general benchmark
Aider-Polyglot
A coding benchmark that evaluates LLMs on 225 challenging Exercism programming exercises across C++, Go, Java, JavaScript, Python, and Rust. Models receive two attempts to solve each problem, with test error feedback provided after the first attempt if it fails. The benchmark measures both initial problem-solving ability and capacity to edit code based on error feedback, providing an end-to-end evaluation of code generation and editing capabilities across multiple programming languages.
Updated Aug 11, 2026
Models22
Model coverage22
MetricScore
EvidenceB
Aider-Polyglot Ranking
Higher score ranks better on this benchmark.
| 01 | OP | 88.0% | 100.0% | 22 | C | |
| 02 | GO | 82.2% | 95.2% | 22 | C | |
| 03 | OP | 81.3% | 90.5% | 22 | C | |
| 04 | GO | 76.5% | 85.7% | 22 | C | |
| 05 | DE | 74.5% | 81.0% | 22 | C | |
| 06 | DE | 71.6% | 76.2% | 22 | C | |
| 07 | OP | 68.9% | 71.4% | 22 | C | |
| 08 | DE | 68.4% | 66.7% | 22 | C | |
| 09 | OP | 66.7% | 61.9% | 22 | C | |
| 10 | GO | 61.9% | 57.1% | 22 | C | |
| 11 | AC | 61.8% | 52.4% | 22 | C | |
| 12 | MA | 60.0% | 47.6% | 22 | C | |
| 13 | MA | 60.0% | 42.9% | 22 | C | |
| 14 | AC | 57.3% | 38.1% | 22 | C | |
| 15 | OP | 51.6% | 33.3% | 22 | C | |
| 16 | AC | 49.8% | 28.6% | 22 | C | |
| 17 | DE | 49.6% | 23.8% | 22 | C | |
| 18 | MA | 47.1% | 19.1% | 22 | C | |
| 19 | OP | 34.7% | 14.3% | 22 | C | |
| 20 | OP | 30.7% | 9.5% | 22 | C | |
| 21 | GO | 26.7% | 4.8% | 22 | C | |
| 22 | OP | 9.8% | 0.0% | 22 | C |
Aider-Polyglot Score Distribution
A closer view of the leading scores on this benchmark.
Aider-Polyglot Highlights
The leading models and scores on this benchmark.
What is Aider-Polyglot?
What Aider-Polyglot measures and how its scores work.
A coding benchmark that evaluates LLMs on 225 challenging Exercism programming exercises across C++, Go, Java, JavaScript, Python, and Rust. Models receive two attempts to solve each problem, with test error feedback provided after the first attempt if it fails. The benchmark measures both initial problem-solving ability and capacity to edit code based on error feedback, providing an end-to-end evaluation of code generation and editing capabilities across multiple programming languages.
Scores are shown in ratio. This benchmark is not independently verified and has an evidence level of B.
- Family
- Aider-Polyglot
- Modality
- text
- Primary category
- general
- Score direction
- higher
- LLMBoard eligible
- Yes
- Evaluation key
- aider-polyglot|llm-stats-current
Benchmark scores retain their original unit. Overall score eligibility is shown separately.
FAQ
Common questions about Aider-Polyglot.
Which model scores highest on Aider-Polyglot?
GPT-5 is currently ranked first with 88.0%.
What does Aider-Polyglot measure?
A coding benchmark that evaluates LLMs on 225 challenging Exercism programming exercises across C++, Go, Java, JavaScript, Python, and Rust. Models receive two attempts to solve each problem, with test error feedback provided after the first attempt if it fails. The benchmark measures both initial problem-solving ability and capacity to edit code based on error feedback, providing an end-to-end evaluation of code generation and editing capabilities across multiple programming languages.
Is a higher score better?
Yes. Higher values rank better for this benchmark.
How many models are compared?
22 model results are currently shown.
Does this benchmark affect the overall score?
Yes. This benchmark can contribute to the current LLMBoard capability score.