https://github.com/numz/ComfyUI-SeedVR2_VideoUpscaler
Non-Official SeedVR2 Vudeo Upscaler for ComfyUI
https://github.com/numz/ComfyUI-SeedVR2_VideoUpscaler
Last synced: 2 days ago
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Non-Official SeedVR2 Vudeo Upscaler for ComfyUI
- Host: GitHub
- URL: https://github.com/numz/ComfyUI-SeedVR2_VideoUpscaler
- Owner: numz
- License: mit
- Created: 2025-06-20T15:51:18.000Z (7 days ago)
- Default Branch: main
- Last Pushed: 2025-06-20T17:08:30.000Z (7 days ago)
- Last Synced: 2025-06-20T17:42:20.650Z (7 days ago)
- Language: Python
- Size: 1.98 MB
- Stars: 0
- Watchers: 0
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- Contributing: CONTRIBUTING.md
- License: LICENSE
Awesome Lists containing this project
- awesome-comfyui - **ComfyUI-SeedVR2_VideoUpscaler** - SeedVR2 Video Upscaler repository! This project offers a non-official video upscaling tool designed specifically for ComfyUI. With this tool, you can enhance your video quality, making your visual content more engaging and clearer. (All Workflows Sorted by GitHub Stars)
README
# ComfyUI-SeedVR2_VideoUpscaler
[](https://github.com/numz/ComfyUI-SeedVR2_VideoUpscaler)
Official release of [SeedVR2](https://github.com/ByteDance-Seed/SeedVR) for ComfyUI that enables Upscale Video/Images generation.
## 🆙 Todo
- Fixed unloading the 3B model when the process is finished (sorry about that, I'm trying to find out what's going on)
## 🚀 Updates
**2025.06.24**
- 🚀 Speed up the process until x4 (see new benchmark)
**2025.06.22**
- 💪 FP8 compatibility !
- 🚀 Speed Up all Process
- 🚀 less VRAM consumption (Stay high, batch_size=1 for RTX4090 max, I'm trying to fix that)
- 🛠️ Better benchmark coming soon
**2025.06.20**
- 🛠️ Initial push
## Features
- High-quality Upscaling
- Suitable for any video length once the right settings are found
- Model Will Be Download Automatically from [Models](https://huggingface.co/numz/SeedVR2_comfyUI/tree/main)
## Requirements
- A Huge VRAM capabilities is better, from my test, even the 3B version need a lot of VRAM at least 18GB.
- Last ComfyUI version with python 3.12.9 (may be works with older versions but I haven't test it)
## Installation
1. Clone this repository into your ComfyUI custom nodes directory:
```bash
cd ComfyUI/custom_nodes
git clone https://github.com/numz/ComfyUI-SeedVR2_VideoUpscaler.git
```
2. Install the required dependencies:
load venv and :
```bash
pip install -r ComfyUI-SeedVR2_VideoUpscaler/requirements.txt
```
install flash_attn or triton if it ask for it
```bash
pip install flash_attn
pip install triton
```
or from https://github.com/loscrossos/lib_flashattention/releases
and
https://github.com/woct0rdho/triton-windows
Or use python_embeded :
```bash
python_embeded\python.exe -m pip install -r ComfyUI-SeedVR2_VideoUpscaler/requirements.txt
```
```bash
python_embeded\python.exe -m pip install -r flash_attn
```
3. Models
Will be automtically download into :
`models/SEEDVR2`
or can be found here ([MODELS](https://huggingface.co/numz/SeedVR2_comfyUI/tree/main))
