Exploring Azure AI Model Inference: A Comprehensive Guide

Azure AI model inference provides access to a wide range of flagship models from leading providers such as AI21 Labs, Azure OpenAI, Cohere, Core42, DeepSeek, Meta, Microsoft, Mistral AI, and NTT Data https://learn.microsoft.com/azure/ai-foundry/model-inference/concepts/models . 

These models can be consumed as APIs, allowing you to integrate advanced AI capabilities into your applications seamlessly.

Model Families and Their Capabilities

Azure AI Foundry categorises its models into several families, each offering unique capabilities:

AI21 Labs: Known for the Jamba family models, which are production-grade large language models (LLMs) using AI21's hybrid Mamba-Transformer architecture. These models support chat completions, tool calling, and multiple languages including English, French, Spanish, Portuguese, German, Arabic, and Hebrew. https://learn.microsoft.com/azure/ai-foundry/model-inference/concepts/models 

Azure OpenAI: Offers diverse models designed for tasks such as reasoning, problem-solving, natural language understanding, and code generation. These models support text and image inputs, multiple languages, and tool calling https://learn.microsoft.com/azure/ai-foundry/model-inference/concepts/models 

Cohere: Provides models for embedding and command tasks, supporting multilingual capabilities and various response formats https://learn.microsoft.com/azure/ai-foundry/model-inference/concepts/models 

Core42: Features the Jais-30B-chat model, designed for chat completions https://learn.microsoft.com/azure/ai-foundry/model-inference/concepts/models 

DeepSeek: Includes models like DeepSeek-V3 and DeepSeek-R1, focusing on advanced AI tasks https://learn.microsoft.com/azure/ai-foundry/model-inference/concepts/models 

Meta: Offers the Llama series models, which are instruction-tuned for various AI tasks https://learn.microsoft.com/azure/ai-foundry/model-inference/concepts/models 

Microsoft: Provides the Phi series models, supporting multimodal instructions and vision tasks https://learn.microsoft.com/azure/ai-foundry/model-inference/concepts/models 

Mistral AI: Features models like Ministral-3B and Mistral-large, designed for high-performance AI tasks https://learn.microsoft.com/azure/ai-foundry/model-inference/concepts/models 

NTT Data: Offers the Tsuzumi-7b model, focusing on specific AI capabilities https://learn.microsoft.com/azure/ai-foundry/model-inference/concepts/models 

Deployment and Integration

Azure AI model inference supports global standard deployment, ensuring consistent throughput and performance. Models can be deployed in various configurations, including regional deployments and sovereign clouds such as Azure Government, Azure Germany, and Azure China https://learn.microsoft.com/azure/ai-foundry/model-inference/concepts/models 

To integrate these models into your applications, you can use the Azure AI model inference API, which supports multiple programming languages including Python, C#, JavaScript, and Java. This flexibility allows you to deploy models multiple times under different configurations, providing a robust and scalable solution for your AI needs https://learn.microsoft.com/en-us/azure/ai-foundry/model-inference/overview 

Conclusion

Azure AI model inference in Azure AI Foundry offers a comprehensive solution for integrating advanced AI models into your applications. With a wide range of models from leading providers, flexible deployment options, and robust API support, Azure AI Foundry empowers you to leverage cutting-edge AI capabilities without the complexity of hosting and managing the infrastructure.

Explore the Azure AI model catalog today and unlock the potential of AI for your business.

 Join the Conversation on Azure AI Foundry Discussions! 
Have ideas, questions, or insights about AI? Don't keep them to yourself! Share your thoughts, engage with experts, and connect with a community that’s shaping the future of artificial intelligence.
👉 Click here to join the discussion!