OpenAI models offered by Azure as a fully managed service with guardrails built in, covering GPT-4.1, GPT-5, o-series, image, audio and embeddings. Rather than running infrastructure, you pick a deployment type.
Also called Azure OpenAI Service, Azure OpenAI Service.
Read more: Microsoft Learn
In the Ultra Transcenders books
Each book explains Azure OpenAI in Foundry Models in context, with comparison tables and the common traps.
Terms in this definition
- Fully managed
An Android Enterprise setup for company-owned devices that one person uses only for work, with Intune in control of the entire device.
- GPT-4.1
OpenAI chat models gpt-4.1, gpt-4.1-mini and gpt-4.1-nano, which accept images and text and return text. They are deprecated in Azure: nano retires on 14 October 2026, while the full and mini models follow on 14 April 2027.
- o-series
Reasoning models from OpenAI, namely o1, o3 and o4-mini, that think longer to tackle science, coding and maths problems. Azure has deprecated all of them, with retirement on 19 November 2026 and GPT-5.6 models as successors.
- Embeddings
Vectors of numbers encoding what text means, placing related content close together as judged by cosine similarity. Switching model or vector size requires embedding all content again.
- Model deployment
Inside a resource, each deployment is a named copy of a Foundry model with its own TPM quota and deployment type. Requests identify the model by this deployment name.