LLM Reference
Code editing across 8 programming languagesactiveCoding

Code editing across 8 programming languages: Aider Polyglot

Metric: % Exercises CompletedIntroduced: 2024

About

Real-world code editing benchmark measuring a model's ability to apply changes to existing codebases across 8 programming languages using Exercism platform exercises.

How to read this benchmark

This benchmark uses a scoring system where higher is better. Scores are useful for directional filtering and model shortlisting, not for universal quality ranking.

Interpretation checklist: prefer benchmarks that are closest to your workload style, then validate against the linked model pages for pricing, context window, and provider availability.

Trust when:

  • There is a fresh timestamped snapshot (or multiple snapshots) for this benchmark.
  • Model list covers the same version family you can actually deploy today.
  • Top candidates overlap with your required routing and feature requirements.

Don't trust when:

  • There is only one benchmark snapshot or the dataset appears stale.
  • Benchmark metric direction is opposite of your decision objective.
  • The score difference between options is narrow and likely within implementation variance.

Current modeled score band for tracked entries is roughly 88.0 – 79.6.

Window

May 5 to May 29

last 3 snapshots

Mean delta

-4.90

score points

Coverage

1

models in latest snapshot

Leaderboard preview (top 5)

  1. 1. GPT-588.0
  2. 2. o3-pro84.9
  3. 3. Gemini 2.5 Pro83.1
  4. 4. o381.3
  5. 5. Grok 479.6