CPU3DAI tools for 3D, video and audio

AnimateDiff: video generator — what it does and what you need to run it

AnimateDiff is an open source tool for generating short animated clips from text descriptions. Its goal is to add controllable motion to static images produced by popular models like Stable Diffusion, without requiring fine-tuning of the base model itself.

What it does

  • Turns a text description into an animated video using a motion module.
  • Works on top of community-trained personalized models (for example, those posted on CivitAI), preserving their style and objects.
  • As stated by the developers, it can create high-resolution videos — up to 1024x1024 pixels at 16 frames — with different aspect ratios.
  • Can generate clips both with and without personalized models.

What you need to run it

  • Platform: runs locally on the user's machine; the code is written in Python.
  • VRAM: as described by the authors, inference typically requires about 13 GB of VRAM. Exact usage depends on the chosen personalized model and settings (for example, the number of sampling steps).
  • License: the code is distributed under the Apache-2.0 license.
  • Repository: github.com/guoyww/AnimateDiff (last code update — July 31, 2024).
  • Additional requirements: a base image generation model (for example, Stable Diffusion) is required, which the user downloads separately.

Who it's for

The tool is aimed at practitioners who are already familiar with the Stable Diffusion ecosystem and are comfortable working with the command line and Python scripts. It will be useful for those who want to bring their custom models or characters to life without lengthy training of new neural networks. A clear repository and a site with examples make it easier to get started.

It is not suitable for beginners looking for a ready-made one-click GUI application. It's also worth noting that comfortable use requires a graphics card with at least 13 GB of memory — a requirement that rules out most consumer laptops and older desktop GPUs. The authors do not provide a cloud version, so running the service locally is not possible without your own hardware.

AnimateDiff solves a specific problem — adding controllable animation to the world of Stable Diffusion. It does not try to replace full-featured video editors or complex 3D animation systems, but rather serves as a bridge between static generation and short looping clips that you can create on your own computer.

AnimateDiff pipeline Text-to-video generator Text prompt Scene description and motion Base SD model Stable Diffusion 1.5 or higher Motion module Motion Module temporal consistency Personalization (optional) LoRA, DreamBooth or other adapters with/without Animated video High resolution, 1024×1024, 16 frames Various aspect ratios MP4 GIF WebP PNG frames Required VRAM: ~13 GB VRAM · Language: Python · License: Apache-2.0
How the AnimateDiff pipeline works. The diagram is drawn from the tool’s fact sheet.

Fact sheet

Code licenseApache-2.0 source
VRAM13 GB per the author’s description source
LanguagePython source
Last code change2024-07-31 source
Repository created2023-06-17 source
Changes often — as of 2026-08-19
GitHub stars12208 source
Forks1091 source

Values are collected automatically from official sources and were checked on 2026-08-19. Each one links to its source, and values taken from the developer’s pages also carry a verbatim quote — hover over the note. Pricing and versions are shown as of the check date and change most often; verify on the vendor’s site before buying.

See also