Merge pull request #6955 from MicrosoftDocs/main

Auto Publish – main to live - 2025-09-05 17:01 UTC

Author: learn-build-service-prod[bot]

articles/ai-foundry/concepts/foundry-models-overview.md

@@ -7,7 +7,7 @@ ms.custom:
   - build-2025
   - ai-learning-hub
 ms.topic: how-to
-ms.date: 07/06/2025
+ms.date: 09/04/2025
 ms.reviewer: jcioffi
 ms.author: ssalgado
 manager: nitinme
@@ -20,34 +20,37 @@ Azure AI Foundry Models is your one-stop destination for discovering, evaluating
 
 With Foundry Models, you can: 
 
-* Explore a rich catalog of cutting-edge models from Microsoft, OpenAI, DeepSeek,  Hugging Face, Meta, and more. 
+* Explore a rich catalog of cutting-edge models from Microsoft, OpenAI, DeepSeek, Hugging Face, Meta, and more. 
 * Compare and evaluate models side-by-side using real-world tasks and your own data. 
 * Deploy with confidence, thanks to built-in tools for fine-tuning, observability, and responsible AI. 
 * Choose your path—bring your own model, use a hosted one, or integrate seamlessly with Azure services. 
-* Whether you're a developer, data scientist, or enterprise architect, Foundry Models gives you the flexibility and control to build AI solutions that scale—securely, responsibly, and fast.
+* Whether you're a developer, data scientist, or enterprise architect, Foundry Models gives you the flexibility and control to build AI solutions that scale—securely, responsibly, and fast. 
 
-Azure AI Foundry offers a comprehensive catalog of AI models. There are over 1900+ models ranging from Foundation Models, Reasoning Models, Small Language Models, Multimodal Models, Domain Specific Models, Industry Models and more.
+Azure AI Foundry offers a comprehensive catalog of AI models. There are over 1900+ models ranging from Foundation Models, Reasoning Models, Small Language Models, Multimodal Models, Domain Specific Models, Industry Models and more. 
 
 Our catalog is organized into two main categories: 
 
 * [Models sold directly by Azure](#models-sold-directly-by-azure)
 * [Models from Partners and Community](#models-from-partners-and-community)
 
 Understanding the distinction between these categories helps you choose the right models based on your specific requirements and strategic goals. 
+
+> [!NOTE]
+> * For all models, Customers remain responsible for (i) complying with the law in their use of any model or system; (ii) reviewing model descriptions in the model catalog, model cards made available by the model provider, and other relevant documentation; (iii) selecting an appropriate model for their use case, and (iv) implementing appropriate measures (including use of Azure AI Content Safety) to ensure Customer's use of the Microsoft AI Services complies with the Acceptable Use Policy in Microsoft’s Product Terms and the Microsoft Enterprise AI Services Code of Conduct. 
  
 ## Models Sold Directly by Azure 
 
-These are models that are hosted and sold by Microsoft under Microsoft Product Terms. These models have undergone rigorous evaluation and are deeply integrated into Azure's AI ecosystem. The models come from a variety of top providers and they offer enhanced integration, optimized performance, and direct Microsoft support, including enterprise-grade Service Level Agreements (SLAs).
+These are models that are hosted and sold by Microsoft under Microsoft Product Terms. Microsoft has evaluated these models and they are deeply integrated into Azure's AI ecosystem. The models come from a variety of providers and they offer enhanced integration, optimized performance, and direct Microsoft support, including enterprise-grade Service Level Agreements (SLAs).
 
 Characteristics of models sold directly by Azure: 
 
-- Official first-party support from Microsoft 
-- High level of integration with Azure services and infrastructure 
-- Extensive performance benchmarking and validation 
-- Adherence to Microsoft's Responsible AI standards 
-- Enterprise-grade scalability, reliability, and security
+- Support available from Microsoft.
+- High level of integration with Azure services and infrastructure. 
+- Subject to internal review based on Microsoft’s Responsible AI standards.
+- Model documentation and transparency reports provide customer visibility to model risks, mitigations, and limitations. 
+- Enterprise-grade scalability, reliability, and security. 
 
-These Models also have the benefit of fungible Provisioned Throughput, meaning you can flexibly use your quota and reservations across any of these models.
+Some of these Models also have the benefit of fungible Provisioned Throughput, meaning you can flexibly use your quota and reservations across any of these models.
 
