Nvidia Revenue Concentrated in Two Big Customers

Nvidia’s Q2 boom masks heavy customer concentration

Nvidia reported a record $46.7 billion in revenue for the quarter ended July 27, a 56% year-over-year jump driven by demand for AI data center chips. But an SEC filing revealed a sharper picture underneath: one direct customer accounted for 23% of Q2 revenue and a second for 16%, meaning nearly 40% of the quarter came from just two buyers.

Those buyers are listed only as “Customer A” and “Customer B.” Nvidia clarifies these are direct customers—OEMs, system integrators, or distributors who buy chips straight from Nvidia. Indirect buyers, such as cloud service providers and major internet companies, typically purchase through those direct channels.

Nvidia’s CFO noted that large cloud service providers make up 50% of data center revenue, and data center sales represented 88% of total revenue—showing how cloud-driven AI demand funnels through the ecosystem and amplifies concentration at the vendor level.

• Revenue concentration: heavy dependence on a handful of buyers increases cash-flow volatility if buying patterns shift.
• Pricing and supply leverage: large customers can demand better terms or priority, affecting margins and allocation.
• Operational risk: production hiccups or shifts in a single buyer’s roadmap could ripple through Nvidia’s top-line performance.

Analysts note the double-edged nature of this concentration. On one hand, big customers have deep pockets and are expected to keep investing in AI infrastructure. On the other, the reliance on a small number of buyers is a material risk to monitor—think of it like a ship carrying most of its cargo in just two containers. If either container is lost, the voyage changes.

Beyond financial volatility, this pattern affects partners and policymakers. Suppliers and system integrators may need to rework contracts, governments and regulators may scrutinize market concentration, and customers downstream should assess whether their cloud provider’s demand creates hidden dependencies.

Practical steps for organizations

• Map direct and indirect supplier exposure to understand who ultimately drives demand.
• Run scenario-based forecasts for revenue and capacity under different customer spending trajectories.
• Negotiate diversified contracts and contingency supply channels to reduce single-buyer risk.

For investors and partners, the headline growth is impressive but the concentration detail changes the risk profile. Companies riding the AI wave should ask hard questions about how much of their growth depends on a very small set of customers and whether those buyers’ spending is sustainable beyond the current AI infrastructure cycle.

Nvidia’s numbers illustrate a familiar pattern in fast-growing tech markets: explosive demand can come bundled with concentrated exposure. Organizations that combine rigorous supplier mapping, scenario modeling, and operational contingency planning will be best positioned to turn that exposure into predictable, long-term growth.

QuarkyByte’s approach to this kind of disclosure is to translate percentages into practical actions: we trace indirect dependencies, quantify financial sensitivity to customer shifts, and build stress tests that show when to diversify, when to lock in supply, and when to seize negotiating leverage.