MaxxBench: leaderboard

MaxxBench tests whether a coding agent follows a changed requirement instead of reproducing a solution it may have seen. It takes 89 feature-implementation tasks from DeepSWE and alters their instructions or starting code, with reference solutions and tests revised to match. Each model configuration attempts every task twice with mini-swe-agent in a sandboxed container at a stated reasoning effort, and a separate container grades the patch: an attempt passes only if every required feature and regression test passes. Unlike DeepSWE, its parent, the original task's known answer no longer satisfies the tests, so a model that scores lower here than there is leaning on the familiar task. This board is the share of the 178 attempts (89 tasks, two each) that pass.

Metric: Attempts passed on 89 changed DeepSWE tasks, two attempts each (%). Source: maxxbench.unlap.ai. Saturation forecast: Around March 2027. 16 models tracked.

Top models

#ModelScoreOverall rank
1Claude Opus 5.5 (Max)76.4#5 (Claude Opus 5.5)
2GPT-6 Astra (xHigh)71.91#6 (GPT-6 Astra)
3GPT-5.6 Sol (Max)69.1#29 (GPT-5.6 Sol)
4Claude Sonnet 5.5 (Max)66.85#18 (Claude Sonnet 5.5)
5Claude Opus 5 (Max)63.48#20 (Claude Opus 5)
6Claude Fable 5 (xHigh)63.48#26 (Claude Fable 5)
7GLM-5.3 (Max)56.74#62 (GLM-5.3)
8DeepSeek V4.1 Flash (Max)55.62#58 (DeepSeek V4.1 Flash)
9GLM-5.3 Flash (Max)55.06#119 (GLM-5.3 Flash)
10Gemini 3.8 Flash (High)53.37#36 (Gemini 3.8 Flash)
11Muse Spark 1.3 (xHigh)53.37#42 (Muse Spark 1.3)
12GPT-6 Luna (Max)51.69#93 (GPT-6 Luna)
13GPT-5.6 Luna (Max)46.07#117 (GPT-5.6 Luna)
14Muse Spark 1.2 (xHigh)38.76#97 (Muse Spark 1.2)
15DeepSeek V4 Flash (Max)28.09#254 (DeepSeek V4 Flash)

No result here: #1 Claude Fable 5.2, #2 Gemini 4 Carbon, #10 GPT-6.1 Sol.

Interactive version: theaggregate.ai/benchmark?slug=maxxbench · How It Works · Data refreshed daily, snapshot 2026-11-12.