👑 Wan2.1-VACE-14B (LoRA Accelerated): 10x Speed with CausVid LoRA for 3-Step Video Creation

🎬 Skyrocket Your Video Creation: Achieve ~10x Speed with Wan2.1 & the CausVid LoRA! 🎬

the pro Workflow > https://civarchive.com/models/1620800

II. ℹ️ Important Note / Alert ℹ️ Note: The CausVid LoRA (Wan21_CausVid_14B_T2V_lora_rank32.safetensors) is key to this workflow! It enables a significant speedup, reducing generation time for 81 frames at 720p from approximately 40 minutes to just around 4 minutes on an RTX 4090 (or even faster with quantized models like Q3KL GGUF). This guide focuses on leveraging this LoRA for fast video generation.

III. 📌 Overview / Introduction The Wan2.1-VACE-14B video diffusion model, when supercharged by the CausVid LoRA, is designed for high-quality, highly efficient video generation. It particularly excels at 480p and 720p resolutions through a streamlined 3-step ComfyUI workflow. This guide will walk you through the setup process to unlock this accelerated video generation capability, including options for full precision and quantized models like the fast Q3KL GGUF.

IV. 🔑 Key Components / Dependencies

1. Diffusion Model (14B):

   • Full Precision: wan2.1_vace_14B_fp16.safetensors (Recommended for compatibility with LoRA examples)

   • Quantized (Civitai): wan2.1_vace_14B_Q4KM.safetensors

   • Quantized (GGUF - Civitai): wan2.1_vace_14B_Q3kl.gguf (Used in the 5-min example, requires GGUF loader)

2. Performance LoRA (Essential for Speed):

   • Wan21_CausVid_14B_T2V_lora_rank32.safetensors (original)

3. VAE:

   • wan_2.1_vae.safetensors

4. Text Encoder: Choose one:

   • umt5_xxl_fp16.safetensors (Recommended to match Kijai's wrapper compatibility for the LoRA workflow)

   • umt5_xxl_fp8_e4m3fn_scaled.safetensors (Smaller, fp8 version)

V. 📁 File Organization / Installation Place the downloaded files in the following structure within your ComfyUI directory:

ComfyUI/
├── models/
│   ├── diffusion_models/
│   │   └── wan2.1_vace_14B_fp16.safetensors  # Or Q4KM.safetensors, or Q3kl.gguf
│   ├── text_encoders/
│   │   └── umt5_xxl_fp16.safetensors         # Or the fp8 version
│   ├── loras/
│   │   └── Wan21_CausVid_14B_T2V_lora_rank32.safetensors
│   └── vae/
│       └── wan_2.1_vae.safetensors

VI. 🎨 Model Showcase: Rapid 720p Cinematic Shots This setup, featuring Wan2.1-VACE-14B and the CausVid LoRA, excels at producing 720p (and 480p) video clips with remarkable speed—even faster with quantized GGUF models. It's ideal for quick iterations, creative experimentation, and efficient content creation, all streamlined by a 3-step workflow.

VII. 🛠️ Step-by-Step Tutorial / Workflow The core of this accelerated workflow relies on integrating the CausVid LoRA.

• Context for the LoRA and its benefits can be found in Kijai's Reddit Post announcing the LoRA. The workflow is designed to generate videos in approximately 3 main steps within ComfyUI after initial model and LoRA loading. 💡 A ComfyUI workflow JSON demonstrating this 3-step process (especially one for the Q3KL GGUF version if available) would be invaluable. If you have one, consider linking it here: [LINK_TO_YOUR_COMFYUI_WORKFLOW.json]

VIII. 💡 Usage Tips / Best Practices / Performance

• Model & LoRA Configuration: For maximum speed and quality, ensure you are using the appropriate 14B model (e.g., wan2.1_vace_14B_fp16.safetensors or wan2.1_vace_14B_Q3kl.gguf) paired with the Wan21_CausVid_14B_T2V_lora_rank32.safetensors LoRA.

• Text Encoder: The umt5_xxl_fp16.safetensors text encoder is recommended for best compatibility with existing examples and Kijai's original demonstrations. The fp8 version can save VRAM.

• Resolution: This setup is optimized for 480p and 720p video generation.

• Performance Gains:

  • Without LoRA (fp16): An 81-frame 720p video might take ~40 minutes on an RTX 4090.

  • With CausVid LoRA (fp16): The same video can be generated in ~4 minutes on an RTX 4090.

  • With CausVid LoRA & Q3KL GGUF: Potentially even faster, around 5 minutes or less for similar output on capable hardware with a GGUF loader.

🌟 Credits & Acknowledgements

Original Wan 2.1 models repackaged for ComfyUI by Comfy-Org: Wan 2.1 ComfyUI Repackaged on Hugging Face. The performance-boosting CausVid LoRA (Wan21_CausVid_14B_T2V_lora_rank32.safetensors) was extracted and shared by Kijai. Original announcement and details: Kijai's Reddit Post. Quantized GGUF and Safetensors versions available on Civitai, enabling broader accessibility and speed. Gratitude to the developers of the underlying CausVid technique

My Other ComfyUI Guides(in workflow):

• 📽️ ComfyUI VFI: Video Duration Extension Guide

• Guide for 🧠 ComfyUI-OllamaGemini Custom Node Setup

• 🎞️ ComfyUI LayerStyle for Video: Full Guide

👨‍💻 Developer Information

This guide was created by Abdallah Al-Swaiti:

1. Hugging Face

2. GitHub

3. LinkedIn

4. ComfyUI-OllamaGemini

For additional tools and updates, check out my other repositories.

✨ Create Dreamy Videos with WAN 2.1 VACE and Pastel Dream! ✨