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

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Mistral AI offers two categories of models, namely:
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- _Premium models_: These include Mistral Large, Mistral Small, Mistral-OCR-2503, and Ministral 3B models, and are available as serverless APIs with pay-as-you-go token-based billing.
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- _Premium models_: These include Mistral Large, Mistral Small, Mistral-OCR-2503, Mistral Medium 3 (25.05), and Ministral 3B models, and are available as serverless APIs with pay-as-you-go token-based billing.
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- _Open models_: These include Mistral-small-2503, Codestral, and Mistral Nemo (that are available as serverless APIs with pay-as-you-go token-based billing), and [Mixtral-8x7B-Instruct-v01, Mixtral-8x7B-v01, Mistral-7B-Instruct-v01, and Mistral-7B-v01](../how-to/deploy-models-mistral-open.md)(that are available to download and run on self-hosted managed endpoints).
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| [Mistral-Large-2411](https://ai.azure.com/explore/models/Mistral-Large-2411/version/2/registry/azureml-mistral) | [chat-completion](../model-inference/how-to/use-chat-completions.md?context=/azure/ai-foundry/context/context) | - **Input:** text (128,000 tokens) <br /> - **Output:** text (4,096 tokens) <br /> - **Tool calling:** Yes <br /> - **Response formats:** Text, JSON |
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| [Mistral-large-2407](https://ai.azure.com/explore/models/Mistral-large-2407/version/1/registry/azureml-mistral) <br /> (deprecated) | [chat-completion](../model-inference/how-to/use-chat-completions.md?context=/azure/ai-foundry/context/context) | - **Input:** text (131,072 tokens) <br /> - **Output:** text (4,096 tokens) <br /> - **Tool calling:** Yes <br /> - **Response formats:** Text, JSON |
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| [Mistral-large](https://ai.azure.com/explore/models/Mistral-large/version/1/registry/azureml-mistral) <br /> (deprecated) | [chat-completion](../model-inference/how-to/use-chat-completions.md?context=/azure/ai-foundry/context/context) | - **Input:** text (32,768 tokens) <br /> - **Output:** text (4,096 tokens) <br /> - **Tool calling:** Yes <br /> - **Response formats:** Text, JSON |
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| [Mistral-medium-2505](https://aka.ms/aistudio/landing/mistral-medium-2505) | [chat-completion](../model-inference/how-to/use-chat-completions.md?context=/azure/ai-foundry/context/context) | - **Input:** text (128,000 tokens), image <br /> - **Output:** text (128,000 tokens) <br /> - **Tool calling:** No <br /> - **Response formats:** Text, JSON |
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| [Mistral-OCR-2503](https://aka.ms/aistudio/landing/mistral-ocr-2503) | [image to text](../how-to/use-image-models.md) | - **Input:** image or PDF pages (1,000 pages, max 50MB PDF file) <br> - **Output:** text <br /> - **Tool calling:** No <br /> - **Response formats:** Text, JSON, Markdown |
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| [Mistral-small-2503](https://aka.ms/aistudio/landing/mistral-small-2503) | [chat-completion (with images)](../model-inference/how-to/use-chat-multi-modal.md?context=/azure/ai-foundry/context/context) | - **Input:** text and images (131,072 tokens), <br> image-based tokens are 16px x 16px <br> blocks of the original images <br /> - **Output:** text (4,096 tokens) <br /> - **Tool calling:** Yes <br /> - **Response formats:** Text, JSON |
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| [Mistral-small](https://ai.azure.com/explore/models/Mistral-small/version/1/registry/azureml-mistral) | [chat-completion](../model-inference/how-to/use-chat-completions.md?context=/azure/ai-foundry/context/context) | - **Input:** text (32,768 tokens) <br /> - **Output:** text (4,096 tokens) <br /> - **Tool calling:** Yes <br /> - **Response formats:** Text, JSON |

