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Tutorial SeriesComfyUI Advanced Tutorialvideowan2.2Wan2.2 S2V

Tencent Open Sources Hunyuan Image 3.0 - World's Largest Open-Source Text-to-Image Model

09/27/2025

Wan2.2-S2V Audio-Driven Video Generation ComfyUI workflow and tutorial

Wan2.2-S2V represents a significant advancement in AI video generation technology, capable of creating dynamic video content from static images and audio inputs. This innovative model excels at producing synchronized videos with natural lip-sync, making it particularly valuable for content creators working on dialogue scenes, musical performances, and character-driven narratives.

Model Highlights

  • Audio-Driven Video Generation: Transforms static images and audio into synchronized videos with natural lip-sync and expressions
  • Cinematic-Grade Quality: Generates film-quality videos with authentic facial expressions, body movements, and camera language
  • Minute-Level Generation: Supports long-form video creation up to minute-level duration in a single generation
  • Multi-Format Support: Works with real people, cartoons, animals, digital humans, and supports portrait, half-body, and full-body formats
  • Enhanced Motion Control: Generates actions and environments from text instructions with AdaIN and CrossAttention control mechanisms
  • High Performance Metrics: Achieves FID 15.66, CSIM 0.677, and SSIM 0.734 for superior video quality and identity consistency

Wan2.2 S2V ComfyUI Native Workflow

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1. Download Workflow File

Download the following workflow file and drag it into ComfyUI to load the workflow.

Download the following image and audio as input: input

2. Model Links

You can find the models in our repo

diffusion_models

audio_encoders

vae

text_encoders

ComfyUI/
├───📂 models/
│   ├───📂 diffusion_models/
│   │   ├─── wan2.2_s2v_14B_fp8_scaled.safetensors
│   │   └─── wan2.2_s2v_14B_bf16.safetensors
│   ├───📂 text_encoders/
│   │   └─── umt5_xxl_fp8_e4m3fn_scaled.safetensors 
│   ├───📂 audio_encoders/ # Create one if you can't find this folder
│   │   └─── wav2vec2_large_english_fp16.safetensors 
│   └───📂 vae/
│       └── wan_2.1_vae.safetensors

3. Workflow Instructions

Workflow Instructions

3.1 Lightning LoRA（Optional, for acceleration）

Lightning LoRA reduces generation time from 20 steps to 4 steps but may affect quality. Use for quick previews, disable for final output.

3.1.1 Audio Preprocessing Tips

Voice Separation for Better Results: Since ComfyUI core doesn’t include voice separation nodes, we recommend using external tools to separate vocals from background music before processing. This is especially important for dialogue and lip-sync generation, as clean vocal tracks produce significantly better results than mixed audio with background music or noise.

3.2 About fp8_scaled and bf16 Models

You can find both models here:

The template uses wan2.2_s2v_14B_fp8_scaled.safetensors for lower VRAM usage. Try wan2.2_s2v_14B_bf16.safetensors for better quality.

3.3 Step-by-Step Operation Instructions

Step 1: Load Models

  1. Load Diffusion Model: Load wan2.2_s2v_14B_fp8_scaled.safetensors or wan2.2_s2v_14B_bf16.safetensors
    • The workflow uses wan2.2_s2v_14B_fp8_scaled.safetensors for lower VRAM requirements
    • Use wan2.2_s2v_14B_bf16.safetensors for better quality output
  2. Load CLIP: Load umt5_xxl_fp8_e4m3fn_scaled.safetensors
  3. Load VAE: Load wan_2.1_vae.safetensors
  4. AudioEncoderLoader: Load wav2vec2_large_english_fp16.safetensors
  5. LoraLoaderModelOnly: Load wan2.2_t2v_lightx2v_4steps_lora_v1.1_high_noise.safetensors (Lightning LoRA)
    • This LoRA reduces generation time but may affect quality
    • Disable if output quality is insufficient
  6. LoadAudio: Upload the provided audio file or your own audio
  7. Load Image: Upload reference image
  8. Batch sizes: Set according to the number of Video S2V Extend subgraph nodes
    • Each Video S2V Extend subgraph adds 77 frames to the output
    • Example: 2 Video S2V Extend subgraphs = batch size 3
    • Chunk Length: Keep default value of 77
  9. Sampler Settings: Choose based on Lightning LoRA usage
    • With 4-step Lightning LoRA: steps: 4, cfg: 1.0
    • Without Lightning LoRA: steps: 20, cfg: 6.0
  10. Size Settings: Set the output video dimensions
  11. Video S2V Extend: Video extension subgraph nodes
    • Each extension generates 77 / 16 = 4.8125 seconds of video
    • Calculate nodes needed: audio length (seconds) × 16 ÷ 77
    • Example: 14s audio = 224 frames ÷ 77 = 3 extension nodes
  12. Use Ctrl-Enter or click the Run button to execute the workflow

Related Links