Open Dreamer is an open-source, real-time JAX/Flax implementation of the Dreamer 4 world model pipeline, providing training code for a causal video tokenizer and action-conditioned latent dynamics model on Minecraft/VPT-style gameplay.

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Last updated

2026-07-26

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Why it is worth attention

This repository offers a complete, production-ready training pipeline for a state-of-the-art world model (Dreamer 4) with an impressive live browser demo that lets you play a generated Minecraft world in real time, making advanced world modeling accessible to practitioners.

Who it is for

  • Researchers in world models and model-based reinforcement learning
  • Deep learning engineers using JAX/Flax for video generation
  • Game AI enthusiasts interested in Minecraft simulation
  • Developers building interactive neural environments

Use cases

  • Training a world model on Minecraft video datasets to predict future frames conditioned on actions
  • Generating interactive, real-time rollouts of game environments for agent training or visualization
  • Evaluating video prediction quality using Fréchet Video Distance (FVD)
  • Reproducing and extending Dreamer 4 research results in an open framework

Strengths

  • Provides a complete training workflow from raw Minecraft MP4 data to tokenizer and dynamics model, with detailed configuration via Hydra
  • Includes a live, in-browser demo powered by Reactor, demonstrating real-time world model inference without setup
  • Leverages JAX for high performance and GPU acceleration, with clear documentation of dependencies and workflow
  • Offers modular code with separate scripts for tokenizer training, dataset tokenization, dynamics training, and evaluation (FVD)

Considerations

  • Requires Minecraft/VPT-style ArrayRecord data in a specific format, limiting immediate applicability to other domains
  • The roadmap indicates full Dreamer 4 Behaviour-Cloning / RL agent training is not yet implemented
  • Current license is 'All rights reserved' with a temporary notice, which may hinder open-source adoption until a formal open-source license is added

README quick start

An open, real-time implementation of the Dreamer 4 world-model pipeline in JAX/Flax.

🌐 Website & Blog Post  ·  🎮 Live Demo  ·  ⚡ Inference Code

Authors

Diego Marti Monso*  ·  Francesco Sacco*  ·  Edward Hu

  • Equal contribution

REAL-TIME DEMO POWERED BY


Open Dreamer is a simple, performant, and easy-to-use JAX/Flax NNX implementation of the Dreamer 4 world model — trained on Minecraft/VPT-style gameplay and playable in real time. This repository holds the training pipeline: a causal video tokenizer, an action-conditioned latent dynamics model, and the tools to generate rollouts and measure quality.

This repo currently supports:

  • Training a causal video tokenizer
  • Tokenizing Minecraft/VPT-style MP4 datasets
  • Training an action-conditioned latent dynamics model
  • Generating rollouts and computing FVD

🎮 Try it now

The fastest way to experience Open Dreamer is the live, in-browser demo — step into a generated Minecraft world and play it in real time, with a Game ⟷ Dream toggle that hands the stream from the real game to the world model frame by frame. No setup required; the real-time model runs in the cloud on Reactor.

👉 Open the demo

The website also walks through how the model works, with interactive figures and result galleries.

⚡ Run it yourself

To roll out the trained model locally on your own video and actions — generating new frames from an MP4 and a matching action sequence — use the inference repository:

👉 reactor-team/open-dreamer

The rest of this README covers training the model from scratch.

📋 Roadmap

  • Full Dreamer 4 Behaviour-Cloning / RL agent training loop

⚙️ Requirements

Install

pip install uv
uv sync
source .venv/bin/activate

The dependency lock targets CUDA 12 JAX. If your machine needs a different JAX build, in

Description

Open-source Dreamer world-model implementation in JAX

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