Embodied-BenchClaw Aerial-Bench - Multi Choice: leaderboard
Metric: Score (%) on multi-choice selection questions that require choosing every correct visible target; 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: Around 2030. 14 models tracked.
Top models
| # | Model | Score |
|---|---|---|
| 1 | GPT-4.1 | 63 |
| 2 | Kimi K2.5 | 56.5 |
| 3 | Claude Opus 4.7 | 56 |
| 4 | Claude Sonnet 4.6 | 55 |
| 5 | Qwen 3.6 27B | 55 |
| 6 | Grok 4.20 0309 (Reasoning) | 54.5 |
| 7 | GPT-5.5 | 54 |
| 8 | Gemini 3 Pro (Preview) | 54 |
| 9 | GPT-5.2 | 53 |
| 10 | Qwen 3.6 35B A3B | 53 |
| 11 | Claude Haiku 4.5 (20251001) | 43.5 |
Interactive version: theaggregate.ai/benchmark?slug=embodied-benchclaw-aerial-bench-multi-choice · How It Works · Data refreshed daily, snapshot 2026-09-29.