Nvidia

An estimated half a trillion dollars was wiped out from the financial markets this week, as some of the biggest tech companies, including Nvidia, Microsoft, and Palantir Technologies saw a temporary but sizeable drop in their share prices on Tuesday. It may have been just a short-lived correction, but experts warn of mounting signs of a financial market crash, which could cost several times this amount.

With dependence on tech and AI growing, critics argue that betting on these profits is a gamble, stressing that the future remains uncertain.

Singapore’s central bank joined a global chorus of warnings from the IMF, Fed Chair Jerome Powell, and Andrew Bailey about overvalued stocks.

The Monetary Authority of Singapore said on Wednesday that such a trend is fuelled by “optimism in AI’s ability to generate sufficient future returns”, which could trigger sharp corrections in the broader stock market.

Goldman Sachs and Morgan Stanley predict a 10–20% decline in equities over the next one to two years, their CEOs told the Global Financial Leaders’ Investment Summit in Hong Kong, CNBC reported.

Experts interviewed by Euronews Business also agree that a sizeable correction could be on the way.

In a worst-case scenario, a market crash could wipe out trillions of dollars from the financial markets.

According to Mathieu Savary, chief European strategist at BCA Research, Big Tech companies, including Nvidia and Alphabet, would cause a $4.4 trillion (€3.8tn) market wipeout if they were to lose just 20% of their stock value.

“If they go down 50%, you’re talking about an $11tr (€9.6tr) haircut,” he said.

AI rally: Bubble or boom?

The US stock market has defied expectations this year. The S&P 500 is up nearly 20% over the past 12 months, despite geopolitical tensions and global trade uncertainty driven by Washington’s tariff policies. Gains have been strongest in tech, buoyed by optimism over future AI profits.

While Big Tech continues to deliver, with multibillion-dollar AI investments and massive infrastructure buildouts now routine, concerns are growing over a slowing US economy, compounded by limited data during the government shutdown. Once fresh figures emerge, they could rattle investors.

AI enthusiasm is most evident in Nvidia’s extraordinary stock gains and soaring valuation. The company is central to the tech revolution as its graphics processing units (GPUs) are essential for AI computing.

Nvidia’s shares have surged over 3,000% since early 2020, recently making it the world’s most valuable public company. Between July and October alone, it gained $1tr (€870bn) in market capitalisation — roughly equal to Switzerland’s annual GDP. Its stock trades at around 45 times projected earnings for the current fiscal year.

Derren Nathan, head of equity research at Hargreaves Lansdown, said: “Much of this growth is backed by real financial progress, and despite the massive nominal increase in value, relative valuations don’t look overstretched.”

Analysts debate whether the current market mirrors the dot-com bubble of 2000. Nathan notes that many tech companies that failed back then never reached profitability, unlike today’s giants, which generate strong revenues and profits, with robust demand for their products.

Ben Barringer, global head of technology research at Quilter Cheviot, added: “With governments investing heavily in AI infrastructure and rate cuts likely on the horizon, the sector has solid foundations. It is an expensive market, but not necessarily a screaming bubble. Momentum is hard to sustain, and not every company will thrive.”

BCA Research sees a bubble forming, though not set to burst immediately. Chief European strategist Mathieu Savary said such bubbles historically peak when firms begin relying on external financing for large projects.

Investments in assets for future growth, or capital expenditures, as a share of operating cash flow, have jumped from 35% to 70% for hyperscalers, according to Savary. Hyperscalers are tech firms such as Microsoft, Google, and Meta that run massive cloud computing networks.

“The share of operating earnings is likely to move above 100% before we hit the peak,” Savary added. This means that they may soon be investing more than they earn from operations.

Recent examples of Big Tech firms turning to external financing for such moves include Meta’s Hyperion project with Blue Owl Capital and Alphabet’s €3 billion bond issue for AI and cloud expansion.

While AI investment growth is hard to sustain, Quilter’s Barringer told Euronews: “If CapEx starts to moderate later this year, markets may start to get nervous.”

