NVIDIA’s Cosmos-Framework Tutorial: Designing a Colab-Friendly Miniature of Cosmos 3 World Models with Omnimodal Mixture-of-Transformers

This tutorial demonstrates how to use NVIDIA's cosmos-framework to build a smaller, trainable version of Cosmos 3 world models that can run on standard Colab hardware, which lacks the resources needed for full Cosmos 3 inference. The tutorial first checks the actual hardware requirements for real Cosmos 3 checkpoints, then uses the framework's real structure and input schema as a foundation to create a compact omnimodal Mixture-of-Transformers model that learns relationships across text, vision, and action data streams. The miniature implementation mirrors the core Cosmos concept of shared cross-modal attention with modality-specific expert routing, using synthetic data and autoregressive rollout to show how the model predicts future states. This approach allows developers to understand and experiment with the framework's architecture within the practical constraints of limited hardware.