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Diving overview:
- Infrastructure major Revenue reported by Nvidia of $81.6 billion The company’s first quarter of fiscal 2027 increased 85% compared to the previous year As demand for AI infrastructure increases, executives said at an earnings conference: Wednesday.
- Data center revenue achieved $75.2 billion Sales for the quarter nearly doubled compared to the same period last year due to sustained demand. Blackwell Infrastructure Frontier model developers and hyperscalers deployed hundreds of thousands of Blackwell GPUs; CFO Colette Cress said On a call.
- Nvidia has introduced a new reporting framework for data center revenue. It contains two subsegments called. Hyperscale and ACIEThis includes AI Cloud, Industrial, and Enterprise. Hyperscale revenue accounted for half of total data center revenue.ACIE’s revenue reached $38 billion, an increase of 31% sequentially.
Dive Insight:
Nvidia’s latest earnings report shows that revenue is not entirely concentrated in hyperscalers, and the company is increasingly competing with hyperscalers for a larger slice of the AI infrastructure layer.
Nvidia’s data center revenue It was almost equally divided in between Hyperscale and ACIE subsegment. In addition to chips, the company sells integrated rack-scale infrastructure to customers across AI clouds, sovereign governments and enterprises, and said its customer base is growing. Futurum Group CEO Daniel Newman Emailed to CIO Dive.
“The introduction of ACIE as a permanent disclosure shows that the company views diversification from hyperscaler concentration as a feature of its business, rather than a hedge against it,” Newman said.
The company positions itself as the operating layer of AI infrastructure, including the entire enterprise AI stack. Scott Bickley, Info-Tech Research Group Advisory Fellowhe told CIO Dive in an email. Google, Microsoft, and AWS are also competing for enterprise spending by investing in the entire AI infrastructure layer, including chips, models, and applications. Global AI spending is expected to reach 2.59 trillion dollars in 2026, According to Gartner.
“This is important because the next phase of AI spending will not be driven solely by model training.” Bickley Said. “As inference expands across enterprises, governments, and hyperscalers, Nvidia is looking to further leverage the entire AI infrastructure stack.”
Nvidia’s customer base is “diverse and growing.” Cress he said at the financial results conference. Nvidia AI infrastructure is deployed in about 40 countries, and the company’s government revenue has increased more than 80% year over year, she said.
One of the drivers of the acceleration of AI infrastructure construction is the increased adoption of AI-native products and services and the increasing adoption of mainstream agents, Cress It added that the adoption of AI in the industry is driving revenue growth across energy, chips, infrastructure, models and applications.
On other fronts, Kress said the company has started shipping smoothly. vera rubin platform starting from second half of this year. The platform is expected to offer up to the following features: 35 times She said it has higher inference throughput compared to Blackwell.
Additionally, the U.S. government approved a license to Nvidia; Shipping H200 GPUs Kress said the company is not yet generating revenue from exports to China.
As Nvidia demonstrates diversification of its customer base, moves forward with Vera Rubin’s transition, monitors its re-entry into China and keeps an eye on ACIE’s earnings, Newman said the company’s durability heading into the new fiscal year becomes more important than the question of whether the hype cycle is real.
“NVIDIA remains the central nervous system of the AI economy,” Neumann said. “Rather than weakening, that position appears to be becoming more entrenched.”
