
Azure Maia
Microsoft's in-house family of AI chips and systems, built to power the AI inference workloads behind its own products and services.
About Azure Maia
Azure Maia is Microsoft's in-house family of AI inference chips and systems. According to Microsoft's official blog, the multi-generational Azure Maia project has become a foundational part of Microsoft's AI infrastructure strategy: Maia 200 is in production, being deployed in the US, Europe, and Australia, and serves inference for the built-in AI capabilities of Microsoft Teams, Copilot, and Cowork, delivering up to 1.7 times token output per watt compared with leading GPU infrastructure, according to the official announcement. The next-generation Maia 300 is planned for 2027 and targets emerging AI workloads such as long-context inference, latency-sensitive conversational experiences, and multi-step agent tasks; Microsoft expects it to deliver 40% more tokens per megawatt than leading GPU-based systems and, in its full 96-accelerator configuration, up to 7 times the rack-level token throughput of Maia 200. Microsoft has also announced that from 2027 it will scale the Maia family to multi-gigawatt deployments, making it the primary inference system for Microsoft's products and services. Note that this is an infrastructure-level announcement: Azure Maia is not a standalone tool intended for direct use by individual users.
Best for
Best use cases
The underlying inference service for built-in AI capabilities in products such as Microsoft Teams, Copilot, and Cowork
Long-context inference, latency-sensitive conversational experiences, and multi-step agent tasks (design goals for Maia 300)
Microsoft's scaling infrastructure for multi-gigawatt AI deployments starting in 2027
Features
Powers Microsoft's built-in AI capabilities
According to the official blog, it serves inference for the built-in AI capabilities in Microsoft Teams, Copilot, and Cowork, achieving up to 1.7 times token output per watt in the comparison cited.
A full intelligence system for new AI workloads (Maia 300)
According to the official blog, Maia 300 is designed for emerging AI workloads and is expected to deliver 40% more tokens per megawatt through system-level efficiency improvements.
High rack-level throughput (Maia 300)
According to the official blog, in its full 96-accelerator configuration, Maia 300 delivers up to 7 times the rack-level token throughput of Maia 200.
Pros
- The official blog states that Maia 200 is in production and being deployed in the US, Europe, and Australia
- The official blog states that, compared with leading GPU infrastructure, Maia 200 achieves up to 1.7 times token output per watt for the built-in AI capabilities of Microsoft Teams, Copilot, and Cowork
- The official blog states that Maia 300 is expected to deliver 40% more tokens per megawatt than leading GPU-based systems and, in its full 96-accelerator configuration, up to 7 times the rack-level token throughput of Maia 200