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Data Center News > Blog > Global Market > Google’s cheaper, faster TPUs are here, while users of other AI processors face a supply crunch
Global Market

Google’s cheaper, faster TPUs are here, while users of other AI processors face a supply crunch

Last updated: November 8, 2025 11:36 am
Published November 8, 2025
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Alternatives for the AI businessThe legacy drawback

Alternatives for the AI business

LLM distributors resembling OpenAI and Anthropic, which nonetheless have comparatively younger code bases and are repeatedly evolving them, even have a lot to achieve from the arrival of Ironwood for coaching their fashions, mentioned Forrester vice chairman and principal analyst Charlie Dai.

Actually, Anthropic has already agreed to acquire 1 million TPUs for coaching and its fashions and utilizing them for inferencing. Different, smaller distributors utilizing Google’s TPUs for coaching fashions embrace Lightricks and Important AI.

Google has seen a gradual enhance in demand for its TPUs (which it additionally makes use of to run interna providers), and is predicted to purchase $9.8 billion value of TPUs from Broadcom this 12 months, in comparison with $6.2 billion and $2.04 billion in 2024 and 2023 respectively, in response to Harrowell.

“This makes them the second-biggest AI chip program for cloud and enterprise information facilities, simply tailing Nvidia, with roughly 5% of the market. Nvidia owns about 78% of the market,” Harrowell mentioned.

The legacy drawback

Whereas some analysts have been optimistic in regards to the prospects for TPUs within the enterprise, IDC analysis director Brandon Hoff mentioned enterprises will most certainly to avoid Ironwood or TPUs typically due to their current code base written for different platforms.

“For enterprise prospects who’re writing their very own inferencing, they are going to be tied into Nvidia’s software program platform,” Hoff mentioned, referring to CUDA, the software program platform that runs on Nvidia GPUs. CUDA was launched to the general public in 2007, whereas the primary model of TensorFlow has solely been round since 2015.

See also  Google's newest Gemini 2.5 model aims for 'intelligence per dollar'

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TAGGED: Cheaper, crunch, face, faster, Googles, processors, Supply, TPUs, users
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