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general benchmark

Aider-Polyglot Edit

A challenging multi-language coding benchmark that evaluates models' code editing abilities across C++, Go, Java, JavaScript, Python, and Rust. Contains 225 of Exercism's most difficult programming problems, selected as problems that were solved by 3 or fewer out of 7 top coding models. The benchmark focuses on code editing tasks and measures both correctness of solutions and proper edit format usage. Designed to re-calibrate evaluation scales so top models score between 5-50%.

Updated Aug 11, 2026

Models10
Model coverage10
MetricScore
EvidenceB

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  • Ranking
  • Distribution
  • Highlights
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  • FAQ

Aider-Polyglot Edit Ranking

Higher score ranks better on this benchmark.

10 rows
Columns

Show columns

01DEDeepSeek-V3DeepSeek79.7%100.0%10CAug 11, 2026
02GOGemini 2.5 ProGoogle72.7%88.9%10CAug 11, 2026
03OPo3-miniOpenAI60.4%77.8%10CAug 11, 2026
04OPo4-miniOpenAI58.2%66.7%10CAug 11, 2026
05GOGemini 2.5 FlashGoogle56.7%55.6%10CAug 11, 2026
06OPGPT-4.1OpenAI52.9%44.4%10CAug 11, 2026
07OPGPT-4.5OpenAI44.9%33.3%10CAug 11, 2026
08OPGPT-4.1 miniOpenAI31.6%22.2%10CAug 11, 2026
09OPGPT-4oOpenAI18.2%11.1%10CAug 11, 2026
10OPGPT-4.1 nanoOpenAI6.2%0.0%10CAug 11, 2026

Aider-Polyglot Edit Score Distribution

A closer view of the leading scores on this benchmark.

Aider-Polyglot Edit

Aider-Polyglot Edit Highlights

The leading models and scores on this benchmark.

Rank #1DeepSeek-V379.7%Rank #2Gemini 2.5 Pro72.7%Rank #3o3-mini60.4%Rank #4o4-mini58.2%

What is Aider-Polyglot Edit?

What Aider-Polyglot Edit measures and how its scores work.

A challenging multi-language coding benchmark that evaluates models' code editing abilities across C++, Go, Java, JavaScript, Python, and Rust. Contains 225 of Exercism's most difficult programming problems, selected as problems that were solved by 3 or fewer out of 7 top coding models. The benchmark focuses on code editing tasks and measures both correctness of solutions and proper edit format usage. Designed to re-calibrate evaluation scales so top models score between 5-50%.

Scores are shown in ratio. This benchmark is not independently verified and has an evidence level of B.

Family
Aider-Polyglot Edit
Modality
text
Primary category
general
Score direction
higher
LLMBoard eligible
Yes
Evaluation key
aider-polyglot-edit|llm-stats-current

Benchmark scores retain their original unit. Overall score eligibility is shown separately.

FAQ

Common questions about Aider-Polyglot Edit.

Which model scores highest on Aider-Polyglot Edit?

DeepSeek-V3 is currently ranked first with 79.7%.

What does Aider-Polyglot Edit measure?

A challenging multi-language coding benchmark that evaluates models' code editing abilities across C++, Go, Java, JavaScript, Python, and Rust. Contains 225 of Exercism's most difficult programming problems, selected as problems that were solved by 3 or fewer out of 7 top coding models. The benchmark focuses on code editing tasks and measures both correctness of solutions and proper edit format usage. Designed to re-calibrate evaluation scales so top models score between 5-50%.

Is a higher score better?

Yes. Higher values rank better for this benchmark.

How many models are compared?

10 model results are currently shown.

Does this benchmark affect the overall score?

Yes. This benchmark can contribute to the current LLMBoard capability score.