Other factors to watch include return on invested capital and rising yields and inflation pressures, which could signal a higher cost of capital and a bubble approaching its end.

“But we’re not there yet,” said Savary.

Further concerns and how to hedge against market turbulence

Even as tech companies ride the AI wave, inflated expectations for future profits may prove difficult to meet.

“The sceptics’ main problem may not be with AI’s potential itself, but with the valuations investors are paying for that potential and the speed at which they expect it to materialise,” said AJ Bell investment director Russ Mould.

A recent report by BCA reflects the mounting reasons to question the AI narrative, but the technology “remains a potent force”, said the group.

If investor optimism does slow, “a sharp correction in tech could still have ripple effects across broader markets, given the sector’s dominant weight in global indices,” Barringer said. He added that other regions and asset classes, such as bonds and commodities, would be less directly affected and could provide an important balance during a downturn.

According to Emma Wall, chief investment strategist at Hargreaves Lansdown, “investors should use this opportunity to crystallise impressive gains and diversify their portfolios to include a range of sectors, geographies and asset classes — adding resilience to portfolios. The gold price tipping up is screaming a warning again — a siren that this rally will not last.”

Published on 29/10/2025 – 11:09 GMT+1
•Updated
11:11

Nvidia shares continued their dramatic rise this week as investors banked on an easing of semiconductor trade restrictions between the US and China.

Ahead of a meeting with Chinese President Xi Jinping on Thursday, US President Donald Trump said he planned to discuss Nvidia’s advanced Blackwell artificial intelligence chip with Xi.

“We’ll be speaking about Blackwell, it’s the super duper chip,” he told reporters on Wednesday.

The president didn’t elaborate on specific policy aims, although he said he was “very optimistic” about the meeting with his Chinese counterpart.

By around 11:00 CET, Nvidia shares had jumped over 3% in pre-market trading, bringing the firm closer to a $5 trillion market capitalisation.

Semiconductors have been a key point of contention between the US and China as both nations seek to lead on advanced technologies such as AI.

The tiny chips, used to power a range of electronic devices from smartphones to medical equipment, are essential to this ambition. Since 2022, the US has therefore restricted Nvidia’s sales of advanced chips to China for national security reasons.

Trump has flip-flopped on export controls since his arrival in the White House, first restricting and then approving sales of Nvidia’s H20 AI chip to China. Nvidia designed the H20 specifically for the Chinese market to comply with Biden-era export curbs, although the Trump administration previously said it was concerned the tech could be used for military purposes.

With regard to the Blackwell processor, Trump suggested months ago that he would consider allowing Nvidia to export a downgraded version of the chip to China.

Progress on such a proposal would come as a relief to Nvidia CEO Jensen Huang, who has long criticised US restrictions. Huang has notably argued that such curbs are boosting China’s AI capabilities as the Chinese market is forced to become less reliant on US products.

It seems that such logic is already understood in Beijing, even as the US softens its stance. After Washington gave the green light to H20 exports, China’s regulator banned the country’s biggest tech companies from buying Nvidia’s artificial intelligence chips.

“The president has licensed us to ship to China, but China has blocked us from being able to ship to China,” Huang said at a Nvidia event this week in Washington. “They’ve made it very clear that they don’t want Nvidia to be there right now.”

In a document released by Beijing on Tuesday, the Communist party reiterated the importance of self-sufficiency, calling for “extraordinary measures” to achieve “decisive breakthroughs” in technologies such as semiconductors.

“The most important factor in promoting high-quality development is to accelerate high-level scientific and technological self-reliance,” Xi said in a speech released by state news agency Xinhua.

While it’s possible that Chinese restrictions on Nvidia chips could be a long-lasting policy, experts have suggested that the move may be a bargaining chip in trade negotiations with Washington.

Such policy U-turns are creating uncertainty for investors despite the fact that Nvidia shares have risen roughly 50% this year, driven higher by AI ambitions.

