AI BriefingNVIDIA Alpamayo 2 Edge Optimized to 45 ms Latency on Jetson AGX Thor
·2026.11.13 19:05
Key point
Optimization reduces planning time from 0.6–0.8 s to 45 ms, enabling 20 Hz camera processing on a single board.
Details
- NVIDIA Alpamayo 2 Edge is a vision-language-action model that processes inputs from 6 cameras and recent motion to plan paths and explain actions.
- The model is trained in a reinforcement learning loop and released in PyTorch format.
- Default performance on Jetson AGX Thor is approximately 0.6–0.8 s per plan, limiting updates to about once per second for a 20 Hz camera.
- Optimized implementation achieves 45 ms per plan, supporting 20 decisions per second on the same hardware to match camera rates.
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