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DeepSeek R1 is now available on Azure AI Foundry and GitHub
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  • Technology

DeepSeek R1 is now available on Azure AI Foundry and GitHub

  • aster.cloud
  • February 2, 2025
  • 3 minute read

DeepSeek R1 is now available in the model catalog on Azure AI Foundry and GitHub, joining a diverse portfolio of over 1,800 models, including frontier, open-source, industry-specific, and task-based AI models. As part of Azure AI Foundry, DeepSeek R1 is accessible on a trusted, scalable, and enterprise-ready platform, enabling businesses to seamlessly integrate advanced AI while meeting SLAs, security, and responsible AI commitments—all backed by Microsoft’s reliability and innovation. 

Accelerating AI reasoning for developers on Azure AI Foundry

AI reasoning is becoming more accessible at a rapid pace transforming how developers and enterprises leverage cutting-edge intelligence. As DeepSeek mentions, R1 offers a powerful, cost-efficient model that allows more users to harness state-of-the-art AI capabilities with minimal infrastructure investment. 


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One of the key advantages of using DeepSeek R1 or any other model on Azure AI Foundry is the speed at which developers can experiment, iterate, and integrate AI into their workflows. With built-in model evaluation tools, they can quickly compare outputs, benchmark performance, and scale AI-powered applications. This rapid accessibility—once unimaginable just months ago—is central to our vision for Azure AI Foundry: bringing the best AI models together in one place to accelerate innovation and unlock new possibilities for enterprises worldwide. 

Develop with trustworthy AI

We are committed to enabling customers to build production-ready AI applications quickly while maintaining the highest levels of safety and security. DeepSeek R1 has undergone rigorous red teaming and safety evaluations, including automated assessments of model behavior and extensive security reviews to mitigate potential risks. With Azure AI Content Safety, built-in content filtering is available by default, with opt-out options for flexibility. Additionally, the Safety Evaluation System allows customers to efficiently test their applications before deployment. These safeguards help Azure AI Foundry provide a secure, compliant, and responsible environment for enterprises to confidently deploy AI solutions. 

Read More  The Coca-Cola Company And Microsoft Announce Five-year Strategic Partnership To Accelerate Cloud And Generative AI Initiatives

How to use DeepSeek in model catalog

If you don’t have an Azure subscription, you can sign up for an Azure account here.

Search for DeepSeek R1 in the model catalog.

Open the model card in the model catalog on Azure AI Foundry.

Click on deploy to obtain the inference API and key and also to access the playground. 

You should land on the deployment page that shows you the API and key in less than a minute. You can try out your prompts in the playground.

You can use the API and key with various clients.

Get started today

DeepSeek R1 is now available via a serverless endpoint through the model catalog in Azure AI Foundry. Get started on Azure AI Foundry here and select the DeepSeek model.

On GitHub, you can explore additional resources and step-by-step guides to integrate DeepSeek R1 seamlessly into your applications. Read the GitHub Models blog post.

Customers will be able to use distilled flavors of the DeepSeek R1 model to run locally on their Copilot+ PCs. Read the Windows Developer blog post.

As we continue expanding the model catalog in Azure AI Foundry, we’re excited to see how developers and enterprises leverage DeepSeek R1 to tackle real-world challenges and deliver transformative experiences. We are committed to offering the most comprehensive portfolio of AI models, ensuring that businesses of all sizes have access to cutting-edge tools to drive innovation and success. 

By: Asha Sharma, Corporate Vice President, AI Platform
Originally published at: Azure Blog

Source: zedreviews.com


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Related Topics
  • Azure
  • Azure AI
  • Azure AI Foundry
  • DeepSeek
  • DeepSeek R1
  • GitHub
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