Use cases

Built for how your team actually works

VESSL Cloud adapts to different workloads and teams. See how each one puts it to work.

Physical AI

Self-serve GPUs and multi-node clusters for training robot foundation models and running RL in simulation.

Self-serve GPUs for academic labs: no procurement wait, reproducible environments, storage built for research that moves in bursts.

Full-stack multi-node clusters for pretraining and RL post-training of foundation models: MoE and 100B+ parameter runs, scaled to 1,000+ GPUs.

However your team works, it runs on the same self-serve GPUs, multi-node clusters, and storage.

Spin up GPUs the moment you need them, and release them when the run ends.

$1.39/hr

A100 SXM, self-serve

Per-second

billing, pay as you go

When one node isn't enough, scale to InfiniBand-wired clusters with full root access.

8 per node

H100 to Blackwell

400 Gbps

NDR InfiniBand

Keep hundreds of terabytes on Object Storage, and share files fast across concurrent jobs.

$0.03

per GiB-month, cold tier

Read-write-many

shared across workloads

Root SSH

on every cluster node

SOC 2 Type II

security compliance