Catenaa, Friday, June 19, 2026- Google is making an ambitious play for a major stake in chips that power AI, using Nvidia’s playbook.
Google has been demonstrating how it can use Nvidia’s playbook to win customers by hosting an AI data center cluster called Lake Mariner.
Alphabet-owned Google has provided a $3.2 billion financial guarantee for the project, whose developers will rent the computing power from thousands of its microprocessors to the AI giant Anthropic, according to people familiar with the matter.
It is the same strategy Nvidia has used time and again to stoke already-blazing demand for its own artificial-intelligence chips.
Until recently, Nvidia had that market all but to itself, with its graphics processing units (GPUs) coveted by tech companies for their power to train and run AI models.
As the AI race has morphed over the past year into a contest for computing resources, challengers have begun to edge in—none of them more formidable than Google.
“You have all these very well-capitalized companies who are big believers that this market around compute is going to have tremendous value,” said Nazar Khan, Co-Founder and Chief Technology Officer of the AI infrastructure company TeraWulf, which is developing Lake Mariner with FluidStack, a Google-backed cloud provider, to WSJ. “They want to be in the game; they don’t want to be left behind.”
In corralling customers for its chip, known as tensor processing units, or TPUs, Google has mimicked Nvidia’s practice of using financial guarantees to help data centers raise cheaper debt and provide so-called circular financing, in which some of the money it invests flows back in the form of chip purchases.
A shake-up in the leadership of its Cloud unit has increased the level of urgency, WSJ reported.
Nvidia has a close partnership with and is a major investor in OpenAI; Google has a similar relationship with Anthropic, as well as its own frontier model, Gemini.
In private and in public, Huang has played down Google’s ability to compete with his company meaningfully.
In April, appearing on the podcaster Dwarkesh Patel’s show, Huang said Nvidia enjoys a wide lead over Google and other makers of custom chips, known as ASICs, and argued that Anthropic is Google’s only significant external customer for the TPU.
“Our market reach is far greater than any TPU or ASIC can have,” Huang said. “I would love to hear them demonstrate the cost advantage of TPUs. It makes no sense in my mind.”
In its most direct challenge to date, Google recently struck a $5 billion deal with Blackstone to establish a new cloud-services company that would compete with CoreWeave and Nebius, two Nvidia-backed cloud providers that exclusively use the chip giant’s hardware stack.
Google saw the computing crunch coming a long way off, beginning with what one of its top scientists called a “thought experiment.”
In 2013, Jeff Dean was working alongside other artificial-intelligence researchers on speech recognition, using the neural-network technology that underpins today’s large language models.
At first, the company kept that hardware to itself. It used the chips to develop AI models and features for its search engine and other products.
As demand for chips exploded, the company began making them available to other companies through its Cloud platform. The move has driven the rapid growth of that unit.
