LibreAI / Video / Video2X
// video · k4yt3x/video2x

Video2X

A machine learning-based video super resolution and frame interpolation framework. Est. Hack the Valley II, 2018

★ 21.9k stars⑂ 1.9k forksAGPL-3.0updated 2026-03
▦ visual — this project's README ships no embeddable screenshot,
so here's a placeholder. The guide below is complete regardless.
// project facts

Project facts

Video2X is an open-source video project by k4yt3x (k4yt3x/video2x on GitHub). It has 21,948 GitHub stars and 1,901 forks, is released under the AGPL-3.0 license, and was last updated on GitHub on 7 March 2026.

Repository
k4yt3x/video2x
GitHub stars
21,948
Forks
1,901
License
AGPL-3.0
Last updated on GitHub
7 March 2026
Category
Video
Listing
Full install guide
Official site
Official site
// how it works

How it works

  1. Pick your task

    Generation, restoration, upscaling, face swap, or lip sync — each project here specializes, so start from the job to be done.

  2. Get the weights

    Download the model files the project needs; most READMEs link exact versions and where to place them.

  3. Set up the environment

    Python environments or Docker images are the norm — follow the install section for your GPU.

  4. Run and iterate

    Feed in prompts or source media, tune the settings, and re-run until the result lands.

// features

Why people love it

Open weights

Real model files you download and run — no API key, no per-second billing.

Local inference

Everything happens on your machine; footage never uploads anywhere.

Specialized pipelines

Each tool focuses on one job and does it well, instead of a shallow all-in-one.

Active research roots

Many of these ship alongside papers and keep absorbing new techniques.

Community workflows

Shared settings, presets, and integrations (especially around ComfyUI) multiply what one tool can do.

Commercial-friendly options

Several use permissive licenses — always confirm the model license for your use case.

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// run it

Run it yourself

  1. Step 1 — Get the code

    Clone the repository or download the latest release for your OS.

    git clone https://github.com/k4yt3x/video2x.git
  2. Step 2 — Follow the install guide

    Every project documents its own setup — the README's install section is the source of truth.

  3. Step 3 — Launch

    Start the app or server as documented and open the interface it provides.

// use cases

What you can build

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// faq

Questions, answered

What GPU do I need?

It varies widely — upscalers run on modest cards, while full video diffusion wants serious VRAM. Check each project's docs.

Are the outputs commercially usable?

Often yes for the code, but model weights carry their own licenses — read both.

Who maintains Video2X?

It is an open-source project at k4yt3x/video2x with 1,901 forks. Check the repo's contributors and recent commits to see how active maintenance is.

How is quality vs commercial tools?

The gap keeps shrinking; for restoration and upscaling, open tools already match or beat paid ones.

Do these run on Mac?

Some do via MPS or CPU, but NVIDIA on Linux/Windows is the best-supported path.

Where do I get help?

GitHub issues and Discussions on each repo, plus Discord communities for the popular ones.

// keep exploring

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// alternatives

Alternatives in Video

The most-starred other Video projects in the LibreAI catalogue — the realistic shortlist if Video2X is not the right fit.

Get Video2X

Free and open — grab the source, star the repo, and start creating.