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Benchmarks · coding

Aider Polyglot

Evaluates LLMs on 225 Exercism coding exercises across six languages, testing code editing without human intervention. Maintained by Paul Gauthier. Score: Percent of the 225 Exercism exercises completed with a correct edit.

37 models · 42 results · data as of 2026-10-29 · aider.chat ↗

Leaderboard

Chart settings
37 of 37 selected
GPT-5 high

All results

42 rows
#ModelEffortAider PolyglotHarness
1GPT-5high88.0%
2GPT-5medium86.7%
3o3 prohigh84.9%
4Gemini 2.5 Prohigh83.1%
5GPT-5low81.3%
6o3high81.3%
7Grok 4high79.6%
8Gemini 2.5 Promedium79.1%
9GPT-4.1high78.2%
10DeepSeek V3.2high74.2%
11Opus 4medium72.0%
12o4 minihigh72.0%
13DeepSeek R1xhigh71.4%
14o1high61.7%
15Sonnet 4high61.3%
16o3 minihigh60.4%
17Qwen 3 235B-A22Bxhigh59.6%
18Kimi K2medium59.1%
19DeepSeek V3none55.1%aider, 'diff' edit format
20Gemini 2.5 Flashmedium55.1%
21o3 minimedium53.8%
22Grok 3none53.3%
23Sonnet 3.5medium51.6%
24Grok 3 Minihigh49.3%
25GPT-4.544.9%
26gpt-oss-120bhigh41.8%
27Qwen 3 32Bnone40.0%
28Gemini 120638.2%
29Gemini 2.0 Pronone35.6%
30Grok 3 Minilow34.7%