Alpha magic: instant transparent background videos for VFX and design.
Who it's for: creators who want this pipeline in ComfyUI without assembling nodes from scratch. Not for: one-click results with zero tuning — you still choose inputs, prompts, and settings.
Open preloaded workflow on RunComfy
Open preloaded workflow on RunComfy (browser)
Why RunComfy first
- Fewer missing-node surprises — run the graph in a managed environment before you mirror it locally.
- Quick GPU tryout — useful if your local VRAM or install time is the bottleneck.
- Matches the published JSON — the zip follows the same runnable workflow you can open on RunComfy.
When downloading for local ComfyUI makes sense — you want full control over models on disk, batch scripting, or offline runs.
How to use (local ComfyUI)
1. Load inputs (images/video/audio) in the marked loader nodes.
2. Set prompts, resolution, and seeds; start with a short test run.
3. Export from the Save / Write nodes shown in the graph.
Expectations — First run may pull large weights; cloud runs may require a free RunComfy account.
Overview
This workflow helps you generate high-quality video clips with built-in transparency, eliminating the need for manual masking or green screen removal. You can easily place characters, objects, or animated elements over any background of your choice. Its output is highly flexible, making it perfect for VFX, motion graphics, and compositing work. You will save time and streamline your creative process by working with ready-to-use transparent video assets. Designed for professionals, it ensures seamless integration into existing design pipelines. Built on the Wan 2.1 model, it delivers fidelity and precision with each render.
Important nodes:
Key nodes in Comfyui Wan Alpha workflow
EmptyHunyuanLatentVideo (#40)
- Role: defines spatial and temporal resolution of the generated clip. Tune width, height, frames, and fps to match delivery. Larger canvases and longer durations raise VRAM needs; consider shorter drafts for look development, then scale up for finals.
KSampler (#3)
- Role: the main denoiser for Wan Alpha. Adjust seed for explorations, steps to trade speed for detail, sampler and scheduler for stability, and cfg to balance prompt adherence with natural motion. With LightX2V LoRA active, you can reduce steps significantly while preserving quality thanks to step-distillation. See LightX2V for context on fast sampling. ModelTC/LightX2V
LoraLoaderModelOnly (#59)
- Role: loads the LightX2V LoRA that accelerates Wan2.1 sampling. Use the strength control to blend its effect if you see oversharpening or tempo artifacts. Keep this LoRA closest to the base model in the chain so downstream LoRAs inherit its speed benefits.
LoraLoaderModelOnly (#65)
- Role: loads an additional LoRA for style or domain refinement. Moderate strength to avoid overpowering motion coherence; combine with your prompt rather than replacing it. If artifacts appear, lower this LoRA before changing the sampler.
VAELoader (#39) RGB
- Role: provides the RGB VAE used by RGB VAE Decode (#8). Keep this paired with the Wan‑Alpha alpha VAE to ensure both decoders interpret latents coherently. Swapping to unrelated VAEs can misalign edges or soften transparency. Background on the joint RGB–alpha design is in the Wan‑Alpha report. Wan‑Alpha (arXiv)
VAELoader (#51) Alpha
- Role: provides the alpha VAE used by Alpha VAE Decode (#52). It reconstructs the matte from the same latent space as RGB so transparency matches motion and detail. If you customize VAEs, test that RGB and alpha still align on subpixel edges like hair.
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Notes
Wan Alpha in ComfyUI | Alpha Channel Video Workflow — see RunComfy page for the latest node requirements.