Animate It vs AnimateDiff
Animate It
animateit.studioAnimateDiff
github.comSide by side
| Figure | Animate It | AnimateDiff |
|---|---|---|
| Price from | — | Free |
| Free plan | — | Yes |
| Free trial | — | — |
| Open source | — | — |
| Web | Yes | Yes |
| Linux | — | Yes |
| Self-hosted | — | Yes |
| Plans published | 3 | 1 |
| Spec score · AI Animation Makers | 7.8 (#13) | 8.1 (#8) |
| Intended audience | The homepage presents the service for making memoirs, comedies, bedtime stories, fashion stories, adventures, histories, lessons, and fantasy animations. | The project page presents AnimateDiff as a framework for animating personalized text-to-image models without model-specific tuning. |
| Security | The privacy policy says stored data uses Supabase with row-level security and encryption in transit and at rest. | The repository page does not state security certifications or compliance claims. |
Plans
Animate It
- 15-Second Trailer$23, paid once
- 2-Minute Trailer$111, paid once
- 22-Minute Episode$751, paid once
In their own words
Animate It
Animate It has no write-up on Specifiction yet; its figures are above.
AnimateDiff
AnimateDiff is a free, open-source module that turns many community text-to-image models into animation generators without additional training. Its main branch targets Stable Diffusion 1.5, with a separate branch for Stable Diffusion XL. MotionLoRA adapts motion modules for patterns such as zooming and rolling, while SparseCtrl uses sparse RGB images or sketches to guide animation content. The project runs locally: install dependencies with pip and run its animation scripts, which save generated samples in a samples folder. A local Gradio demo runs at localhost:7860 by default. The project points to official Diffusers support and community integrations for Stable Diffusion WebUI and ComfyUI; scripts handle checkpoint downloads automatically. For SDXL beta inference, the project notes a typical need of about 13 GB of VRAM, depending on the model and settings. It lists small flicker and limited general text-to-video quality as limitations, and suggests using images from the same community model for closer style alignment. The repository lists an Apache-2.0 license and says the project is released for academic use.