Template · Desktops & VMs · CUDA 13

Run Pinokio on a cloud GPU, in 30 seconds

The Pinokio 1-click app browser on a desktop — install AI apps with a click. Pinokio is the one-click installer for community AI apps — hundreds of scripts that set up ComfyUI, TTS tools, LLM UIs and research demos with a single button. On a rented GPU it becomes a disposable playground: install, try, destroy. From $0.131/hr on an interruptible RTX 4090.

Deploy Pinokio All 37 templates

Running in ~30 s

Pre-cached image, ports mapped, TLS terminated — the stack is working before you finish reading this.

Template is free

You pay the GPU price only: Pinokio on a RTX 4090 is $0.262/hr on-demand, $0.131/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 Pinokio

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 4090	24 GB	$0.262	$0.131	Runs nearly every Pinokio script in 24 GB.	Deploy
Better	RTX 5090	32 GB	$0.318	$0.159	32 GB for the video and large-model scripts.	Deploy
Best	RTX PRO 6000 WS	96 GB	$1.097	$0.548	96 GB when you want several apps loaded at once.	Deploy

Need more VRAM? The full catalogue lists all 76 models with live availability; the VRAM guide sizes models to cards.

Deploy Pinokio from the console, CLI or API

Pick the template in the console deploy bar, or script it:

Console — filter by GPU, choose Pinokio 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": "pinokio". REST reference.
Own image — any OCI reference works too; we inject the NVIDIA runtime. Template docs.

deploy — pinokio

$ powergpu launch --gpu rtx-4090 --template pinokio \
    --disk 100 --volume models:/workspace/models
✓ instance i-7a41c0e2 running (27.9s)
# Pinokio · RTX 4090 · $0.262/hr · per second
# https://i-7a41c0e2.powergpu.io:8888 (TLS)
$ powergpu stop i-7a41c0e2   # billing ends this second

What is inside the Pinokio template

Image	powergpu/pinokio
CUDA	CUDA 13
Access	also builds for ARM hosts · SSH shell · JupyterLab on a mapped port
Category	Desktops & VMs
Storage	Instance NVMe disk (sized at deploy) + optional network volumes
Billing	GPU price only, per second — no template fee, no setup fee

Other desktops & vms templates

Linux Desktop on a cloud GPU — A full GPU Linux desktop over the browser — XFCE, VNC/RDP, run GUI apps.
Ubuntu 22.04 VM on a cloud GPU — A full KVM virtual machine — your own kernel, root, systemd, any stack.
Ubuntu Desktop VM on a cloud GPU — The Ubuntu VM with a GNOME desktop over VNC/RDP — a full graphical workstation.
All 37 templates

Pinokio on a cloud GPU: FAQ

Environment variables, ports and custom images are covered in the template docs.

How much does it cost to run Pinokio on a cloud GPU?

Only the GPU price — the template is free. From $0.131/hr on an interruptible RTX 4090, $0.262/hr on-demand on a RTX 4090. Billing is per second, so an hour of tinkering costs an hour, not a day. Storage is $0.08/GB/month.

How long does Pinokio 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.

Do installed apps survive a restart?

Mount a volume on the Pinokio home directory and every installed app, model and output persists across instances.