Insights from the sentdex episode “Testing VLMs and LLMs for robotics w/ the Jetson Thor devkit”, published August 30, 2025.
The Jetson Thor devkit offers an impressive 128GB of memory at 130 watts, making it a breakthrough for edge robotics. While its memory bandwidth limits traditional high-speed compute tasks, creative techniques like pipeline parallelism allow developers to maximize its potential for local LLM and VLM inference, outperforming standard setups in power-constrained environments.
Topics: NVIDIA Jetson Thor, Edge AI, Robotics, Local LLM, Memory Bandwidth
