Add initial details for 4.1 and 4.1-mini.

Author: voutilad

articles/ai-services/openai/how-to/fine-tuning-deploy.md

@@ -370,15 +370,15 @@ Azure OpenAI fine-tuning supports the following deployment types.
 
 | Models | Region |
 |--|--|
+|GPT-4.1-finetune|East US2, North Central US, and Sweden Central|
+|GPT-4.1-mini-finetune|East US2, North Central US, and Sweden Central|
 |GPT-4o-finetune|East US2, North Central US, and Sweden Central|
 |GPT-4o-mini-finetune|East US2, North Central US, and Sweden Central|
 
 [Global standard](./deployment-types.md#global-standard) fine-tuned deployments offer [cost savings](https://azure.microsoft.com/pricing/details/cognitive-services/openai-service/), but custom model weights may temporarily be stored outside the geography of your Azure OpenAI resource.
 
 :::image type="content" source="../media/fine-tuning/global-standard.png" alt-text="Screenshot of the global standard deployment user experience with a fine-tuned model." lightbox="../media/fine-tuning/global-standard.png":::
 
-Global Standard fine-tuned deployments currently support structured outputs only on GPT-4o.
-
 ### Provisioned Managed (preview)
 
 | Models | Region |
@@ -391,8 +391,6 @@ Global Standard fine-tuned deployments currently support structured outputs only
 
 [Provisioned managed](./deployment-types.md#provisioned) fine-tuned deployments offer [predictable performance](../concepts/provisioned-throughput.md) for fine-tuned deployments. As part of public preview, provisioned managed deployments may be created regionally via the data-plane [REST API](../reference.md#data-plane-inference) version `2024-10-01` or newer. See below for examples.
 
-Provisioned Managed fine-tuned deployments currently support structured outputs only on GPT-4o.
-
 #### Creating a Provisioned Managed deployment
 
 To create a new deployment, make an HTTP PUT call via the [Deployments - Create or Update REST API](/rest/api/aiservices/accountmanagement/deployments/create-or-update?view=rest-aiservices-accountmanagement-2024-10-01&tabs=HTTP&preserve-view=true). The approach is similar to performing [cross region deployment](#cross-region-deployment) with the following exceptions:

articles/ai-services/openai/includes/fine-tune-models.md

@@ -20,4 +20,6 @@ manager: nitinme
 | `gpt-35-turbo` (1106) | East US2 <br> North Central US <br> Sweden Central <br> Switzerland West | Input: 16,385<br> Output: 4,096 |  Sep 2021|
 | `gpt-35-turbo` (0125)  | East US2 <br> North Central US <br> Sweden Central <br> Switzerland West | 16,385 | Sep 2021 |
 | `gpt-4o-mini` (2024-07-18) | North Central US <br> Sweden Central | Input: 128,000 <br> Output: 16,384  <br> Training example context length: 64,536 | Oct 2023 |
-| `gpt-4o` (2024-08-06) | East US2 <br> North Central US <br> Sweden Central | Input: 128,000 <br> Output: 16,384  <br> Training example context length: 64,536 | Oct 2023 | 
+| `gpt-4o` (2024-08-06) | East US2 <br> North Central US <br> Sweden Central | Input: 128,000 <br> Output: 16,384  <br> Training example context length: 64,536 | Oct 2023 |
+| `gpt-4.1` (2025-04-14) | North Central US <br> Sweden Central | Input: 128,000 <br> Output: 32,768 <br> Training example context length: 64,536 | May 2024 |
+| `gpt-4.1-mini` (2025-04-14) | North Central US <br> Sweden Central | Input: 128,000 <br> Output: 32,768 <br> Training example context length: 64,536 | May 2024 |