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VaultLayer vs renting GPUs directly

Renting H100s straight from RunPod, Lambda, or Vast.ai is the cheapest-looking option until you count the babysitting tax: hunting for a region with capacity, paying for idle boot minutes, wiring your own checkpoint sync, and writing resume logic because a crash just hands you a fresh pod. VaultLayer wraps those providers and handles that work for you.

What you own, with and without VaultLayer

 Renting directlyWith VaultLayer
Find capacityManually shop regions/providers for a free GPURouted to available capacity automatically
Cold-boot idleYou pay while the pod boots and the image pullsManaged provisioning across providers
Checkpoint syncYou wire it to S3/R2 yourselfBuilt in, automatic
After a crashFresh empty pod; you write resume logicAuto-resume from the last checkpoint
Your contractDirect with the providerKeep it — BYOC runs on your account

Your account, less glue

VaultLayer isn't a replacement for renting GPUs directly — it's the reliability layer on top. You can connect your own provider account and keep your pricing, or use elastic external capacity through the same CLI. Either way, vl run train.py handles provisioning, checkpointing, and recovery so you stop maintaining wrapper scripts around every run.

Frequently asked questions

Does VaultLayer replace RunPod, Lambda, or Vast.ai?

No. VaultLayer is the reliability layer on top. You can connect your own provider account (BYOC) and keep your contract, or use external capacity through the same CLI — VaultLayer adds orchestration, checkpointing, and recovery.

Can I keep my existing provider contract?

Yes. With BYOC, the job runs on your connected account and is billed by your provider; VaultLayer adds the reliability layer with no per-run GPU charge.

Keep every training job moving.

Sign up, install the CLI, and submit your first training job in minutes — on your own cloud or elastic GPU capacity.

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Evaluating for a team, or bringing your own cloud or GPU contract? Talk to us — you'll reach the founder directly.