Running in ~30 s
Pre-cached image, ports mapped, TLS terminated — the stack is working before you finish reading this.
Template · Image generation · CUDA 12.9
Run InvokeAI on a cloud GPU, in 30 seconds
A polished Stable Diffusion studio — canvas, layers and workflow nodes. InvokeAI is the polished studio for image generation: an infinite canvas, layers, inpainting, workflow nodes and a model manager that understands SD 1.5, SDXL and Flux. It suits illustrators and teams who want a designed tool rather than a graph editor. From $0.033/hr on an interruptible RTX 4070.
Template is free
You pay the GPU price only: InvokeAI on a RTX 4070 is $0.066/hr on-demand, $0.033/hr interruptible, billed per second.
Volumes for state
Models, datasets and outputs live on a $0.08/GB/mo volume; the instance stays disposable.
Private by default
Dedicated GPU, encrypted disk, crypto payments, no KYC, no stored IPs — Jupyter and SSH behind your own credentials.
Best GPUs for InvokeAI
Three price points that run this template well — Good, Better, Best. Every model in the catalogue works; these are the value picks.
| Tier | GPU | VRAM | On-demand | Interruptible | Why this card | Action |
|---|---|---|---|---|---|---|
| Good | RTX 4070 | 12 GB | $0.066 | $0.033 | 12 GB runs SD 1.5 and SDXL with FP8 comfortably at low cost. | Deploy |
| Better | RTX 4090 | 24 GB | $0.262 | $0.131 | 24 GB for Flux and large canvases. | Deploy |
| Best | RTX 5090 | 32 GB | $0.318 | $0.159 | 32 GB for multi-model pipelines and big batch renders. | Deploy |
Need more VRAM? The full catalogue lists all 76 models with live availability; the VRAM guide sizes models to cards.
Deploy InvokeAI from the console, CLI or API
Pick the template in the console deploy bar, or script it:
- Console — filter by GPU, choose InvokeAI in the template picker, set disk and env, deploy.
- CLI — pip install powergpu, then the command on the right. CLI reference.
- API — POST /v1/instances with "template": "invokeai". REST reference.
- Own image — any OCI reference works too; we inject the NVIDIA runtime. Template docs.
$ powergpu launch --gpu rtx-4070 --template invokeai \
--disk 100 --volume models:/workspace/models
✓ instance i-7a41c0e2 running (27.9s)
# InvokeAI · RTX 4070 · $0.066/hr · per second
# https://i-7a41c0e2.powergpu.io:8888 (TLS)
$ powergpu stop i-7a41c0e2 # billing ends this secondWhat is inside the InvokeAI template
| Image | powergpu/invokeai |
|---|---|
| CUDA | CUDA 12.9 |
| Access | also builds for ARM hosts · SSH shell · JupyterLab on a mapped port |
| Category | Image generation |
| Storage | Instance NVMe disk (sized at deploy) + optional network volumes |
| Billing | GPU price only, per second — no template fee, no setup fee |
Other image generation templates
ComfyUI on a cloud GPU — Node-based image and video workflows with ComfyUI-Manager pre-installed.
SD WebUI Forge on a cloud GPU — The Forge fork of the SD WebUI — faster attention, lower VRAM, same extensions.- SD WebUI A1111 on a cloud GPU — The classic AUTOMATIC1111 Stable Diffusion WebUI with the full extension ecosystem.
Fooocus on a cloud GPU — Prompt-and-go image generation — Midjourney-style simplicity on SDXL.
SwarmUI on a cloud GPU — A ComfyUI-backed UI that scales generation across multiple GPUs.- All 37 templates
InvokeAI on a cloud GPU: FAQ
Environment variables, ports and custom images are covered in the template docs.
How much does it cost to run InvokeAI on a cloud GPU?
Only the GPU price — the template is free. From $0.033/hr on an interruptible RTX 4070, $0.066/hr on-demand on a RTX 4070. Billing is per second, so an hour of tinkering costs an hour, not a day. Storage is $0.08/GB/month.
How long does InvokeAI take to start?
About 30 seconds from the deploy click: the image is pre-cached on hosts, ports are mapped and TLS is terminated for you. Restarting a stopped instance is faster, and your disk is exactly as you left it.
Can I keep my models and outputs between sessions?
Yes — attach a volume at deploy. Everything on the volume survives instance destruction and mounts on the next instance in the region in seconds, at $0.08/GB/month. The instance disk itself survives stop/start but not destroy.
Can I import my Automatic1111 models?
Yes — point the model manager at a mounted volume containing your .safetensors files; InvokeAI scans and registers them.