AI benchmarks and leaderboards are different things
Learn the difference between a benchmark, an evaluation run and a leaderboard, and use each to answer the right question.
LLM Stats
Aider
Aider is a comprehensive code editing benchmark based on 133 practice exercises from Exercism's Python repository, designed to evaluate AI models' ability to translate natural language coding requests into executable code that passes unit tests. The benchmark measures end-to-end code editing capabilities, including GPT's ability to edit existing code and format code changes for automated saving to local files. The Aider Polyglot variant extends this evaluation across 225 challenging exercises spanning C++, Go, Java, JavaScript, Python, and Rust, making it a standard benchmark for assessing multilingual code editing performance in AI research.
Evaluation context and evidence
- Source
- LLM Stats
- Publisher
- Not recorded
- Benchmark release
- Not recorded
- Collected
- 2026-08-17
- Modality
- text
These are source-reported observations, not independent reruns by this site. Check the task version, evaluation protocol, unit and reporting date before comparing models. Results from different setups are not a universal ranking.
Original sources
Reported results 4
Shown in source observation order, not ranked. Dates retain the precision provided by the source.
| Model | Value | Unit | Protocol | Reported date and basis | Source |
|---|---|---|---|---|---|
| DeepSeek-V2.5 | 0.722 | Not recorded | Not recorded | 2024-05-08 · model_announcement | LLM Stats |
| Qwen3 235B A22B | 0.618 | Not recorded | Not recorded | 2025-04-29 · model_announcement | LLM Stats |
| Qwen2.5-Coder 7B Instruct | 0.556 | Not recorded | Not recorded | 2024-09-19 · model_announcement | LLM Stats |
| Qwen3 32B | 0.502 | Not recorded | Not recorded | 2025-04-29 · model_announcement | LLM Stats |