DisasterBench (UAV) - Collapsed Building Analysis: 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 collapsed building analysis questions of the test split; higher is better.

Metric: Accuracy (%) on collapsed building analysis (CBA) 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

#ModelScoreOverall rank
1GPT-574.56#167
2Claude Sonnet 4.571.01#250
3Gemini 2.5 Pro70.41#266
4Gemini 2.5 Flash69.82#453
5Gemini 2.0 Flash65.68#704
6Grok 462.72#307
7GPT-4o Mini55.03#1623
8GPT-4o53.85#741
9InternVL2-8B42.6#2988
10Qwen 2.5 VL 7B Instruct40.83#1833

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-collapsed-building-analysis · How It Works · Data refreshed daily, snapshot 2026-11-13.