Meet Ironwood: Google’s most powerful AI chip, which is 24 times faster than world’s top supercomputer

Google Ironwood

At Cloud Next 2025, Google took the wraps off Ironwood, its seventh-generation Tensor Processing Unit — and a serious leap forward in AI computing muscle. Billed as the company’s most powerful, scalable, and energy-efficient AI chip to date, Ironwood, as per Google represents a significant shift in the development of AI and the infrastructure that powers its progress

Unlike previous TPUs optimised primarily for training AI models, Ironwood is the first purpose-built for inference — the phase where AI systems actually generate answers, make decisions, and reason in real time. That means it’s designed to handle the heavy compute demands of large language models, mixture-of-experts architectures, and complex reasoning tasks with speed and efficiency.

Each Ironwood chip packs a staggering 4,614 TFLOPs of peak compute, and Google Cloud customers can scale up to massive 9,216-chip pods. At full scale, that’s 42.5 exaflops of raw compute — more than 24 times the processing power of the world’s current largest supercomputer, El Capitan.

Google also says Ironwood doubles performance-per-watt over last year’s Trillium TPUs, while boasting 192GB of ultra-fast memory per chip — six times more than before. By minimizing data movement and latency on-chip, Ironwood is engineered to keep up with the increasingly “thinking” nature of today’s AI models.

“Our advanced liquid cooling solutions and optimized chip design can reliably sustain up to twice the performance of standard air cooling even under continuous, heavy AI workloads. In fact, Ironwood is nearly 30x more power efficient than our first Cloud TPU from 2018,” said Google.

Google is calling this the beginning of the “age of inference” — where AI doesn’t just spit out data for humans to analyze, but proactively generates insights and collaborates to provide full-fledged answers. “Ironwood represents a unique breakthrough in the age of inference with increased computation power, memory capacity, ICI networking advancements and reliability, said Google.