TEMPO.CO, Jakarta
The American semiconductor manufacturer Nvidia has announced unprecedented quarterly revenue, with the ongoing global artificial intelligence (AI) surge driving substantial investments in data center infrastructure.
According to Anadolu Agency, Nvidia achieved revenue of $81.6 billion for the fiscal first quarter concluding on April 26, 2026. This marks an impressive 85 percent increase from the same timeframe last year, alongside a 20 percent rise from the preceding quarter.
The data center sector of the company has been the primary catalyst for this growth, yielding a record $75.2 billion in revenue—a remarkable 92 percent increase year-over-year. Previously, Nvidia reported $60.4 billion in data center compute revenue and $14.8 billion from networking services.
Jensen Huang, the founder and CEO of Nvidia, characterized this rapid acceleration of AI infrastructure as “the largest infrastructure expansion in human history.”
“The construction of AI factories is hastening at an extraordinary pace,” Huang noted in the company’s earnings report. He emphasized that “agentic AI has arrived,” a reference to advanced AI systems now capable of executing increasingly autonomous functions across diverse sectors.
Nvidia’s financial metrics are widely interpreted by investors as indicative of the broader global AI boom, particularly reflecting the swift establishment of data centers by leading technology firms.
The report highlighted that US tech giants are projected to collectively invest around $750 billion this year in AI infrastructure, with a significant portion earmarked for Nvidia’s chips and systems that are essential for powering AI models and cloud computing.
Surpassing Wall Street projections of $78.86 billion in quarterly revenue, Nvidia also reported earnings of $1.87 per share, eclipsing analysts’ forecasts of $1.76.
Net income in accordance with Generally Accepted Accounting Principles (GAAP) surged by 211 percent year-over-year, reaching $58.3 billion. In parallel, non-GAAP net income grew by 139 percent to $45.5 billion.
Free cash flow for the quarter amounted to $48.6 billion, up from $34.9 billion in the previous quarter and $26.1 billion a year ago.
Additionally, Nvidia announced an extraordinary $80 billion share repurchase authorization and increased its quarterly cash dividend from $0.01 to $0.25 per share.
For the forthcoming second fiscal quarter, Nvidia anticipates revenue of roughly $91 billion, with a margin of variance of two percent. However, the company noted this forecast excludes any expected revenue from data center compute in China.
China represents a politically sensitive market for Nvidia, particularly amidst rising geopolitical strains between Washington and Beijing concerning the export of advanced semiconductors.
A report from The Guardian indicated that Huang recently joined Donald Trump and Elon Musk aboard Air Force One en route to China, where he expressed optimism regarding potential Nvidia expansion in the Chinese market, despite existing export restrictions on advanced AI chips.
Nvidia’s Chief Financial Officer, Colette Kress, revealed that the company has yet to generate revenue from China under current export protocols, further stressing the uncertainty surrounding the situation.
In addition to its focus on China, Nvidia is amplifying its footprint in Southeast Asia. Singapore recently disclosed that Nvidia intends to establish a new AI research hub in the nation, aimed at enhancing AI infrastructure efficiency.
Earlier this year, Nvidia unveiled its upcoming AI platform, Vera Rubin, expected to launch in the second half of 2026. Huang described this platform as a “generational leap” that could potentially expedite global AI infrastructure advancement.
“I anticipate that we will face supply constraints throughout the entire lifecycle of Vera Rubin,” Huang remarked.
In the broader context, Nvidia has positioned itself at the epicenter of the global AI race, supplying pivotal components and systems to major organizations, including OpenAI and Anthropic, facilitating the training and operation of advanced AI models at scale.
Source link: En.tempo.co.
