Nvidia GPUs are everywhere. Here are the ways companies are accessing them

Marc Benioff, chief executive officer of Salesforce Inc., left, and Jensen Huang, chief executive officer of Nvidia Corp., during the 2026 Dreamforce conference in San Francisco, California, US, on Tuesday, Sept. 15, 2026.

David Paul Morris | Bloomberg | Getty Images

Nvidia GPUs are the most sought-after processors in AI, and they're in such demand that the chipmaker's stock climbed to yet another record this week, lifting its market cap close to $6 trillion.

Customers can now shop around for access to the chips at the giant clouds from Amazon, Microsoft and Google, as well as at so-called neoclouds like CoreWeave. They can also go to various online marketplaces or even buy the costly hardware directly.

For Nvidia, it all adds up to unrelenting growth, as management anticipates $108 billion in revenue for the October quarter, which would mark an 89% year-over-year jump.

But the paradox of choice can be a headache for companies needing computing power yesterday.

While cloud infrastructure providers have ranked at the top of Nvidia's customer list for several years, the business is diversifying. Five clients accounted for at least 10% of Nvidia's accounts receivable in July quarter, up from three in January, according to a filing.

Industry research firm SemiAnalysis counted 323 Nvidia GPU providers as of September, up from 209 less than 11 months earlier.

"You're going to see a whole new crop of really, really exciting neoclouds with hundreds of billions of dollars backlog together," Nvidia CEO Jensen Huang said at a Goldman Sachs tech conference in San Francisco last month.

Here's a rundown of the various options for accessing GPUs, and why each might make sense:

Hyperscalers

Many big companies spend tens of millions of dollars per year on a smorgasbord of cloud services from Amazon, Google and Microsoft. Since the 2022 launch of ChatGPT, companies have increasingly turned to the hyperscalers for GPUs so they can run generative AI workloads.