Today’s frontier models, including Google’s Gemini, Veo, Imagen, and Anthropic’s Claude train and serve on Tensor Processing Units (TPUs). For many organizations, the focus is shifting from training these models to powering useful, responsive interactions with them. Constantly shifting model architectures, the rise of agentic workflows, plus near-exponential growth in demand for compute, define this […]

Today, we are thrilled to announce C4A metal, our first bare metal instance running on Google Axion processors, available in preview soon. C4A metal is designed for specialized workloads that require direct hardware access and Arm®-native compatibility.  Now, organizations running environments such as Android development, automotive simulation, CI/CD pipelines, security workloads, and custom hypervisors can […]

Decision makers and builders today face a constant challenge: managing rising cloud costs while delivering the performance their customers demand. As applications evolve to use scale-out microservices and handle ever-growing data volumes, organizations need maximum efficiency from their underlying infrastructure to support their growing general-purpose workloads. To meet this need, we’re excited to announce our […]

As machine learning models continue to scale, a specialized, co-designed hardware and software stack is no longer optional, it’s critical. Ironwood, our latest generation Tensor Processing Unit (TPU), is the cutting-edge hardware behind advanced models like Gemini and Nano Banana, from massive-scale training to high-throughput, low-latency inference. This blog details the core components of Google’s […]

If you’re a developer, you’ve seen generative AI everywhere. It can feel like a complex world of models and advanced concepts. It can be difficult to know where to actually start. The good news is that building your first AI-powered application is more accessible than you might imagine. You don’t need to be an AI expert […]