Merge pull request #2450 from mrbullwinkle/mrb_01_22_2025_reasoning

[Azure OpenAI] Reasoning models update

Author: prmerger-automator[bot]

articles/ai-services/openai/how-to/gpt-with-vision.md

@@ -13,17 +13,13 @@ manager: nitinme
 # Use vision-enabled chat models
 
 
-Vision-enabled chat models are large multimodal models (LMM) developed by OpenAI that can analyze images and provide textual responses to questions about them. They incorporate both natural language processing and visual understanding. The current vision-enabled models are GPT-4 Turbo with Vision, GPT-4o, and GPT-4o-mini.
+Vision-enabled chat models are large multimodal models (LMM) developed by OpenAI that can analyze images and provide textual responses to questions about them. They incorporate both natural language processing and visual understanding. The current vision-enabled models are [o1](./reasoning.md), GPT-4o, and GPT-4o-mini, GPT-4 Turbo with Vision.
 
 The vision-enabled models answer general questions about what's present in the images you upload.
 
 > [!TIP]
 > To use vision-enabled models, you call the Chat Completion API on a supported model that you have deployed. If you're not familiar with the Chat Completion API, see the [Vision-enabled chat how-to guide](/azure/ai-services/openai/how-to/chatgpt?tabs=python&pivots=programming-language-chat-completions).
 
-## GPT-4 Turbo model upgrade
-
-[!INCLUDE [GPT-4 Turbo](../includes/gpt-4-turbo.md)]
-
 ## Call the Chat Completion APIs
 
 The following command shows the most basic way to use the GPT-4 Turbo with Vision model with code. If this is your first time using these models programmatically, we recommend starting with our [GPT-4 Turbo with Vision quickstart](../gpt-v-quickstart.md). 
@@ -39,8 +35,6 @@ Send a POST request to `https://{RESOURCE_NAME}.openai.azure.com/openai/deployme
 - `Content-Type`: application/json 
 - `api-key`: {API_KEY} 
 
-
-
 **Body**: 
 The following is a sample request body. The format is the same as the chat completions API for GPT-4, except that the message content can be an array containing text and images (either a valid HTTP or HTTPS URL to an image, or a base-64-encoded image). 
 
@@ -368,6 +362,11 @@ Every response includes a `"finish_reason"` field. It has the following possible
     ```
 -->
 
+## GPT-4 Turbo model upgrade
+
+[!INCLUDE [GPT-4 Turbo](../includes/gpt-4-turbo.md)]
+
+
 ## Next steps
 
 * [Learn more about Azure OpenAI](../overview.md).

articles/ai-services/openai/how-to/reasoning.md

@@ -47,9 +47,10 @@ Once access has been granted, you'll need to create a deployment for each model.
 | **[Structured Outputs](./structured-outputs.md)** | ✅ | - | - |
 | **[Context Window](../concepts/models.md#o1-and-o1-mini-models-limited-access)** | Input: 200,000 <br> Output: 100,000 | Input: 128,000  <br> Output: 32,768 | Input: 128,000  <br> Output: 65,536 |
 | **[Reasoning effort](#reasoning-effort)** | ✅ | - | - |
-| System Messages | - | - | - |
+| **[Vision Support](./gpt-with-vision.md)** |✅ | - | - |
 | Functions/Tools | ✅  | -  |  - |
 | `max_completion_tokens` |✅ |✅ |✅ |
+| System Messages | - | - | - |
 
 **o1 series** models will only work with the `max_completion_tokens` parameter.