Nvidia reported earnings on Wednesday, and as expected, the numbers were good. Really good. The company gets more than 91% of its sales from its data center unit, which generated revenue of $193,737 billion, up 68% year-over-year.<\/p>\n
\u201cWe have now scaled our data center business by nearly 13x since the emergence of ChatGPT in fiscal 2023,\u201d Nvidia CFO Colette Kress said in the company\u2019s earnings call on Wednesday.<\/p>\n
While very impressive, the number is not all that surprising given that global AI spending is expected to reach $2.5 trillion<\/a> this year, and Nvidia\u2019s largest customers, the major AI hyperscalers Amazon<\/a>, Alphabet<\/a>, Meta<\/a>, and Microsoft<\/a>, all reported record capex figures earlier this month.<\/p>\n The hyperscalers also made eyewatering financial commitments for 2026 totaling nearly $700 billion,<\/a> which came to the dismay of many investors who have been growing wary of AI spending.<\/p>\n Earlier this month, Evercore analysts warned<\/a> that the huge capex could turn the hyperscalers\u2019 cash flow negative.<\/p>\n And despite the record after record multibillion-dollar commitment made to scale AI infrastructure and grow the technology\u2019s adoption across the American economy, the results are yet to fully materialize. A Goldman Sachs analyst recently said that AI contributed \u201cbasically zero<\/a>\u201d to U.S. GDP in 2025.<\/p>\n Nvidia CEO Jensen Huang spent most of his time in the investor call trying to justify that capex growth.<\/p>\n \u201cI am confident in their cash flow growing, and the reason for that is very simple: we have now seen the inflection of agentic AI and the usefulness of agents across the world in enterprises everywhere,\u201d Huang said.<\/p>\n AI adoption by enterprises beyond the tech world, and whether these companies actually see real productivity gains and revenue returns from AI integration, is really important to Nvidia, because that\u2019s a major thing that the AI industry is currently lacking to quell worries over an AI bubble<\/a>.<\/p>\n A recent survey<\/a> found that despite 70% of firms employing AI, over 80% reported no impact on employment or productivity.<\/p>\n Last week, OpenAI COO Brad Lightcap told TechCrunch<\/a> that his company had \u201cnot really seen enterprise AI penetrate enterprise business process.\u201d<\/p>\n Some experts believe that Anthropic\u2019s Claude Cowork<\/a> unveiled earlier this month is going to be a turning point in AI\u2019s penetration into the workforce, so much so that they believe it will lead to a mass extinction-level event<\/a> for software companies, and maybe even white-collar work. Huang gave a special shout-out to Claude Cowork in the call as well.<\/p>\n Huang also had a technical explanation to justify the capex commitments.<\/p>\n \u201cIn this new world of AI, compute equals revenues,\u201d Huang said, a phrase that he repeated many times throughout the call. Huang argues that tokens<\/a>, aka the chunks of data that AI models process, are the most important part of a new AI economy. The more tokens a model uses, the more computing power and time it requires. So, as models are getting more complex, the demand for computing is also going up \u201cexponentially,\u201d Huang said. He argued that the capex commitments will go towards building this compute capacity, which will thus power higher-level models and translate to revenue.<\/p>\n \u201cThe amount of token generation capability that the world needs is a lot, more than $700 billion, and I\u2019m fairly confident that we\u2019re going to continue to generate tokens\u2026fundamentally because every single company depends on software, every software will depend on AI, and so every company will produce tokens,\u201d Huang said. \u201cIf the new software requires tokens to be generated and the tokens are monetized, then it stands to reason that their data center build-out directly drives their revenues.\u201d<\/p>\n Huang\u2019s justifications may not have immediately convinced the market. Even though shares rose at first in response to the report, after the call, gains eventually pulled back to less than 1%. That\u2019s despite revenue that exceeded market expectations.<\/p>\n OpenAI and China are still blind spots <\/p>\n Throughout the call, Huang also tried to address rumors<\/a> of a falling out with OpenAI, first spurred after a $100 billion Nvidia investment announced back in September 2025 reportedly failed to progress beyond the early stages after months. Then, two back-to-back reports claimed that Huang was privately criticizing OpenAI\u2019s business approach while OpenAI was unhappy with the inference speed of Nvidia\u2019s chips.<\/p>\n In the call on Wednesday, Huang repeatedly praised the AI giant\u2019s offerings, but revealed that the investment was still not finalized.<\/p>\n \u201cWe continue to work with OpenAI toward a partnership agreement, and believe we are close,\u201d Huang said on the call. The filing also refuses to give any assurance that \u201ca transaction will be completed.\u201d<\/p>\n Another piece of uncertainty weighing on Nvidia is China. The company shared that, as of this month, the Trump administration has finally allowed it to start shipping small amounts of its H200 chips<\/a> to China, where it once held 95% of the market share<\/a> before Trump first banned the chipmaker\u2019s sales to China, sparking a saga<\/a> of dizzying trade tit-for-tat between the two global superpowers. But executives still don\u2019t know if the imports will be allowed in, and are not factoring it into the revenue they expect this year.<\/p>\n","protected":false},"excerpt":{"rendered":"Nvidia reported earnings on Wednesday, and as expected, the numbers were good. Really good. The company gets more…\n","protected":false},"author":2,"featured_media":19456,"comment_status":"","ping_status":"","sticky":false,"template":"","format":"standard","meta":{"footnotes":"","_share_on_mastodon":"0"},"categories":[4],"tags":[225,9161,12796,6007,17],"class_list":["post-19455","post","type-post","status-publish","format-standard","has-post-thumbnail","category-switzerland","tag-artificial-intelligence","tag-gpus","tag-jensen-huang","tag-nvidia","tag-switzerland"],"share_on_mastodon":{"url":"","error":""},"_links":{"self":[{"href":"https:\/\/www.europesays.com\/ch\/wp-json\/wp\/v2\/posts\/19455","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.europesays.com\/ch\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.europesays.com\/ch\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.europesays.com\/ch\/wp-json\/wp\/v2\/users\/2"}],"replies":[{"embeddable":true,"href":"https:\/\/www.europesays.com\/ch\/wp-json\/wp\/v2\/comments?post=19455"}],"version-history":[{"count":0,"href":"https:\/\/www.europesays.com\/ch\/wp-json\/wp\/v2\/posts\/19455\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.europesays.com\/ch\/wp-json\/wp\/v2\/media\/19456"}],"wp:attachment":[{"href":"https:\/\/www.europesays.com\/ch\/wp-json\/wp\/v2\/media?parent=19455"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.europesays.com\/ch\/wp-json\/wp\/v2\/categories?post=19455"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.europesays.com\/ch\/wp-json\/wp\/v2\/tags?post=19455"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}