update ML docs and remove 2402 from Mistral name

Author: msakande

articles/ai-studio/how-to/model-catalog-overview.md

@@ -77,7 +77,7 @@ The following list contains Serverless API models. For Azure OpenAI models, see
 Model | Managed compute | Serverless API (pay-per-token)
 --|--|--
 Llama family models | Llama-3.2-3B-Instruct<BR>  Llama-3.2-1B-Instruct<BR>  Llama-3.2-1B<BR>  Llama-3.2-90B-Vision-Instruct<BR>  Llama-3.2-11B-Vision-Instruct<BR>  Llama-3.1-8B-Instruct<BR>  Llama-3.1-8B<BR>  Llama-3.1-70B-Instruct<BR>  Llama-3.1-70B<BR>  Llama-3-8B-Instruct<BR>  Llama-3-70B<BR>  Llama-3-8B<BR>  Llama-Guard-3-1B<BR>  Llama-Guard-3-8B<BR>  Llama-Guard-3-11B-Vision<BR>  Llama-2-7b<BR>  Llama-2-70b<BR>  Llama-2-7b-chat<BR>  Llama-2-13b-chat<BR>  CodeLlama-7b-hf<BR>  CodeLlama-7b-Instruct-hf<BR>  CodeLlama-34b-hf<BR>  CodeLlama-34b-Python-hf<BR>  CodeLlama-34b-Instruct-hf<BR>  CodeLlama-13b-Instruct-hf<BR>  CodeLlama-13b-Python-hf<BR>  Prompt-Guard-86M<BR>  CodeLlama-70b-hf<BR> | Llama-3.2-90B-Vision-Instruct<br>  Llama-3.2-11B-Vision-Instruct<br>  Llama-3.1-8B-Instruct<br>  Llama-3.1-70B-Instruct<br>  Llama-3.1-405B-Instruct<br>  Llama-3-8B-Instruct<br>  Llama-3-70B-Instruct<br>  Llama-2-7b<br>  Llama-2-7b-chat<br>  Llama-2-70b<br>  Llama-2-70b-chat<br>  Llama-2-13b<br>  Llama-2-13b-chat<br>
-Mistral family models | mistralai-Mixtral-8x22B-v0-1 <br> mistralai-Mixtral-8x22B-Instruct-v0-1 <br> mistral-community-Mixtral-8x22B-v0-1 <br> mistralai-Mixtral-8x7B-v01 <br> mistralai-Mistral-7B-Instruct-v0-2 <br> mistralai-Mistral-7B-v01 <br> mistralai-Mixtral-8x7B-Instruct-v01 <br> mistralai-Mistral-7B-Instruct-v01 | Mistral-large (2402) <br> Mistral-large (2407) <br> Mistral-large (2411) <br> Mistral-small <br> Ministral-3B <br> Mistral-NeMo
+Mistral family models | mistralai-Mixtral-8x22B-v0-1 <br> mistralai-Mixtral-8x22B-Instruct-v0-1 <br> mistral-community-Mixtral-8x22B-v0-1 <br> mistralai-Mixtral-8x7B-v01 <br> mistralai-Mistral-7B-Instruct-v0-2 <br> mistralai-Mistral-7B-v01 <br> mistralai-Mixtral-8x7B-Instruct-v01 <br> mistralai-Mistral-7B-Instruct-v01 | Mistral-large <br> Mistral-large (2407) <br> Mistral-large (2411) <br> Mistral-small <br> Ministral-3B <br> Mistral-NeMo
 Cohere family models | Not available | Cohere-command-r-plus-08-2024 <br> Cohere-command-r-08-2024 <br> Cohere-command-r-plus <br> Cohere-command-r <br> Cohere-embed-v3-english <br> Cohere-embed-v3-multilingual <br> Cohere-rerank-v3-english <br> Cohere-rerank-v3-multilingual
 JAIS | Not available | jais-30b-chat
 AI21 family models | Not available | Jamba-1.5-Mini <br> Jamba-1.5-Large