Published on 28/10/2025 – 16:58 GMT+1
•Updated
16:59

Apple’s stock reached new heights on Tuesday, trading above $269 a share and pushing the company’s market capitalisation to a record $4 trillion (€3.4tr). That followed stronger-than-expected demand for its latest iPhone 17.

The Cupertino-based technology giant therefore joins the elite club with Nvidia and Microsoft, which both surpassed the same valuation earlier this year.

Nvidia, the semiconductor powerhouse, became the first company in history to hit the $4tn milestone in July 2025. News of soaring AI investments and the firm’s strong profit outlook have continued to lift its share price since then, now approaching $4.7tn (€4tn).

The so-called Magnificent Seven, the seven largest publicly traded technology companies in the world, have been cashing in on the AI boom this year, with tech share prices rising accordingly. Since January, Apple shares are up more than 18%, Nvidia’s nearly 40%, and Microsoft’s close to 30%.

However, Apple has mostly stayed out of the race to invest billions in AI projects. Current market enthusiasm for the iPhone maker’s stock instead stems from the successful launch of its updated iPhone range, along with signs of easing trade and tariff pressures.

According to Counterpoint Research, the iPhone 17 series has outsold the iPhone 16 range by 14% during its first ten days on sale in China and the United States.

Five members of the Magnificent Seven, Alphabet, Apple, Amazon, Microsoft, and Meta, are reporting earnings this week. They will need to demonstrate strong growth and justify the massive spending currently underway in artificial intelligence, amid growing concerns that the sector may be forming a bubble reminiscent of the dot-com boom that burst in 2000.

According to Kate Leaman, chief market analyst at AvaTrade:”Markets move on leadership, and right now, the leadership of Microsoft, Meta, Alphabet, Amazon, and Apple is inseparable from the risk appetite of investors worldwide.”

She noted that more than 40% of S&P 500 gains this year have come via these giants.

“But with that concentration comes fragility,” she added, saying that even as revenues climb, the commentary provided by executives “will critically frame how far and how confidently the market can chase the AI story into 2026”.

Oct. 27 (UPI) — Tech giant Qualcomm said Monday its release of new AI accelerator chips was looming.

Qualcomm officials said its Snapdragon 6s Gen 4 mobile chip set will offer a 36% CPU performance boost and its Adreno GPU upgrades will deliver a 59% faster user experience.

On Monday, company stock spiked up about 12% at midday after release of the news.

“We first wanted to prove ourselves in other domains, and once we built our strength over there, it was pretty easy for us to go up a notch into the data center level,” Durga Malladi, Qualcomm’s general manager for data center and edge, said last week.

Its shift puts Qualcomm in direct competition with AI semiconductor giant Nvidia.

In 2022, Qualcomm announced it joined forces with Facebook parent company Meta to develop custom chipsets for the social media giant’s virtual reality products about seven months before Qualcomm was fined nearly $800 million by South Korea’s high court for alleged unfair business practices.

Meanwhile, Qualcomm’s AI200 and AI250 will go on sale in 2026 and 2027, respectively.

Nvidia (NVDA -0.31%) stock has been a fantastic performer over the short and long terms. Shares of the artificial intelligence (AI) chip and infrastructure leader have returned 1,440% and 26,960% over the last three years and decade, respectively, as of Friday, Oct. 17. These performances have transformed a $1,000 investment into $15,400 and $270,600, respectively. By comparison, one grand invested in the S&P 500 index has turned into $1,894 in three years and $3,910 in 10 years.

With Nvidia stock’s eye-popping gains, it’s easy to wonder if you missed your chance at buying shares. The answer is no, in my view, as Nvidia stock has many years of great performance left.

There are two reasons for my optimism. First, the AI revolution is still in its early stages. Second, Nvidia’s graphics processing units (GPUs) are the gold standard for processing AI workloads, and there is no indication that they’re in danger of losing that status, at least not for some time.

