NVIDIA's VLA driving model hits 20 decisions/s on Jetson Thor after Embedl optimization
No-Dragonfly6246 · reddit · 2026-11-13
NVIDIA's Alpamayo 2 Edge is a vision-language-action driving model: it takes 6 cameras plus recent motion, verbalizes what it's about to do and why, then plans a path — trained in an RL loop. The stock PyTorch release needs 0.6–0.8s per plan on a Jetson AGX Thor, so a 20Hz camera gets a new plan only about once per second. Embedl optimized it to 45ms per plan — 20 decisions/s on the same board — letting reasoning keep up with the camera. Numbers, methodology, and a live run on a real Thor are available in-browser.
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