Manual Install

Manual installation gives you full control over your Python environment, PyTorch version, and CUDA configuration. This method is recommended for developers and advanced users.

Prerequisites

Install these before starting:

1. Python 3.12 or 3.13 (3.13 recommended) — Download from python.org
   • During install, check "Add Python to PATH"
2. Git — Download from git-scm.com
3. NVIDIA GPU drivers — Download from nvidia.com

Step 1: Clone the Repository

Open Command Prompt or PowerShell:

git clone https://github.com/comfyanonymous/ComfyUI.git
cd ComfyUI

Step 2: Create a Virtual Environment (Recommended)

python -m venv venv
venv\Scripts\activate

You should see (venv) at the start of your command prompt.

Step 3: Install PyTorch

Install PyTorch with the CUDA version that matches your NVIDIA driver. First, check your driver version:

nvidia-smi

Then choose the right PyTorch install command:

NVIDIA GPU — CUDA Version Matching

Driver Version	CUDA Version	PyTorch Command
560+	CUDA 12.6	pip install torch torchvision torchaudio --extra-index-url https://download.pytorch.org/whl/cu126
570+	CUDA 12.8	pip install torch==2.8.0 torchvision==0.23.0 torchaudio==2.8.0 --index-url https://download.pytorch.org/whl/cu128
575+	CUDA 13.0	pip install torch==2.9.1 torchvision==0.24.1 torchaudio==2.9.1 --index-url https://download.pytorch.org/whl/cu130

RTX 50 Series Users

RTX 5070 Ti / 5080 / 5090 require CUDA 12.8 or higher. Make sure your driver is version 570+, and use the CUDA 12.8 or 13.0 PyTorch build. See GPU Compatibility for the full driver-CUDA-PyTorch matrix.

If you're unsure, the CUDA 12.6 build works for most RTX 20/30/40 series cards:

pip install torch torchvision torchaudio --extra-index-url https://download.pytorch.org/whl/cu126

AMD GPU (Linux with ROCm)

pip install torch torchvision torchaudio --index-url https://download.pytorch.org/whl/rocm6.2.4

CPU Only

pip install torch torchvision torchaudio

Step 4: Install Dependencies

pip install -r requirements.txt

Faster alternative: uv

uv is a much faster Python package installer (written in Rust). If you install it, you can replace any pip install command with uv pip install for 10-100x faster downloads:

pip install uv
uv pip install -r requirements.txt

Step 5: Download a Model

Place at least one checkpoint model in models/checkpoints/:

ComfyUI/
└── models/
    └── checkpoints/    ← Put your .safetensors file here

See Download Models for model recommendations.

Step 6: Run ComfyUI

python main.py

Once you see Starting server, open http://127.0.0.1:8188 in your browser.

Using comfy-cli (Alternative)

comfy-cli is a command-line tool that automates the manual install process:

pip install comfy-cli
comfy install

This handles cloning, virtual environment creation, PyTorch installation, and dependency setup in one command.

Updating

cd ComfyUI
git pull
pip install -r requirements.txt

Troubleshooting

Problem	Solution
python command not found	Reinstall Python with "Add to PATH" checked, or use python3
CUDA not available after PyTorch install	PyTorch CUDA version doesn't match your driver. Check with nvidia-smi and reinstall the matching PyTorch
ModuleNotFoundError	Make sure your venv is activated and run pip install -r requirements.txt
Build errors during pip install	Install Visual Studio Build Tools — some packages need a C++ compiler
torch.cuda.OutOfMemoryError	Run with python main.py --lowvram

Next Steps

• Generate your first image
• Download models
• Install custom nodes
• System requirements
• Troubleshoot common issues