Below are my prediction ranges (a best case and a base case) for Nvidia stock’s price in about five years, or by the end of 2030. My estimates are built upon data provided by Nvidia’s CEO and CFO on the company’s most recent quarterly earnings call. (Nvidia’s earnings calls are chock-full of valuable data — and listening to them is worth the time.)

Image source: Getty Images.

Nvidia CFO: “We see $3 [trillion] to $4 trillion in AI infrastructure spend by the end of the decade.”

From CFO Colette Kress’ remarks on Nvidia’s fiscal second-quarter earnings call in late August:

We are at the beginning of an industrial revolution that will transform every industry. We see $3 [trillion] to $4 trillion in AI infrastructure spend by the end of the decade. The scale and scope of these [AI infrastructure] buildouts present significant long-term growth opportunities for Nvidia Corporation. [Emphasis mine.]

Numbers from CEO: 58% to 70% of an AI faciility’s cost goes to Nvidia

From CEO Jensen Huang’s remarks on the fiscal Q2 earnings call:

And so our contribution … is a large part of the AI infrastructure. Out of a gigawatt AI factory, which can go [cost] anywhere from … $50 to $60 billion, we represent about $35 [billion] plus or minus of that.

Huang is saying that a typical 1-gigawatt AI data center or other AI facility costs about $50 billion to $60 billion to build, and that about $35 billion of that cost is for Nvidia’s AI technology.

So, about 58% ($35 billion divided by $60 billion) to 70% ($35 billion divided by $50 billion) of the total cost of an AI facility is the cost of buying Nvidia’s tech.

Putting together the data provided by Nvidia’s CFO and CEO

Kress said the company expects total global AI infrastructure spending to be $3 trillion to $4 trillion annually by the end of the decade. (It’s not clear whether she meant by 2029 or 2030, but I’m using 2030 to be conservative. Moreover, Nvidia just published a presentation that uses the $3 trillion to $4 trillion projection by 2030.)

Of that $3 trillion to $4 trillion, Nvidia stands to take in 58% to 70% of it, according to Huang. This assumes that percentage range remains about the same. This will be part of my “best-case estimate,” but I am also going to calculate a “base-case estimate” that assumes Nvidia’s percentage of total AI infrastructure spend declines moderately, by 20%. This will account for the potential for increased competition by chipmaker Advanced Micro Devices (AMD) and others.

Revenue from AI infrastructure spend that Nvidia should generate in about five years:

• Best-case estimate: 58% to 70% of $3 trillion to $4 trillion = $1.74 trillion to $2.8 trillion.
• Base-case estimate: 46% to 56% (I chopped 20% off the percentages in the best-case range) of $3 trillion to $4 trillion = $1.38 trillion to $2.24 trillion.

Calculating my Nvidia stock price target ranges for 2030

Now, I’ll use the numbers calculated above to come up with price target ranges for Nvidia stock in about five years. Two additional data points needed:

• Nvidia stock’s closing price on Oct. 17: $183.22.
• Nvidia’s AI-driven data center revenue was $41.1 billion (of its total revenue of $46.7 billion) in its most recently reported quarter (fiscal Q2, ended July 27). This equates to an annual run rate of $164.4 billion ($41.4 billion X 4).

Nvidia stock best-case price target in five years: $1,942 to $3,115.

1. Nvidia’s projected AI infrastructure revenue in five years: $1.74 trillion to $2.8 trillion.
2. Nvidia’s AI infrastructure revenue currently: annual revenue run rate of $164.4 billion.
3. Step 1 numbers divided by Step 2 number: 10.6 to 17.0. This means Nvidia’s annual data center revenue should increase by 10.6 to 17.0 times in 5 years.
4. Nvidia stock price at market close on Oct. 17: $183.22.
5. Valuation assumption: I am assuming that Nvidia stock’s earnings-based valuation will remain the same in five years. That’s because its valuation is reasonable now given its growth and projected growth dynamics, in my view. (Trailing and forward price-to-earnings (P/E) ratios are 51.5 and 28.7, respectively.)
6. The above assumption means the conversion from revenue growth (Step 3 numbers) to stock price growth will be straightforward.
7. $183.22 X 10.6 to 17.0.
8. Stock price target in five years: $1,942 to $3,115.

