Embodied-BenchClaw Aerial-Bench - Interval Selection: leaderboard

Aerial-Bench (2026) is a UAV and aerial-view spatial understanding benchmark built automatically by the Embodied-BenchClaw multi-agent system, covering object recognition, counting, image-plane relations, area and scale comparison and depth-based reasoning. This board is the score in percent on interval selection questions on counts and depth or scale ranges; higher is better.

Metric: Accuracy (%) on interval selection questions (counts, quantities and depth or scale ranges); questions over aerial and UAV images from the 5,000-question benchmark built by the Embodied-BenchClaw pipeline (object and category recognition, counting with interval choices, image-plane spatial relations, visible-area and scale comparison, depth-based near-far reasoning), vision-language setting; higher is better. Source: arxiv.org. Saturation forecast: Not forecast. 14 models tracked.

Top models

#ModelScoreOverall rank
1Qwen 3.6 27B44#341
2Qwen 3.6 35B A3B43#462
3GPT-5.542#49
4Kimi K2.535#256
5Gemini 3 Pro (Preview)33#113
6Grok 4.20 0309 (Reasoning)33#230 (Grok 4.20 0309)
7GPT-5.232#176
8Claude Sonnet 4.631#161
9Claude Opus 4.730#79
10GPT-4.124#495
11Claude Haiku 4.5 (20251001)24#536

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

Interactive version: theaggregate.ai/benchmark?slug=embodied-benchclaw-aerial-bench-interval-selection · How It Works · Data refreshed daily, snapshot 2026-11-13.