UAVQA-Bench - Existence Detection: leaderboard

UAVQA-Bench (Fudan University, 2026) asks multimodal models 1,500 human-annotated questions about drone images drawn from 13 public UAV datasets, mostly multiple choice with some bounding-box grounding. This dimension covers scene, conditional and multi-target presence questions. Score is accuracy in percent; higher is better.

Metric: Accuracy (%; scene, conditional and multi-target presence questions; direct answering over UAVQA-Bench: 1,500 human-annotated questions on images from 13 public UAV datasets, 16 tasks in six capability dimensions, multiple choice plus box grounding counted correct at IoU 0.5). Source: arxiv.org. Saturation forecast: Around February 2027. 14 models tracked.

Top models

#ModelScoreOverall rank
1Gemini 3 Flash82.33#164
2Qwen 3 VL 32B Instruct80#585
3Gemini 3 Pro79.67#137
4Qwen 3 VL 8B (Thinking)79#887
5Qwen 3 VL 30B A3B (Thinking)78.33#712
6Qwen 3 VL 32B (Thinking)77.33#559
7Qwen 3 VL 30B A3B Instruct75#871
8Qwen 3 VL 8B Instruct72.33#981
9Qwen 3.5 9B65.67#803

No result here: #1 Claude Fable 5.2, #2 Gemini 4 Carbon, #5 Claude Opus 5.5.

Interactive version: theaggregate.ai/benchmark?slug=uavqa-bench-existence-detection · How It Works · Data refreshed daily, snapshot 2026-11-13.