Stable-Worldmodel: A High Performance Platform for Reproducible World Model Research

Stable-Worldmodel is an open-source research platform that standardizes world model development with unified abstractions for data collection, training, and evaluation. Built on LanceDB’s multimodal lakehouse, the platform achieves approximately 4,815 samples per second with Lance compared to 1,416 with HDF5, enabling efficient GPU utilization during training. The system includes reference implementations of modern baselines like LeWorldModel and supports training directly from cloud storage without local synchronization.