Nvidia's Q2 FY27 Revenue Hits $96.2 Billion, With $108 Billion Forecast for Next Quarter

Nvidia reported $96.2 billion in revenue for the second quarter of fiscal 2027, a record that topped the previous quarter's $81.6 billion by more than $10 billion. The company forecast third-quarter revenue of $108.0 billion, plus or minus 2%, above analysts' average estimate of $104.19 billion (Economic Times). If Nvidia hits the midpoint of that guidance, it will join a revenue tier reached only by Amazon, Apple, and Alphabet — companies that have repeatedly posted $100 billion-plus quarters (The Verge).

The results, announced August 26, 2026, were driven almost entirely by data center demand. Data center revenue more than doubled year-over-year to a record $89 billion. Net income more than doubled as well, reaching $59.7 billion (Nvidia).

The trajectory is steep by any measure. Q2 FY27 revenue is up from $81.6 billion in Q1 FY27, which itself was up 85% year-over-year (Nvidia). In Q1, Nvidia had forecast revenue of $91.0 billion, plus or minus 2%; the actual result cleared that by roughly $5 billion. The quarter before that, Q4 FY26, posted $62.3 billion in data center revenue alone, up 22% sequentially. Full-year fiscal 2026 revenue was $215.9 billion (Nvidia). Going back further, Q3 FY26 brought $57.0 billion in total revenue with $51.2 billion from data center (Nvidia Investor Relations). Each quarter has set a new record.

What stands out is the acceleration, not just the magnitude. Data center revenue went from $51.2 billion in Q3 FY26 to $89 billion in Q2 FY27 — a span of three quarters. That is a 74% increase in a business line that was already the largest in the industry. Profits tracked accordingly, from a business whose margins have remained structurally high throughout the AI buildout.

The consumer side of Nvidia's business tells a different story. The company's "edge computing" category, which includes gaming GPUs, generated $7.2 billion last quarter, up 27% year-over-year. Nvidia attributed softer consumer PC sales to "elevated memory and systems prices" (The Verge). Component shortages are driving up prices for consumer graphics cards, creating a tension between demand and affordability that Nvidia has flagged explicitly in its own commentary (CFO Commentary).

Nvidia also warned of price hikes for its AI chips ahead of the earnings report (The Verge). With data center customers already absorbing massive capex commitments, the prospect of rising per-unit costs adds a variable that enterprise buyers will need to model. Supply constraints across the AI chip stack, from HBM (high-bandwidth memory, a type of fast memory used in AI accelerators) to advanced packaging, have been a persistent theme, and Nvidia's decision to signal higher prices suggests those pressures are not abating.

In practical terms, Nvidia's quarterly revenue is now growing at an absolute scale that few companies have reached in history. A $12 billion sequential increase, the jump from Q1 to Q2 FY27, exceeds the total quarterly revenue of most S&P 500 companies. The $108 billion guidance for Q3 implies another $12 billion step up, which would bring Nvidia to roughly the quarterly run rate of Alphabet if the guidance is met.

The demand signal is clear: hyperscaler (the largest cloud providers — Amazon, Microsoft, Google, and Meta) and enterprise AI infrastructure spending continues to compound, and Nvidia is capturing the overwhelming majority of the spend on accelerators — specialized chips designed to speed up AI workloads. The supply-side picture is more mixed. Consumer GPU prices are rising due to component shortages, and AI chip prices are headed upward too. Nvidia is selling everything it can make and still forecasting another record.

Worth noting: Nvidia has now forecast, delivered, and exceeded record quarters in succession for over a year. Each guidance number has been met with skepticism about sustainability, and each quarter has cleared it. The pattern does not guarantee the next quarter will follow, but the consistent beat-and-raise cycle reflects a demand environment that, at least so far, has shown no sign of cooling.

The tension to watch is pricing. If AI chip prices rise meaningfully, the economics of large-scale model training and inference (the process of running a trained AI model to produce outputs) will shift, potentially reshaping which workloads remain cost-effective on Nvidia silicon versus alternative accelerators or cloud-provider custom silicon. Consumer GPU buyers, meanwhile, face a market where the cards they want are getting more expensive, not less. The data center is generating extraordinary profits. The consumer side is growing but constrained. Both stories are Nvidia's, and they are pulling in different directions.