DiCoBench - Spatial Commonality: leaderboard
Accuracy on the spatial-commonality task (locating the shared element on a 6 by 6 grid) 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 spatial-commonality task (locate the shared element on a 6 x 6 grid) of DiCoBench (765 multi-image samples at near-2K resolution): 5-option multiple choice (four candidate image pairs or instructions plus a no-visible-commonality option, chance 20%), answer letter matched exactly, VLMEvalKit settings at temperature 0; higher is better. Source: arxiv.org. Saturation forecast: Around February 2027. 18 models tracked.
Top models
| # | Model | Score | Overall rank |
|---|---|---|---|
| 1 | Gemini 3 Pro | 58.4 | #137 |
| 2 | Qwen 3.5 35B A3B | 49.6 | #482 |
| 3 | O4 Mini | 48 | #353 |
| 4 | Gemini 3 Flash | 41.7 | #164 |
| 5 | Gemma 3 27B (IT) | 36.8 | #1289 |
| 6 | GPT-5 | 36 | #167 |
| 7 | Gemma 3 12B (IT) | 29.6 | #1837 |
| 8 | GPT-4.1 | 27.2 | #495 |
| 9 | GPT-4.1 Mini | 25.6 | #779 |
| 10 | Qwen 2.5 VL 7B Instruct | 23.2 | #1833 |
| 11 | Qwen 2.5 VL 32B Instruct | 21.6 | #1053 |
No result here: #1 Claude Fable 5.2, #2 Gemini 4 Carbon, #5 Claude Opus 5.5.
Interactive version: theaggregate.ai/benchmark?slug=dicobench-spatial-commonality · How It Works · Data refreshed daily, snapshot 2026-11-13.