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

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Mistral OCR 25.03 | [Microsoft Managed Countries/Regions](/partner-center/marketplace/tax-details-marketplace#microsoft-managed-countriesregions) <br> Brazil <br> Hong Kong SAR <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 |
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Mistral Nemo | [Microsoft Managed Countries/Regions](/partner-center/marketplace/tax-details-marketplace#microsoft-managed-countriesregions) <br> Brazil <br> Hong Kong SAR <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 | East US 2 <br> East US <br> North Central US <br> South Central US <br> West US <br> West US 3 |
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Mistral Small 25.03 <br> Mistral Small | [Microsoft Managed Countries/Regions](/partner-center/marketplace/tax-details-marketplace#microsoft-managed-countriesregions) <br> Brazil <br> Hong Kong SAR <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 |
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Mistral Medium 3 (25.05) | [Microsoft Managed Countries/Regions](/partner-center/marketplace/tax-details-marketplace#microsoft-managed-countriesregions) <br> Brazil <br> Hong Kong SAR <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 |
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Ministral-3B | [Microsoft Managed Countries/Regions](/partner-center/marketplace/tax-details-marketplace#microsoft-managed-countriesregions) <br> Brazil <br> Hong Kong SAR<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 | East US 2 <br> East US <br> North Central US <br> South Central US <br> West US <br> West US 3 |
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Mistral Large (2407) <br> Mistral-Large | [Microsoft Managed Countries/Regions](/partner-center/marketplace/tax-details-marketplace#microsoft-managed-countriesregions) <br> Brazil <br> Hong Kong SAR<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 |
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Mistral-Large (2411) | [Microsoft Managed Countries/Regions](/partner-center/marketplace/tax-details-marketplace#microsoft-managed-countriesregions) <br> Brazil <br> Hong Kong SAR<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 | East US 2 <br> East US <br> North Central US <br> South Central US <br> West US <br> West US 3 |