Nvidia stock base-case price target in five years: $1,300 to $2,125.

1. Nvidia’s projected AI infrastructure revenue in five years: $1.38 trillion to $2.24 trillion.
2. Nvidia’s AI infrastructure revenue currently: annual run rate of $164.4 billion.
3. Step 1 numbers divided by Step 2 number: 8.4 to 13.6. So, Nvidia’s annual data center revenue should increase by 8.4 to 13.6 times in five years.
4. Nvidia stock price at market close on Oct. 17: $183.22.
5. Valuation assumption: I am assuming that Nvidia stock’s earnings-based valuation remains the same in five years.
6. The above assumption means the conversion from revenue growth (Step 3 numbers) to stock price growth would be straightforward.
7. BUT, I’m going to assume that the data center platform’s profitability declines modestly due to the possibility of increased competition. I can adjust the factors in Step 3 down by 15% to account for this since I had been assuming a straightforward relationship between revenue, earnings, and price target growth.
8. [8.4 to 13.6] x [85%] = 7.1 to 11.6.
9. $183.22 X 7.1 to 11.6.
10. Stock price target in five years: $1,300 to $2,125.

Why there is upside to both these target ranges

I only considered Nvidia’s data center market platform growth when calculating my price targets. That’s because this AI-driven platform accounts for the vast majority of the company’s revenue and earnings — and stock price gains are usually driven by earnings growth.

In the first half of the current fiscal year, the data center platform accounted for 88% of Nvidia’s total revenue. And it accounted for an even higher percentage of total earnings. That percentage is unknown because management does not break out earnings or other profitability metric by platform. But management has said that its data center platform is more profitable than its overall business. So, the data center platform probably accounts for in the mid-90% of total earnings.

If one or more of the company’s other market platforms (gaming, professional visualization, and auto) grows revenue and earnings tremendously over the next five years, that should be upside for my price targets. The auto platform has the potential to be a big winner over the next five years due to driverless vehicles steadily progressing toward legality. Nvidia’s end-to-end AI-powered driverless tech platform is widely adopted.

Caveat about the economy and overall stock market performance

My estimates assume the U.S. economy remains in at least a minimal growth mode and the stock market remains in a bull market for much of the next five years.

I don’t think a mild and relatively brief recession would derail my Nvidia stock price targets, at least not by much, but a deep or long-lasting recession and long-lasting bear market would almost surely derail them.

My wrap-up

Nvidia stock best-case price target in five years: $1,942 to $3,115. (Of course, the stock would most likely split before it reached these levels, but the underlying growth remains the same.) This equates to Nvidia’s stock price increasing by 10.6 to 17.0 times. It also equates to a compound annual growth rate (CAGR) of 60% to 76%.

Nvidia stock base-case price target in five years: $1,300 to $2,125. This equates to Nvidia’s stock price increasing by 7.1 to 11.6 times. It also equates to a CAGR of 48% to 63%.

Taken together, the Nvidia stock price target range in five years is $1,300 to $3,115.

With roughly 10 weeks to go before 2025 comes to a close, it looks as if it’ll be another banner year on Wall Street — and the evolution of artificial intelligence (AI) is a big reason why.

Empowering software and systems with AI capabilities affords them the opportunity to make split-second decisions and become more efficient at their assigned tasks without human intervention. It’s a game-changing technology that the analysts at PwC believe can add $15.7 trillion to the global economy by the turn of the decade.

