SpatialTrust - Indirect Factor Identification: leaderboard

SpatialTrust (University of Washington, 2026) tests whether multimodal LLMs recognize, localize and explain environmental information-leakage risks in laptop-camera authentication scenes, with evidence grounding at an IoU threshold of 0.5. Score for grounded identification of indirect factors that create a disclosure risk, in percent, higher is better.

Metric: Grounded identification score (%; indirect factors that create a disclosure risk; over SpatialTrust's 577 secure-authentication images (five questions each); IoU threshold 0.5 for grounded evidence). Source: arxiv.org. Saturation forecast: Around 2031. 8 models tracked.

Top models

#ModelScoreOverall rank
1Qwen 3 VL 30B A3B Instruct28.65#870
2Qwen 3 VL 8B Instruct17.85#982
3Gemini 2.5 Flash12.36#452
4GLM-4.1V-9B (Thinking)8.64#1061 (GLM-4.1V-9B)
5GPT-5.45.83#121
6Qwen 2 VL 7B Instruct3.9#2569

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

Interactive version: theaggregate.ai/benchmark?slug=spatialtrust-indirect-factor-identification · How It Works · Data refreshed daily, snapshot 2026-11-12.