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Azure OpenAI Service provides REST API access to OpenAI's powerful language models including o3-mini, o1, o1-mini, GPT-4o, GPT-4o mini, GPT-4 Turbo with Vision, GPT-4, GPT-3.5-Turbo, and Embeddings model series. These models can be easily adapted to your specific task including but not limited to content generation, summarization, image understanding, semantic search, and natural language to code translation. Users can access the service through REST APIs, Python/C#/JS/Java/Go SDKs.
Feature | Azure OpenAI |
---|---|
Models available | o3-mini & o1 - (Limited Access - Request Access) o1-mini GPT-4o & GPT-4o mini GPT-4 series (including GPT-4 Turbo with Vision) GPT-3.5-Turbo series Embeddings series Learn more in our Models page. |
Fine-tuning | GPT-4o-mini (preview) GPT-4 (preview) GPT-3.5-Turbo (0613). |
Price | Available here For details on vision-enabled chat models, see the special pricing information. |
Virtual network support & private link support | Yes. |
Managed Identity | Yes, via Microsoft Entra ID |
UI experience | Azure portal for account & resource management, Azure AI Foundry for model exploration and fine-tuning |
Model regional availability | Model availability |
Content filtering | Prompts and completions are evaluated against our content policy with automated systems. High severity content is filtered. |
At Microsoft, we're committed to the advancement of AI driven by principles that put people first. Generative models such as the ones available in Azure OpenAI have significant potential benefits, but without careful design and thoughtful mitigations, such models have the potential to generate incorrect or even harmful content. Microsoft has made significant investments to help guard against abuse and unintended harm, which includes incorporating Microsoft’s principles for responsible AI use, adopting a Code of Conduct for use of the service, building content filters to support customers, and providing responsible AI information and guidance that customers should consider when using Azure OpenAI.
To get started with Azure OpenAI Service, you need to create an Azure OpenAI Service resource in your Azure subscription.
Start with the Create and deploy an Azure OpenAI Service resource guide.
You can create a resource via Azure portal, Azure CLI, or Azure PowerShell.
When you have an Azure OpenAI Service resource, you can deploy a model such as GPT-4o.
When you have a deployed model, you can:
For example, you can try real-time audio and assistants in the playgrounds or via code.
Note
A Limited Access registration form is required to access some Azure OpenAI Service models or features. Learn more on the Azure OpenAI Limited Access page.
Azure OpenAI Service gives customers advanced language AI with OpenAI GPT-4, GPT-3, Codex, DALL-E, Whisper, and text to speech models with the security and enterprise promise of Azure. Azure OpenAI co-develops the APIs with OpenAI, ensuring compatibility and a smooth transition from one to the other.
With Azure OpenAI, customers get the security capabilities of Microsoft Azure while running the same models as OpenAI. Azure OpenAI offers private networking, regional availability, and responsible AI content filtering.
The completions endpoint is the core component of the API service. This API provides access to the model's text-in, text-out interface. Users simply need to provide an input prompt containing the English text command, and the model generates a text completion.
Here's an example of a simple prompt and completion:
Prompt:
""" count to 5 in a for loop """
Completion:
for i in range(1, 6): print(i)
Azure OpenAI processes text by breaking it down into tokens. Tokens can be words or just chunks of characters. For example, the word “hamburger” gets broken up into the tokens “ham”, “bur” and “ger”, while a short and common word like “pear” is a single token. Many tokens start with a whitespace, for example “ hello” and “ bye”.
The total number of tokens processed in a given request depends on the length of your input, output, and request parameters. The quantity of tokens being processed will also affect your response latency and throughput for the models.
Azure OpenAI's image processing capabilities with GPT-4o, GPT-4o mini, and GPT-4 Turbo with Vision models uses image tokenization to determine the total number of tokens consumed by image inputs. The number of tokens consumed is calculated based on two main factors: the level of image detail (low or high) and the image’s dimensions. Here's how token costs are calculated:
Azure OpenAI is a new product offering on Azure. You can get started with Azure OpenAI the same way as any other Azure product where you create a resource, or instance of the service, in your Azure Subscription. You can read more about Azure's resource management design.
Once you create an Azure OpenAI Resource, you must deploy a model before you can start making API calls and generating text. This action can be done using the Deployment APIs. These APIs allow you to specify the model you wish to use.
The GPT-3, GPT-3.5, and GPT-4 models from OpenAI are prompt-based. With prompt-based models, the user interacts with the model by entering a text prompt, to which the model responds with a text completion. This completion is the model’s continuation of the input text.
While these models are powerful, their behavior is also sensitive to the prompt. This makes prompt engineering an important skill to develop.
Prompt construction can be difficult. In practice, the prompt acts to configure the model weights to complete the desired task, but it's more of an art than a science, often requiring experience and intuition to craft a successful prompt.
The service provides users access to several different models. Each model provides a different capability and price point.
The DALL-E models (some in preview; see models) generate images from text prompts that the user provides.
The Whisper models can be used to transcribe and translate speech to text.
The text to speech models, currently in preview, can be used to synthesize text to speech.
Learn more about each model on our models concept page.
Learn more about the underlying models that power Azure OpenAI.
Events
Mar 17, 11 p.m. - Mar 21, 11 p.m.
Join the meetup series to build scalable AI solutions based on real-world use cases with fellow developers and experts.
Register nowTraining
Module
Get started with Azure OpenAI Service - Training
Azure OpenAI Service enables engineers to build enterprise-grade generative AI solutions.
Certification
Microsoft Certified: Azure AI Fundamentals - Certifications
Demonstrate fundamental AI concepts related to the development of software and services of Microsoft Azure to create AI solutions.