Wan 2.2 Video: Multi-LoRA Character & Style Stack in ComfyUI
Blueprint for combining character and lighting LoRAs without overcooking with Wan 2.2 Video (8 GB–16 GB VRAM) using Loader → Load LoRA #1 (0.75) → Load LoRA #2 (0.50) → KSampler.
Updated Oct 17, 2026 · 1 min read
- Model Architecture
- Wan 2.2 Video
- Workflow Task
- Multi-LoRA Character & Style Stack
- VRAM Requirement
- 8 GB–16 GB
- Primary Loader
- Load Diffusion Model + CLIPLoader
- Model Directory
- models/diffusion_models/
Node graph blueprint: Wan 2.2 Video × Multi-LoRA Character & Style Stack
This route pairs **Wan 2.2 Video** with a **Multi-LoRA Character & Style Stack** setup designed for combining character and lighting LoRAs without overcooking. Place your model weights in `models/diffusion_models/` and start the graph with **Load Diffusion Model + CLIPLoader**.
Core wiring chain: `Loader → Load LoRA #1 (0.75) → Load LoRA #2 (0.50) → KSampler`. Connect your positive and negative conditioning from CLIP Text Encode into KSampler and decode to RGB pixels.
VRAM tuning and execution tips on Windows
- **Memory target (8 GB–16 GB):** If your GPU sits at 8 GB or 12 GB, use FP8 or GGUF Q4/Q5 weights and swap in VAE Decode (Tiled) to avoid end-of-pass memory spikes.
- **Workflow persistence:** Every image saved by this route embeds the full JSON graph inside the PNG metadata — drag the output back onto ComfyUI Studio anytime to resume.
- **Get the app:** Download the Windows desktop or portable build from /download.
FAQs
Which loader node do I use for Wan 2.2 Video in a Multi-LoRA Character & Style Stack?
Use `Load Diffusion Model + CLIPLoader` with weights stored in `models/diffusion_models/`, then wire the output into `Loader → Load LoRA #1 (0.75) → Load LoRA #2 (0.50) → KSampler`.
How much VRAM does Wan 2.2 Video need for Multi-LoRA Character & Style Stack?
Target VRAM is 8 GB–16 GB. On 8 GB cards, load quantized FP8 or GGUF weights and enable tiled VAE decoding.
Run on your hardware. Free forever.
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