Google Adds Secure and Long-Context Versions of Its TPUs in Push Against Nvidia
The TPU 8tx, built with AMD for governments and regulated industries, and the dual-chip TPU 8i Max are due next year, taking Google's eighth-generation line to four systems.
By Nakoda News Desk
·2 min read
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Google has introduced two new versions of its eighth-generation tensor processing units. One is aimed at governments and regulated companies that need to keep sensitive data protected while it is processed. The other is built for AI applications that work with very long context windows.
The products are called TPU 8tx and TPU 8i Max. Amin Vahdat, Google's chief technologist for AI infrastructure, told Bloomberg News they are "not new chips, but reconfigured versions designed to handle workloads customers have been asking for." He said both are due for release next year.
The launch matters because Google's chips, once kept for its own data centres, have become the most credible alternative to Nvidia's graphics processors in a market worth hundreds of billions of dollars. Selling several variants tuned to specific jobs, rather than one general-purpose accelerator, is how Google is trying to win customers that would otherwise buy Nvidia systems.
The TPU 8tx is a variant of the TPU 8t training chip. It is meant for secure and confidential workloads and runs alongside AMD processors under a partnership between the two companies, according to reports on the launch. Data Center Dynamics reported that the system pairs Google's silicon with custom AMD CPU hosts and is aimed at regulated enterprises and government agencies running sensitive data.
The TPU 8i Max builds on the TPU 8i inference chip. It puts two TPU chips in a single package to raise compute performance and memory capacity, which matters for models that must hold large amounts of text or data in working memory at once.
Google describes the new products as "TPU systems" rather than new chips, Data Center Dynamics reported, because the change is in how compute, networking, storage and packaging around the existing silicon are configured. The TPU 8t and TPU 8i were first shown at Google Cloud Next in April, when Google split its accelerator line into separate training and inference designs for the first time. The two additions bring the eighth generation to four configurations.
The pace is also new. Google has historically released one new AI processor about every two years, and this year it has announced two chips and now two further variants. Vahdat said the approach reflects Google's long-held view that "the future belongs to specialization," according to Bloomberg's report.
Investors are betting on that strategy. Analysts expect TPU-related sales, including chips, software and hardware, to exceed $135 billion by 2028, compared with about $12 billion estimated for this year, according to figures cited in coverage of the launch.
Alphabet shares rose more than 2% in premarket trading on Monday, Reuters reported. The stock had fallen 9% this year through Friday's close. Nvidia was down nearly 6% before the open. Its shares have been under pressure since its board opened an inquiry into reports that chief executive Jensen Huang was the target of a suspected Chinese intelligence operation, and after an analyst downgrade on Monday.
The security-focused variant matters for markets such as the Gulf, where governments and state-linked companies are building sovereign AI capacity and often require data to stay protected and under local control. Google has not said which customers have committed to the new systems, how they will be priced, or whether they will be offered only through Google Cloud or also installed in customers' own facilities.
Sources
- Bloomberg · Google Escalates Nvidia Rivalry With New Versions of Its TPU Systems
- Global Banking & Finance Review (Reuters) · Google to introduce two variants of in-house chips, Bloomberg News reports
- Data Center Dynamics · Google expands eighth-generation TPU portfolio with two new TPU systems
- TechFlow · Google Launches TPU 8tx and 8i Max, Ramping Up Its Challenge to NVIDIA
Produced with AI assistance from the sources above. How we work
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