Easy Fresh ComfyUI Install on Windows 11 with Flash-Attention 2 & SageAttention (Low VRAM Boost!)

Описание: Step 1: Prepare Prerequisites

*Install NVIDIA CUDA Toolkit*
Download and install the latest version:
https://developer.nvidia.com/cuda-dow...

*Download and add FFmpeg to PATH*
Download the latest FFmpeg build:
https://github.com/BtbN/FFmpeg-Builds...
Unzip the downloaded file.
Copy the full path to the `bin` folder inside the unzipped directory.
Open *System Properties* → *Advanced* → **Environment Variables**.
Under *User variables**, select **Path* → *Edit* → **New**.
Paste the `bin` path → *OK* to save and exit.

*Install Git* (recommended; skip if you prefer manually downloading ZIP files)
https://git-scm.com/download/win
Keeping ComfyUI updated with Git is the easiest way to get first-day support for the latest models. You can update via the ComfyUI Manager or by running `git pull` in the ComfyUI directory.

Step 2: Install ComfyUI with Miniconda

1. *Clone the repositories*
Open a terminal (Command Prompt or PowerShell) and run:
```
git clone https://github.com/comfyanonymous/Com...
cd ComfyUI
git clone https://github.com/Comfy-Org/ComfyUI-... custom_nodes/ComfyUI-Manager
```

2. *Install Miniconda* (if not already installed)
Download and install from:
https://repo.anaconda.com/miniconda/

3. *Create and activate a Conda environment*
Open *Anaconda PowerShell Prompt (Miniconda3)* from the Start menu.
Create a new environment (replace `comfyui` with your preferred name):
```
conda create -n comfyui python=3.12
```
When prompted, accept the terms and let it finish creating.
Activate the environment:
```
conda activate comfyui
```

4. *Install ComfyUI requirements*
Navigate to your ComfyUI folder:
```
cd path\to\your\ComfyUI
```
Install dependencies:
```
pip install -r requirements.txt
```

5. *Launch ComfyUI*
```
python main.py
```
If you encounter PyTorch-related errors, follow the reinstall steps shown in the video (using `--force-reinstall` for PyTorch).

Step 3: Install Performance Boosters (Flash-Attention, SageAttention, Triton)

These optional wheels (Flash-Attention, SageAttention, and Triton for Windows) significantly improve performance and allow you to run demanding workflows like:
Qwen-Image-Edit in BF16
WAN2.2 in FP16
even on GPUs with 10 GB VRAM (when paired with 64 GB system RAM).

*Flash-Attention 2 for Windows*
Download the appropriate wheel for your setup:
https://huggingface.co/ussoewwin/Flas...

*SageAttention (precompiled wheels by Kijai)*
Download the matching wheel:
https://huggingface.co/Kijai/Precompi...

After downloading the `.whl` files, install them in your activated Conda environment:
```
pip install path\to\downloaded-wheel.whl
```

Restart ComfyUI after installation to apply the changes.

Enjoy the extra speed and reduced VRAM usage!