 ## Models from Partners and Community
 

articles/ai-foundry/foundry-models/concepts/content-filter.md

@@ -6,7 +6,8 @@ author: ssalgadodev
 ms.author: ssalgado
 ms.reviewer: yinchang
 reviewer: ychang-msft
-ms.service: azure-ai-model-inference
+ms.service: azure-ai-foundry
+ms.subservice: azure-ai-foundry-model-inference
 ms.topic: concept-article
 ms.date: 08/29/2025
 ms.custom: ignite-2024, github-universe-2024

articles/ai-foundry/foundry-models/concepts/default-safety-policies.md

@@ -6,7 +6,8 @@ author: ssalgadodev
 ms.author: ssalgado
 ms.reviewer: yinchang
 reviewer: ychang-msft
-ms.service: azure-ai-model-inference
+ms.service: azure-ai-foundry
+ms.subservice: azure-ai-foundry-model-inference
 ms.topic: concept-article
 ms.date: 08/29/2025
 ai-usage: ai-assisted

articles/ai-foundry/foundry-models/concepts/deployment-types.md

@@ -3,7 +3,8 @@ title: Understanding deployment types in Azure AI Foundry Models
 titleSuffix: Azure AI Foundry
 description: Learn how to use deployment types in Azure AI model deployments
 author: msakande
-ms.service: azure-ai-model-inference
+ms.service: azure-ai-foundry
+ms.subservice: azure-ai-foundry-model-inference
 ms.topic: how-to
 ms.date: 08/15/2025
 ms.author: mopeakande

articles/ai-foundry/foundry-models/concepts/endpoints.md

@@ -3,7 +3,8 @@ title: Endpoints for Azure AI Foundry Models
 titleSuffix: Azure AI Foundry
 description: Learn how to access and use Azure AI Foundry Models endpoints for secure model inference, flexible deployments, and keyless authentication.
 author: msakande
-ms.service: azure-ai-model-inference
+ms.service: azure-ai-foundry
+ms.subservice: azure-ai-foundry-model-inference
 ms.topic: how-to
 ms.date: 08/25/2025
 ms.author: mopeakande

articles/ai-foundry/foundry-models/concepts/model-versions.md

@@ -2,7 +2,8 @@
 title: Model versions in Azure AI Foundry Models
 titleSuffix: Azure AI Foundry
 description: Learn about model versions in Foundry Models.
-ms.service: azure-ai-model-inference
+ms.service: azure-ai-foundry
+ms.subservice: azure-ai-foundry-model-inference
 ms.topic: concept-article
 ms.custom: ignite-2024, github-universe-2024
 ms.date: 08/15/2025

articles/ai-foundry/foundry-models/concepts/models.md

@@ -7,7 +7,8 @@ ms.author: mopeakande
 reviewer: santiagxf
 ms.reviewer: fasantia
 ms.date: 09/03/2025
-ms.service: azure-ai-model-inference
+ms.service: azure-ai-foundry
+ms.subservice: azure-ai-foundry-model-inference
 ms.topic: how-to
 ms.custom:
   - references_regions
@@ -101,14 +102,15 @@ See [the Mistral model collection in Azure AI Foundry portal](https://ai.azure.c
 
 ### xAI models sold directly by Azure
 
-xAI's Grok 3 and Grok 3 Mini models excel in various enterprise domains. 
+xAI's Grok models in Azure AI Foundry Models include a diverse set of models designed to excel in various enterprise domains with different capabilities and price points, including: 
 
