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.”
Read more about Anthropic’s S-1 filing
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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