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articles/ai-foundry/.openpublishing.redirection.ai-studio.json

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

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manager: scottpolly
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reviewer: santiagxf
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ms.reviewer: fasantia
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ms.date: 07/11/2025
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ms.date: 07/29/2025
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ms.service: azure-ai-foundry
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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, 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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- _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(that are available to download and run on self-hosted managed endpoints).
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The following table provides links to examples of how to use Mistral models.
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- [Use Requests library with Stable Diffusion 3.5 Large for image to image requests](https://github.com/Azure/azureml-examples/blob/main/sdk/python/foundation-models/stabilityai/Image_to_Image.ipynb)
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- [Example of a fully encoded image generation response](https://github.com/Azure/azureml-examples/blob/main/sdk/python/foundation-models/stabilityai/Sample_image_generation_response.txt)
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## Gretel Navigator
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Gretel Navigator employs a compound AI architecture specifically engineered for synthetic data, by combining top open-source small language models (SLMs) fine-tuned across more than 10 industry domains. This purpose-built system creates diverse, domain-specific datasets at scales of hundreds to millions of examples. The system also preserves complex statistical relationships and offers increased speed and accuracy compared to manual data creation.
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| Description | Language | Sample |
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|-------------------------------------------|-------------------|-----------------------------------------------------------------|
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| Azure AI Inference package for JavaScript | JavaScript | [Link](https://aka.ms/azsdk/azure-ai-inference/javascript/samples) |
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| Azure AI Inference package for Python | Python | [Link](https://aka.ms/azsdk/azure-ai-inference/python/samples) |
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## Related content
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articles/ai-foundry/foundry-models/overview.md

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