NVIDIA Stock Price, Performance & Key Factors to Watch

NVIDIA trades near USD 219, holding above its historic USD 5 trillion market cap. Record Q2 revenue hit USD 96.2 billion, with Data Center sales up 117 %. Huang's trillion-dollar demand outlook remains unfulfilled orders, not booked revenue. September's semiconductor selloff exposed real doubts about AI spending's staying power.
NVIDIA Stock Price, Performance & Key Factors to Watch
Written By:
Murali Teja
Published on
Updated on

Overview

  • NVIDIA trades near USD 219, holding above the USD 5 trillion market cap it first reached in October 2025

  • Q2 fiscal 2027 revenue hit a record USD 96.2 billion, with Data Center revenue up 117 % from a year earlier

  • A mid-September semiconductor selloff highlighted growing market questions about the durability of AI infrastructure spending

NVIDIA has turned into one of the clearest signals of how fast the AI infrastructure boom is moving. Every earnings call now shapes expectations across the entire technology sector, not just for the company itself. 

The stock does not just track NVIDIA's own results anymore. It tracks how much money hyperscalers, governments, and enterprises are willing to pour into GPUs, networking gear, and data centers over the next few years.

NVIDIA stock price today

As of September 17, 2026, NVDA closed near USD 219.34, giving NVIDIA a market capitalization of roughly USD 5.30 trillion. The company became the first in history to cross the USD 5 trillion market cap mark in October 2025. At the time, it stood ahead of Microsoft, near USD 4 trillion, and Apple, near USD 3.9 trillion. NVIDIA has stayed above that USD 5 trillion level since.

NVIDIA stock snapshot

The wide gap between the lowest and highest price targets shows how much analysts disagree on how much of the AI buildout is already priced into the stock.

Earnings and Data Center growth

NVIDIA's most recent report, for the second quarter of fiscal 2027, showed record revenue of USD 96.2 billion, up 106 % from the same quarter last year. Data Center revenue reached USD 89.0 billion, up 117 %, as Blackwell systems drove most of the demand while NVIDIA began early production shipments of its next-generation Vera Rubin platform. 

GAAP gross margin came in at 75.0 %. Diluted earnings per share reached USD 2.46 on a GAAP basis. NVIDIA guided third-quarter revenue to USD 108.0 billion, plus or minus 2 %, and said that number assumes no Data Center compute revenue from China.

Trillion-Dollar Blackwell and Rubin Demand Outlook

CEO Jensen Huang told investors at NVIDIA' sGTC event that the company expects at least USD 1 trillion in demand and purchase orders for its Blackwell and Vera Rubin chips through 2027. 

He later said that figure could grow once other product lines get counted in. This is a forward-looking outlook from management. It is not a signed order book. Analysts will watch each earnings report closely to see how actual shipments track against that projection. 

NVIDIA' s disclosed purchase and supply commitments had climbed to about USD 279 billion by the end of fiscal Q2, showing how much capacity the company is trying to lock in.

AI spending durability is the real question

Demand for AI computing clearly exists. The harder question is whether hyperscalers, AI labs, and enterprises can keep raising capital spending fast enough to match it. That question came into sharp focus on 14th September, when the Philadelphia Semiconductor index fell 5.9 % in a single session, and Nvidia shares dropped about 3.4 %. 

The drop followed warnings from several AI industry executives about the pace and economics of AI infrastructure spending. It was one of a few sector-wide selloffs this year tied to worries about debt-funded data center buildouts. Nvidia's future growth depends heavily on that spending pace holding up.

Also Read: US Stocks Fall as Rising Bond Yields and Oil Prices Pressure AI Tech Shares

China, Competition, and Valuation

Nvidia's current guidance leaves out Data Center compute revenue from China, a reflection of ongoing US export limits on advanced AI chips. China was once an important market for Nvidia before those restrictions cut off shipments of its top-tier processors. Any policy shift, in either direction, could affect future revenue, product mix and margins.

NVIDIA's edge also rests on its CUDA software ecosystem, its combined hardware and networking lineup, and its deep ties with major cloud and AI customers. Custom chips built by cloud providers, including Google's TPU line, along with AMD's accelerators, pose a longer-term threat, though neither has slowed NVIDIA's order momentum so far. The stock's low dividend yield reflects a clear choice: NVIDIA is putting cash into growth rather than shareholder payouts.

Also Read: Lloyds Share Price Outlook: What Investors Should Watch in 2026

Final Thought

NVIDIA's stock price today reflects a company posting real, verified growth while carrying a demand outlook that assumes years of heavy AI infrastructure spending. The September selloff was a reminder that markets are now pricing confidence in that spending pace, not just the chips themselves. The next earnings report will offer fresh evidence on whether Data Center growth holds its current speed and whether customer AI budgets stay strong.

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FAQs

1. What is the NVIDIA stock price in September 2026?
NVIDIA (NVDA) closed at around USD 219.34 on September 17th, with a market capitalization of roughly USD 5.30 trillion.

2. What was NVIDIA's latest quarterly revenue?
NVIDIA reported USD 96.2 billion in revenue for fiscal Q2 2027, up 106% year over year. Data Center revenue reached USD 89 billion, up 117%.

3. What is driving NVIDIA stock in 2026?
Key drivers include AI infrastructure spending, Data Center demand, Blackwell and Vera Rubin shipments, NVIDIA's earnings growth, China export restrictions and competition from custom AI chips.

4. When is NVIDIA's next earnings report?
NVIDIA's next earnings report is scheduled for 25th November.

5. What are the main risks for Nvidia stock?
Key risks include a slowdown in AI capital spending, tighter export restrictions, competition from custom AI accelerators, product-transition challenges and high market expectations.

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