Google’s New Ironwood Chip is 24x More Powerful Than the World’s Fastest Supercomputer
upstart writes:
Google's new Ironwood chip is 24x more powerful than the world's fastest supercomputer:
Google Cloud unveiled its seventh-generation Tensor Processing Unit (TPU),Ironwood,on Wednesday. This custom AI accelerator, the company claims, delivers more than 24 times the computing power of the world's fastest supercomputer when deployed at scale.
The new chip, announced at Google Cloud Next '25, represents a significant pivot in Google's decade-long AI chip development strategy. While previous generations of TPUs were designed primarily for both training and inference workloads, Ironwood is the first purpose-built specifically for inference - the process of deploying trained AI models to make predictions or generate responses.
"Ironwood is built to support this next phase of generative AI and its tremendous computational and communication requirements," said Amin Vahdat, Google's Vice President and General Manager of ML, Systems, and Cloud AI, in a virtual press conference ahead of the event. "This is what we call the 'age of inference' where AI agents will proactively retrieve and generate data to collaboratively deliver insights and answers, not just data."
The technical specifications of Ironwood are striking. When scaled to 9,216 chips per pod, Ironwood delivers 42.5 exaflops of computing power - dwarfing El Capitan's 1.7 exaflops, currently the world's fastest supercomputer. Each individual Ironwood chip delivers peak compute of 4,614 teraflops.
Ironwood also features significant memory and bandwidth improvements. Each chip comes with 192GB of High Bandwidth Memory (HBM), six times more than Trillium, Google's previous-generation TPU announced last year. Memory bandwidth reaches 7.2 terabits per second per chip, a 4.5x improvement over Trillium.
Perhaps most importantly, in an era of power-constrained data centers, Ironwood delivers twice the performance per watt compared to Trillium, and is nearly 30 times more power efficient than Google's first Cloud TPU from 2018.
"At a time when available power is one of the constraints for delivering AI capabilities, we deliver significantly more capacity per watt for customer workloads," Vahdat explained.
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