DisasterBench (UAV) - Emergency Resource Allocation: leaderboard
DisasterBench (2026, UAV disaster response) is a multiple-choice reasoning benchmark over low-altitude drone images of 14 disaster-related scene types, covering tasks before, during and after a disaster. This board is exact-match accuracy (%) on the emergency resource allocation questions of the test split; higher is better.
Metric: Accuracy (%) on emergency resource allocation (ERA) questions on the 3,000-question test split of low-altitude UAV disaster images (14 disaster scene types), multiple choice scored by strict exact match on the final option letter; higher is better. Source: arxiv.org. Saturation forecast: Estimated already saturated. 21 models tracked.
Top models
| # | Model | Score | Overall rank |
|---|---|---|---|
| 1 | GPT-5 | 97.48 | #167 |
| 2 | Gemini 2.5 Pro | 93.28 | #266 |
| 3 | Claude Sonnet 4.5 | 93.28 | #250 |
| 4 | Qwen 2.5 VL 7B Instruct | 92.44 | #1833 |
| 5 | InternVL2-8B | 92.44 | #2988 |
| 6 | Gemini 2.5 Flash | 91.6 | #453 |
| 7 | Grok 4 | 89.92 | #307 |
| 8 | Gemini 2.0 Flash | 88.24 | #704 |
| 9 | GPT-4o | 83.19 | #741 |
| 10 | GPT-4o Mini | 83.19 | #1623 |
No result here: #1 Claude Fable 5.2, #2 Gemini 4 Carbon, #5 Claude Opus 5.5.
Interactive version: theaggregate.ai/benchmark?slug=disasterbench-uav-emergency-resource-allocation · How It Works · Data refreshed daily, snapshot 2026-11-13.