… But having said all of that, here is the basic math: At $60 billion per gigawatt, a good, high-end ballpark figure for a datacenter tricked out with the best AI gear, that 4.5 gigawatts costs $270 billion. …
… If you do the math, that means the OpenAI backlog is now $265.6 billion, down 5.6 percent sequentially. That math implies that OpenAI spent $15.65 billion on Azure capacity in Q3 F2026 – but I would be careful jumping to that conclusion. …
… Azure has doubled in size in two years by our math, and there is no reason to believe it will not double in half the time given the GenAI boom. …
… Set against this backdrop, the hyperscalers and cloud builders are designing their own CPUs and XPUs or partnering with companies other than Nvidia and AMD to try to get better bang for the buck for AI inference workloads – or just to get any kind of matrix math compute at all. …
… And hence it divulged the “Athena” Maia 100 XPU in November 2023 with very few details and some rack photos. The Maia 100 chip was designed to support both AI training and inference, and was explicitly designed to run OpenAI’s GPT as a backend for Microsoft’s OpenAI API services and its copilots. …