#
Storage Regions on the Hub

> This feature is part of the Team & Enterprise plans.

Regions allow you to specify where your organization’s models, datasets and Spaces are stored. For non-Enterprise Hub users, repositories are always stored in the US.

This offers two key benefits:

- Regulatory and legal compliance
- Performance (faster download/upload speeds and lower latency)

Currently available regions:

- US 🇺🇸
- EU 🇪🇺
- Coming soon: Asia-Pacific 🌏

##
Getting started with Storage Regions

Organizations subscribed to Enterprise Hub can access the Regions settings page to manage their repositories storage locations.

This page displays:

- An audit of your organization’s repository locations
- Options to select where new repositories will be stored

> Some advanced compute options for Spaces, such as ZeroGPU, may not be available in all regions.

##
Repository Tag

Any repository (model or dataset) stored in a non-default location displays its Region as a tag, allowing organization members to quickly identify repository locations.

##
Regulatory and legal compliance

Regulated industries often require data storage in specific regions.

For EU companies, you can use the Hub for ML development in a GDPR-compliant manner, with datasets, models and inference endpoints stored in EU data centers.

##
Performance

Storing models and datasets closer to your team and infrastructure significantly improves performance for both uploads and downloads.

This impact is substantial given the typically large size of model weights and dataset files.

For example, European users storing repositories in the EU region can expect approximately 4-5x faster upload and download speeds compared to US storage.

##
Spaces

Both Spaces’s storage and runtime use the chosen region.

Available hardware configurations vary by region, and some features may not be available in all regions, like persistent storage associated to a Space.

Update on GitHub