Jensen Huang Recently Delivered Incredible News for Nvidia Investors

Source Motley_fool

Nvidia (NASDAQ: NVDA) supplies some of the world's most advanced graphics processing units (GPUs) for data centers -- hardware that developers use to power and train artificial intelligence (AI) software. Demand for its chips far exceeds what it can currently supply, which helps explain how the company has added over $2.3 trillion to its market capitalization since the start of 2023.

At Nvidia's annual GPU Technology Conference (GTC) last month, CEO Jensen Huang laid out some incredible catalysts that could accelerate the company's already rapid growth. With its stock currently trading down 27% from its record high amid the sharp sell-off in the broader market, this could be a significant buying opportunity.

Where to invest $1,000 right now? Our analyst team just revealed what they believe are the 10 best stocks to buy right now. Learn More »

Nvidia's headquarters with a black Nvidia sign out the front.

Image source: Nvidia.

New AI models need 100 times the computing power of their predecessors

Large language models (LLMs) sit at the foundation of every AI application. These models are trained on mountains of data, and the more data an LLM can access, the "smarter" the resulting tool will be. However, training them requires massive amounts of computing power -- particularly parallel processing power -- which is why there is so much demand for Nvidia's data center GPUs.

Up until recently, LLMs delivered "one-shot" responses, meaning a chatbot would rapidly generate a single output for every prompt input by the user. While this method was fast and effective, it failed to weed out inaccuracies, which detracted from their value and the user experience. Now, top developers like OpenAI, Anthropic, and DeepSeek are focusing on an entirely different approach called test-time scaling, or "reasoning."

Rather than simply ingesting endless amounts of data, these models spend more time "thinking" before rendering responses to inputs. In other words, they make better use of the data they already have, and are more apt to clear up any inaccuracies behind the scenes before releasing the final output. This approach has been wildly successful, producing some of the most advanced AI models to date, such as OpenAI's GPT-4o series, DeepSeek's R1, Anthropic's Claude 3.7 Sonnet, and Alphabet's Gemini 2.5 Pro.

However, reasoning models require significantly more computing power. Huang says each response consumes 10 times more tokens (words, punctuation, and symbols) because of how much "thinking" goes on in the background, and as a result, the models are also much slower to render a final output. Huang says GPUs will need to be 10 times faster to offset this, and he estimates that developers will soon need a staggering 100 times more computing power to deploy reasoning models with a satisfactory user experience.

Nvidia's new Blackwell GPU architecture is a step in that direction. In some configurations, a Blackwell GB200 GPU can perform AI inference 30 times faster than the company's previous generation of chips, which were based on its Hopper architecture. Plus, last month, Nvidia revealed its new Blackwell Ultra architecture, which will be capable of delivering 50 times more performance than Hopper because it's specifically designed for reasoning models.

A $1 trillion annual opportunity by 2028

The continuing shift toward reasoning models could be a significant tailwind for Nvidia's GPU sales. At GTC last month, Huang said the top four providers of cloud infrastructure services (and thus, the world's largest operators of data centers) have ordered a whopping 3.6 million Blackwell GPUs already, which is almost triple the number of Hopper chips they purchased last year.

Those four cloud providers are Amazon Web Services, Microsoft Azure, Google Cloud, and Oracle Cloud Infrastructure. That list doesn't include other big spenders that are developing AI for their own purposes, like Meta Platforms, Tesla, and OpenAI, so the total number of Blackwell orders is almost certainly much higher.

This could just be the beginning: Huang predicts AI infrastructure spending will top $1 trillion annually by 2028, and much of that will go toward AI accelerator chips such as those that Nvidia provides.

Nvidia's data center business generated $115.2 billion in revenue during its fiscal 2025 (which ended Jan. 26). That was up 142% compared to the prior year. If Huang's forecast is right, the company's sales likely have substantial room to grow.

Nvidia stock looks like a bargain right now

The 27% drop in Nvidia stock from its recent all-time high has created an opportunity for investors to buy it at an attractive valuation relative to its history. It currently trades at a price-to-earnings (P/E) ratio of 36.9. That's its cheapest level in three years, and also a 38% discount to its 10-year average P/E ratio of 59.5.

NVDA PE Ratio Chart

Data by YCharts.

