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title: Upgrade from GitHub Models to Azure AI Foundry Models
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titleSuffix: Azure AI Foundry for GitHub
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description: Learn how to upgrade your endpoint from GitHub Models to Azure AI Foundry Models
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description: Learn how to upgrade from GitHub Models to Azure AI Foundry Models for production-ready AI applications with enhanced features.
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ms.service: azure-ai-foundry
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ms.subservice: azure-ai-foundry-model-inference
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ms.topic: how-to
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ms.date: 05/19/2025
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ms.date: 09/30/2025
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ms.custom: ignite-2024, github-universe-2024
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author: msakande
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ms.author: mopeakande
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recommendations: false
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ms.reviewer: fasantia
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reviewer: santiagxf
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#CustomerIntent: As a developer using GitHub Models, I want to learn how to upgrade my endpoint to Azure AI Foundry Models so that I can access enhanced features and capabilities for my AI applications.
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---
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# Upgrade from GitHub Models to Azure AI Foundry Models
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If you want to develop a generative AI application, you can use [GitHub Models](https://docs.github.com/en/github-models/) to find and experiment with AI models for free. The playground and free API usage are [rate limited](https://docs.github.com/en/github-models/prototyping-with-ai-models#rate-limits) by requests per minute, requests per day, tokens per request, and concurrent requests. If you get rate limited, you need to wait for the rate limit that you hit to reset before you can make more requests.
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In this article, you learn to develop a generative AI application by starting from GitHub Modelsand then upgrading your experience by deploying an Azure AI Services resource with Azure AI Foundry Models.
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Once you're ready to bring your application to production, you can upgrade your experience by deploying an Azure AI Services resource in an Azure subscription and start using Azure AI Foundry Models service. You don't need to change anything else in your code.
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[GitHub Models](https://docs.github.com/en/github-models/) are useful when you want to find and experiment with AI models for free as you develop a generative AI application. When you're ready to bring your application to production, upgrade your experience by deploying an Azure AI Services resource in an Azure subscription and start using Azure AI Foundry Models service. You don't need to change anything else in your code.
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The following article explains how to get started from GitHub Models and deploy an Azure AI Services resource with Azure AI Foundry Models.
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The playground and free API usage for GitHub Models are [rate limited](https://docs.github.com/en/github-models/prototyping-with-ai-models#rate-limits) by requests per minute, requests per day, tokens per request, and concurrent requests. If you get rate limited, you need to wait for the rate limit that you hit to reset before you can make more requests.
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## Prerequisites
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@@ -31,45 +30,45 @@ To complete this tutorial, you need:
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## Upgrade to Azure AI Foundry Models
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The rate limits for the playground and free API usage are intended to help you experiment with models and develop your AI application. Once you're ready to bring your application to production, use a key and endpoint from a paid Azure account. You don't need to change anything else in your code.
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The rate limits for the playground and free API usage help you experiment with models and develop your AI application. When you're ready to bring your application to production, use a key and endpoint from a paid Azure account. You don't need to change anything else in your code.
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To obtain the key and endpoint:
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To get the key and endpoint:
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1. Go to [GitHub Models](https://github.com/marketplace/models) and select the model you're interested in.
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1. In the playground for your model, select **Get API key**.
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2. Select **Get production key**.
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1. Select **Get production key**.
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:::image type="content" source="../media/quickstart-github-models/github-models-upgrade.gif" alt-text="An animation showing how to upgrade GitHub Models to get a production ready resource." lightbox="../media/quickstart-github-models/github-models-upgrade.gif":::
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3. If you don't have an Azure account, select Create my account and follow the steps to create one.
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1. If you don't have an Azure account, select **Create my account** and follow the steps to create one.
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4. If you have an Azure account, select **Sign back in**.
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1. If you have an Azure account, select **Sign back in**.
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5. If your existing account is a free account, you first have to upgrade to a Standard plan. Once you upgrade, go back to the playground and select **Get API key** again, then sign in with your upgraded account.
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1. If your existing account is a free account, you first have to upgrade to a Standard plan. Once you upgrade, go back to the playground and select **Get API key** again, then sign in with your upgraded account.
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6. Once you've signed in to your Azure account, you're taken to [Azure AI Foundry > GitHub](https://ai.azure.com/GitHub). It might take one or two minutes to load your initial model details in AI Foundry.
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1. When you sign in to your Azure account, you're taken to [Azure AI Foundry > GitHub](https://ai.azure.com/GitHub). It might take one or two minutes to load your initial model details in AI Foundry.
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7. The page is loaded with your model's details. Select the **Deploy** button to deploy the model to your account.
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1. The page loads with your model's details. Select the **Deploy** button to deploy the model to your account.
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8. Once it's deployed, your model's API Key and endpoint are shown in the Overview. Use these values in your code to use the model in your production environment.
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1. When it's deployed, your model's API Key and endpoint appear in the Overview. Use these values in your code to use the model in your production environment.
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At this point, the model you selected is ready to consume.
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## Upgrade your code to use the new endpoint
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Once your Azure AI Services resource is configured, you can start consuming it from your code. To consume the Azure AI Services resource, you need the endpoint URL and key, which are available in the **Overview** section:
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After you configure your Azure AI Services resource, you can start using it from your code. To use the Azure AI Services resource, you need the endpoint URL and key, which you can find in the **Overview** section:
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:::image type="content" source="../media/overview/overview-endpoint-and-key.png" alt-text="Screenshot showing how to get the URL and key associated with the resource." lightbox="../media/overview/overview-endpoint-and-key.png":::
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You can use any of the supported SDKs to get predictions out from the endpoint. The following SDKs are officially supported:
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You can use any of the supported SDKs to get predictions from the endpoint. The following SDKs are officially supported:
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* OpenAI SDK
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* Azure OpenAI SDK
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* Azure AI Inference SDK
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See the [supported languages and SDKs](../../model-inference/supported-languages.md) section for more details and examples. The following example shows how to use the Azure AI Foundry Models SDK with the newly deployed model:
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For more details and examples, see the [supported languages and SDKs](../supported-languages.md) section. The following example shows how to use the Azure AI Foundry Models SDK with the newly deployed model:
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Use the parameter `model="<deployment-name>` to route your request to this deployment. *Deployments work as an alias of a given model under certain configurations*. See [Routing](inference.md#routing) concept page to learn how Azure AI Services route deployments.
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> [!IMPORTANT]
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> As opposite to GitHub Models where all the models are already configured, the Azure AI Services resource allows you to control which models are available in your endpoint and under which configuration. Add as many models as you plan to use before indicating them in the `model` parameter. Learn how to [add more models](../../model-inference/how-to/create-model-deployments.md) to your resource.
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> Unlike GitHub Models where all the models are already configured, the Azure AI Services resource allows you to control which models are available in your endpoint and under which configuration. Add as many models as you plan to use before indicating them in the `model` parameter. Learn how to [add more models](../../model-inference/how-to/create-model-deployments.md) to your resource.
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## Explore additional features
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Azure AI Foundry Models supports additional features not available in GitHub Models, including:
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Azure AI Foundry Models supports additional features that aren't available in GitHub Models, including:
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*[Explore the model catalog](https://ai.azure.com/github/models) to see additional models not available in GitHub Models.
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*[Explore the model catalog](https://ai.azure.com/github/models) to see more models.
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