Windflow

EdenLive

VAST · Released 12 October 2026

EdenLive is a generative renderer: you feed it a rough source video, such as game footage or a live camera, plus a scene prompt and a reference image, and it re-renders each chunk as a new world while keeping the source motion. Movement comes from the source video, not from direct keyboard commands.

See 2 places to try itGet the weightsCan I use it commercially?
Weights
Open weightsMixed component licenses
Commercial use
Custom terms
Real-time
Real-time, per authorsNot independently measured
Where to try
2 placesReactor, Windflow

01 Controls

What you control

  • A source video: game footage or a live camera
  • A scene prompt
  • A reference image for appearance

02 License

Can you use it commercially?

Custom terms

Only under its own license (Mixed component licenses). The video pipeline's weights are Apache-2.0, with an MIT CLIP encoder and a vision encoder under Meta's DINOv3 License. The optional first-frame workbench uses FLUX.2 [klein] under a non-commercial license.

Declared license: Mixed component licenses · Model card

A reading of the published license text, not legal advice.

03 Speed

Does it run in real time?

Real-time, per authors. 24 fps or higher at 480p or 720p, minute-scale generation.

Figures are the authors' own, with their settings and hardware. They are not comparable across models.

04 Setup

How to run it

  1. 01Clone VAST-AI-Research/EdenLive, create a Python 3.10 conda environment, and install PyTorch and the pinned packages from the README.
  2. 02Download VAST-AI/EdenLive from Hugging Face.
  3. 03For offline clips, run python -m edenlive.scripts.infer.
  4. 04For the live service, start the TURN relay (bash turn_server.sh), then the model service (bash start.sh 14b, or 5b).

Summarised from the project's own instructions. Follow the source for exact commands and versions.

05 Access

Where to try it

Listed alphabetically. Windflow maintains this directory and is one of the hosts; a listing does not promise capacity at any given moment.

06 Questions

EdenLive FAQ

Is EdenLive open source?

EdenLive publishes downloadable weights under Mixed component licenses. Read the license terms before you build on it.

Can I use EdenLive commercially?

Only under its own license (Mixed component licenses). The video pipeline's weights are Apache-2.0, with an MIT CLIP encoder and a vision encoder under Meta's DINOv3 License. The optional first-frame workbench uses FLUX.2 [klein] under a non-commercial license.

Does EdenLive run in real time?

Yes, according to its authors. 24 fps or higher at 480p or 720p, minute-scale generation. This directory has not measured it independently.

Where can I try EdenLive?

You can try it on Reactor and Windflow.

What does EdenLive take as input?

You give it a source video: game footage or a live camera, a scene prompt and a reference image for appearance.

How do I run EdenLive?

Following the official instructions: Clone VAST-AI-Research/EdenLive, create a Python 3.10 conda environment, and install PyTorch and the pinned packages from the README. Download VAST-AI/EdenLive from Hugging Face. For offline clips, run python -m edenlive.scripts.infer. For the live service, start the TURN relay (bash turn_server.sh), then the model service (bash start.sh 14b, or 5b).

What are alternatives to EdenLive?

Similar models in this directory include Helios (open weights, permissive license), Krea Realtime 14B (open weights, permissive license) and LongLive 2.0 (open weights, custom terms).

Similar world models

All 56 in the directory