At Google Cloud Next 2025 in Las Vegas, Google unveiled Ironwood—its most powerful and efficient TPU (Tensor Processing Unit) yet. Designed specifically for AI inference, Ironwood marks the company’s seventh generation of TPUs and is engineered to meet the growing demand for real-time AI performance.
“Inference is not new,” said Amin Vahdat, Google’s vice president overseeing systems and services infrastructure. “It’s just that the relative importance of inference is going up significantly.”
And with that, Google has launched a chip that could change how quickly—and efficiently—AI models deliver results.
Why Ironwood TPU Stands Out
The Ironwood TPU isn’t just another chip upgrade. It’s been purpose-built to deliver large-scale inference for AI models like Google’s Gemini. Here’s what makes it special:
- Massive compute power: Each Ironwood chip delivers 4,614 teraflops (TFLOPs)—more than enough to handle advanced AI workloads.
- Highly scalable: A single pod can connect 9,216 of these chips to deliver a whopping 42.5 exaflops.
- Memory boost: Each chip is backed with 192 GB of high-bandwidth memory, moving data at a lightning-fast 7.4 TB per second.
- Energy efficiency: It’s twice as efficient as the previous generation (Trillium), offering better performance per watt—a critical edge for sustainable AI computing.
Built for Gemini and the Future of AI Inference
Ironwood isn’t just about raw specs—it’s a core component of Google’s AI Hypercomputer platform. This system brings together custom-designed hardware, low-latency networking, and a robust software stack—all optimized for models like Gemini 1.5 and beyond.
The AI Arms Race: Why Inference Now Matters More Than Ever
As AI goes mainstream, inference—the part where the AI delivers a real-time response—is becoming just as critical as training. Google’s pivot toward optimizing inference comes at a time when chatbots, voice assistants, search enhancements, and business tools are all becoming AI-driven.
With Ironwood, Google aims to stay ahead of the curve in delivering low-latency, high-efficiency AI responses at scale.
What It Means for the Future
The unveiling of Ironwood sends a strong message to the industry: Google is not just competing in AI software—it’s building the infrastructure that powers it. By combining raw computing power with sustainability, Ironwood sets a new standard in AI performance.
As more businesses integrate AI into daily operations, tools like Ironwood may become essential in balancing speed, cost, and energy demands. For developers, startups, and enterprises alike, the arrival of Ironwood opens doors to build more powerful, scalable, and real-time AI applications.
Setting a New Standard in AI Infrastructure
By unveiling Ironwood, Google is sending a clear message: it’s not just building AI models—it’s building the infrastructure that runs them.
With enterprise adoption of AI soaring, Ironwood gives developers and organizations the tools they need to:
- Deliver faster, real-time AI outputs
- Operate with lower energy and operational costs
- Scale applications without hitting performance ceilings
