Stable Diffusion on cloud GPUs
Generate with SD 1.5, SDXL and Flux on a dedicated NVIDIA RTX 3090, 5090 or RTX PRO 6000 with up to 96 GB of VRAM, hosted in EU datacenters in Belgium. Billed per second from $0.08/GPU/hr — pay only while you generate.
- RTX 3090 · 5090 · RTX PRO 6000
- SD 1.5, SDXL & Flux
- Per-second billing
- From $0.08/GPU/hr
- EU jurisdiction, GDPR-native
What to look for in a Stable Diffusion GPU cloud
Picking a Stable Diffusion GPU cloud comes down to three things: enough VRAM for the models you actually use, a billing model that matches how bursty image generation really is, and — if you do client or commercial work — knowing exactly where your assets are processed. Plenty of Stable Diffusion cloud hosting options tick the first box; far fewer tick all three.
Why 24 GB is the sweet spot for AI image generation
The RTX 3090's 24 GB of GDDR6X and 936 GB/s of memory bandwidth put it in a different class from the 8–12 GB cards most people generate on locally. SD 1.5 runs with room to spare; SDXL fits with refiner, ControlNet and hi-res upscaling in the same session; Flux fits too, with quantized checkpoints the practical choice for its largest variants — and when you need more headroom, the lineup steps up to a 32 GB RTX 5090 or a 96 GB RTX PRO 6000. The headroom also covers LoRA training for SD-family models, so you can fine-tune a style on the same RTX 3090 instance you generate on. It is not the card for training a diffusion model from scratch or for the biggest video-generation pipelines — for multi-GPU needs, talk to sales about clusters.
ComfyUI, A1111 and your own stack
Every instance is a dedicated machine — not a shared slice, not a marketplace host — with root SSH and JupyterLab included. If you are searching for a ComfyUI cloud GPU, the workflow is simple: install ComfyUI, Automatic1111 or InvokeAI exactly as you would at home, tunnel the web UI over SSH, and keep your models on persistent storage at $0.15/GB/mo so the environment survives between sessions. A full REST API lets you script render farms or batch jobs — see Jupyter on a cloud GPU for the notebook-first route.
Pay only while you generate
Image generation is bursty: an afternoon of iteration, then nothing for days. Hourly-rounded SDXL GPU rental punishes that pattern; per-second billing doesn't. Create an account on the console, load prepaid credit and launch in minutes — no commitments, stop anytime. And because the datacenters are European-owned, renewable-powered sites in Belgium, agencies can put client assets on them without the jurisdiction questions raised by anonymous marketplace hosts — see GDPR-compliant GPU hosting.
What fits in 24 GB
| Workload | Fit on 24 GB | Notes |
|---|---|---|
| SD 1.5 | Comfortable | Large batches, ControlNet stacks and upscaling in one session |
| SDXL | Comfortable | Base + refiner plus hi-res fix without offloading tricks |
| Flux | Fits | Largest variants sit near the 24 GB ceiling — quantized checkpoints recommended |
| LoRA / DreamBooth training | Fits | Style and subject fine-tunes for SD-family models |
| Foundation-model training | Out of scope | Needs multi-GPU clusters — ask sales about reserved capacity |
RTX 3090 tiers: Guaranteed $0.25 · Balanced $0.12 · Flexible $0.08 per GPU/hr, billed per second. RTX 5090 $0.65 / $0.44 / $0.26 · RTX PRO 6000 $1.49 / $0.99 / $0.59. Storage $0.15/GB/mo · bandwidth $0.02/GB. See full pricing details.
Stable Diffusion in the cloud, answered
Can an RTX 3090 run SDXL and Flux?
Yes. With 24 GB of GDDR6X, an RTX 3090 runs SD 1.5 and SDXL comfortably, including refiner passes, ControlNet stacks and high-resolution upscaling. Flux also fits — the larger variants sit near the top of 24 GB, so quantized checkpoints are the usual choice for heavier Flux workflows. For more headroom, the 32 GB RTX 5090 and 96 GB RTX PRO 6000 Blackwell are also available.
Can I run ComfyUI or Automatic1111 on EponEdge?
Yes. Every instance is a dedicated machine with root SSH, so you can install ComfyUI, Automatic1111, Forge or InvokeAI exactly as you would locally, then reach the web UI through an SSH tunnel. JupyterLab is also included out of the box.
How does per-second billing work for image generation?
You pay only for the seconds your instance runs, with no commitments — start it for a render batch, stop it when you are done. Paused time is never billed, and persistent storage at $0.15/GB/mo keeps your models and outputs between sessions.
Why does EU hosting matter for commercial image work?
Agencies and studios often work with client assets — product shots, brand material, sometimes images of real people. EponEdge instances are dedicated hardware in European-owned Belgian datacenters under EU jurisdiction, GDPR-native and without exposure to foreign cloud acts such as the US CLOUD Act, which makes the processing location easy to document.
Which tier should I pick for Stable Diffusion?
For interactive sessions in ComfyUI or A1111, Guaranteed (from $0.25/GPU/hr) is never paused. Balanced (from $0.12) pauses only during severe grid stress, which is rare in practice. Flexible (from $0.08) follows clean-power availability and suits queued batch renders — instances resume with GPU memory intact, and you keep the rate you launched at.
Related solutions
Your next render batch,
billed by the second.
Launch a 24 GB RTX 3090 for Stable Diffusion now, or ask us about reserved capacity and multi-node clusters.