Oracle and Google Announce Google TPUs on Oracle Cloud Infrastructure: Coming in 2027, a First for a Hyperscale Cloud Outside Google
Oracle and Google announced at Oracle AI World in Las Vegas, Nevada, on October 27 that Google's Tensor Processing Units (TPUs) will be available through Oracle Cloud Infrastructure (OCI), marking the first time Google TPUs will be offered on a hyperscale cloud platform outside Google. Google TPUs on OCI will be available in calendar year 2027, ramping over a multi-year period.
Google's eighth-generation TPU portfolio introduces two purpose-built architectures: TPU 8t, for training, cuts frontier model development cycles from months to weeks and delivers nearly three times the compute performance per pod over the previous generation; TPU 8i, for inference, is designed to handle the iterative work of many specialized agents. Google TPUs are custom accelerators co-designed with open software to power the full lifecycle — from frontier training and large-scale inference to the multi-step reasoning demands of agentic systems — and OCI will provide the power, cooling, and datacenter networking to deploy them at scale within its infrastructure.
'Different AI workloads have different compute needs,' said Mahesh Thiagarajan, president of Oracle Cloud Infrastructure. 'Bringing Google TPUs to OCI gives customers access to multiple leading AI compute architectures in one cloud. That choice gives them the flexibility to choose the right infrastructure for the performance, throughput, and economics of each AI workload.' Amin Vahdat, Google's senior vice president and chief technologist, AI & Infrastructure, said: 'The next generation of AI will require a diverse range of compute. TPUs give customers a powerful, purpose-built option for demanding training and inference workloads. Bringing Google TPUs to OCI will give more organizations access to this technology and greater flexibility in how they build and run their most complex AI applications.' (Quotations are reproduced as issued in the companies' release.)
The companies said that as models grow and production inference demands increase, the performance and economics of every training run and inference request become increasingly important, and customers will be able to choose Google TPUs within OCI, optimized for their workloads, performance requirements, and cost objectives.
Source: GSM · USA (original Chinese edition)
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