Unlock the full potential of Wan2.2 for creating stunning, high-motion videos from a single image! This efficient and powerful ComfyUI workflow is designed for simplicity and exceptional results. It combines the best available LoRAs and models into a seamless, multi-stage process:
Base Generation: Uses the massive Wan2.2-Fun-A14B-InP model with the fantastic Lightx2v 4-step LoRAs for fast, high-quality motion generation.
Quality & Style Enhancement: Applies Wan2.2 Reward LoRAs to refine details and artistic style.
Latent Upscaling & Refinement: Boosts resolution and cleans up the video using the efficient Wan2.2-Fun-5B-InP model, supercharged by the FastWan LoRA to require only 8 steps.
Final Enhancement: Upscales the final video with RealESRGAN_x2plus and interpolates frames with RIFE for a buttery-smooth 32FPS output.
This is a true "set it and forget it" pipeline for achieving professional-looking animated results.
✨ Features & Highlights
Enhanced Motion: Leverages specialized LoRAs (Lightx2v) designed explicitly for strong, coherent image-to-video motion.
Two-Pass Quality: Uses both High-Noise and Low-Noise Reward LoRAs for maximum detail and aesthetic quality.
Efficient HD Upscaling: The 5B upscaler model with the FastWan LoRA delivers high-quality results in just 8 steps, saving you time and VRAM.
Cinematic Output: Final output is smoothly interpolated to 32FPS and upscaled for a professional finish.
Organized Workflow: Cleanly grouped nodes make the workflow easy to navigate, understand, and modify.
GPU Memory Management: Includes
cleanGpuUsednodes to help manage memory during the complex generation process.
📦 Required Models (Please Download First!)
For this workflow to function, you must download and place the following models in your respective ComfyUI models folders.
1. Core Wan2.2 GGUF Models:
Wan2.2-Fun-A14B-InP_HighNoise-Q8_0.ggufWan2.2-Fun-A14B-InP_LowNoise-Q8_0.ggufWan2.2-Fun-5B-InP-Q8_0.gguf
2. Motion & Quality LoRAs (for A14B):
lightx2v_I2V_14B_480p_cfg_step_distill_rank128_bf16.safetensors(The key to great motion!)Wan2.2-Fun-A14B-InP-high-noise-HPS2.1.safetensorsWan2.2-Fun-A14B-InP-low-noise-HPS2.1.safetensors
3. Upscaler LoRA (for 5B):
Wan2_2_5B_FastWanFullAttn_lora_rank_128_bf16.safetensors(Drastically reduces required steps!)
4. VAE & Upscaler:
Wan2_1_VAE_fp32.safetensors(orWan2.2_VAE.safetensorsfor the upscaler sub-graph)RealESRGAN_x2plus.pth(Standard upscaling model)Source: https://huggingface.co/dtarnow/UPscaler/tree/main (or any standard model repository)
clip_vision_h.safetensors(For the IP-Adapter-like functionality in the inpaint node)
5. CLIP Encoder:
umt5-xxl-encoder-Q8_0.gguf(Typically bundled with the Wan GGUF downloads)
⚙️ Installation & Usage
Download the Workflow: Download the provided
.jsonfile from this Civitai page.Download All Models: Ensure you have all the models listed above downloaded to the correct folders.
Load in ComfyUI: Open ComfyUI, drag the
.jsonfile into the window, and the workflow will load.Check Loaders: The workflow uses ComfyUI-GGUF and ComfyUI-VideoHelperSuite (VHS). Please ensure you have these custom nodes installed.
Input Your Image:
Drag your starting image to the "Load START Image" node.
(Optional) You can add an ending image to the "Load END Image" node to guide the animation.
Modify Prompts: Change the positive and negative prompts in the CLIP Text Encode nodes to suit your image.
Queue Prompt! You're ready to go. The workflow will handle the rest, from generation to upscaling and interpolation.
Pro Tip: The default megapixel setting for the upscaler is conservative (0.9). You can increase this value in the "Upscaler" group for higher resolutions, but be mindful of your VRAM!
Conclusion
This workflow represents a curated "best-of" approach to using the Wan2.2 model family. It simplifies a complex multi-step process into a single, powerful pipeline that delivers consistently impressive motion and quality.
Enjoy creating! If you have any questions, feel free to ask in the comments. Don't forget to like and share your amazing results!
Description
Enhanced output quality and increased stability have been achieved.
you'll need this two Loras:
https://huggingface.co/lightx2v/Wan2.1-I2V-14B-480P-StepDistill-CfgDistill-Lightx2v/tree/main/loras
and
https://huggingface.co/Kijai/WanVideo_comfy/tree/main/Wan22-Lightning.
Now using beta57 scheduler.
Additional features have been implemented, providing convenient access.
FAQ
Comments (9)
Can you give an idea of what kind of vram is needed for this workflow?
Start at 0.2 megapixels and increase untill you reach the sweet spot
Thanks for sharing this workflow. It worked so much more smoothly than any workflow I’ve created so far.
Thank for sharing your great work.
I keep getting this error: !!! Exception during processing !!! The size of tensor a (16) must match the size of tensor b (48) at non-singleton dimension 1
I've double and triple checked all the models, settings, loras, everything. Any idea what is causing that?
Wrong clip maybe 🤔
@zardozai That wasn't it. Turns out it has been saving all the versions up to the final one. I changed the frame rate in the final Video Combine to 16 and now there are no errors but I don't understand why that would cause a conflict. I think I may just do away with RIFE in the workflow anyway and only interpolate the videos I'm happy with. RIFE takes longer than the rest of the workflow combined. I'm getting the upscaled gen, 81 frames at 1168x1760 in 90 seconds! That's incredible. I'm also able to do runs with 221 frames in about 5 minutes. (using a 5090). I think I can probably go longer because I'm still not hitting the VRAM limit. And I'm doing the first run at .5 megapixels instead of .31. The overall quality of these videos is a little less than other WAN 2.2 and 2.1 workflows but the speed is amazing.
@haldabarn449 Use kijai/ComfyUI-GIMM-VFI
Its a litle bit quicker but the results are better than any other VFI like Rife etc
Can I create consistent characters with this?