SIS-Bench - Action Recall: leaderboard

SIS-Bench (2026) tests multimodal LLMs on UAV self-awareness and spatial cognition with four-option questions about drone videos. The action recall task asks which action the drone executes in a given clip of a stitched video; accuracy in percent, higher is better.

Metric: Accuracy (%; 804 action recall questions; 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 May 2027. 26 models tracked.

Top models

#ModelScoreOverall rank
1Seed 1.859.2#242
2Kimi K2.553#256
3GPT-5.449.9#123
4Gemini 3 Flash (Preview)42.4#144
5Qwen 3.5 Plus42.4#232
6GLM-4.1V-9B (Thinking)34.8#1060 (GLM-4.1V-9B)
7Qwen 3 VL 8B (Thinking)33.6#887
8Qwen 2 VL 7B Instruct33.3#2553
9Qwen 3 VL 8B Instruct32.2#981
10Qwen 2.5 VL 7B Instruct29.2#1833
11Qwen 3 VL 4B Instruct29.1#1279
12Qwen 3 VL 30B A3B Instruct28.4#871
13InternVL3-14B24.9#1182

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-action-recall · How It Works · Data refreshed daily, snapshot 2026-11-13.