Although dozens of public companies have benefited from the AI revolution, none have taken their spot on Wall Street’s mantle quite like Nvidia (NVDA 0.86%), the largest publicly traded company, and Palantir Technologies (PLTR 0.11%). Since 2022 came to a close, Nvidia stock has rocketed higher by more than 1,100% and added over $4 trillion in market value. Meanwhile, Palantir shares are approaching a nearly 2,700% cumulative gain, as of the closing bell on Oct. 16, 2025.

Image source: Getty Images.

While there’s a laundry list of reasons that can justify the breathtaking rallies we’ve witnessed in both companies, this dynamic AI duo has also issued a very clear warning to Wall Street that can’t be swept under the rug.

Nvidia’s and Palantir’s success derives from their sustainable moats

There are few business characteristics investors appreciate more than sustainable moats. Companies that possess superior technology, production methods, or platforms don’t have to worry about competitors siphoning away their customers.

Nvidia is best known for its world-leading graphics processing units (GPUs), which act as the brains of enterprise AI-accelerated data centers. Though estimates vary, Nvidia is believed to control 90% or more of the AI-GPUs currently deployed in corporate data centers.

No external GPU developers have come close to challenging Nvidia’s Hopper (H100), Blackwell, or Blackwell Ultra chips, in terms of compute abilities. With CEO Jensen Huang targeting the release of a new advanced AI chip in the latter half of 2026 and 2027, it seems highly unlikely that Nvidia will cede much of its AI-GPU data center share anytime soon.

To add fuel to the fire, Nvidia’s CUDA software platform has served as an unsung hero. This is the toolkit used by developers to build and train large language models, as well as maximize the compute abilities of their Nvidia hardware. The value of this software is exemplified by Nvidia’s ability to keep its clients within its ecosystem of products and services.

Meanwhile, the beauty of Palantir’s operating model is that no other company exists that can match its two core AI- and machine learning-inspired platforms at scale.

Gotham is Palantir’s true breadwinner. This software-as-a-service platform is used by the U.S. government and its primary allies to plan and oversee military missions, as well as gather and analyze data. The other core platform is Foundry, which is a subscription-based service for businesses looking to make sense of their data and automate some aspects of their operations to improve efficiency.

Palantir’s government contracts have supported a consistent annual sales growth rate of 25% or above, and played a key role in pushing the company to recurring profitability well ahead of Wall Street’s consensus forecast.

Yet in spite of these well-defined competitive edges, this AI-inspired dynamic duo has offered a stark warning to Wall Street and investors.

Image source: Getty Images.

Nvidia’s and Palantir’s insiders are sending a clear message to Wall Street

Though AI has been the hottest thing since sliced bread over the last three years, it’s not without headwinds.

For example, every next-big-thing technology and hyped innovation since (and including) the advent of the internet more than 30 years ago has endured an early innings bubble-bursting event. This is to say that all new technologies have needed time to mature, and evidence of that maturation isn’t wholly evident from the companies investing in AI solutions.

But perhaps the most damning message of all comes from the insiders at Nvidia and Palantir Technologies.

An “insider” refers to a high-ranking employee, member of the board, or beneficial owner holding at least 10% of a company’s outstanding shares. These are folks who may possess non-public information and know their company better than anyone on Wall Street or Main Street.

Insiders of publicly traded companies are required to be transparent with their trading activity. No later than two business days following a transaction — buying or selling shares of their company, or exercising options — insiders are required to file Form 4 with the Securities and Exchange Commission. These filings tell quite the tale with these two high-flying AI stocks.

Over the trailing five-year period, net-selling activity by insiders is as follows:

• Nvidia: $5.342 billion in net selling of shares
• Palantir: $7.178 billion in net selling of shares

In other words, insiders at the two hottest stocks in the AI arena have, collectively, sold $12.5 billion more of their own company’s stock than has been purchased since Oct. 16, 2020.

The stipulation to this publicly reported data is that most executive and board members at public companies receive their compensation in the form of common stock and/or options. To cover the federal and/or state tax liability tied to their compensation, company insiders often sell stock. In short, there are viable reasons for insiders to head for the exit that aren’t necessarily bad news.

