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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

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  • Distribution
  • Highlights
  • About
  • FAQ

PolyMath-en Ranking

Higher score ranks better on this benchmark.

2 rows
Columns

Show columns

1MAKimi K2 InstructMoonshot AI65.1%100.0%2CAug 11, 2026
2MAKimi K2-Instruct-0905Moonshot AI65.1%0.0%2CAug 11, 2026

PolyMath-en Score Distribution

A closer view of the leading scores on this benchmark.

PolyMath-en

PolyMath-en Highlights

The leading models and scores on this benchmark.

Rank #1Kimi K2 Instruct65.1%Rank #2Kimi K2-Instruct-090565.1%

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.

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