# Orbis 2

A hierarchical driving world model: a low-frame-rate predictor supplies long-range context and a high-rate predictor fills in detail, generating long future video from past frames. An optional steering trajectory lets you ask what happens if the car turns. Released under MIT.

Organization: University of Freiburg. Released: July 2026. Kind: Driving.

## What you control

- An input driving video to take context from
- An optional trajectory file that steers the car

## License

Weights: Available (https://huggingface.co/sud0301/orbis2). Declared license: MIT.
The weights' model card declares MIT, a permissive license that allows commercial use. Check what the model was built on, because a base model's terms can still apply.

## Real-time

No real-time claim.

## How to run it

1. Clone lmb-freiburg/orbis2 and create the conda environment from environment.yml.
2. Download the tokenizer and the L1 and L2 checkpoints with hf download sud0301/orbis2.
3. Run evaluate/rollout_demo_v2.py on an input video; add a trajectory file to steer the rollout.

## Where to try

No hosted destination verified.

## Sources

- [Project source](https://github.com/lmb-freiburg/orbis2)
- [Weights and model card](https://huggingface.co/sud0301/orbis2)
- [Paper](https://arxiv.org/abs/2607.15898)

## Questions

### Is Orbis 2 open source?

Orbis 2 publishes downloadable weights under MIT. The declared license is permissive.

### Can I use Orbis 2 commercially?

The weights' model card declares MIT, a permissive license that allows commercial use. Check what the model was built on, because a base model's terms can still apply.

### Does Orbis 2 run in real time?

The cited sources do not claim real-time operation.

### Where can I try Orbis 2?

No hosted version was verified; run the published weights yourself.

### What does Orbis 2 take as input?

You give it an input driving video to take context from and an optional trajectory file that steers the car.

### How do I run Orbis 2?

Following the official instructions: Clone lmb-freiburg/orbis2 and create the conda environment from environment.yml. Download the tokenizer and the L1 and L2 checkpoints with hf download sud0301/orbis2. Run evaluate/rollout_demo_v2.py on an input video; add a trajectory file to steer the rollout.

### What are alternatives to Orbis 2?

Similar models in this directory include comma.ai world model 4B (open weights, permissive license), Oasis 3 (no public weights, service terms) and Orbis (open weights, permissive license).

Checked 2026-11-03. Corrections: https://github.com/windflow-labs/world-model-directory