articles/ai-studio/includes/region-availability-maas.md

@@ -60,7 +60,7 @@ Phi-3-Medium-4K-Instruct  <br>  Phi-3-Medium-128K-Instruct  | Not applicable | E
 Mistral Nemo     | [Microsoft Managed Countries](/partner-center/marketplace/tax-details-marketplace#microsoft-managed-countriesregions)  <br> Brazil <br> Hong Kong <br> Israel     | East US <br> East US 2 <br> North Central US <br> South Central US <br> Sweden Central <br> West US <br> West US 3           | Not available       |
 Ministral-3B     | [Microsoft Managed Countries](/partner-center/marketplace/tax-details-marketplace#microsoft-managed-countriesregions)   <br> Brazil <br> Hong Kong <br> Israel      | East US <br> East US 2 <br> North Central US <br> South Central US <br> Sweden Central <br> West US <br> West US 3           |  Not available       |
 Mistral Small     | [Microsoft Managed Countries](/partner-center/marketplace/tax-details-marketplace#microsoft-managed-countriesregions)   <br> Brazil <br> Hong Kong <br> Israel      | East US <br> East US 2 <br> North Central US <br> South Central US <br> Sweden Central <br> West US <br> West US 3           |  Not available       |
-Mistral Large (2402) <br>  Mistral-Large (2407) <br> Mistral-Large (2411)    | [Microsoft Managed Countries](/partner-center/marketplace/tax-details-marketplace#microsoft-managed-countriesregions)  <br> Brazil <br> Hong Kong <br> Israel    | East US <br> East US 2 <br> North Central US <br> South Central US <br> Sweden Central <br> West US <br> West US 3           | Not available       |
+Mistral Large <br>  Mistral-Large (2407) <br> Mistral-Large (2411)    | [Microsoft Managed Countries](/partner-center/marketplace/tax-details-marketplace#microsoft-managed-countriesregions)  <br> Brazil <br> Hong Kong <br> Israel    | East US <br> East US 2 <br> North Central US <br> South Central US <br> Sweden Central <br> West US <br> West US 3           | Not available       |
 
 
 

articles/machine-learning/concept-model-catalog.md

@@ -57,7 +57,7 @@ Network isolation | Managed Virtual Network with Online Endpoints. [Learn more.]
 Model | Managed compute | Serverless API (pay-as-you-go)
 --|--|--
 Llama family models  | Llama-2-7b <br> Llama-2-7b-chat <br> Llama-2-13b <br> Llama-2-13b-chat <br> Llama-2-70b <br> Llama-2-70b-chat <br> Llama-3-8B-Instruct <br> Llama-3-70B-Instruct <br> Llama-3-8B <br> Llama-3-70B | Llama-3-70B-Instruct <br> Llama-3-8B-Instruct <br> Llama-2-7b <br> Llama-2-7b-chat <br> Llama-2-13b <br> Llama-2-13b-chat <br> Llama-2-70b <br> Llama-2-70b-chat 
-Mistral family models | mistralai-Mixtral-8x22B-v0-1 <br> mistralai-Mixtral-8x22B-Instruct-v0-1 <br> mistral-community-Mixtral-8x22B-v0-1 <br> mistralai-Mixtral-8x7B-v01 <br> mistralai-Mistral-7B-Instruct-v0-2 <br> mistralai-Mistral-7B-v01 <br> mistralai-Mixtral-8x7B-Instruct-v01 <br> mistralai-Mistral-7B-Instruct-v01 | Mistral-large (2402) <br> Mistral-large (2407) <br> Mistral-small <br> Ministral-3B <br> Mistral-Nemo
+Mistral family models | mistralai-Mixtral-8x22B-v0-1 <br> mistralai-Mixtral-8x22B-Instruct-v0-1 <br> mistral-community-Mixtral-8x22B-v0-1 <br> mistralai-Mixtral-8x7B-v01 <br> mistralai-Mistral-7B-Instruct-v0-2 <br> mistralai-Mistral-7B-v01 <br> mistralai-Mixtral-8x7B-Instruct-v01 <br> mistralai-Mistral-7B-Instruct-v01 | Mistral-large <br> Mistral-large (2407) <br> Mistral-large (2411) <br> Mistral-small <br> Ministral-3B <br> Mistral-Nemo
 Cohere family models | Not available | Cohere-command-r-plus-08-2024 <br> Cohere-command-r-08-2024 <br> Cohere-command-r-plus <br> Cohere-command-r <br> Cohere-embed-v3-english <br> Cohere-embed-v3-multilingual <br> Cohere-rerank-v3-english <br> Cohere-rerank-v3-multilingual
 JAIS | Not available | jais-30b-chat
 Phi-3 family models | Phi-3-mini-4k-Instruct <br> Phi-3-mini-128k-Instruct <br> Phi-3-small-8k-Instruct <br> Phi-3-small-128k-Instruct <br> Phi-3-medium-4k-instruct <br> Phi-3-medium-128k-instruct <br> Phi-3-vision-128k-Instruct <br> Phi-3.5-mini-Instruct <br> Phi-3.5-vision-Instruct <br> Phi-3.5-MoE-Instruct | Phi-3-mini-4k-Instruct <br> Phi-3-mini-128k-Instruct <br> Phi-3-small-8k-Instruct <br> Phi-3-small-128k-Instruct <br> Phi-3-medium-4k-instruct <br> Phi-3-medium-128k-instruct <br> <br> Phi-3.5-mini-Instruct <br> Phi-3.5-vision-Instruct <br> Phi-3.5-MoE-Instruct  