Moreover, Wall Street's consensus estimates (as provided by Yahoo! Finance) suggest that Nvidia's earnings per share (EPS) for fiscal 2026 will come in at $4.53. That gives the stock a forward P/E ratio of just 23.9. In other words, Nvidia would have to soar by 149% by the end of this fiscal year just to trade in line with its 10-year average P/E ratio of 59.5 (assuming Wall Street's EPS estimate proves to be accurate).

With that said, I think investors should look beyond the next 12 months because, if Huang is correct, Nvidia shareholders' best returns might be realized over the next three to five years instead.

Don’t miss this second chance at a potentially lucrative opportunity

Ever feel like you missed the boat in buying the most successful stocks? Then you’ll want to hear this.

On rare occasions, our expert team of analysts issues a “Double Down” stock recommendation for companies that they think are about to pop. If you’re worried you’ve already missed your chance to invest, now is the best time to buy before it’s too late. And the numbers speak for themselves:

  • Nvidia: if you invested $1,000 when we doubled down in 2009, you’d have $286,347!*
  • Apple: if you invested $1,000 when we doubled down in 2008, you’d have $42,448!*
  • Netflix: if you invested $1,000 when we doubled down in 2004, you’d have $504,518!*

Right now, we’re issuing “Double Down” alerts for three incredible companies, and there may not be another chance like this anytime soon.

Continue »

*Stock Advisor returns as of April 1, 2025

John Mackey, former CEO of Whole Foods Market, an Amazon subsidiary, is a member of The Motley Fool's board of directors. Suzanne Frey, an executive at Alphabet, is a member of The Motley Fool's board of directors. Randi Zuckerberg, a former director of market development and spokeswoman for Facebook and sister to Meta Platforms CEO Mark Zuckerberg, is a member of The Motley Fool's board of directors. Anthony Di Pizio has the following options: long April 2025 $200 puts on Tesla and long April 2025 $210 puts on Tesla. The Motley Fool has positions in and recommends Alphabet, Amazon, Meta Platforms, Microsoft, Nvidia, Oracle, and Tesla. The Motley Fool recommends the following options: long January 2026 $395 calls on Microsoft and short January 2026 $405 calls on Microsoft. The Motley Fool has a disclosure policy.

Disclaimer: For information purposes only. Past performance is not indicative of future results.
placeholder
Samsung Electronics Forecasts Stronger-Than-Expected Q3 Profit on AI Demand Samsung forecasts Q3 profit of 12.1 trillion won, boosted by strong AI chip demand.
Author  Mitrade
Oct 14, Tue
Samsung forecasts Q3 profit of 12.1 trillion won, boosted by strong AI chip demand.
placeholder
Dollar Gains as US-China Trade Tensions Ease The U.S. dollar remained steady on Tuesday following a shift in President Donald Trump’s harsh stance on tariffs against China.
Author  Mitrade
Oct 14, Tue
The U.S. dollar remained steady on Tuesday following a shift in President Donald Trump’s harsh stance on tariffs against China.
placeholder
Asian Stocks Mixed as Commodities Pause and Yen Draws AttentionAsian equity markets struggled to close the week on a weak note Friday, influenced by ongoing losses on Wall Street that extended into early Asian trading.
Author  Mitrade
Oct 10, Fri
Asian equity markets struggled to close the week on a weak note Friday, influenced by ongoing losses on Wall Street that extended into early Asian trading.
placeholder
Oil Prices Hold Steady Amid Gaza Ceasefire and US Sanctions Oil prices held steady in early Asian trading on Friday following the announcement of a ceasefire between Israel and Hamas.
Author  Mitrade
Oct 10, Fri
Oil prices held steady in early Asian trading on Friday following the announcement of a ceasefire between Israel and Hamas.
placeholder
Bitcoin drops below $110K ahead of $22B options expiry; altcoins tumbleBitcoin fell below the $110,000 mark on Friday, heading for a steep weekly loss as nearly $22 billion in cryptocurrency options were set to expire. The drop also comes as traders await key U.S. inflation data that could influence the Federal Reserve’s policy outlook.
Author  Mitrade
Sept 26, Fri
Bitcoin fell below the $110,000 mark on Friday, heading for a steep weekly loss as nearly $22 billion in cryptocurrency options were set to expire. The drop also comes as traders await key U.S. inflation data that could influence the Federal Reserve’s policy outlook.
goTop
quote