articles/ai-services/agents/concepts/model-region-support.md

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- **Standard** is offered with a global deployment option, routing traffic globally to provide higher throughput.
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- **Provisioned** is also offered with a global deployment option, allowing customers to purchase and deploy provisioned throughput units across Azure global infrastructure.
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All deployments can perform the exact same inference operations, however the billing, scale, and performance are substantially different. To learn more about Azure OpenAI deployment types see our [deployment types guide](../../openai/how-to/deployment-types.md).
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All deployments can perform the exact same inference operations, however the billing, scale, and performance are substantially different. To learn more about Azure OpenAI deployment types see [deployment types guide](../../openai/how-to/deployment-types.md).
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Azure AI Agent Service supports the following Azure OpenAI models in the listed regions.
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> [!NOTE]
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> The following table is for pay-as-you-go. For information on Provisioned Throughput Unit (PTU) availability, see [provisioned throughput](../../openai/concepts/provisioned-throughput.md) in the Azure OpenAI documentation. `GlobalStandard` customers also have access to [global standard models](../../openai/concepts/models.md#global-standard-model-availability).
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| **Region** | **gpt-4o**, **2024-11-20** | **gpt-4o**, **2024-05-13** | **gpt-4o**, **2024-08-06** | **gpt-4o-mini**, **2024-07-18** | **gpt-4**, **0613** | **gpt-4**, **1106-Preview** | **gpt-4**, **0125-Preview** | **gpt-4**, **turbo-2024-04-09** | **gpt-4-32k**, **0613** | **gpt-35-turbo**, **0613** | **gpt-35-turbo**, **1106** | **gpt-35-turbo**, **0125** | **gpt-35-turbo-16k**, **0613** |
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|:--------------|:--------------------------:|:--------------------------:|:--------------------------:|:-------------------------------:|:-------------------:|:---------------------------:|:---------------------------:|:-------------------------------:|:--------------------------:|:--------------------------:|:--------------------------:|:------------------------------:|
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| australiaeast | | - | - | - ||| -| - ||||||
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| canadaeast || - | - | - ||| -| - || - ||||
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| eastus | |||| - | - ||| - || - |||
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| eastus2 | |||| - || - || - || - |||
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| francecentral | | - | - | - ||| - | - |||| - ||
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| japaneast || - | - | - | - | - | - | - | - || - |||
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| koreacentral | - |- | - | - | - | - | - |- | - | - | - | - | - |
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| norwayeast | |- | - | - | - || - |- | - | - | - | - | - |
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| polandcentral | - | - | - | - | - | - | - | - | - | - | - | - | - |
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| southindia | | - | - | - | - || - | - | - | - ||| - |
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| swedencentral ||||||| - ||||| - ||
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| switzerlandnorth | - | - | - | - || - | - | - || - | - |||
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| uaenorth | | - | - | - | - | - | - | - | - | - | - | - | - |
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| uksouth | | - | - | - | - ||| - | - |||||
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| westus | |||| - || - || - | - ||| - |
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| westus3 | |||| - || - || - | - | - || - |
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| REGION | o1 | o3-mini | gpt-4.1, 2025-04-14 | gpt-4.1-mini, 2025-04-14 | gpt-4.1-nano, 2025-04-14 | gpt-4o, 2024-05-13 | gpt-4o, 2024-08-06 | gpt-4o, 2024-11-20 | gpt-4o-mini, 2024-07-18 | gpt-4, 0613 | gpt-4, turbo-2024-04-09 | gpt-4-32k, 0613 | gpt-35-turbo, 1106 | gpt-35-turbo, 0125 |
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|------------------|----|---------|---------------------|--------------------------|--------------------------|--------------------|--------------------|--------------------|-------------------------|-------------|-------------------------|-----------------|--------------------|--------------------|
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| australiaeast | | | | | | | | X | | X | | X | X | X |
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| canadaeast | | | | | | | | X | | X | | X | X | X |
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| eastus | | | | | | X | X | X | X | X | X | | | X |
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| eastus2 | | | | | | X | X | X | X | X | X | | | X |
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| francecentral | | | | | | | | X | | X | | X | X | X |
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| japaneast | | | | | | | | X | | | | | | X |
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| koreacentral | | | | | | | | | | | | | | |
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| norwayeast | | | | | | | | X | | | | | | |
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| polandcentral | | | | | | | | | | | | | | |
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| southindia | | | | | | | | X | | | | | X | |
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| swedencentral | | | | | | X | X | X | X | X | X | X | X | X |
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| switzerlandnorth | | | | | | | | X | | X | | X | | X |
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| uaenorth | | | | | | | | | | | | | | |
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| uksouth | | | | | | | | X | | | | | X | X |
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| westus | | | | | | X | X | X | X | | X | | X | |
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| westus3 | | | | | | X | X | X | X | | X | | | |
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## Non-Microsoft models
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The Azure AI Agent Service also supports the following models from the Azure AI Foundry model catalog.
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* Meta-Llama-405B-Instruct
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* Cohere-command-r-plus
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* Cohere-command-r
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To use these models, you can use [Azure AI Foundry portal](https://ai.azure.com/) to make a deployment, and then reference the deployment name in your agent. For example:
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```python
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agent = project_client.agents.create_agent( model="llama-3", name="my-agent", instructions="You are a helpful agent" )
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## Azure AI Foundry models
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### Models with tool-calling
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To best support agentic scenarios, we recommend using models that support tool-calling. The Azure AI Agent Service currently supports all agent-compatible models from the Azure AI Foundry model catalog.
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To use these models, use the [Azure AI Foundry portal](https://ai.azure.com/) to make a model deployment, then reference the deployment name in your agent. For example:
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`agent = project_client.agents.create_agent( model="llama-3", name="my-agent", instructions="You are a helpful agent")`
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> [!NOTE]
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> This option should only be used for open-source models (for example, Cepstral, Mistral, Llama) and not for OpenAI models, which are natively supported in the service. This option should also only be used for models that support tool-calling.
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### Models without tool-calling
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Though tool-calling support is a core capability for agentic scenarios, we now provide the ability to use models that don’t support tool-calling in our API and SDK. This option can be helpful when you have specific use-cases that don’t require tool-calling.
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The following steps will allow you to utilize any chat-completion model that is available through a [serverless API](/azure/ai-foundry/how-to/model-catalog-overview):
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1. Deploy your desired model through serverless API. Model will show up on your **Models + Endpoints** page.
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1. Click on model name to see model details, where you'll find your model's target URI and key.
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1. Create a new Serverless connection on **Connected Resources** page, using the target URI and key.
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The model can now be referenced in your code (`Target URI` + `@` + `Model Name`), for example:
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`Model=https://Phi-4-mejco.eastus.models.ai.azure.com/@Phi-4-mejco`
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## Next steps
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