SWE Atlas
Evaluating coding agents on codebase comprehension, test writing and refactoring
Update September 22, 2026
SWE Atlas v1.1 is live. It combines the three category leaderboards into a single, easy-to-run index covering the same 284 tasks as v1.0. Every model was re-run with a new judge (GPT-6.1 Sol, majority of 3 votes), refined grading criteria and restricted network access, so v1.1 scores aren’t directly comparable to v1.0.
Overview
SWE Atlas evaluates coding agents on professional software engineering work beyond issue resolution, across three complementary categories. Tasks come from 15 production repositories in 6 languages (Go, Python, TypeScript, C, C++ and JavaScript), and the agent works in each repository inside a Docker container with standard shell tools, so it can build, run and test the code. Every task is single-turn: the prompt states the goal and leaves the approach to the agent. For the full methodology, see the paper: SWE Atlas: Benchmarking Coding Agents Beyond Issue Resolution.
Score vs. cost
Results by Category
Acknowledgements
Thanks to Artificial Analysis and Inductive ML for their contributions to the v1.1 release. Artificial Analysis’s SWE-Atlas-QnA-AA dataset provided wording for several updated Codebase QnA rubric criteria, and Inductive ML’s reward-hacking feedback further hardened the task environments.
Performance Comparison
Opus 5.5
77.40±5.00
Fable 5.1
74.10±5.30
Gemini 4 Argon
70.10±5.50
GPT-6 Astra
69.40±5.60
Sonnet 5.5
67.50±5.70
GPT-6.1 Sol
65.90±5.70
Muse Wonder 1.0
64.80±5.80
Grok 4.7
62.10±5.80
DeepSeek V4.1 Flash
62.10±5.80
Inkling 2 Small
NEW61.90±5.80
Kimi K3
61.00±5.90
Haiku 5.5
59.40±5.90
GPT-6.1 Terra
57.70±5.90
Gemini 3.8 Flash
57.30±5.80
GPT-6 Luna
50.80±6.00
Muse Spark Open
42.30±5.90