• Anthropic is touting its ability to use different AI chips in its initial public offering filing.
• Analysts say a multichip strategy could weaken Nvidia's pricing power.
• Switching chips is hard and expensive, putting it out of reach for smaller players.

Anthropic is hedging its bets by using multiple chips to handle its AI work — a strategy that could eventually erode Nvidia's dominance.

The AI lab says it manages compute "as a single, fungible pool from multiple strategic partners" — with software that can direct its work to different chips depending on where they're most productive, according to Anthropic's S-1 filing, which came out Monday as the company prepares to go public.

Anthropic says it uses hardware from four chip families: Amazon Trainium, Google TPUs, Nvidia GPUs, and AMD GPUs.

That flexibility, which Anthropic said "took years and significant investment to build," could make major AI companies less dependent on Nvidia over time and give them more negotiating leverage, analysts said.

"The real exposure could be Nvidia's pricing power," said Patrick Moorhead, founder and CEO of Moor Insights & Strategy, "because a customer that can shift work across four platforms negotiates very differently than one that can't."

Ashish Nadkarni, an analyst at IDC, added that a multichip approach also makes Anthropic less vulnerable to fluctuations in Nvidia's chip supply.

Breaking Nvidia's grip isn't easy

Although Anthropic's chip mix isn't new, the company is now pitching it as a core advantage to investors, Moorhead said.

The threat has its limits. Switching between chips is still difficult — especially when it comes to training AI models as opposed to running them, Moorhead said — and only the biggest AI companies have the resources to do it.

Anthropic also continues to spend billions on Nvidia compute, Moorhead said.

Gil Luria, head of technology research at D.A. Davidson, said that while other major companies like OpenAI likely take a multichip approach, it may not be worth the effort and investment for smaller players.

Brad Gastwirth, global head of research and market intelligence at Circular Technology, said Anthropic's strategy doesn't represent a major near-term threat. Having more chip options doesn't erase Nvidia's advantages in performance, networking, and software, he said.

There's a broader risk for Nvidia if AI compute becomes more of a commodity.

Citadel CEO Ken Griffin has warned that if supply overtakes demand, it could drive down rental prices.

"GPUs, like airlines, have a very low marginal cost to run," he told Bloomberg last week. "The moment you have overcapacity, pricing goes into freefall."

Nvidia did not immediately respond to a request for comment from Business Insider.

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• Infrastructure startup Hyperbolic raised a $30 million round led by Intel CEO Lip-Bu Tan's VC firm.
• The startup connects companies with neoclouds and makes their AI chips easier to use.
• Hyperbolic also wants to let customers resell unused computing power.

Intel CEO Lip-Bu Tan is backing an infrastructure startup that has raised $30 million to help companies rent compute across hundreds of different AI cloud providers.

Hyperbolic, an AI chip marketplace and software startup, has raised $50 million to date.

Walden Catalyst, the venture capital firm founded by Tan and former Samsung president Young Sohn, led the Series A-1 funding round. Dell Technologies Capital, General Catalyst, Vista Equity Partners, and Cambium Capital also participated.

As companies scramble for computing power, one challenge is that AI cloud providers, or neoclouds, use a mix of different chips, networking, and software. Hyperbolic helps customers find compute resources from different providers and creates software that makes it easier to use them all, rather than dealing with each one separately.

"It's been a really fragmented market that makes the customer experience really painful," said 31-year-old founder and CEO Jasper Zhang.

Hyperbolic also wants to let customers resell compute that they're paying for but no longer need.

The four-year-old startup works closely with about 30 neoclouds, including WhiteFiber and Vector Core Compute. It says it has roughly $200 million worth of compute connected to its software annually.

Hyperbolic previously raised a $12 million Series A round in 2024, led by Variant and Polychain Capital, following a $7 million seed round earlier that year. The company expects to have 50 employees by the end of the year and will use its funding to expand software tools for managing AI chips across different neoclouds.

Zhang said the company is aiming for $150 million in annual recurring revenue by the end of the year and is already breaking even. More than 250,000 developers, including teams at Modal, Higgsfield, and Daytona, use Hyperbolic.

Before founding the company, Zhang worked as a quantitative researcher at Citadel Securities. As Wall Street explores ways to financialize AI chips, he said his startup's plans to let companies resell unused compute could help pave the way for a futures market.

Here's a look at the pitch deck Hyperbolic used to raise its $30 million Series A-1. Slides have been redacted so that the deck can be shared publicly.