VaultLayer vs RunPod
RunPod is a GPU cloud where you rent pods and clusters by the hour. VaultLayer runs on top of providers like RunPod, wrapping your training command and handling the parts a raw pod leaves to you: provisioning, checkpoint sync, and resume after an interruption.
At a glance
| VaultLayer | RunPod (directly) | |
|---|---|---|
| What it is | Managed training control plane | GPU cloud — rent pods and clusters |
| Job submission | vl run python train.py | Launch a pod, set up your script on it |
| Checkpoint sync | Built in, automatic | You wire it to storage yourself |
| After a crash | Auto-resume from the last checkpoint | Fresh pod; you write resume logic |
| Your account | Keep it — BYOC runs on your RunPod | Direct with RunPod |
Same pods, less glue
VaultLayer doesn't replace RunPod — it runs on top of it. Connect your own RunPod account with vl connect runpod and keep your pricing, or use external capacity through the same CLI; either way vl run handles provisioning, checkpointing, and recovery. For the broader case against renting any GPU cloud directly, see VaultLayer vs renting GPUs directly.
Frequently asked questions
Does VaultLayer replace RunPod?
No. VaultLayer runs on top of RunPod. You can connect your own RunPod account (BYOC) and keep your contract, while VaultLayer adds orchestration, checkpointing, and automatic recovery.
Can I use my own RunPod account?
Yes. Run vl connect runpod to connect it, then vl run --byoc python train.py runs on your RunPod with no per-run charge from VaultLayer.
Keep every training job moving.
VaultLayer is in invite-only early access for teams running real GPU workloads.
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