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Nvidia forecasts Q3 revenue of $108B, above $104B est., expects FY 2028 revenue to grow by ~70%, and expands its AWS deal through 2028; NVDA jumps 6%+

Deborah Mary Sophia /Reuters:

Reuters Deborah Mary Sophia

Context & Ripple Effects

Nvidia’s earnings guidance has repeatedly reset expectations: its 2023 outlook shock followed a revenue decline, while its 2024 Data Center surge and 2025 results showed that the data-center business was becoming the company’s primary growth engine.

The latest figures put that trajectory at a far larger scale. Q2 revenue reached $96.2 billion, including $89 billion from Data Center, while Edge Computing contributed $7.2 billion; the Q3 outlook and FY 2028 growth expectation extend the same infrastructure-demand signal beyond a single quarter.

First-order effects

  • Nvidia sets a $108 billion Q3 revenue benchmark above the $104 billion estimate, lifting expectations for the company’s near-term sales and prompting a more than 4% after-hours move in NVDA.
  • The $89 billion Data Center business remains the central driver of Nvidia’s outlook, while $7.2 billion in Edge Computing gives Nvidia a second reported growth channel.

Second-order effects

  • Data-center buyers using Nvidia systems receive a stronger signal that AI-computing spending is persisting, making Nvidia’s delivery capacity and product roadmap more consequential to their infrastructure plans.
  • A projected roughly 70% FY 2028 revenue increase raises the performance bar for Nvidia’s chip rivals and for companies seeking to capture value in AI infrastructure beyond the accelerator itself.

Third-order effects

  • If Nvidia sustains guidance at this scale, the AI infrastructure cycle becomes increasingly defined by whether customers can finance, deploy and utilize the computing capacity Nvidia supplies rather than by chip demand alone.
  • The mix of large Data Center revenue and growing Edge Computing revenue points toward AI value capture spanning centralized training infrastructure and distributed inference deployments, though the reported figures do not establish the eventual balance between them.

The trend: Nvidia’s forecast is another marker of an AI infrastructure supercycle in which accelerator demand is shaping both data-center investment and the economics of deploying inference at scale.

Discussion

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