OpenAI is deploying inference services on Google TPUs, according to various free-to-read sites parroting The Information, reducing its reliance on Nvidia GPUs hosted by partners Microsoft and Oracle. Google, meanwhile, monetizes its AI investment; although whether it’s offering Ironwood, Trillium, or an earlier TPU is undisclosed.
Nvidia has uniquely benefited financially from the rise of OpenAI and its competitors, which depend on Blackwell and its other GPUs, paying dearly for them. Undoubtedly, OpenAI is keen to mitigate supplier risk, reduce costs, and access more AI-acceleration capacity than Nvidia can supply. Inference (model execution) is easier to port to a new architecture than training and development, which in almost all cases depends on Nvidia’s Cuda ecosystem. If OpenAI started training on the TPU (as Apple is said to have done and as Google itself does), that would be a man-bites-dog story.
Like many of its competitors, OpenAI is developing its own AI accelerator (NPU), which—if successful—would yield even more independence than diversifying by using the TPU. CEO Sam Altman has also expressed interest in AMD’s forthcoming MI400 GPU. These various efforts might not pan out, but OpenAI is opening up options.