SIS-Bench - Action Sequence: leaderboard

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

Metric: Accuracy (%; 315 action sequence 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 February 2027. 26 models tracked.

Top models

#ModelScoreOverall rank
1Seed 1.885.1#242
2Gemini 3 Flash (Preview)84.1#144
3Qwen 3.5 Plus82.5#232
4GPT-5.477.8#123
5Kimi K2.577.8#256
6Qwen 3 VL 8B (Thinking)62.9#887
7Qwen 3 VL 4B Instruct61.3#1279
8Qwen 3 VL 8B Instruct60.3#981
9GLM-4.1V-9B (Thinking)55.9#1060 (GLM-4.1V-9B)
10Qwen 2.5 VL 7B Instruct55.6#1833
11Qwen 2 VL 7B Instruct51.4#2553
12Qwen 3 VL 30B A3B Instruct44.8#871
13InternVL3-14B43.8#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-sequence · How It Works · Data refreshed daily, snapshot 2026-11-13.