AI RESEARCH
Characterizing Vision-Language-Action Models across XPUs: Constraints and Acceleration for On-Robot Deployment
arXiv CS.AI
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ArXi:2604.24447v1 Announce Type: cross Vision-Language-Action (VLA) models are promising for generalist robot control, but on-robot deployment is bottlenecked by real-time inference under tight cost and energy budgets. Most prior evaluations rely on desktop-grade GPUs, obscuring the trade-offs and opportunities offered by heterogeneous edge accelerators (GPUs/XPUs/NPUs). We present a systematic analysis for low-cost VLA deployment via model-hardware co-characterization.