# Microsoft Unveiled Maia 300 on October 12, Saying It Will Make Maia Its Main Inference System From 2027

Times of AI Desk · 2026-10-13 · Hardware

[https://timesof.ai/2026/10/microsoft-maia-300-inference-chip-2027](https://timesof.ai/2026/10/microsoft-maia-300-inference-chip-2027)

> On October 12 Microsoft announced Maia 300, an inference chip built on TSMC's N2P process, and said it will scale the Maia family to multi-gigawatt deployments from 2027. Microsoft projects 40% more tokens per megawatt than leading GPU systems; that is the company's own estimate.

**Microsoft** says its in-house **Maia** chips will become "the primary inference system for Microsoft products and services." It announced the third-generation **Maia 300** in a blog post on **Monday, October 12**, and said it will scale the Maia family to multi-gigawatt deployments starting in **2027**.

## What Microsoft claims

Microsoft says it expects Maia 300 to deliver **40% more tokens per megawatt** than leading GPU-based systems, and up to **7x** the rack-scale token throughput of Maia 200 in a 96-accelerator configuration. Both figures are Microsoft's projections; Maia 300 begins production deployments in 2027, the company says.

## The hardware

According to Microsoft, Maia 300 uses eight **HBM4** stacks for 18.0 TB/s of peak memory bandwidth within a 950-watt TDP, with compute chiplets built on **TSMC's N2P** process. A rack holds 96 accelerators within 167 kilowatts and 27.6 TB of HBM, the company says.

**SiliconANGLE** reports that Maia 300's 288 GB of HBM matches Nvidia's Rubin accelerator but that it has about 20% less memory bandwidth than Rubin; that comparison is SiliconANGLE's own. It also reports that Microsoft plans superpods of 12,288 accelerators linked over a custom Ethernet-based network.

## Where Maia 200 stands

Microsoft says Maia 200 already serves production workloads including Microsoft Copilot, with GitHub Copilot and Microsoft Foundry to follow by the end of the year, and runs OpenAI models, Microsoft's MAI models and open-source models.

## Limits

- Performance and efficiency numbers are Microsoft's own and have not been independently measured.
- The Rubin comparison is SiliconANGLE's analysis, not Microsoft's.

## Sources

- [Microsoft: Microsoft to expand Azure Maia system to multi-gigawatt deployments (October 12, 2026)](https://blogs.microsoft.com/blog/2026/10/12/microsoft-to-expand-azure-maia-system-to-multi-gigawatt-deployments/)
- [SiliconANGLE: Microsoft debuts multichiplet Maia 300 inference accelerator (October 12, 2026)](https://siliconangle.com/2026/10/12/microsoft-debuts-multichiplet-maia-300-inference-accelerator/)