VLM-SubtleBench - Synthetic Domain: leaderboard
Metric: Accuracy (%) on the synthetic-domain two-image multiple-choice questions of VLM-SubtleBench's test split (pairs of highly similar images from natural, game, industrial, aerial, synthetic and medical sources); temperature 0.5; higher is better. Source: arxiv.org. Saturation forecast: Around January 2027. 12 models tracked.
Top models
| # | Model | Score | Overall rank |
|---|---|---|---|
| 1 | GPT-5 (Thinking) | 78.8 | #91 (GPT-5) |
| 2 | O3 | 72.5 | #121 |
| 3 | GPT-5 Chat | 63.6 | #233 |
| 4 | Claude Sonnet 4 | 56.3 | #194 |
| 5 | Qwen 2.5 VL 72B Instruct | 54.8 | #364 |
| 6 | Qwen 2.5 VL 32B Instruct | 53 | #443 |
| 7 | Gemini 2.5 Pro | 50.6 | #145 |
| 8 | GPT-4o | 45 | #333 |
| 9 | Qwen 2.5 VL 7B Instruct | 43.8 | #643 |
| 10 | Gemini 2.5 Flash | 43.3 | #237 |
No result here: #3 Claude Opus 5.5, #5 GPT-6 Astra, #8 Claude Fable 5.1.
Interactive version: theaggregate.ai/benchmark?slug=vlm-subtlebench-synthetic-domain · How It Works · Data refreshed daily, snapshot 2026-10-11.