Benchmarks
326 sources · 1,256 models × 2,956 benchmarks · 154,484 scoresMaxxBench (unLAP) changes the instructions or starting code of 89 DeepSWE v1.1 tasks while keeping the engineering problem, with reference solutions and tests revised to match, to test whether a coding agent's DeepSWE score holds when the requirements shift. Each model runs twice on every task in mini-swe-agent under Pier, with no network but its model API, up to three hours per attempt. The score is the share of the 178 attempts in which every required feature and regression test passes.
122nd strongest of 779 fitted benchmarks
Signal-to-noise +12.27
280th hardest of 779 fitted benchmarks
Capability needed ≲ 158.2
| # | Model | Setting | Score | Source |
|---|---|---|---|---|
| 1 | Claude Opus 5.5 | max · Mini-SWE-Agent | 76.4 | |
| 2 | GPT-6 Astra | x-high · Mini-SWE-Agent | 71.9 | |
| 3 | GPT-5.6 Sol | max · Mini-SWE-Agent | 69.1 | |
| 4 | Claude Sonnet 5.5 | max · Mini-SWE-Agent | 66.9 | |
| 5 | Claude Fable 5 | x-high · Mini-SWE-Agent | 63.5 | |
| 6 | Claude Opus 5 | max · Mini-SWE-Agent | 63.5 | |
| 7 | GLM-5.3 | max · Mini-SWE-Agent | 56.7 | |
| 8 | GLM-5.3 Flash | max · Mini-SWE-Agent | 55.1 | |
| 9 | Gemini 3.8 Flash | high · Mini-SWE-Agent | 53.4 | |
| 10 | GPT-6 Luna | max · Mini-SWE-Agent | 51.7 | |
| 11 | GPT-5.6 Luna | max · Mini-SWE-Agent | 46.1 | |
| 12 | Qwen3.8-Flash-Next | x-high · Mini-SWE-Agent | 46.1 |