general benchmark
Aider-Polyglot Edit Leaderboard
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 17, 2026
Models10
Model coverage10
MetricScore
EvidenceB
Aider-Polyglot Edit Ranking
Higher score ranks better on this benchmark.
Sort by
Rank | Model | Score | Percentile | Participants | Evidence | Evaluated |
|---|
| Rank01 | ModelDE | Score79.7% | Percentile100.0% | Participants10 | EvidenceC | Evaluated |
| Rank02 | ModelGO | Score72.7% | Percentile88.9% | Participants10 | EvidenceC | Evaluated |
| Rank03 | ModelOP | Score60.4% | Percentile77.8% | Participants10 | EvidenceC | Evaluated |
| Rank04 | ModelOP | Score58.2% | Percentile66.7% | Participants10 | EvidenceC | Evaluated |
| Rank05 | ModelGO | Score56.7% | Percentile55.6% | Participants10 | EvidenceC | Evaluated |
| Rank06 | ModelOP | Score52.9% | Percentile44.4% | Participants10 | EvidenceC | Evaluated |
| Rank07 | ModelOP | Score44.9% | Percentile33.3% | Participants10 | EvidenceC | Evaluated |
| Rank08 | ModelOP | Score31.6% | Percentile22.2% | Participants10 | EvidenceC | Evaluated |
| Rank09 | ModelOP | Score18.2% | Percentile11.1% | Participants10 | EvidenceC | Evaluated |
| Rank10 | ModelOP | Score6.2% | Percentile0.0% | Participants10 | EvidenceC | Evaluated |
Aider-Polyglot Edit Highlights
The leading models and scores on this benchmark.
Aider-Polyglot Edit Score Distribution
A closer view of the leading scores on this benchmark.
The Top AI Models for Aider-Polyglot Edit
The first five results on this benchmark, with official price and output speed added where the model identity can be matched.
Ranking basisThis aider-polyglot edit AI model leaderboard uses descending score in the benchmark's original unit. The leaderboard ranking keeps matched price and speed data separate from benchmark evidence.
- 01DEDeepSeek-V3DeepSeek
- Score
- 79.7%
- Speed
- Up to 100 tok/s via DeepSeek
Strengths
- Ranks #1 of 10 compared models
- 100th percentile on this benchmark
- C evidence result
Considerations
- This result measures Aider-Polyglot Edit, not total model capability
- 02GOGemini 2.5 ProGoogle
- Score
- 72.7%
- Price
- $1.3 input / $10 output per 1M tokens
- Speed
- Up to 86 tok/s via Google
Strengths
- Ranks #2 of 10 compared models
- 89th percentile on this benchmark
- C evidence result
Considerations
- This result measures Aider-Polyglot Edit, not total model capability
- 03OPo3-miniOpenAI
- Score
- 60.4%
- Price
- $1.1 input / $4.4 output per 1M tokens
- Speed
- Up to 115 tok/s via Azure
Strengths
- Ranks #3 of 10 compared models
- 78th percentile on this benchmark
- C evidence result
Considerations
- This result measures Aider-Polyglot Edit, not total model capability
- 04OPo4-miniOpenAI
- Score
- 58.2%
- Price
- $1.1 input / $4.4 output per 1M tokens
- Speed
- Up to 115 tok/s via OpenAI
Strengths
- Ranks #4 of 10 compared models
- 67th percentile on this benchmark
- C evidence result
Considerations
- This result measures Aider-Polyglot Edit, not total model capability
- 05GOGemini 2.5 FlashGoogle
- Score
- 56.7%
- Price
- $0.30 input / $2.5 output per 1M tokens
- Speed
- Up to 85 tok/s via Google
Strengths
- Ranks #5 of 10 compared models
- 56th percentile on this benchmark
- C evidence result
Considerations
- This result measures Aider-Polyglot Edit, not total model capability
Selection summary
Best AI Models for Aider-Polyglot Edit
DeepSeek-V3 currently leads Aider-Polyglot Edit with 79.7%. It is the top model on this specific benchmark, while the best LLM for the broader task should also be checked against other benchmarks, price and runtime.
Use this leaderboard with the supporting benchmark results and coverage details above. A leaderboard position summarizes the selected ranking signal; it does not replace workload-specific testing.
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.