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​Nvidia Stock Soars After Blowout Earnings as AI Demand Sends Shockwaves Through Big Tech

by
November 20, 2025

Nvidia (NVDA) delivered another blockbuster quarter on Wednesday, igniting a rally across the tech sector and reinforcing its position as the heart of the global AI buildout. The chipmaker smashed estimates and issued a stronger-than-expected revenue forecast, fueling double-digit gains in after-hours trading before the stock surged again Thursday morning.

The results sent waves through Big Tech and the entire semiconductor industry, with analysts pointing to one theme dominating the earnings call: demand for Nvidia’s AI chips is not just strong—it’s growing faster than the industry can produce supply.

Earnings That Reinforce Nvidia’s Grip on AI

For the fourth quarter, Nvidia projected roughly $65 billion in revenue, beating expectations by about $3 billion. The company posted $57.01 billion in Q3 revenue, far ahead of last year’s $35.1 billion, while earnings per share climbed to $1.30 compared with $0.81 a year earlier. CEO Jensen Huang described demand as “off the charts,” with Nvidia’s Blackwell chips and cloud GPUs sold out across sectors and geographies. The company’s data center division alone brought in $51.2 billion—nearly the size of some entire enterprise tech companies.

Nvidia’s CFO Colette Kress underscored that even older GPU architectures continue generating returns thanks to CUDA software improvements. “Our 6-year-old A100s are still running,” she emphasized, pushing back on recent claims that AI firms are inflating earnings by understating data center depreciation.

​A Rally That Lifts Big Tech and Reshapes Competition

Nvidia’s earnings didn’t just lift its own stock—they pulled the entire tech market higher. Shares of Meta, Alphabet, Amazon, Microsoft, and AMD all climbed on Thursday, supported by fresh faith that the AI cycle is nowhere near peaking.

Industry analysts noted that Nvidia’s ability to sustain overwhelming demand effectively forces hyperscalers, cloud providers, and model developers to follow its roadmap. With GPUs backlogged and cloud capacity stretched, companies across Silicon Valley are being pushed into multi-year commitments for Nvidia’s chips, locking the whole sector into a capital-intensive race for compute.

Even competition appears to benefit. AMD CEO Lisa Su recently projected that the data-center AI market could hit $1 trillion by 2030. Bloomberg analysts noted that AMD, far from being crushed by Nvidia’s dominance, may instead ride the same wave as customers clamor for alternatives in an undersupplied market.

Wall Street, Hedge Funds, and AI Skeptics Hold Their Breath

Despite Nvidia’s record performance, the rally comes amid skepticism from high-profile investors. Michael Burry recently argued that AI companies are masking costs by minimizing infrastructure depreciation. At the same time, Peter Thiel’s hedge fund and SoftBank both dumped their Nvidia stakes before the earnings announcement—selling billions in stock.

The response from Nvidia executives was pointed: long GPU life is a feature, not an accounting trick. CUDA’s software stack keeps older hardware relevant, they say, extending its value in a way physical capital typically can’t achieve. Yet the controversy captures a larger debate: are AI firms truly in a “virtuous cycle,” as Huang says, or is Wall Street racing ahead of tangible returns?

Looking Ahead

Nvidia’s earnings confirmed that the AI rollout is scaling faster than even bullish analysts predicted, and the company remains at the center of nearly every major deployment. With chips sold out, cloud capacity stretched, and Big Tech racing to secure compute, the market is treating Nvidia’s guidance as a signal that the AI boom still has years of runway.

But investors are watching two pressure points: sustained profitability in cloud AI and whether competitors like AMD, Intel, and custom in-house chips from hyperscalers can meaningfully loosen Nvidia’s grip. For now, the rally stands. What remains to be seen is whether the rest of Big Tech can translate AI spending into broader earnings before the bill for the race comes due.

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