Compute
From a single GPU to a cluster
Provision exactly what a job needs and tear it down when you're done.
Hourly GPU instances
Launch single-GPU or multi-GPU pods with SSH, Jupyter, and a browser terminal.
Multi-replica clusters
Scale to multiple replicas for distributed training or multi-node serving, managed from one panel.
Web terminal
Drop into a shell from any browser — no SSH key required.
File upload
Upload files straight into your pod from the console.
Auto-expiry protection
Set a duration and instances stop automatically, so you never get a surprise bill.
Up to 96GB VRAM
Professional server GPUs in 1, 2, 4, or 8-GPU configurations.
At a glance
Configurations
- GPUs per instance
- 1 / 2 / 4 / 8
- Memory
- Up to 96GB VRAM
- Billing
- Per GPU-hour
Storage
Persistent storage that travels with your work
Keep datasets and model weights close to the GPUs. Storage outlives any single instance and reattaches on demand.
Cloud Drive
Block storage (read-write-once) for a single instance — a durable workspace that survives restarts.
Shared Filesystem
CephFS-backed shared storage (read-write-many) mounted across replicas — ideal for datasets and model weights.
Seamless mounts
Attach storage to any GPU instance; your first drive mounts automatically.
5-day grace period
Suspended storage stays readable for five days, so you can download your data before it is removed.