MM-JudgeBias - Response Dominance: leaderboard
Metric: Bias-Deviation (0 to 1) on MM-JudgeBias (about 200 image-query-response triplets per bias type, 1,804 in all, each judged on a 1-10 scale before and after a controlled perturbation; mean of three runs): mean drop of the judge's score, normalized by the largest possible drop, when both the query and the image are replaced with null inputs; higher is better. Source: arxiv.org. Saturation forecast: Estimated already saturated. 30 models tracked.
Top models
| # | Model | Score |
|---|---|---|
| 1 | Gemini 3 Pro (High) | 0.99 |
| 2 | Gemini 2.5 Pro | 0.98 |
| 3 | Claude Opus 4.5 (Thinking) | 0.92 |
| 4 | Qwen 3 VL 8B Instruct | 0.91 |
| 5 | Gemini 2.5 Flash Lite (Thinking) | 0.89 |
| 6 | Claude Opus 4.5 | 0.84 |
| 7 | Claude Sonnet 4.5 (Thinking) | 0.83 |
| 8 | Qwen 3 VL 30B A3B (Thinking) | 0.81 |
| 9 | Gemini 2.5 Flash | 0.74 |
| 10 | Claude Haiku 4.5 (Thinking) | 0.74 |
| 11 | Claude Sonnet 4.5 | 0.72 |
| 12 | Qwen 3 VL 30B A3B Instruct | 0.64 |
| 13 | Claude Haiku 4.5 | 0.6 |
| 14 | O3 (High) | 0.6 |
| 15 | Gemini 2.0 Flash Lite | 0.57 |
Interactive version: theaggregate.ai/benchmark?slug=mm-judgebias-response-dominance · How It Works · Data refreshed daily, snapshot 2026-10-07.