## Usage
1. In ComfyUI, locate the **SeedVR2 Video Upscaler** node in the node menu.
2. things to know
**temporal consistency** : at least a batch_size of 5 is required to activate temporal consistency
2. Configure the node parameters:
- `model`: Select your 3B or 7B model
- `seed`: a seed but it generate another seed from this one
- `new_width`: New desired Width, will keep ration on height
- `cfg_scale`:
- `batch_size`: VERY IMPORTANT!, this model consume a lot of VRAM, All your VRAM, even for the 3B model, so for GPU under 24GB VRAM keep this value Low, good value is "1" without temporal consistency
- `preserve_vram`: for VRAM < 24GB, If true, It will unload unused models during process, longer but works, otherwise probably OOM with
## Performance
**NVIDIA H100 93GB VRAM** (values in parentheses are from the previous benchmark):
| nb frames | Resolution | Batch Size | Time fp8 (s) | FPS fp8 | Time fp16 (s) | FPS fp16 |
| --------- | ------------------- | ---------- | ---------------- | ----------- | ---------------- | ----------- |
| 3 | 512×768 → 1080×1620 | 1 | 10.18 (58.10) | 0.29 (0.05) | 10.67 (60.13) | 0.28 (0.05) |
| 15 | 512×768 → 1080×1620 | 5 | 26.71 (135.63) | 0.56 (0.11) | 27.75 (144.18) | 0.54 (0.10) |
| 27 | 512×768 → 1080×1620 | 9 | 33.97 (163.22) | 0.79 (0.17) | 35.08 (177.61) | 0.77 (0.15) |
| 39 | 512×768 → 1080×1620 | 13 | 41.01 (189.36) | 0.95 (0.21) | 42.08 (210.11) | 0.93 (0.19) |
| 51 | 512×768 → 1080×1620 | 17 | 48.12 (215.80) | 1.06 (0.24) | 49.44 (242.64) | 1.03 (0.21) |
| 63 | 512×768 → 1080×1620 | 21 | 55.40 (241.79) | 1.14 (0.26) | 56.70 (275.55) | 1.11 (0.23) |
| 75 | 512×768 → 1080×1620 | 25 | 62.60 (267.93) | 1.20 (0.28) | 63.80 (308.51) | 1.18 (0.24) |
| 123 | 512×768 → 1080×1620 | 41 | 91.38 (373.60) | 1.35 (0.33) | 92.90 (440.01) | 1.32 (0.28) |
| 243 | 512×768 → 1080×1620 | 81 | 164.25 (642.20) | 1.48 (0.38) | 166.09 (780.20) | 1.46 (0.31) |
| 363 | 512×768 → 1080×1620 | 121 | 238.18 (913.61) | 1.52 (0.40) | 239.80 (1114.32) | 1.51 (0.33) |
| 453 | 512×768 → 1080×1620 | 151 | 296.52 (1132.01) | 1.53 (0.40) | 298.65 (1384.86) | 1.52 (0.33) |
| 633 | 512×768 → 1080×1620 | 211 | 406.65 (1541.09) | 1.56 (0.41) | 409.44 (1887.62) | 1.55 (0.34) |
| 903 | 512×768 → 1080×1620 | 301 | OOM (OOM) | OOM (OOM) | OOM (OOM) | OOM (OOM) |
**NVIDIA RTX4090 24GB VRAM** (preserved_vram=off)
| Model | Images | Resolution | Batch Size | Time (seconds) | FPS | Note |
| ------------------------- | ------ | ------------------- | ---------- | -------------- | --- | --- |
| 3B fp8 | 5 | 512x768 → 1080x1620 | 1 | 22.52 | 0.22 | |
| 3B fp16 | 5 | 512x768 → 1080x1620 | 1 | 27.84 | 0.18 | |
| 7B fp8 | 5 | 512x768 → 1080x1620 | 1 | 75.51 | 0.07 | |
| 7B fp16 | 5 | 512x768 → 1080x1620 | 1 | 78.93 | 0.06 | |
| 3B fp8 | 10 | 512x768 → 1080x1620 | 5 | 39.75 | 0.15 | preserve_memory=on|
| 3B fp8 | 20 | 512x768 → 1080x1620 | 1 | 65.40 | 0.31 | |
| 3B fp16 | 20 | 512x768 → 1080x1620 | 1 | 91.12 | 0.22 | |
| 3B fp8 | 20 | 512x768 → 1280x1920 | 1 | 89.10 | 0.22 | |
| 3B fp8 | 20 | 512x768 → 1480x2220 | 1 | 136.08| 0.15 | |
| 3B fp8 | 20 | 512x768 → 1620x2430 | 1 | 191.28 | 0.10 | preserve_memory=on without GPU overload so longer 320sec |
## Limitations
- Use a lot of VRAM, it will take all!!
- Processing speed depends on GPU capabilities
## Credits
- Original [SeedVR2](https://github.com/ByteDance-Seed/SeedVR) implementation
# 📜 License
- The code in this repository is released under the MIT license as found in the [LICENSE file](LICENSE).