Apple Trained its Apple Intelligence Models on Google TPUs, Not NVIDIA GPUs

Apple has disclosed that its newly announced Apple Intelligence features were developed using Google's Tensor Processing Units (TPUs) rather than NVIDIA's widely adopted hardware accelerators like H100. This unexpected choice was detailed in an official Apple research paper, shedding light on the company's approach to AI development. The paper outlines how systems equipped with Google's TPUv4 and TPUv5 chips played a crucial role in creating Apple Foundation Models (AFMs). These models, including AFM-server and AFM-on-device, are designed to power both online and offline Apple Intelligence features introduced at WWDC 2024. For the training of the 6.4 billion parameter AFM-server, Apple's largest language model, the company utilized an impressive array of 8,192 TPUv4 chips, provisioned as 8×1024 chip slices. The training process involved a three-stage approach, processing a total of 7.4 trillion tokens. Meanwhile, the more compact 3 billion parameter AFM-on-device model, optimized for on-device processing, was trained using 2,048 TPUv5p chips.