SIS-Bench - Action Prediction: leaderboard

SIS-Bench (2026) tests multimodal LLMs on UAV self-awareness and spatial cognition with four-option questions about drone videos. The action prediction task asks where the drone ends up after a given action sequence in a long flight; accuracy in percent, higher is better.

Metric: Accuracy (%; 263 action prediction 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 July 2028. 26 models tracked.

Top models

#ModelScoreOverall rank
1Qwen 3.5 Plus69.2#232
2GPT-5.465.8#123
3Kimi K2.565.4#256
4Qwen 3 VL 8B (Thinking)64.6#887
5Seed 1.863.1#242
6Gemini 3 Flash (Preview)61.6#144
7Qwen 2.5 VL 7B Instruct60.8#1833
8Qwen 3 VL 30B A3B Instruct59.7#871
9Qwen 2 VL 7B Instruct58.9#2553
10Qwen 3 VL 8B Instruct57#981
11Qwen 3 VL 4B Instruct57#1279
12InternVL3-14B55.5#1182
13GLM-4.1V-9B (Thinking)48.7#1060 (GLM-4.1V-9B)

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