How we cut π0.5 (a robot VLA) inference from 230 ms to 87 ms on a laptop GPU, and what each fix bought
π0.5 is a vision-language-action model for robot arms: a SigLIP vision encoder, a Gemma language backbone, and a small "action expert" that generates motor commands over 10 denoising steps. Starting from the stock LeRobot inference code, one step took over 230 ms on an RTX 5090 Mobile. Here's what…
Read the full story at r/learnmachinelearning ↗
Timeline · 1 report
- 2026-10-29 16:49 · r/learnmachinelearning
How we cut π0.5 (a robot VLA) inference from 230 ms to 87 ms on a laptop GPU, and what each fix bought