ComfyUI-FlashVSR

ComfyUI-FlashVSR ⚡

A powerful ComfyUI custom node based on the FlashVSR model, enabling real-time diffusion-based video super-resolution for streaming applications.

https://github.com/user-attachments/assets/1d1528c5-e3c1-487f-9c29-267ddb817809

Features

High-Quality Video Upscaling: Utilizes the advanced FlashVSR model to upscale videos to 2x or 4x resolution.

• Multiple Model Versions:
  • Full (Best Quality): Highest quality results with significant VRAM usage.
  • Tiny (Fast): Balanced quality and speed for faster processing.
  • Tiny Long (Low VRAM): Optimized for GPUs with limited VRAM, ideal for long videos.
• SageAttention Optimization (Optional): Automatic ~20-30% speedup when SageAttention is installed. Falls back gracefully if not available.
• Intelligent Tiling: Supports enable_tiling to process high-resolution videos efficiently on low-VRAM GPUs.
• Automatic Model Download: On the first run, the node will automatically download the required .safetensors models from Hugging Face (1038lab/FlashVSR).
• Audio Passthrough: Maintains the original audio during video frame processing, ensuring synchronization and quality preservation.

News & Updates

2025/11/15: FlashVSR 1.1 Model Update + Frame Duplication Fix ( update.md )

• Added new model: Wan2_1-T2V-1.1_3B_FlashVSR_fp32.safetensors
• Improved T2V → VSR quality, stability, details
• Applied frame duplication fix (Issue #3)
• Updated UPDATE.md accordingly

2025/10/24: Initial release of ComfyUI-FlashVSR.

• Added FlashVSR ⚡ and FlashVSR Advanced ⚡ nodes.
• Implemented automatic model download from Hugging Face (1038lab/FlashVSR).
• Supports .safetensors models, audio passthrough, and tiling for low VRAM.

Installation

Method 1: Install via ComfyUI Manager (Recommended)

1. Start ComfyUI.
2. Click the “Manager” button in the sidebar → “Install Custom Nodes”.
3. Search for ComfyUI-FlashVSR.
4. Click the “Install” button.
5. Restart ComfyUI.

Method 2: Clone the Repository

1. Navigate to your ComfyUI custom_nodes directory.
2. Run:

   git clone https://github.com/1038lab/ComfyUI-FlashVSR.git

3. Restart ComfyUI.

Method 3: Install via Comfy CLI

1. Ensure that comfy-cli is installed with:

   pip install comfy-cli
   

2. Install ComfyUI-FlashVSR using:

   comfy node install ComfyUI-FlashVSR
   

3. Restart ComfyUI.

Method 4: Manually Download the Models

• The models will be automatically downloaded to ComfyUI/models/FlashVSR/ on the first run.
• To manually download the models, visit 1038lab/FlashVSR on Hugging Face and download the .safetensors files into the ComfyUI/models/FlashVSR/ folder.

Model File	Purpose
Wan2_1-T2V-1.1_3B_FlashVSR_fp32.safetensors	New FlashVSR 1.1 Main Diffusion Model
Wan2_1-T2V-1_3B_FlashVSR_fp32.safetensors	Previous FlashVSR 1.0 Main Model
Wan2.1_VAE.safetensors	Video VAE
Wan2_1_FlashVSR_LQ_proj_model_bf16.safetensors	Low-Quality Projection
Wan2_1_FlashVSR_TCDecoder_fp32.safetensors	Tiny Model Decoder

📖 For optional performance optimization (~20-30% speedup), see SageAttention Installation Guide

Usage

This node processes image (frame) sequences. For a complete video workflow, combine it with other nodes in ComfyUI.

• Load: Use a video loader (e.g., VHS - Video Load) to load video frames and audio.
• Process: Connect the frames and audio to the FlashVSR node.
• Save: Use a video combiner (e.g., VHS - Video Combine) to combine the output frames and audio into a final upscaled video.

FlashVSR Nodes

Optional Settings 💡 Tips

Optional Setting	Description	Tips
preset (Simple)	Choose between: Fast (Tiny model), Balanced (Tiny model), High Quality (Full model).	High Quality requires significant VRAM. Consider using the Advanced node if you face OOM errors.
model_version (Advanced)	Options: Tiny (Fast), Tiny Long (Low VRAM), Full (Best Quality).	Full offers the best quality, while Tiny Long is optimized for minimal VRAM.
enable_tiling (Advanced)	Breaks the video into smaller chunks to save VRAM.	Enable this if you encounter OOM errors, especially with the Full model at 4x scale.
speed_optimization	Optimizes for processing speed. Higher values yield faster results.	Default is 2.0.
quality_boost	Boosts quality at the cost of VRAM usage. Higher values yield better results.	Default is 2.0. The Full model can handle 3.0 without crashing.
Input Frames	The video frames to process.	Requires at least 21 frames for initialization.
4x Upscaling	Optimized for 4x upscaling.	2x upscaling is supported, but 4x generally provides better results.
sageattention (Advanced)	Enable/Disable SageAttention optimization.	Enabled by default. Provides ~20-30% speedup if sageattention package is installed.

About FlashVSR Model

FlashVSR is a real-time diffusion-based video super-resolution model. It is designed to provide high-quality upscaling, particularly suited for streaming applications. The .safetensors versions are included for enhanced compatibility and security.

Requirements

• ComfyUI

• Python 3.10+

• Required packages:

  • torch >= 2.0.0
  • torchvision >= 0.15.0
  • safetensors >= 0.4.0
  • huggingface_hub >= 0.19.0
  • einops >= 0.6.0
  • numpy >= 1.24.0
  • tqdm >= 4.65.0
  • pillow >= 9.5.0

• Optional packages (for performance boost):

  • sageattention >= 1.0.0 - Provides ~20-30% speedup (see Optional Performance Optimization)
  • triton >= 2.1.0 - Required by SageAttention

These packages are typically included in ComfyUI environments. If you encounter an import error, run:

pip install torch>=2.0.0 torchvision>=0.15.0 safetensors>=0.4.0 huggingface-hub>=0.19.0 einops>=0.6.0

Optional Performance Optimization

For an automatic ~20-30% performance boost, you can install SageAttention:

pip install sageattention triton

Note:

• SageAttention requires a CUDA-capable GPU and may conflict with some ComfyUI environments.
• For detailed installation instructions and troubleshooting, see SageAttention Installation Guide.
• If you encounter issues after installing SageAttention, you can:
  1. Disable it in the FlashVSR ⚡ Advanced node by setting sageattention to disable.
  2. Or uninstall it: pip uninstall sageattention triton
• The node will work perfectly fine without SageAttention installed - it will automatically fall back to standard PyTorch attention.

Troubleshooting

• FileNotFoundError: Missing Wan2.1_VAE.safetensors:

  • This error usually occurs when the model download fails or is skipped.
  • Fix: Delete the FlashVSR folder in ComfyUI/models/, then restart ComfyUI to trigger the automatic download again.

• Out-of-Memory (OOM) Error / CUDAMallocAsyncAllocator.cpp error:

  • Occurs when VRAM is exhausted, especially with the High Quality preset or Full model at 4x scale.
  • Fix: Use the FlashVSR Advanced ⚡ node and enable enable_tiling to reduce VRAM usage.

Credits

• FlashVSR: OpenImagingLab/FlashVSR
• Original HF Models: JunhaoZhuang/FlashVSR
• Safetensors Models: 1038lab/FlashVSR
• Created by: AILab

Star History

If this custom node helps you or if you appreciate the work, please give a ⭐ on this repo! It’s a great encouragement for my efforts!

License

GPL-3.0 License