GPU Rental
GPU power, grown on demand.
Rent cloud GPUs for AI training and inference. No hardware to own — just a working notebook, minutes after you pay.
Rent cloud GPUs for AI training and inference. No hardware to own — just a working notebook, minutes after you pay.
Every instance ships with JupyterLab and SSH preconfigured.
Every tile is a GPU. Terracotta means it's rented right now.
A single GPU isn't always enough. Clusters will let you rent several GPUs networked together for large-scale training — same billing model, same one-click access, just bigger.
JupyterLab plus full SSH — same machine, same files.
Fresh credentials, never reused.
Files persist while your instance runs. Some GPUs offer a persistent volume that survives between rentals.
Stop anytime, pay only for use.
No invented uptime numbers — just how billing and access work, plainly stated.
No rounding up to the hour, no compute charge for a box you're no longer using. The only thing that keeps billing after you stop is a persistent storage volume, if your GPU uses one — shown at checkout before you rent.
Both are included in the hourly price shown — not sold separately.
Never reused or shared with a previous customer.
Rent for an hour or a week — nothing to cancel.
Your instance keeps running until you stop it, or until your balance runs out — at zero balance it's stopped automatically so you're never billed past what you've paid. We email you when your balance gets low, and again if a rental has been running for a long time. Save your work regularly: a stopped instance's local files may not be recoverable.
No. JupyterLab runs in your browser. If you prefer the terminal, any standard SSH client — already built into Mac, Linux, and modern Windows — will connect.
Anything that runs on a standard Linux machine with an NVIDIA GPU — training scripts, fine-tuning jobs, inference servers, image or video generation, general CUDA work.
Each rental is an isolated instance with credentials generated fresh for you, never reused across customers. Instances run on third-party data-center hardware, so treat them like any cloud server: don't store secrets you can't rotate, and delete data you no longer need before stopping.