MMR-AD - MPDD Localization: leaderboard
Metric: Anomaly localization accuracy (%) on MPDD test images (from MMR-AD): a predicted anomaly box counts as correct at IoU of at least 0.1 with an annotated anomalous region, zero-shot, the model sees a spatially aligned normal reference image and the test image with the MMR-AD instruction template; dataset-level average over the subdataset's product classes; higher is better. Source: arxiv.org. Saturation forecast: Around August 2027. 13 models tracked.
Top models
| # | Model | Score |
|---|---|---|
| 1 | O4 Mini | 23.9 |
| 2 | GPT-5 | 21.2 |
| 3 | Gemini 2.5 Pro | 16.3 |
| 4 | GPT-4o | 13.6 |
| 5 | Llama 4 Maverick | 10 |
| 6 | Qwen 2.5 VL 7B | 7.2 |
| 7 | InternVL3-38B | 5.4 |
| 8 | InternVL3-8B | 3.9 |
| 9 | Gemma 3 27B | 3.5 |
Interactive version: theaggregate.ai/benchmark?slug=mmr-ad-mpdd-localization · How It Works · Data refreshed daily, snapshot 2026-10-07.