WAN2.2 S2V QuantStack - GGUF 14B Sound-to-Video

Breakthrough efficiency for Sound-to-Video. This revolutionary workflow runs the massive 14B parameter WAN2.2 S2V model on consumer hardware by leveraging fully quantized GGUF models for the UNET and CLIP. Experience true audio-driven animation with drastically reduced VRAM requirements, making high-end S2V generation accessible to everyone. CPU/GPU hybrid execution enabled.

Workflow Description

This workflow is a technical marvel, designed to democratize access to the powerful WAN2.2 Sound-to-Video 14B model. By utilizing the ComfyUI-GGUF plugin, it loads both the UNET and CLIP models in highly compressed, quantized GGUF formats. This translates to:

• Massive VRAM Savings: The Q2_K quantized UNET allows the 14B model to run on GPUs with as little as 8-10GB of VRAM, or even on capable CPU systems.

• Hybrid Execution: Seamlessly offloads layers between GPU and CPU to maximize performance on any hardware setup.

• Full Fidelity Functionality: Despite the compression, you retain the complete S2V feature set: audio-driven motion, high-quality output, and professional video encoding.

This is the ultimate solution for users who thought the 14B S2V model was out of reach. Now you can run it.

Features & Technical Details

🧩 The Quantized Stack (The Magic Sauce):

• UNET (GGUF): Wan2.2-S2V-14B-Q2_K.gguf - The core video generation model, quantized to 2-bit for extreme efficiency.

• CLIP (GGUF): umt5-xxl-encoder-q4_k_m.gguf - The text encoder, quantized to 4-bit for optimal performance.

• VAE: Wan2.1_VAE.safetensors - Loaded normally for maximum visual fidelity.

• Audio Encoder: wav2vec2_large_english.safetensors - Encodes the input audio for the model.

🎬 Core Functionality:

• True Sound-to-Video: The generated animation is directly influenced by the characteristics of your input audio.

• Auto-Duration: Automatically calculates the correct number of video frames (length) based on your audio file's duration.

• Smart Image Preprocessing: Automatically scales your input image to an optimal size (0.2 megapixels) while preserving its original aspect ratio for animation.

• Professional Output: Uses VHS_VideoCombine to render a final MP4 video with perfect audio sync.

⚙️ Optimized Pipeline:

• Clean, grouped node layout for easy understanding and operation.

• Efficient routing with reroute nodes to keep the workflow organized.

How to Use / Steps to Run

Prerequisites (CRITICAL):

1. ComfyUI-GGUF Plugin: You MUST install the ComfyUI-GGUF plugin from its GitHub repository. This is non-negotiable.

2. GGUF Model Files: Download the required quantized models:

   • Wan2.2-S2V-14B-Q2_K.gguf (Place in Qwen 2SV\ folder)

   • umt5-xxl-encoder-q4_k_m.gguf

3. Standard Models: Ensure you have Wan2.1_VAE.safetensors and wav2vec2_large_english.safetensors.

Instructions:

1. Load Your Image: In the LoadImage node, select your starting image.

2. Load Your Audio: In the LoadAudio node, select your .wav or .mp3 file.

3. Craft Your Prompt: Describe your scene in the Positive Prompt node. The negative prompt is pre-configured.

4. Queue Prompt. The workflow will encode your audio, process it through the quantized 14B model, and generate the video.

⏯️ Output: Your finished video will be saved in your ComfyUI output/video/ folder as an MP4 file.