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The new model-independent quota shows up as a quota item named **Provisioned Managed Throughput Unit**, with model and version no longer included in the name. In the Studio Quota pane, expanding the quota item still shows all of the deployments that contribute to the quota item.
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The new model-independent quota shows up as a quota item named **Provisioned Managed Throughput Unit**, with model and version no longer included in the name. In the Azure AI Foundry's quota pane, expanding the quota item still shows all of the deployments that contribute to the quota item.
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### Default quota
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## Quota as a limit
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Prior to the August update, Azure OpenAI Provisioned was only available to a few customers, and quota was allocated to maximize the ability for them to deploy and use it. With these changes, the process of acquiring quota is simplified for all users, and there is a greater likelihood of running into service capacity limitations when deployments are attempted. A new API and Studio experience are available to help users find regions where the subscription has quota and the service has capacity to support deployments of a desired model.
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Prior to the August update, Azure OpenAI Provisioned was only available to a few customers, and quota was allocated to maximize the ability for them to deploy and use it. With these changes, the process of acquiring quota is simplified for all users, and there is a greater likelihood of running into service capacity limitations when deployments are attempted. A new API and portal experience are available to help users find regions where the subscription has quota and the service has capacity to support deployments of a desired model.
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We also recommend that customers using commitments now create their deployments before creating or expanding commitments to cover them. This guarantees that capacity is available before creating a commitment and prevents over-purchase of the commitment. To support this, the restriction that prevented deployments from being created larger than their commitments has been removed. This new approach to quota, capacity availability and commitments matches what is provided under the hourly/reservation model, and the guidance to deploy before purchasing a commitment (or reservation, for the hourly model) is the same for both.
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## Managing Provisioned Throughput Commitments
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Provisioned throughput commitments are created and managed from the**Manage Commitments**menu in Azure OpenAI Studio. You can navigate to this view by selecting **Manage Commitments** from the Quota menu:
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Provisioned throughput commitments are created and managed by selecting**Management center** in the Azure AI Foundry portal's navigation menu > **Quota** > **Manage Commitments**.
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:::image type="content" source="../media/how-to/provisioned-onboarding/notifications.png" alt-text="Screenshot of commitment purchase UI with notifications." lightbox="../media/how-to/provisioned-onboarding/notifications.png":::
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## Purchase a Provisioned Throughput Commitment
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With your commitment plan ready, the next step is to create the commitments. Commitments are created manually via Azure OpenAI Studio and require the user creating the commitment to have either the [Contributor or Cognitive Services Contributor role](../how-to/role-based-access-control.md) at the subscription level.
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With your commitment plan ready, the next step is to create the commitments. Commitments are created manually via the Azure AI Foundry and require the user creating the commitment to have either the [Contributor or Cognitive Services Contributor role](../how-to/role-based-access-control.md) at the subscription level.
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For each new commitment you need to create, follow these steps:
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**Move a commitment/deployment to a new resource in the same subscription/region**
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It isn't possible in Azure OpenAI Studio to directly *move* a deployment or a commitment to a new resource. Instead, a new deployment needs to be created on the target resource and traffic moved to it. There will need to be a commitment purchased established on the new resource to accomplish this. Because commitments are charged up-front for a 30-day period, it's necessary to time this move with the expiration of the original commitment to minimize overlap with the new commitment and “double-billing” during the overlap.
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It isn't possible in Azure AI Foundry to directly *move* a deployment or a commitment to a new resource. Instead, a new deployment needs to be created on the target resource and traffic moved to it. There will need to be a commitment purchased established on the new resource to accomplish this. Because commitments are charged up-front for a 30-day period, it's necessary to time this move with the expiration of the original commitment to minimize overlap with the new commitment and “double-billing” during the overlap.
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There are two approaches that can be taken to implement this transition.
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### View and edit an existing resource
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In Azure OpenAI Studio, select **Quota** > **Provisioned** > **Manage commitments** and select a resource with an existing commitment to view/change it.
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In Azure AI Foundry, select**Management center** >**Quota** > **Provisioned** > **Manage commitments** and select a resource with an existing commitment to view/change it.
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