Microsoft’s Maia 200 chips cut operational costs 30% to 40% vs Nvidia for some models

Microsoft’s homegrown Maia 200 AI chip is delivering operational costs that are 30% to 40% lower than comparable Nvidia hardware for certain models. The second-generation custom accelerator, built on TSMC’s 3nm process, represents a meaningful escalation in the tech giant’s effort to wean itself off the GPU maker that currently dominates the AI infrastructure market. The Maia 200 was unveiled on January 26, 2026, and deployed in an Iowa data center that same week. A second rollout near Phoenix, Arizona, is already in the works. What the Maia 200 actually brings to the table The chip packs over 140 billion transistors and delivers more than 10 petaFLOPS at FP4 precision and over 5 petaFLOPS at FP8, all within a 750-watt thermal envelope. Microsoft claims a 30% improvement in performance per dollar compared to its existing hardware fleet, along with better performance per watt. The chip was purpose-built for inference, the phase of AI where a trained model actually responds to queries and generates outputs. Microsoft designed the Maia 200 to support inference clusters of up to 6,144 accelerators using Ethernet-based scale-up networking. It’s already running OpenAI’s GPT-5.2 models an...