Benchmark

Aider-Polyglot

general code text

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.

语言EN
满分1
参评模型31

模型排名

名次 模型 机构 分数 来源
1 GPT-5 OpenAI 88.0 来源 ↗
2 Gemini 2.5 Pro Preview 06-05 Google 82.2 来源 ↗
3 o3 OpenAI 81.3 来源 ↗
4 Gemini 2.5 Pro Google 76.5 来源 ↗
5 DeepSeek-V3.2-Exp DeepSeek 74.5 来源 ↗
6 DeepSeek Reasoner DeepSeek 74.2 来源 ↗
7 Claude Opus 4 (latest) Anthropic 72.0 来源 ↗
8 DeepSeek-R1-0528 DeepSeek 71.6 来源 ↗
9 DeepSeek Chat DeepSeek 70.2 来源 ↗
10 o4-mini OpenAI 68.9 来源 ↗
11 DeepSeek-V3.1 DeepSeek 68.4 来源 ↗
12 o3-mini OpenAI 66.7 来源 ↗
13 Gemini 2.5 Flash Google 61.9 来源 ↗
14 Claude Sonnet 4 (latest) Anthropic 61.3 来源 ↗
15 Kimi K2 Instruct Moonshot AI 60.0 来源 ↗
16 Kimi K2-Instruct-0905 Moonshot AI 60.0 来源 ↗
17 Qwen3-235B-A22B-Instruct-2507 Alibaba Cloud / Qwen Team 57.3 来源 ↗
18 GPT-4.1 OpenAI 51.6 来源 ↗
19 Qwen3-Next-80B-A3B-Instruct Alibaba Cloud / Qwen Team 49.8 来源 ↗
20 DeepSeek-V3 DeepSeek 49.6 来源 ↗
21 Magistral Medium Mistral AI 47.1 来源 ↗
22 GPT-4.1 mini OpenAI 34.7 来源 ↗
23 GPT-4o OpenAI 30.7 来源 ↗
24 Gemini 2.5 Flash-Lite Google 26.7 来源 ↗
25 GPT-4o OpenAI 23.1 来源 ↗
26 Qwen Max Alibaba Cloud / Qwen Team 21.8 来源 ↗
27 GPT-4o (2024-11-20) OpenAI 18.2 来源 ↗
28 Llama 4 Maverick 17B Instruct Meta 15.6 来源 ↗
29 Command A Cohere 12.0 来源 ↗
30 Codestral (latest) Mistral AI 11.1 来源 ↗
31 GPT-4.1 nano OpenAI 9.8 来源 ↗