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 Gradient Installer.
Find out more about Gradient's multi-cloud capabilities here.
Notebooks, experiments, deployments, model repo, data management, GradientCI
Notebooks, experiments, deployments, model repo, data management, GradientCI
Target audience:
Hobbyists & students
Startups & SMBs running production workloads
Mid-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 our free tier). 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.
Self-Hosted
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.
Subscription
Gradient Private Clusters require an Essentials or great subscription.