This is the ultimate AI video tool. Wan Animate tutorial
Wan Animate provides AI filmmakers with a powerful, free, and open-source alternative for character motion transfer and video replacement, significantly lowering the barrier for advanced character control.
What this lesson covers
This tutorial demonstrates Alibaba's Wan Animate, an open-source tool for transferring character movements and replacing characters in existing videos. It provides a complete local installation guide using Wan2GP to run the model efficiently on personal hardware.
Key takeaways from the creator
AI-extracted notes, not independently verified product claims. Timestamp links let you check each point in the original video.
- 0:30 ↗
Alibaba's Wan Animate allows users to upload a character photo and a reference video to accurately transfer overall body movement, facial expressions, and hand gestures.
- 2:23 ↗
Wan Animate can also perform character swaps in existing videos while seamlessly matching lighting and white balance.
- 5:45 ↗
The Wan2GP repository by deep beep meep offers a simplified local interface for running Wan variants, supporting setups with as low as 6 GB of VRAM.
- 7:16 ↗
Setting up Wan2GP locally requires installing Git and cloning the repository via the command prompt.
Workflow outlined in the video
- Install Git and Miniconda on your local machine if they are not already configured.
- Clone the Wan2GP repository from GitHub onto your local desktop using the command prompt.
- Follow the repository installation instructions to set up the environment and run Wan Animate offline for character swapping and motion transfer.
Before you use this workflow
These notes describe the source video at its publication date. Model access, pricing, connectors and interfaces may have changed. Check the original source and the provider’s current documentation before installing an add-on, connecting an account or spending credits.
ReelStack has not independently tested this workflow. Preview one representative shot and check motion, continuity and output quality before applying it to a full production. No result, cost saving or model capability is guaranteed.
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Put the lesson in context
When to use Blender previsualization for AI video →How to interpret the numbers
267,144 views captured 23 October 2026. ReelStack recommendation score: 59/100. Formula: radar-v5. This is ReelStack’s calculation, not a YouTube rating or a measure of factual accuracy.
Show the calculation
- 45% performance: 2.58× views vs 7 other channel videos observed at a similar age. View-evidence factor 100% (views / (views + 1,000))
- 25% freshness: 0/100 with a 14-day half-life
- 20% momentum: 129 views/day vs 6 channel baseline (7 comparable uploads), with the same view-evidence factor
- 10% engagement: 80/100; likes + 4× comments, smoothed with a 500-view neutral prior