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NVIDIA reported $96.2 billion in revenue for the second quarter of fiscal 2027, up 106% year over year, with $89.0 billion coming from its Data Center business, up 117%. The company attributed that Data Center growth to the ramp of Blackwell Ultra infrastructure. Those figures show why Blackwell is central to NVIDIA’s results, but they do not mean Blackwell alone caused all of the company’s revenue growth—or that revenue is the same as profit.
What NVIDIA reported for fiscal Q2 2027
NVIDIA’s quarter ended July 26, 2026. In its August 26 results release, the company reported the following:
| Measure | Fiscal Q2 2027 | Year-over-year change |
|---|---|---|
| Total revenue | $96.2 billion | Up 106% |
| Data Center revenue | $89.0 billion | Up 117% |
NVIDIA’s fiscal Q2 2027 results release supplies the reported figures. Its Form 10-Q for the quarter says the Data Center increase reflected the ramp of Blackwell Ultra infrastructure. That is the company’s explanation of a major growth driver, not a breakdown proving how much revenue or profit came from Blackwell alone.
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1Scan for outdated or missing drivers - takes under a minute2Clear out junk files and repair common Windows errors3Fix the driver behind crashes, sound loss and screen glitchesHow much of NVIDIA’s revenue comes from Blackwell?
The reported $89.0 billion is Data Center revenue, not a Blackwell-only figure. NVIDIA’s public results materials attribute the Data Center increase to the Blackwell Ultra infrastructure ramp, but the figures cited here do not isolate revenue from Blackwell products or quantify Blackwell’s contribution to total company revenue. It would therefore be inaccurate to describe the full $96.2 billion as Blackwell revenue.
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Blackwell also spans more than one product category. NVIDIA’s filing discusses its Data Center business as well as graphics and workstation products. Large-scale AI infrastructure and consumer GeForce graphics cards are different offerings, aimed at different buyers and workloads; a consumer GPU is not a stand-in for the systems behind the Data Center result.
Why “earnings” needs a little precision
“Earnings through the roof” is a colloquial way to describe a striking financial result. The headline figures here are revenue figures: money NVIDIA reported from sales. They are not, by themselves, a measure of net income, operating profit, or earnings per share. The revenue increase is substantial, but it should not be described as a profit increase without separate profit figures.
For context, NVIDIA reported $68.1 billion in total revenue and $62.3 billion in Data Center revenue for fiscal Q4 2026, followed by $215.9 billion in full-year fiscal 2026 revenue, up 65%. These earlier company-reported figures provide scale, but differences between fiscal periods mean they should not be treated as a direct measure of Blackwell’s contribution to the later quarter. See NVIDIA’s fiscal 2026 results release.
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What NVIDIA said about demand and future growth
On NVIDIA’s August 26, 2026 earnings call, CEO Jensen Huang described demand across hyperscalers, AI labs, AI-native companies, enterprises, and sovereign customers. He characterized the moment this way: “The surge in AI demand is driving a global infrastructure buildout, supported by an expanding and diverse set of growth opportunities, spanning hyperscalers, AI labs, AI natives, enterprises, and sovereign customers.” This is management’s account of the customer environment, not an independent measurement of the whole AI market.
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Huang also said NVIDIA expected approximately 70% revenue growth in fiscal 2028, adding, “This is a supply-constrained outlook.” That is management guidance—not a result already achieved, an independent consensus estimate, or a guarantee. The company’s Q2 fiscal 2027 earnings call materials are the source for those remarks.
The call also described hyperscaler revenue of $49 billion, up 13% sequentially, with strength attributed to Blackwell. Those are figures and explanations from NVIDIA management. They should be read as reported company commentary, rather than independent confirmation of customer spending or the returns customers receive from deployments.
Customer concentration is a risk to watch
NVIDIA’s fiscal Q2 2027 Form 10-Q disclosed that one direct customer represented 16% of total revenue for the quarter, primarily in Compute & Networking. The filing does not name that customer in this disclosure. This concentration matters when considering how durable growth may be: a significant share of revenue can depend on a small number of large buyers, even as management describes a broader set of customer types.
Cloud deployments are plans, not completed sales
NVIDIA and AWS announced a plan for AWS to deploy two million additional NVIDIA GPUs over a multiyear period, including Blackwell Ultra and later Rubin products, and to expand Blackwell capacity in EC2 G7 instances. The announcement describes planned deployment, not GPUs already installed or revenue NVIDIA is guaranteed to collect. Details are in the AWS and NVIDIA announcement.
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NVIDIA’s May 2025 fiscal Q1 release said Blackwell cloud instances were then available through AWS, Google Cloud, Microsoft Azure, and Oracle Cloud Infrastructure. That is dated availability information, not a guarantee that a particular GPU, region, or price is available now. Check the provider’s current listings before planning a deployment. The historical statement appears in NVIDIA’s fiscal Q1 2026 results release.
Blackwell for a personal PC is a separate story
NVIDIA has consumer Blackwell graphics cards, including the GeForce RTX 5070. It is an adjacent product for PC buyers, not the infrastructure behind the company’s Data Center revenue attribution. The cited material does not establish current RTX 5070 pricing, stock, or marketplace availability, so check retailers and system compatibility before buying. NVIDIA identified the RTX 5070 as a Blackwell graphics card in its May 2025 fiscal Q1 results release.
If you are evaluating a consumer card, focus on the games or applications you use, graphics memory, power and cooling requirements, physical fit, and current local pricing. For cloud AI compute, compare accelerator availability by region, pricing model, memory and interconnect needs, software support, and data-security requirements. The company’s earnings figures do not determine which option is right for an individual user.
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