Price floor Every GPU at least 30% below the market median — re-checked against the marketplace weekly.

See the proof

Template · Desktops & VMs · CUDA 12.1

Run a GPU Linux desktop in the cloud, in 30 seconds

A full GPU Linux desktop over the browser — XFCE, VNC/RDP, run GUI apps. A full XFCE desktop on a GPU, delivered to your browser or any VNC/RDP client. Run GUI tools — Blender, DaVinci Resolve, Unreal, scientific visualisers — on a rented card, with your files on a volume and the desktop gone the second you stop paying. From $0.131/hr on an interruptible RTX 4090.

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: Linux Desktop 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 Linux Desktop

Three price points that run this template well — Good, Better, Best. Every model in the catalogue works; these are the value picks.

TierGPUVRAMOn-demandInterruptibleWhy this cardAction
GoodRTX 409024 GB$0.262$0.131Fast interactive work at the best consumer price.Deploy
BetterRTX A600048 GB$0.281$0.14048 GB ECC with studio drivers for professional apps.Deploy
BestRTX PRO 6000 WS96 GB$1.097$0.54896 GB GDDR7 for the heaviest scenes and datasets.Deploy

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

Deploy Linux Desktop from the console, CLI or API

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

  • Console — filter by GPU, choose Linux Desktop in the template picker, set disk and env, deploy.
  • CLIpip install powergpu, then the command on the right. CLI reference.
  • APIPOST /v1/instances with "template": "linux-desktop". REST reference.
  • Own image — any OCI reference works too; we inject the NVIDIA runtime. Template docs.
deploy — linux-desktop
$ powergpu launch --gpu rtx-4090 --template linux-desktop \
    --disk 100 --volume models:/workspace/models
 instance i-7a41c0e2 running (27.9s)
# Linux Desktop · 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 Linux Desktop template

Imagepowergpu/linux-desktop
CUDACUDA 12.1
Accessalso builds for ARM hosts · SSH shell · JupyterLab on a mapped port
CategoryDesktops & VMs
StorageInstance NVMe disk (sized at deploy) + optional network volumes
BillingGPU price only, per second — no template fee, no setup fee

Other desktops & vms templates

Linux Desktop on a cloud GPU: FAQ

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

How much does it cost to run Linux Desktop 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 Linux Desktop 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.

Is the desktop encrypted in transit?

Browser access goes through the TLS-terminated port; native VNC/RDP should be tunnelled over SSH, which the template exposes as well.

Deploy your first GPU in under a minute

Top up in crypto, benchmark us against your current provider. Per-second billing, fixed prices ≥ 30% below market — cancel by just stopping the instance.