DiffSpot: leaderboard

Fine-grained visual difference benchmark on web-page screenshots (DiffSpot, Zhang et al., WeChat AI, Tencent, 2026): each pair differs by one CSS property change on one element, drawn from 13 operators in three magnitude tiers, or not at all, and the model must describe what changed. A gpt-oss-120b judge credits an answer that names the recorded change, or that reports no change on the 500 unchanged controls; the score is accuracy in percent over all 4,400 pairs, zero-shot with one prompt for all models; higher is better.

Metric: Accuracy (%; (TP+TN)/4,400 over 3,900 changed pairs and 500 unchanged controls, gpt-oss-120b judge). Source: arxiv.org. Saturation forecast: Around February 2027. 13 models tracked.

Top models

#ModelScoreOverall rank
1Gemini 3.1 Pro (Preview)47.2#91
2Kimi K2.542.2#252
3Gemini 3 Flash40.9#159
4Claude Opus 4.738.9#75
5GPT-5.438.3#121
6Qwen 3.5 397B A17B37.6#242
7Qwen 3 VL 235B A22B (Thinking)28.3#451
8GLM-4.6V21.2#698
9Qwen 3 VL 30B A3B Instruct17.6#870
10Qwen 3 VL 30B A3B (Thinking)17.5#710
11Qwen 3 VL 235B A22B Instruct15.9#521

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

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