-Grok 3 is a non-reasoning model pretrained by the Colossus datacenter. It's tailored for business use cases such as data extraction, coding, and text summarization, with exceptional instruction-following capabilities. It supports a 131,072 token context window, so it can handle extensive inputs while maintaining coherence and depth. It's adept at drawing connections across domains and languages. 
-
-On the other hand, Grok 3 Mini is a lightweight reasoning model trained to tackle agentic, coding, mathematical, and deep science problems with test-time compute. It also supports a 131,072 token context window for understanding codebases and enterprise documents. It excels at using tools to solve complex logical problems in novel environments, offering raw reasoning traces for user inspection with adjustable thinking budgets.
+- Grok 3, a non-reasoning model pretrained by the Colossus datacenter, is tailored for business use cases such as data extraction, coding, and text summarization, with exceptional instruction-following capabilities. It supports a 131,072 token context window, allowing it to handle extensive inputs while maintaining coherence and depth, and is adept at drawing connections across domains and languages.
+- Grok 3 Mini is a lightweight reasoning model trained to tackle agentic, coding, mathematical, and deep science problems with test-time compute. It also supports a 131,072 token context window for understanding codebases and enterprise documents, and excels at using tools to solve complex logical problems in novel environments, offering raw reasoning traces for user inspection with adjustable thinking budgets. 
+- Grok Code Fast 1, a fast and efficient reasoning model designed for use in agentic coding applications. It was pre-trained on a coding-focused data mixture, then post-trained on demonstrations of various coding tasks and tool use as well as demonstrations of correct refusal behaviors based on xAI’s safety policy. Learn more about Grok Code Fast 1’s capabilities, risks, and limitations, in the model card [here](https://ai.azure.com/explore/models/grok-code-fast-1/version/1/registry/azureml-xa). 
 
 | Model  | Type | Capabilities | Deployment type (region availability) | Project type |
 | ------ | ---- | ------------ | ------------------------------------- | ------------ |
+| [grok-code-fast-1](https://ai.azure.com/explore/models/grok-code-fast-1/version/1/registry/azureml-xa) | chat-completion | - **Input:** text (256,000 tokens) <br /> - **Output:** text (8,192 tokens) <br /> - **Languages:** `en` <br />  - **Tool calling:** yes <br /> - **Response formats:** text |- Global standard (all regions)  | Foundry, Hub-based |
 | [grok-3](https://ai.azure.com/explore/models/grok-3/version/1/registry/azureml-xai) | chat-completion | - **Input:** text (131,072 tokens) <br /> - **Output:** text (131,072 tokens) <br /> - **Languages:** `en` <br />  - **Tool calling:** yes <br /> - **Response formats:** text |- Global standard (all regions) <br> - Data zone standard (US) | Foundry, Hub-based |
 | [grok-3-mini](https://ai.azure.com/explore/models/grok-3-mini/version/1/registry/azureml-xai) | chat-completion | - **Input:** text (131,072 tokens) <br /> - **Output:** text (131,072 tokens) <br /> - **Languages:** `en` <br />  - **Tool calling:** yes <br /> - **Response formats:** text | - Global standard (all regions) <br> - Data zone standard (US) | Foundry, Hub-based |
 

articles/ai-foundry/foundry-models/faq.yml

@@ -3,9 +3,9 @@ metadata:
   title: Azure AI Foundry Models frequently asked questions
   titleSuffix: Azure AI Foundry
   description: Get answers to the most popular questions about Foundry Models
-  #services: cognitive-services
   manager: nitinme
-  ms.service: azure-ai-model-inference
+  ms.service: azure-ai-foundry
+  ms.subservice: azure-ai-foundry-model-inference
   ms.topic: faq
   ms.date: 1/21/2025
   ms.author: fasantia

articles/ai-foundry/foundry-models/how-to/configure-content-filters.md

@@ -2,7 +2,8 @@
 title: 'How to configure content filters for models in Azure AI Foundry'
 titleSuffix: Azure AI Foundry
 description: Learn to use and configure the content filters that come with Azure AI Foundry, including getting approval for gated modifications.
-ms.service: azure-ai-model-inference
+ms.service: azure-ai-foundry
+ms.subservice: azure-ai-foundry-model-inference
 ms.topic: how-to
 ms.date: 08/29/2025
 author: ssalgadodev

articles/ai-foundry/foundry-models/how-to/configure-entra-id.md

@@ -2,7 +2,8 @@
 title: Configure key-less authentication with Microsoft Entra ID
 titleSuffix: Azure AI Foundry
 description: Learn how to configure key-less authorization to use Azure AI Foundry Models with Microsoft Entra ID.
-ms.service: azure-ai-model-inference
+ms.service: azure-ai-foundry
+ms.subservice: azure-ai-foundry-model-inference
 ms.topic: how-to
 ms.date: 08/29/2025
 ms.custom: ignite-2024, github-universe-2024