Meta's HumanCLAW Benchmark: Best VLM Scores Only 16.8% on Embodied Tasks
liuziwei7 · x · 2026-07-30
Meta and its collaborators have introduced HumanCLAW, a new benchmark designed to evaluate whether Vision-Language Models (VLMs) can effectively act through a physical body.
The benchmark explicitly decouples action decisions from motor control. Across 1,218 embodied episodes, no VLM was able to solve the tasks completely, with the best-performing model reaching only a 16.8% success rate.
The research highlights that current models lack embodied self-awareness, often losing track of the physical body they are supposed to control.
Related event: Meta's HumanCLAW Benchmark Shows Top VLMs Lack Body Awareness(3 posts)→
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