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 computing “as a single, fungible pool from multiple strategic partners” — with software that can direct its work to different chips based on where they are most productive, according to Anthropic’s S-1 filing, released Monday as the company prepares to go public.
Anthropic claims to use 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 large AI companies less dependent on Nvidia over time and give them more negotiating leverage, analysts said.
“The real exposure might be Nvidia’s pricing power,” said Patrick Moorhead, founder and CEO of Moor Insights & Strategy, “because a customer who can move their work across four platforms trades very differently from one who can’t.”
Ashish Nadkarni, an analyst at IDC, added that a multi-chip approach also makes Anthropic less vulnerable to fluctuations in Nvidia’s chip supply.
Breaking Nvidia’s grip isn’t easy
While Anthropic’s chip mix isn’t new, the company is now touting it as a key advantage for investors, Moorhead said.
The threat has its limits. Moving from one chip to another is still difficult — especially when it comes to training AI models rather than 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 DA Davidson, said that while other large companies like OpenAI are likely taking a multi-chip 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 does not pose a major threat in the near term. Having more chip options doesn’t erase Nvidia’s advantages in performance, networking and software, he said.
There is a broader risk for Nvidia if AI computing becomes more of a commodity.
Citadel CEO Ken Griffin warned that if supply exceeds demand, it could drive down rental prices.
“GPUs, like airlines, have a very low marginal cost of running,” he told Bloomberg last week. “As soon as there is overcapacity, prices plummet.”
Nvidia did not immediately respond to a request for comment from Business Insider.
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