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Merge pull request #4455 from aahill/ptu-apr-2
updating PTU
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articles/ai-services/openai/concepts/models.md

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| Model ID | Description | Context Window | Max Output Tokens | Training Data (up to) |
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| --- | :--- |:--- |:---|:---: |
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| `gpt-4.1` (2025-04-14) | - Text & image input <br> - Text output <br> - Chat completions API <br>- Responses API <br> - Streaming <br> - Function calling <br> Structured outputs (chat completions) | 1,047,576 | 32,768 | May 31, 2024 |
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| `gpt-4.1` (2025-04-14) | - Text & image input <br> - Text output <br> - Chat completions API <br>- Responses API <br> - Streaming <br> - Function calling <br> Structured outputs (chat completions) | - 1,047,576 <br> - 128,000 (provisioned managed deployments) | 32,768 | May 31, 2024 |
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| `gpt-4.1-nano` (2025-04-14) <br><br> **Fastest 4.1 model** | - Text & image input <br> - Text output <br> - Chat completions API <br>- Responses API <br> - Streaming <br> - Function calling <br> Structured outputs (chat completions) | 1,047,576 | 32,768 | May 31, 2024 |
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| `gpt-4.1-mini` (2025-04-14) | - Text & image input <br> - Text output <br> - Chat completions API <br>- Responses API <br> - Streaming <br> - Function calling <br> Structured outputs (chat completions) | 1,047,576 | 32,768 | May 31, 2024 |
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articles/ai-services/openai/concepts/provisioned-throughput.md

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description: Learn about provisioned throughput and Azure OpenAI.
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ms.service: azure-ai-openai
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ms.topic: conceptual
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ms.date: 03/31/2025
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ms.date: 04/30/2025
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manager: nitinme
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author: aahill #ChrisHMSFT
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ms.author: aahi #chrhoder

articles/ai-services/openai/how-to/provisioned-throughput-onboarding.md

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> Charges for deployments on a deleted resource will continue until the resource is purged. To prevent this, delete a resource’s deployment before deleting the resource. For more information, see [Recover or purge deleted Azure AI services resources](../../recover-purge-resources.md).
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## How much throughput per PTU you get for each model
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The amount of throughput (measured in tokens per minute or TPM) a deployment gets per PTU is a function of the input and output tokens in a given minute.
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Generating output tokens requires more processing than input tokens. For the models specified in the table below, 1 output token counts as 3 input tokens towards your TPM-per-PTU limit. The service dynamically balances the input & output costs, so users do not have to set specific input and output limits. This approach means your deployment is resilient to fluctuations in the workload.
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To help with simplifying the sizing effort, the following table outlines the TPM-per-PTU for the specified models. To understand the impact of output tokens on the TPM-per-PTU limit, use the 3 input token to 1 output token ratio.
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For a detailed understanding of how different ratios of input and output tokens impact the throughput your workload needs, see the [Azure OpenAI capacity calculator](https://ai.azure.com/resource/calculator). The table also shows Service Level Agreement (SLA) Latency Target Values per model. For more information about the SLA for Azure OpenAI Service, see the [Service Level Agreements (SLA) for Online Services page](https://www.microsoft.com/licensing/docs/view/Service-Level-Agreements-SLA-for-Online-Services?lang=1)
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|Topic| **gpt-4o** | **gpt-4o-mini** | **o1**|
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| --- | --- | --- | --- |
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|Global & data zone provisioned minimum deployment|15|15|15|
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|Global & data zone provisioned scale increment|5|5|5|
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|Regional provisioned minimum deployment|50|25|50|
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|Regional provisioned scale increment|50|25|50|
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|Input TPM per PTU |2,500|37,000|230|
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|Latency Target Value |25 Tokens Per Second|33 Tokens Per Second|25 Tokens Per Second|
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The amount of throughput (measured in tokens per minute or TPM) a deployment gets per PTU is a function of the input and output tokens in a given minute. Generating output tokens requires more processing than input tokens.  Starting with GPT 4.1 models and later, the system matches the global standard price ratio between input and output tokens. Cached tokens are deducted 100% from the utilization.
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For example, for `gpt-4.1:2025-04-14`, 1 output token counts as 4 input tokens towards your utilization limit which matches the [pricing](https://azure.microsoft.com/pricing/details/cognitive-services/openai-service/). Older models use a different ratio and for a deeper understanding on how different ratios of input and output tokens impact the throughput your workload needs, see the [Azure OpenAI capacity calculator](https://ai.azure.com/resource/calculator).
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|Topic| **gpt-4o** | **gpt-4o-mini** | **o1**| gpt-4.1 |
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| --- | --- | --- | --- | --- |
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|Global & data zone provisioned minimum deployment|15|15|15|15 |
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|Global & data zone provisioned scale increment|5|5|5| 5 |
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|Regional provisioned minimum deployment|50|25|50| 50 |
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|Regional provisioned scale increment|50|25|50| 50 |
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|Input TPM per PTU |2,500|37,000|230| 3000 |
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|Latency Target Value |25 Tokens Per Second|33 Tokens Per Second|25 Tokens Per Second| 44 Tokens Per Second |
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For a full list, see the [Azure OpenAI Service in Azure AI Foundry portal calculator](https://ai.azure.com/resource/calculator).
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articles/ai-services/openai/includes/model-matrix/provisioned-global.md

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ms.service: azure-ai-openai
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ms.topic: include
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ms.custom: references_regions
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ms.date: 05/01/2025
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---
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| **Region** | **o3-mini**, **2025-01-31** | **o1**, **2024-12-17** | **gpt-4o**, **2024-05-13** | **gpt-4o**, **2024-08-06** | **gpt-4o**, **2024-11-20** | **gpt-4o-mini**, **2024-07-18** |
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| **Region** | **gpt-4.1**, **2025-04-14** | **o3-mini**, **2025-01-31** | **o1**, **2024-12-17** | **gpt-4o**, **2024-05-13** | **gpt-4o**, **2024-08-06** | **gpt-4o**, **2024-11-20** | **gpt-4o-mini**, **2024-07-18** |
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|:-------------------|:---------------------------:|:---------------------------:|:----------------------:|:--------------------------:|:--------------------------:|:--------------------------:|:-------------------------------:|
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