SWE-InfraBench: leaderboard

SWE-InfraBench (2025) tests infrastructure-as-code editing: in 100 AWS CDK projects a code block is masked, the model writes it from a natural-language request, and unit tests check the CloudFormation template the project then synthesizes; one attempt per task. The board is Correctness, the percentage of tasks whose solution passes every test; higher is better.

Metric: Correctness (%): share of tasks whose generated code passes all unit tests; 100 AWS CDK (Python) infrastructure-as-code tasks built from 34 open-source and custom repositories: the model writes a masked code block from a natural-language request inside a real project, and the synthesized CloudFormation template is checked by hidden unit tests; one attempt per task, temperature 0.25, Anthropic models prompted with extra XML tags; higher is better. Source: arxiv.org. Saturation forecast: Estimated already saturated. 20 models tracked.

Top models

#ModelScoreOverall rank
1Claude 3.7 Sonnet34#458
2Claude 3.5 Sonnet (20241022)32#637
3Claude 3.5 Sonnet (20240620)29#687
4Gemini 2.5 Pro (Preview 03-25)29#236
5Gemini 2.5 Pro (Preview 05-06)29#275
6DeepSeek R124#473
7O323#228
8O4 Mini23#353
9GPT-4.118#495
10Llama 3.1 405B Instruct9#1115
11Claude 3 Haiku8#2609
12Llama 4 Maverick Instruct8#1133
13Gemini 2.0 Flash Lite5#1032
14GPT-4o Mini4#1623
15Llama 4 Scout Instruct2#1543

No result here: #1 Claude Fable 5.2, #2 Gemini 4 Carbon, #5 Claude Opus 5.5.

Interactive version: theaggregate.ai/benchmark?slug=swe-infrabench · How It Works · Data refreshed daily, snapshot 2026-11-13.