
- PolyMath-en
- Modality
- text
- Primary category
- math
- Score direction
- higher
- LLMBoard eligible
- No
- Evaluation key
- polymath-en|llm-stats-current
Benchmark scores retain their original unit. Overall score eligibility is shown separately.
FAQ
Common questions about PolyMath-en.
Which model scores highest on PolyMath-en?
Kimi K2 Instruct is currently ranked first with 65.1%.
What does PolyMath-en measure?
PolyMath is a multilingual mathematical reasoning benchmark covering 18 languages and 4 difficulty levels from easy to hard, ensuring difficulty comprehensiveness, language diversity, and high-quality translation. The benchmark evaluates mathematical reasoning capabilities of large language models across diverse linguistic contexts, making it a highly discriminative multilingual mathematical benchmark.
Is a higher score better?
Yes. Higher values rank better for this benchmark.
How many models are compared?
2 model results are currently shown.
Does this benchmark affect the overall score?
No. This benchmark is shown for reference but does not contribute to the overall score.