Prediction: $2,304 Invested in Nvidia Today Will Be Worth Triple That Amount in 5 Years

Source Motley_fool

Key Points

  • Nvidia continues to have a huge AI opportunity in front of it.

  • Even as revenue growth slows, the path to a stock price of nearly $700 looks quite reasonable.

  • 10 stocks we like better than Nvidia ›

Ahead of Labor Day, you could buy 10 shares of Nvidia (NASDAQ: NVDA) for $2,304. I think those shares could be worth around $6,900 in five years, or about 3 times what the stock trades for today.

Making such a bold claim, of course, requires some proof for the skeptics. First, I'll get into what makes Nvidia special and why its momentum is likely to continue; then I'll get into the math showing how the stock could triple by 2030.

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The Nvidia logo against a green background.

Image source: The Motley Fool.

The biggest AI winner

Nvidia has established itself as the biggest artificial intelligence (AI) winner since the technology started to go mainstream. That's because its graphics processing units (GPUs) are the primary chips powering AI workloads. While there is much more increased competition coming from custom AI chips and the occasional better offerings from Advanced Micro Devices and newer chip upstarts, Nvidia still finds itself in the catbird seat.

The company is the absolute dominant player in the AI training market, and this is unlikely to change. Nvidia has created a wide moat in this area with its CUDA software platform. It developed CUDA to easily program its chips and smartly seeded it among universities and research facilities doing early work on AI. The result is a generation of developers trained on its software, with most early AI code written on its platform and optimized for its chips.

Training is just part of the story, though, as inference is now growing faster and expected to eventually become the larger of the two AI computing markets. CUDA's moat is not as formidable in this area, but the company has made some good moves to remain a top player in this arena as well. Nvidia smartly "acquired" Groq and its language processing units (LPUs) earlier this year and incorporated them into its CUDA ecosystem. Inference tends to be more memory-bound than compute-bound, and LPUs have lightning-fast SRAM (static random-access memory) directly embedded in them. This reduces latency and makes them ideal for the decode phase of inference. Meanwhile, its GPUs can handle the more compute-heavy pre-fill phase.

This also speaks to Nvidia's greater strategy. The company is no longer just a GPU maker; it's become a complete AI infrastructure player. With a world-class networking portfolio, its own central processing units (CPUs), and other chips, the company can now deliver end-to-end complete rack solutions for specific AI tasks, such as training, inference, and agentic AI. At the same time, it's also acquired AI ecosystem players like SchedMD and Hugging Face (pending) to support open-source AI models and ensure that the broader developer ecosystem relies on open standards that run best on its hardware.

This all positions Nvidia to be a long-term AI winner well into the future.

The path to $690 a share

The market for AI infrastructure remains insatiable, and Nvidia recently projected that its revenue would grow by 70% in fiscal 2028 (ending January 2028), even though this growth is supply-constrained. To get to a $690 target in five years, I am still going to have to do a little math.

If it can produce a revenue compound annual growth rate (CAGR) of a little over 40% through 2031 (essentially its fiscal year 2032 ending in January 2031), its revenue would be around $2.3 trillion. This would mean 70% revenue growth next year and 25% revenue growth in fiscal 2032.

If the company's adjusted operating expenses rose at an average of 11% quarter over quarter through 2031 (fiscal 2032) and gross margin gradually stepped down to approximately 70%, and we apply a 15% tax rate on its operating income, Nvidia could generate over $1.1 trillion in adjusted earnings by 2031, or about $46 per share at its current share count of 24.4 billion. Place a 15 forward price-to-earnings ratio on fiscal 2032 projections for the stock, and its share price would be $690 in five years.

Below is a simple model of what its revenue and earnings growth could look like.

Financial Metric

FY 2027

FY 2028

FY 2029

FY 2030

FY 2031

FY 2032

Revenue

$411 billion

$699 billion

$1.05 trillion

$1.47 trillion

$1.91 trillion

$2.29 trillion

Revenue growth

90%

70%

50%

40%

30%

25%

Gross profit

$308 billion

$517 billion

$765 billion

$1.06 trillion

$1.34 trillion

$1.6 trillion

Adjusted operating expenses

$35 billion

$53 billion

$81 billion

$123 billion

$186 billion

$283 billion

Operating income

$273 billion

$464 billion

$684 billion

$934 billion

$1.15 trillion

$1.32 trillion

Net income

$232 billion

$394 billion

$582 billion

$794 billion

$977 billion

$1.12 trillion

Earnings per share

$9.52

$16.16

$23.84

$32.53

$40.02

$45.96

Data source: Author's projections.

If these projections are even close to accurate, Nvidia becomes a top AI stock to own over the next five years.

Should you buy stock in Nvidia right now?

Before you buy stock in Nvidia, consider this:

The Motley Fool Stock Advisor analyst team just identified what they believe are the 10 best stocks for investors to buy now… and Nvidia wasn’t one of them. The 10 stocks that made the cut could produce monster returns in the coming years.

Consider when Netflix made this list on December 17, 2004... if you invested $1,000 at the time of our recommendation, you’d have $414,015!* Or when Nvidia made this list on April 15, 2005... if you invested $1,000 at the time of our recommendation, you’d have $1,385,459!*

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*Stock Advisor returns as of September 9, 2026.

Geoffrey Seiler has positions in Advanced Micro Devices. The Motley Fool has positions in and recommends Advanced Micro Devices and Nvidia. The Motley Fool has a disclosure policy.

Disclaimer: For information purposes only. Past performance is not indicative of future results.
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