Las Vegas, October 27 (Reuters) / PRNewswire — At Oracle AI World, Oracle and Google today announced that Google’s Tensor Processing Units (TPUs) will be available through Oracle Cloud Infrastructure (OCI), marking the first time Google’s TPUs are offered on a hyperscale cloud platform outside of Google. By integrating Google’s TPUs—designed specifically for AI—into OCI’s AI compute portfolio, customers will gain greater flexibility to match their most demanding workloads with infrastructure optimized for near-linear scaling and highly efficient economics.
Mahesh Thiagarajan, President of Oracle Cloud Infrastructure, said: "Different AI workloads have varying compute requirements. Introducing Google TPUs into OCI enables customers to use multiple leading AI compute architectures on a single cloud platform. This choice allows them to select the most suitable infrastructure for each AI workload in terms of performance, throughput, and cost-effectiveness."
Google TPUs are custom accelerators co-designed with open software to support the entire AI lifecycle—from cutting-edge model training and large-scale inference, to the multi-step reasoning data requirements needed for agent AI. OCI will provide power, cooling, and data center networking to enable large-scale deployment of Google TPUs within its infrastructure.
Amin Vahdat, Senior Vice President and Chief Technology Officer of Google AI and Infrastructure, said: "The next generation of AI will require diverse computing power. TPU provides a powerful, purpose-built solution for demanding training and inference workloads. Bringing Google TPU to OCI will enable more organizations to access this technology and gain greater flexibility when building and running the most complex AI applications."
Provide more AI computing options for each workload
As model sizes grow and demand for inference in production environments increases, the performance and cost-efficiency of each training and inference request become increasingly critical. Google’s TPU architecture is designed to maximize AI processing power per watt and enable fast access to model data and high-speed communication between chips.
Google TPUs support large model training and post-training, including dense models and Mixture of Experts (MoE) models, and are also suitable for production inference in applications such as agents and long-context scenarios. Customers will be able to select Google TPUs in OCI that are optimized for their workloads, performance requirements, and cost targets.
With over a decade of experience in custom AI chip development, Google’s TPU portfolio delivers dedicated computing power optimized for large-scale machine learning workloads. Google’s eighth-generation TPU introduces two specialized architectures: the TPU 8t for training and the TPU 8i for inference. Google states that the TPU 8t can reduce the development cycle for state-of-the-art models from months to weeks and nearly triples the computational performance per pod compared to the previous generation; the TPU 8i is designed to handle iterative workloads for numerous specialized agents.
Google TPU services on OCI will be launched within the calendar year 2027 and will be gradually expanded over several years to meet customer needs.
More resources
- Learn about Oracle Cloud Infrastructure
- Learn about Oracle AI infrastructure
- Learn about Google Cloud TPUs
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