Robots need policies that can adapt to their sensors, environments, and tasks while running on onboard computing hardware. World models offer a foundation for learning physical interactions, but their size can make on-device deployment difficult. This changes with the new NVIDIA Cosmos 3 Edge.
Cosmos 3 Edge is a 4B omni-model (with a 2B NVIDIA Nemotron-based reasoner) in the Cosmos 3 family. It was pretrained on the same physical-world data as NVIDIA Cosmos 3 Nano and NVIDIA Cosmos 3 Super and starts with the same grounding in how objects move and interact. Plus, the model is small enough to run on-device on NVIDIA Jetson Thor.
What you’ll build
By the end of this tutorial, you’ll have a post-trained Cosmos 3 Edge manipulation policy that can run on Jetson Thor and be evaluated in closed-loop simulation.
You’ll learn how to:
