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Quickstart

This walks the shortest path from a new account to a shell on a GPU. It assumes nothing except an email address and a card.

1. Sign in​

Go to the console and enter your email. You'll get a six-digit code — there is no password to choose. Google and GitHub sign-in also work, and land you in the same account if the email matches.

The first time you sign in, a personal organization is created for you automatically. Everything you rent belongs to an organization, and yours is ready immediately.

See Create your account for the details.

2. Add credits​

Superheat is prepaid: you cannot start an instance with a zero balance.

Open Billing → Add credits and pick $10, $25 or $100, or enter a custom amount between $5 and $1,000. Checkout is handled by Stripe; credits land on your balance as soon as the payment confirms.

Only organization admins can add credits

On your personal organization you are the admin, so this is not a restriction until you join someone else's team.

3. Add an SSH key​

If you want shell access — and you probably do — add a public key before deploying, so it's baked into the instance at launch.

Generate one if you don't have it:

ssh-keygen -t ed25519 -C "superheat"

Then paste the contents of ~/.ssh/id_ed25519.pub into SSH Keys → Add SSH key. See Supported key types for what the form accepts.

4. Pick a GPU​

Open Rent GPUs. Each card is an offer — a slice of a real machine, showing its GPU model, how many GPUs are in the slice, VRAM per card, TFLOPS, storage, location, a reliability score, and the hourly price for the whole slice.

Filter down to what you need, then select an offer. See Browse the marketplace for what every filter does.

5. Deploy​

Selecting an offer raises a selection bar at the bottom of the page; Continue takes you to Configure & Deploy. You choose:

  • A template — start with a system template such as PyTorch (SSH), PyTorch (Jupyter) or CUDA Devel. See Templates.
  • Disk size — from 10 GB up to the machine's own disk capacity, in 10 GB steps. The API's ceiling is 20,000 GB, and a deploy asking for more than the machine has is rejected. Disk is billed separately while the instance is stopped, so do not over-provision out of habit.
  • An SSH key — the one you added in step 3. Leaving it as No key means no shell access.
  • A label (optional, up to 64 characters), so you can tell instances apart later.

A cost panel updates as you change these, showing the GPU rate, the storage rate, the total per hour, an approximate per-day figure and your balance. Select Deploy instance.

6. Connect​

The instance goes through creating and then running. The instance page has Connect, Logs and Billing tabs; Connect holds a ready-made command:

ssh -p 40123 root@sh-us-ca-02.ssh.superheat.dev

The port is not 22 — each instance publishes its SSH port from the host's range, and the exact port is assigned at launch. Copy the command rather than reconstructing it.

If your template uses the jupyter launch mode, an Open JupyterLab button appears above the SSH command, already carrying the access token. That mode opens port 22 as well, so both routes work.

7. Stop or destroy when you're done​

This is the step people skip, and it's the one that costs money.

ActionContainerYour diskGPU slotBilling
Stopshut downkeptheld for youstorage only
Destroyremoveddeletedreleasednothing

Stop when you'll be back later today and want your data waiting. Destroy when you're finished. Read Stop vs destroy before you decide — a stopped instance keeps charging.

What next​