articles/machine-learning/how-to-deploy-models-mistral.md

@@ -20,7 +20,7 @@ In this article, you learn how to use Azure Machine Learning studio to deploy th
 
 Mistral AI offers two categories of models in Azure Machine Learning studio. These models are available in the [model catalog](concept-model-catalog.md).
 
-* __Premium models__: Mistral Large (2402), Mistral Large (2407), Mistral Small, and Ministral-3B. 
+* __Premium models__: Mistral Large (2402), Mistral Large (2407), Mistral Large (2411), Mistral Small, and Ministral-3B. 
 * __Open models__: Mistral Nemo, Mixtral-8x7B-Instruct-v01, Mixtral-8x7B-v01, Mistral-7B-Instruct-v01, and Mistral-7B-v01. 
 
 All the premium models and Mistral Nemo (an open model) can be deployed as serverless APIs with pay-as-you-go token-based billing. The other open models can be deployed to managed computes in your own Azure subscription.
@@ -31,24 +31,31 @@ You can browse the Mistral family of models in the model catalog by filtering on
 
 # [Mistral Large](#tab/mistral-large)
 
-Mistral Large is Mistral AI's most advanced Large Language Model (LLM). It can be used on any language-based task, thanks to its state-of-the-art reasoning and knowledge capabilities. There are two variants available for the Mistral Large model version:
+Mistral Large models are Mistral AI's most advanced Large Language Models (LLM). They can be used on any language-based task, thanks to their state-of-the-art reasoning, knowledge, and coding capabilities. Several Mistral Large model variants are available:
 
-- Mistral Large (2402)
+- Mistral Large (2402), also abbreviated as Mistral Large
 - Mistral Large (2407)
+- Mistral Large (2411)
 
-Additionally, some attributes of _Mistral Large (2402)_ include:
+Attributes of **Mistral Large (2402)**, also abbreviated as **Mistral Large**, include:
 
-- __Specialized in RAG.__ Crucial information isn't lost in the middle of long context windows (up to 32 K tokens).
-- __Strong in coding.__ Code generation, review, and comments. Supports all mainstream coding languages.
-- __Multi-lingual by design.__ Best-in-class performance in French, German, Spanish, and Italian - in addition to English. Dozens of other languages are supported.
-- __Responsible AI compliant.__ Efficient guardrails baked in the model, and extra safety layer with the `safe_mode` option.
+* **Specialized in RAG**. Crucial information isn't lost in the middle of long context windows (up to 32-K tokens).
+* **Strong in coding**. Code generation, review, and comments. Supports all mainstream coding languages.
+* **Multi-lingual by design**. Best-in-class performance in French, German, Spanish, Italian, and English. Dozens of other languages are supported.
+* **Responsible AI compliant**. Efficient guardrails baked in the model and extra safety layer with the safe_mode option.
 
-And attributes of _Mistral Large (2407)_ include:
+Attributes of **Mistral Large (2407)** include:
+
+* **Multi-lingual by design**. Supports dozens of languages, including English, French, German, Spanish, and Italian.
+* **Proficient in coding**. Trained on more than 80 coding languages, including Python, Java, C, C++, JavaScript, and Bash. Also trained on more specific languages such as Swift and Fortran.
+* **Agent-centric**. Possesses agentic capabilities with native function calling and JSON outputting.
+* **Advanced in reasoning**. Demonstrates state-of-the-art mathematical and reasoning capabilities.
+
+Attributes of **Mistral Large (2411)** include the same as Mistral Large (2407) with the following additional attributes:
+* System prompts are injected before each conversation.
+* Better performance on long content.
+* Improved function calling capabilities.
 
