DisasterBench (UAV) - Trigger Mechanism Identification: 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 trigger mechanism identification questions of the test split; higher is better.
Metric: Accuracy (%) on trigger mechanism identification (TMI) 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: Around February 2027. 21 models tracked.
Top models
| # | Model | Score | Overall rank |
|---|---|---|---|
| 1 | Gemini 2.5 Pro | 84.06 | #266 |
| 2 | GPT-5 | 84.06 | #167 |
| 3 | Gemini 2.5 Flash | 83.33 | #453 |
| 4 | Claude Sonnet 4.5 | 80.07 | #250 |
| 5 | GPT-4o | 76.81 | #741 |
| 6 | Gemini 2.0 Flash | 76.45 | #704 |
| 7 | Grok 4 | 76.09 | #307 |
| 8 | Qwen 2.5 VL 7B Instruct | 67.03 | #1833 |
| 9 | GPT-4o Mini | 64.86 | #1623 |
| 10 | InternVL2-8B | 63.77 | #2988 |
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-trigger-mechanism-identification · How It Works · Data refreshed daily, snapshot 2026-11-13.