NVIDIA adds $442 billion after Q2 earnings reinforce AI demand

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TL;DR:

NVIDIA added about $442 billion in market value after fiscal Q2 results and a 70% growth outlook reassured investors that AI infrastructure demand is still expanding. The rally matters because NVIDIA’s scale now makes its earnings a market-wide test of AI spending.

Article:

NVIDIA added about $442 billion to its market value on Thursday after shares jumped 8.7%, pushing the AI chipmaker to roughly $5.49 trillion. The rally followed fiscal second-quarter 2027 results and a stronger-than-expected growth outlook, signalling that investors still see AI infrastructure spending as durable rather than a near-term peak. It was NVIDIA’s biggest one-day market-cap gain and the second-largest such increase on record.

The operating numbers gave investors the reason. Revenue for the quarter ended July 26 reached $96.2 billion, up 106% year on year, while data-center revenue rose 117% to $89 billion. NVIDIA guided current-quarter revenue to $108 billion and said fiscal 2028 revenue could grow about 70%, well above the roughly mid-40% growth analysts had expected.

Chief executive Jensen Huang said, “AI has reached its inflection point. It’s doing useful work. Its tokens are productive and profitable. Now, compute is revenue.” That framing matters because the debate has shifted from whether companies will buy AI systems to whether those systems can justify the enormous capital committed to chips, data centers and power.

Bloomberg Intelligence called the outlook “jaw-dropping,” saying it implied “more than $100 billion of potential upside to current estimates.” The market reaction also broke a four-quarter pattern in which NVIDIA shares fell after earnings despite meeting or beating expectations.

Risks remain. Reuters reported memory-component shortages could limit supply, while U.S. export restrictions continue to cloud China sales. For investors and the wider tech market, the next test is execution: whether NVIDIA can turn record demand into shipments, protect margins and show that enterprise AI spending is broadening beyond a handful of hyperscalers.