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Gradient Clusters

Gradient Clusters or Gradient Private Clusters are an enterprise-tier feature for organizations that require a private cloud to run Gradient Resources.


Gradient clusters are private clusters that run machine learning workloads. Gradient clusters can be created on Paperspace Cloud, on any other cloud provider (AWS, GCP, Azure), or on your own servers via the Cluster Installer.

Find out more about Gradient's multi-cloud capabilities here.

You can create a managed cluster using the Web UI in a couple of clicks.

Choosing between our managed service, managed private clusters, and self-hosting Gradient

Infrastructure:Shared, managed by PaperspacePrivate, managed by PaperspacePrivate, self-hosted
Setup time:NoneSetup time: 10 minutesSetup time: 20-30 minutes
Target audience:Hobbyists & studentsStartups & SMBs running production workloadsMid-market & enterprise businesses conducting ML at scale

This section of our documentation covers the private cluster options. If you are looking to use our managed service, just create an account to get started right away.

Cluster pricing

Managed Service

We charge per hour for compute time on paid instances (see free machines). Optionally, you can upgrade your subscription to access higher concurrency and additional features.

Managed Private Clusters

Compute, Storage, & Networking

The Kubernetes master node, storage, and networking cost to run the cluster is $0.12/hr. Private Clusters require a minimum of one CPU node for cluster orchestration and clusters include 500GB of storage by default.

In addition, instances used to run workloads are charged at the regular rate (see instance pricing) plus a small compute premium.


Compute, Storage, & Networking

Customers are responsible for their infrastructure costs. Gradient does not bill for any compute, storage, and networking costs other than the compute premium.


Gradient Private Clusters require an Essentials or greater subscription.