explaingit

genmoai/mochi

Analysis updated 2026-05-18

3,647PythonAudience · researcherComplexity · 5/5LicenseSetup · hard

TLDR

An open-source AI model that turns a text description into a short video clip.

Mindmap

mindmap
  root((Mochi 1))
    What it does
      Text to video
      Open source
      480p output
    Tech stack
      PyTorch
      Diffusion Transformer
      Gradio
    Use cases
      Generate video clips
      LoRA fine tuning
      Python API calls
    Audience
      Researchers
      ML engineers

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What do people build with it?

USE CASE 1

Generate a short video from a text prompt using local hardware

USE CASE 2

Fine-tune the model on your own videos with LoRA to match a specific visual style

USE CASE 3

Run the model through a browser-based Gradio interface instead of the command line

USE CASE 4

Call the model directly from your own Python code via its API

What is it built with?

PythonPyTorchDiffusion TransformerGradioHugging Face

How does it compare?

genmoai/mochicharlesq34/pointnet2skorokithakis/catt
Stars3,6473,6473,647
LanguagePythonPythonPython
Setup difficultyhardhardeasy
Complexity5/55/52/5
Audienceresearcherresearcherdeveloper

Figures from each repo's GitHub metadata at analysis time.

How do you get it running?

Difficulty · hard Time to first run · 1day+

Needs a GPU with roughly 60GB VRAM, such as an H100, to run locally.

Free to use for personal and commercial projects under the Apache 2.0 license.

In plain English

Mochi 1 is an open-source video generation model created by Genmo. You give it a text description and it produces a short video clip. It is positioned as one of the most capable freely available video generation models, closing the distance between what open-source projects can do and what proprietary commercial systems offer. The model is very large, with 10 billion parameters, and is built on an architecture Genmo calls AsymmDiT (Asymmetric Diffusion Transformer). The basic idea is that a diffusion model starts from noise and gradually refines it into a final output. This model handles text descriptions and video frames together in one process, spending more of its processing capacity on the visual side of the problem. It compresses video into a much smaller internal representation first (using a separate component called AsymmVAE) and then works on that compressed form before expanding it back out into actual video frames. Videos are currently generated at 480p resolution. Running it requires substantial hardware. On a single graphics card you need roughly 60 GB of video memory, which puts it out of reach for most consumer GPUs. The recommended setup is at least one H100, a high-end data center GPU. The README notes that the ComfyUI integration (a popular visual interface for AI image and video tools) can bring that requirement down to under 20 GB, though that path is separate from this repository. To use it locally, you download the model weights separately (they are available on Hugging Face or via a direct link), then run either a browser-based graphical interface built with Gradio or a simpler command-line script. A Python API is also included if you want to call the model from your own code. The project added support for LoRA fine-tuning in late 2024, which means you can adapt the model to a specific visual style by training it further on your own video examples, though that step still requires a high-end GPU such as an H100 or A100. The model is released under the Apache 2.0 license, which is permissive for both personal and commercial use. Genmo notes that the model reflects biases present in its training data and recommends additional safety review before any commercial deployment.

Copy-paste prompts

Prompt 1
Explain what hardware I need to run Mochi 1 locally to generate videos from text.
Prompt 2
Show me how to set up the Gradio interface for Mochi 1 to generate a video from a prompt.
Prompt 3
Write Python code that calls Mochi 1's API to generate a video clip from a text description.
Prompt 4
How would I fine-tune Mochi 1 with LoRA on my own video clips?

Frequently asked questions

What is mochi?

An open-source AI model that turns a text description into a short video clip.

What language is mochi written in?

Mainly Python. The stack also includes Python, PyTorch, Diffusion Transformer.

What license does mochi use?

Free to use for personal and commercial projects under the Apache 2.0 license.

How hard is mochi to set up?

Setup difficulty is rated hard, with roughly 1day+ to a first successful run.

Who is mochi for?

Mainly researcher.

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