DiCoBench - Attribute Difference: leaderboard

Accuracy on the attribute-difference task (a subtle change of colour, material or shape of one object) of DiCoBench (2026), a fine-grained multi-image perception benchmark of five-option multiple-choice questions on near-2K images, with a no-visible-cue option among the choices. Chance is 20 percent; higher is better.

Metric: Accuracy (%) on the attribute-difference task (a subtle change of colour, material or shape of one object) of DiCoBench (765 multi-image samples at near-2K resolution): 5-option multiple choice (four candidate image pairs or instructions plus a no-visible-difference option, chance 20%), answer letter matched exactly, VLMEvalKit settings at temperature 0; higher is better. Source: arxiv.org. Saturation forecast: Around September 2028. 18 models tracked.

Top models

#ModelScoreOverall rank
1Gemini 3 Pro49.4#137
2GPT-4.1 Mini42.4#779
3O4 Mini38.8#353
4GPT-535.3#167
5Qwen 2.5 VL 7B Instruct33#1833
6GPT-4o32.9#741
7GPT-4.128.3#495
8Qwen 3.5 35B A3B28.3#482
9Gemini 3 Flash25#164
10Gemma 3 12B (IT)22.4#1837
11Qwen 2.5 VL 32B Instruct22.4#1053
12Gemma 3 27B (IT)20#1289

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

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