Open-source motion module that turns Stable Diffusion checkpoints into video models
AnimateDiff is an open research project that adds motion to existing text-to-image diffusion models. Instead of training a video model from scratch, it inserts a motion module into a Stable Diffusion checkpoint, so the large library of community image models and LoRAs can be animated with the same prompts and styles people already use. Most people run it locally through ComfyUI, often pairing it with ControlNet for camera paths and pose guidance. Its differentiator is freedom: no credits, no external filter beyond what your own setup imposes, and full control over the sampling pipeline. The price is a technical install and real hardware.
Last updated: 2026-09-20. This site only provides an index; for exact features, pricing, and licensing, see the official website.
local generation, style experiments, custom pipelines and motion research
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Practically yes. The model runs on consumer cards, but video sampling is far heavier than still image work, so a modest laptop GPU will feel slow or run out of memory. Cloud notebooks are a common workaround.
That is the point of the project. AnimateDiff attaches to existing checkpoints, so community models, LoRAs and fine-tunes keep their look once animated, which is far cheaper than training a video model yourself.
The project itself is code on GitHub. Several third-party sites and front ends host it for a fee or per-generation credits, and those are separate products with their own terms rather than official releases.
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