ComfyUI Fast Setup — Qwen Image Edit (H100)

Reproducible notes for standing up this ComfyUI box quickly. The speed trick is simple: the base image already had a working CUDA PyTorch stack, so nothing large was reinstalled.

Machine

GPU: NVIDIA H100 80GB HBM3 (CUDA 13.0 driver, 580.x)
Python 3.12, pre-installed: torch 2.8.0+cu128, torchvision 0.23.0, torchaudio 2.8.0 (all CUDA-verified)
/workspace is a network filesystem (MooseFS) — model reads are slow when the OS page cache is cold (e.g. right after a restart). Keep the server running to keep weights resident.

1. ComfyUI

git clone --depth 1 https://github.com/comfyanonymous/ComfyUI.git /workspace/ComfyUI
cd /workspace/ComfyUI
pip install -r requirements.txt        # torch stack already present -> only light deps install

2. Fast downloads (hf_xet, not hf_transfer)

huggingface_hub 1.x ships hf_xet (chunked parallel transfer) built in — hf_transfer no longer exists.

export HF_TOKEN=<your token>

3. Standard Qwen Image Edit models (the reproducible core)

Download straight from the public repos into these paths:

File	Repo	Dest
`qwen_image_edit_2511_fp8mixed.safetensors` (20 GB, recommended)	`Comfy-Org/Qwen-Image-Edit_ComfyUI` `split_files/diffusion_models/`	`models/diffusion_models/`
`qwen_image_edit_2511_bf16.safetensors` (39 GB, max quality)	same	`models/diffusion_models/`
`qwen_2.5_vl_7b_fp8_scaled.safetensors`	`Comfy-Org/HunyuanVideo_1.5_repackaged` `split_files/text_encoders/`	`models/text_encoders/`
`qwen_image_vae.safetensors`	`Comfy-Org/Qwen-Image_ComfyUI` `split_files/vae/`	`models/vae/`
`Qwen-Image-Edit-2511-Lightning-4steps-V1.0-bf16.safetensors`	`lightx2v/Qwen-Image-Edit-2511-Lightning`	`models/loras/`

Example (parallelize these for speed):

hf download Comfy-Org/Qwen-Image-Edit_ComfyUI \
  split_files/diffusion_models/qwen_image_edit_2511_fp8mixed.safetensors \
  --local-dir /tmp/dl && mv /tmp/dl/split_files/diffusion_models/*.safetensors \
  /workspace/ComfyUI/models/diffusion_models/

fp8 vs bf16: fp8mixed is half the size (20 vs 39 GB), loads ~2x faster, and on an H100 also computes faster with negligible quality loss for edits. Use bf16 only when chasing maximum fidelity.

4. Custom nodes

git clone --depth 1 https://github.com/rgthree/rgthree-comfy.git \
  /workspace/ComfyUI/custom_nodes/rgthree-comfy      # Power Lora Loader
pip install -U comfyui-manager                        # matches bundled manager_requirements.txt (4.2.2)

ComfyUI-Manager installs node deps with uv pip, which refuses the system Python (PEP 668). If a node's deps fail to install via the Manager UI, install them directly instead: pip install -r custom_nodes/<node>/requirements.txt

5. Run

cd /workspace/ComfyUI
python3 main.py --listen 0.0.0.0 --port 7865

6. Workflows built

qwen-loras.json — master Qwen edit workflow. Single "Accelerate?" boolean toggles Lightning-4step + steps(4↔20) + CFG(1.0↔4.0) together. Content LoRAs go in the Power Lora Loader.
qwen-cat-final.json — multi-reference edit. A second LoadImage feeds image2 of TextEncodeQwenImageEditPlus, so an edit can combine two input images (e.g. subject + object).

Notes / gotchas

Model load is the slow step over the network FS; it's a one-time cost per server start. Avoid restarting mid-session — resident weights make LoRA swaps fast.
Both opencv-python and -headless may end up installed by different node packs; same version = fine.
The RequestsDependencyWarning about urllib3/chardet at startup is cosmetic.