Paperspace vs Spheron

Interactive Jupyter notebooks with a free tier, pre-configured templates, and access to powerful GPUs.

Serve machine learning models as scalable API endpoints.

High-performance virtual machines with a wide variety of NVIDIA GPUs for demanding workloads.

Features for teams to collaborate on projects, including shared drives and SSO.

Offers persistent storage that can be shared across different machines and notebooks.

Programmatic access to the Paperspace platform to automate workflows.

Access GPU capacity from multiple cloud providers and certified data centers from one account, without separate signups per provider

Instances are billed by the minute rather than rounded up to the hour, past a 20-minute minimum runtime (60 minutes for a 2x AMD MI300X)

NVIDIA instances are typically ready in under two minutes with no approval workflow or provisioning queue

Compute spend across every connected provider is tracked in a single dashboard

Each VM or bare metal instance includes NVMe SSD storage, network bandwidth and full root access, with a dedicated IP on NVIDIA instances

Spheron sources large clusters, specific hardware and InfiniBand configurations from its partner data center network, with a typical quote turnaround of 24-48 hours