SIS-Bench: leaderboard

SIS-Bench (2026) tests multimodal LLMs on UAV self-awareness and spatial cognition with four-option questions about drone videos. The score is overall accuracy over 4,856 questions in 13 perception, memory and reasoning tasks, in percent; higher is better.

Metric: Overall accuracy (%; 4,856 questions over 13 tasks on UAV spatial cognition and self-awareness at perception, memory and reasoning levels, question-weighted; four-option multiple choice on UAV videos (at most 32 frames), zero-shot, open models through vLLM with at most 128 generated tokens and proprietary models through their APIs; higher is better). Source: arxiv.org. Saturation forecast: Around February 2027. 26 models tracked.

Top models

#ModelScoreOverall rank
1Gemini 3 Flash (Preview)71.6#144
2Kimi K2.571#256
3Seed 1.870.6#242
4Qwen 3.5 Plus70.1#232
5GPT-5.470#123
6Qwen 3 VL 8B (Thinking)64.7#887
7Qwen 3 VL 8B Instruct64.6#981
8Qwen 3 VL 4B Instruct62.5#1279
9Qwen 3 VL 30B A3B Instruct61#871
10GLM-4.1V-9B (Thinking)60.4#1060 (GLM-4.1V-9B)
11InternVL3-14B59.1#1182
12Qwen 2.5 VL 7B Instruct55.8#1833
13Qwen 2 VL 7B Instruct53.2#2553

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

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