Spin it up.
Throw it away.
Run lets anyone launch a disposable container or hop on a shared VM in seconds — no provisioning, no commitment. Perfect for experiments, notebooks, and quick inference. When you're done, it vanishes. You only pay for what you use.
$ superrails run start \ --image pytorch --gpu 1 ✓ container up in 3.2s → jupyter: run-x9.superrails.io $ # run your experiment... $ exit ✓ torn down · billed 4m12s · $0 idle
Compute when you want it. Gone when you don't.
For the moments between big infrastructure decisions — the quick test, the demo, the one-off run.
Disposable containers
Launch a fresh, isolated container from any image in seconds. Run your job, then let it tear down automatically.
Shared VMs
Hop onto a ready-to-go shared VM for lightweight work — no setup, no waiting, an environment that's already warm.
Per-second billing
Pay only for the seconds you actually run. Idle costs nothing — there's nothing left running to bill.
Notebooks & CLI
Open a hosted Jupyter notebook or drive it from the CLI/API. Bring your own image or use our prebuilt ML stacks.
GPU on tap
Attach a GPU to any container for quick inference or a fast experiment, then release it the moment you stop.
Shared rails
Runs on the same supercomputers owned via Rails — so spare capacity is always nearby and cheap.
When you just need
compute, right now.
Run is for the quick test, the demo, the one-off job. No accounts to provision, no clusters to babysit — just an environment that appears, does the work, and disappears.
- Prototyping a model or running a notebook
- One-off inference or batch jobs
- CI runs and reproducible experiments
- Workshops, demos, and teaching environments
Which machine is right for you?
Set your budget and goal — we'll recommend the SuperRails tier that fits.
Recommendation is illustrative — based on the same figures shown across the store. Not financial advice.