> For the complete documentation index, see [llms.txt](https://run-ai-docs.nvidia.com/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://run-ai-docs.nvidia.com/self-hosted/resources/videos/how-to-allocate-gpu-resources-across-teams.md).

# How to Allocate GPU Resources Across Teams

## Resource Management Across Teams

Learn how NVIDIA Run:ai helps teams share GPU resources efficiently across departments and projects.

{% embed url="<https://www.youtube.com/watch?v=UFArO8_aAYw>" %}

{% hint style="info" %}
**Note**

This video was recorded using NVIDIA Run:ai version 2.24.18. The user interface, features, and workflows may differ in newer releases. For the latest information, refer to the current documentation.
{% endhint %}

### What You'll Learn:

* Configure quotas for departments and projects
* Set workload priorities across teams
* Allocate GPU resources fairly
* Improve cluster utilization
* Maintain governance across shared infrastructure
* Support operational flexibility for AI workloads


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