---
title: "Self-host ComfyUI on Edge | Node-based Stable Diffusion on GPU VMs"
description: "Run ComfyUI on Edge GPU instances — Stable Diffusion XL, FLUX and any diffusion model, with checkpoints and LoRAs in S3-compatible Edge Storage. Headless API mode for production image generation."
url: https://edge.network/solutions/comfyui/
---

# Self-host ComfyUI on Edge | Node-based Stable Diffusion on GPU VMs

For ComfyUI

# ComfyUI on Edge, image generation on your GPUs

Self-host the most flexible diffusion runtime on Edge GPU
instances. SDXL, FLUX, ControlNets, custom workflows — checkpoints
in S3, outputs delivered through the global CDN.

[Start free](https://edge.network/account) [See AI infrastructure](https://edge.network/solutions/ai)

# Provision a GPU VM

$ edge compute create \

--image ubuntu-24-04-cuda --plan gpu-l4 \

--script ./bootstrap-comfy.sh

# Mount Edge Storage as models/

$ s3fs models /opt/comfy/models \

-o url=https://storage.edge.run

# Run headless

$ python main.py --listen 0.0.0.0 --port 8188

# Trigger a workflow from your app

POST https://comfy.example.com/prompt

{ "prompt": { ...workflow JSON... } }

## Why teams self-host ComfyUI

Maximum flexibility per GPU dollar, with no per-image bills.

### Any diffusion model

SDXL, FLUX, SD3, AnimateDiff, video models — if it has a checkpoint, ComfyUI runs it. The most flexible diffusion runtime.

### GPU VMs from L4 to H100

Pick the right card for your model. SDXL flies on an L4; FLUX wants an A10/A100; video models want H100. Sized to fit your workflow.

### Checkpoints + LoRAs in S3

Mount Edge Storage as the `models/` directory. Checkpoints, LoRAs, ControlNets, VAEs all centrally stored — share across multiple GPU VMs.

### Headless API for production

ComfyUI exposes a REST API for triggering workflows. Pair with a small Node/Python service for queue management and you have a production image-gen pipeline.

### Custom nodes welcome

The ComfyUI ecosystem is huge — IPAdapter, ControlNet, AnimateDiff, custom samplers. All install via `git clone` into `custom_nodes/`.

### Per-image bills, gone

Replicate, fal.ai, Together charge per image. An Edge GPU VM running ComfyUI is one fixed monthly fee — generate millions of images for the same bill.

Reference architecture

## How ComfyUI maps to Edge

GPU VM(s) for inference, S3 for shared model weights, CDN for delivery of finished images. Add a small queue service for production volume.

Compute (GPU) ComfyUI on a GPU VM, scaled horizontally for throughput

Storage S3-compatible bucket for checkpoints, LoRAs, outputs

CDN Serves generated images globally with image optimisation

Image Optimization On-the-fly resize/format conversion of generated outputs

DNS Anycast DNS for `comfy.example.com` (admin) and `cdn.example.com` (outputs)

Indicative cost

### ~50k SDXL generations / month

Replicate (SDXL) ~$200–500/mo
fal.ai (SDXL) ~$150–400/mo
Edge GPU VM (L4) flat fee

Edge wins decisively as volume grows past the GPU's monthly cost.

## Common questions

### How does this compare to Replicate / fal.ai?

Cheaper per image at scale, more flexible (any custom workflow you can build in the UI), and your prompts/outputs stay private. Trade-off: you handle scaling and queue management — but for steady-volume workloads it pays back fast.

### How do I expose it as an API to my app?

Run ComfyUI in `--listen` mode behind the Edge CDN. Your app POSTs workflow JSON to `/prompt`; ComfyUI returns a job ID; poll for completion or use the WebSocket. Lots of community wrappers exist.

### How do I share models across multiple GPUs?

Mount Edge Storage as the `models/` directory on every ComfyUI VM. Adding a new GPU is then just spinning up a VM — no model copying.

### What about NSFW / safety filters?

ComfyUI doesn't enforce filters by default — that's your call as the operator. If you're building a public product, add a moderation step (CLIP-based classifier or external API) into the workflow.

By Stack

## Other stacks on Edge

[View all stacks →](https://edge.network/solutions/stacks)
[Docker Run any container on global VMs](https://edge.network/solutions/docker)[Kubernetes k3s and full k8s on real VMs, no control-plane fees](https://edge.network/solutions/kubernetes)[Next.js Self-host Next.js without the lock-in](https://edge.network/solutions/nextjs)[Nuxt Vue-powered SSR on global VMs](https://edge.network/solutions/nuxt)

## Generate images on your terms

Start free. Compute team can size the right GPU for your workflow.

[Start free](https://edge.network/account) [Talk to an engineer](https://edge.network/contact)