# Overview

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This section of the documentation covers our previous generation of Gradient. For the current version go to [Gradient Next](https://docs.paperspace.com/gradient).
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Gradient clusters are private clusters that run machine learning workloads. Gradient clusters can be [created](setup/managed-installation) on Paperspace Cloud, on any other cloud provider (AWS, GCP, Azure), or on your own servers via the [Gradient Installer](setup/self-hosted-clusters).

Find out more about Gradient's multi-cloud capabilities [here](https://gradient.paperspace.com/clusters).

You can [create a managed cluster ](https://console.paperspace.com/clusters/create)using the Web UI in a couple of clicks.

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

|                      | Managed Service (multi-tenant)                                                                    | Managed Private Clusters                                                     | Self-Hosted Clusters                                                         |
| -------------------- | ------------------------------------------------------------------------------------------------- | ---------------------------------------------------------------------------- | ---------------------------------------------------------------------------- |
| **Infrastructure:**  | Shared, managed by Paperspace                                                                     | Private, managed by Paperspace                                               | Private, self-hosted                                                         |
| **Setup time:**      | None                                                                                              | Setup time: 10 minutes                                                       | Setup time: 20-30 minutes                                                    |
| **Features:**        | Notebooks (including [Free GPUs](../instances/instance-types/free-instances)!), basic experiments | 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](https://console.paperspace.com/signup?gradient=true) to get started right away.

## Cluster pricing

### Managed

**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](../instances/instance-types)) plus a small [compute premium](https://gradient.paperspace.com/private-cluster-utilization-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](https://gradient.paperspace.com/private-cluster-utilization-premium).

**Subscription**\
Gradient Private Clusters require a Essentials or great [subscription](https://gradient.paperspace.com/pricing).