-- **Multi-lingual by design.** Supports dozens of languages, including English, French, German, Spanish, and Italian.
-- **Proficient in coding.** Trained on more than 80 coding languages, including Python, Java, C, C++, JavaScript, and Bash. Also trained on more specific languages such as Swift and Fortran.
-- **Agent-centric.** Possesses agentic capabilities with native function calling and JSON outputting.
-- **Advanced in reasoning.**  Demonstrates state-of-the-art mathematical and reasoning capabilities.
 
 
 # [Mistral Small](#tab/mistral-small)
@@ -96,7 +103,7 @@ Additionally, Mistral Nemo is:
 
 Certain models in the model catalog can be deployed as a serverless API with pay-as-you-go billing. This kind of deployment provides a way to consume models as an API without hosting them on your subscription, while keeping the enterprise security and compliance that organizations need. This deployment option doesn't require quota from your subscription.
 
-**Mistral Large (2402)**, **Mistral Large (2407)**, **Mistral Small**, and **Mistral Nemo** can be deployed as a serverless API with pay-as-you-go billing and are offered by Mistral AI through the Microsoft Azure Marketplace. Mistral AI can change or update the terms of use and pricing of these models.
+**Mistral Large**, **Mistral Large (2407)**, **Mistral Large (2411)**, **Mistral Small**, and **Mistral Nemo** can be deployed as a serverless API with pay-as-you-go billing and are offered by Mistral AI through the Microsoft Azure Marketplace. Mistral AI can change or update the terms of use and pricing of these models.
 
 
 ### Prerequisites
@@ -118,13 +125,13 @@ Certain models in the model catalog can be deployed as a serverless API with pay
 
 ### Create a new deployment
 
-The following steps demonstrate the deployment of Mistral Large (2402), but you can use the same steps to deploy Mistral Nemo or any of the premium Mistral models by replacing the model name.
+The following steps demonstrate the deployment of Mistral Large, but you can use the same steps to deploy Mistral Nemo or any of the premium Mistral models by replacing the model name.
 
 To create a deployment:
 
 1. Go to [Azure Machine Learning studio](https://ml.azure.com/home).
 1. Select the workspace in which you want to deploy your model. To use the serverless API model deployment offering, your workspace must belong to one of the regions listed in the [prerequisites](#prerequisites).
-1. Choose the model you want to deploy, for example the Mistral Large (2402) model, from the [model catalog](https://ml.azure.com/model/catalog).
+1. Choose the model you want to deploy, for example the Mistral Large model, from the [model catalog](https://ml.azure.com/model/catalog).
 
    Alternatively, you can initiate deployment by going to your workspace and selecting **Endpoints** > **Serverless endpoints** > **Create**.
 
@@ -135,7 +142,7 @@ To create a deployment:
 
 1. In the deployment wizard, select the link to **Azure Marketplace Terms** to learn more about the terms of use. 
 1. You can also select the **Pricing and terms** tab to learn about pricing for the selected model.
-1. If this is your first time deploying the model in the workspace, you have to subscribe your workspace for the particular offering (for example, Mistral Large (2402)). This step requires that your account has the **Azure AI Developer role** permissions on the Resource Group, as listed in the prerequisites. Each workspace has its own subscription to the particular Azure Marketplace offering, which allows you to control and monitor spending. Select **Subscribe and Deploy**. Currently you can have only one deployment for each model within a workspace.
+1. If this is your first time deploying the model in the workspace, you have to subscribe your workspace for the particular offering (for example, Mistral Large). This step requires that your account has the **Azure AI Developer role** permissions on the Resource Group, as listed in the prerequisites. Each workspace has its own subscription to the particular Azure Marketplace offering, which allows you to control and monitor spending. Select **Subscribe and Deploy**. Currently you can have only one deployment for each model within a workspace.
 
 1. Once you subscribe the workspace for the particular Azure Marketplace offering, subsequent deployments of the _same_ offering in the _same_ workspace don't require subscribing again. If this scenario applies to you, you'll see a **Continue to deploy** option to select.