SIS-Bench - Landmark Recall: leaderboard

SIS-Bench (2026) tests multimodal LLMs on UAV self-awareness and spatial cognition with four-option questions about drone videos. The landmark recall task asks which landmark was seen immediately before a given one in a stitched video; accuracy in percent, higher is better.

Metric: Accuracy (%; 443 landmark 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 February 2027. 26 models tracked.

Top models

#ModelScoreOverall rank
1Seed 1.884.4#242
2Gemini 3 Flash (Preview)84#144
3Qwen 3.5 Plus83.3#232
4Kimi K2.581.9#256
5InternVL3-14B79.7#1182
6GPT-5.478.6#123
7Qwen 3 VL 8B (Thinking)78.6#887
8Qwen 3 VL 30B A3B Instruct76.5#871
9Qwen 3 VL 8B Instruct74.9#981
10Qwen 3 VL 4B Instruct70.7#1279
11GLM-4.1V-9B (Thinking)64.1#1060 (GLM-4.1V-9B)
12Qwen 2 VL 7B Instruct58#2553
13Qwen 2.5 VL 7B Instruct54.2#1833

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