Researchers released an open-source frontier-level world model trained on the Dreamer4 paper using the CoinRun game, featuring a block-causal transformer architecture with a tokenizer and dynamics model. The project demonstrates scaling laws where compute-optimal parameters and data points scale with the square root of compute, and combines world prediction with policy learning through diffusion-based latent state generation.