> ## Documentation Index
> Fetch the complete documentation index at: https://friendli.ai/docs/llms.txt
> Use this file to discover all available pages before exploring further.

# Reserve GPUs

> Reserve GPU capacity on Friendli Suite for a set period, deploy endpoints on your reserved GPUs, then extend or shut them down before the reservation ends.

With [Friendli Dedicated Endpoints](/docs/guides/dedicated-endpoints/introduction), you can deploy any model on dedicated GPUs reserved for you. Reserve them ahead of time at a fixed price for a set period of time. When that period ends, FriendliAI reclaims the GPUs.

To understand how reservations are billed, see the following table:

| Charge                           | How It's Billed                                                                                                                                                                                              |
| -------------------------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------ |
| Your reservation                 | A flat fee, paid upfront, for the GPU type, count, and period you commit to.                                                                                                                                 |
| GPU time within your reservation | Not billed. Your reservation covers it.                                                                                                                                                                      |
| GPU time beyond your reservation | Billed per second at [on-demand rates](/docs/guides/dedicated-endpoints/pricing#supported-instance-types). Prepaid teams buy credits upfront, and postpaid teams pay as the overage accumulates on their balance. |

You must be a team owner or admin to reserve GPUs. To reserve GPUs, complete the following steps:

<Steps>
  <Step title="Sign In to Your Friendli Suite Account">
    If you haven't already, [sign in](https://auth.friendli.ai). Friendli Suite opens your dashboard.
  </Step>

  <Step title="Open the GPUs Tab">
    In the left sidebar, click <Icon icon="gear" size={12} /> **Settings**. Then, under **Team Settings**, click **[Reserved GPUs](https://friendli.ai/suite/~/setting/reserved-gpus/gpus)**. Friendli Suite opens the **Reserved GPUs** > **GPUs** tab.
  </Step>

  <Step title="Request GPUs">
    1. On the **GPUs** tab, find an in-stock option.
    2. Click **Request**. Friendli Suite opens the request form.
    3. Choose the number of days you want to reserve the GPUs.
    4. Choose when you want to start your reservation.
    5. Click **Submit**.

    FriendliAI reviews your request. To track its status, open the **Reserved GPUs** > **[My Reservations](https://friendli.ai/suite/~/setting/reserved-gpus/my-reservations)** tab.

    If you don't see an option that works for you, click **Get a custom quote** and complete the request form.
  </Step>

  <Step title="Pay for Your Reservation">
    If FriendliAI approves your request, pay with the payment method on file. To add or change a payment method, see [Billing and Payments](/docs/guides/suite/billing-payments#managing-payment-methods).

    Once your payment is confirmed, Friendli Suite assigns the capacity to your team, and you can use it from your chosen start date.
  </Step>

  <Step title="Deploy to Your Reserved GPUs">
    Create an endpoint and set its **[Instance type](/docs/guides/dedicated-endpoints/endpoints#what-you-can-configure)** to the GPU type and count you reserved. Your reservation covers the endpoint's GPU time.

    To learn more, see [QuickStart: Friendli Dedicated Endpoints](/docs/guides/dedicated-endpoints/quickstart).
  </Step>
</Steps>

Before your reservation ends, extend it or shut down the endpoints you no longer need. Otherwise, FriendliAI chooses which of your endpoints to scale down.