Post-Train NVIDIA Cosmos 3 Edge for On-Device Robot Control | NVIDIA Technical Blog

This post details the post-training of NVIDIA Cosmos 3 Edge, a 4B omni-model, for on-device robot control on NVIDIA Jetson Thor. It describes the process of adapting a pre-trained world model to fit within device memory and achieve control latency requirements for real-time operation. The post outlines the training data (Cosmos3-DROID dataset), configuration, and deployment steps, including serving the policy via a WebSocket server on Jetson Thor. It demonstrates that the model can run entirely on the robot, generating actions in approximately 1.53 seconds per chunk at 640x540 resolution and 15 Hz, enabling continuous robot motion. The post also provides a smoke test for the policy server and discusses bringing custom robot data.