What may be even more telling with Nvidia and Palantir Technologies is the complete lack of insider buying we’ve witnessed. The last time an Nvidia executive or board member purchased stock, based on Form 4 filings, was in early December 2020. Meanwhile, there’s been just one purchase by an executive or board member for Palantir since the company went public in late September 2020.

Neither Nvidia nor Palantir Technologies are inexpensive stocks, based on their price-to-sales (P/S) ratios. Over the trailing-12-month period, Nvidia and Palantir are valued at P/S ratios of 27 and 131, respectively. History tells us both figures aren’t sustainable over an extended period.

If no insiders from either company are willing to buy shares of their own stock, why should everyday investors?

Nvidia (NVDA 0.86%) has been one of the most successful stocks in the artificial intelligence (AI) arms race, rising 1,130% since it began at the start of 2023. This has delivered long-term investors phenomenal returns, but there’s a new, exciting investment trend in town that could disrupt how investors view Nvidia’s success.

Quantum computing is one of the most popular industries to invest in, and its stocks have surged over the past few months as investor sentiment surrounding the industry has improved. One of the most popular options is IonQ (IONQ -3.92%), which is no stranger to success. If you’d invested in IonQ instead of Nvidia at the start of 2023, you’d be up 2,150% (at the time of this writing)!

That may have some investors thinking they’ve backed the wrong horse in the computing race. So, is it time to move on from Nvidia and scoop up shares of IonQ? Let’s find out.

Image source: Getty Images.

Nvidia and IonQ are similar businesses

At their core, Nvidia and IonQ are quite close in terms of business pursuit. Nvidia makes graphics processing units (GPUs) alongside other equipment to optimize their performance. GPUs have become the gold standard in high-performance computing applications such as artificial intelligence, drug discovery, engineering simulations, and cryptocurrency mining. Their unique ability to process multiple calculations in parallel makes them a computing powerhouse, and AI hyperscalers have widely deployed them to train and run generative AI models.

IonQ appears to be a much earlier version of Nvidia, focusing on quantum computing rather than traditional computing methods. It’s developing a full-stack solution that provides clients with everything they need to run a quantum computer. Once quantum computing becomes mainstream, many believe it can have widespread use cases in applications like AI training and logistics network improvements. This could lead to a massive market opportunity, similar to what Nvidia experienced at the start of the AI arms race.

However, we’re still a ways away from quantum computing becoming relevant. IonQ and many other quantum computing companies point toward 2030 as the year when quantum computing will become a commercially viable technology. That’s five years out, and there’s still a lot of time for things to go wrong for IonQ (or go right).

IonQ competitor Rigetti Computing estimates that the annual value for quantum computing providers will reach $15 billion to $30 billion between 2030 and 2040. Should IonQ replicate Nvidia’s success by 2030, it could still have room to grow between now and then.

If we assume that the market reaches $15 billion annually in 2030 and IonQ replicates Nvidia’s dominant 90% market share and 50% profit margin, IonQ would be producing profits of $6.75 billion. At a 40 times earnings valuation, that would indicate IonQ could be a $270 billion company, more than a 10x from today’s $23 billion valuation.

But is that enough to warrant selling Nvidia shares to invest in IonQ?

Nvidia has a growth trend of its own

Over the next few years, capital expenditures relating to AI data centers are set to explode. Nvidia estimates that total capital expenditures in 2025 will total $600 billion, but reach $3 trillion to $4 trillion by 2030. If that plays out like Nvidia projects, the total amount of money spent on data center capital expenditures will rise at a compound annual growth rate of 42%. If Nvidia’s growth directly follows that trajectory, that means its stock could rise nearly 6 times in value.

So, which is more likely: Quantum computing becomes viable, IonQ establishes a dominant, Nvidia-like market share and achieves incredibly high margins, or Nvidia’s growth follows widely accepted AI spending trends? I think it’s more likely that the AI arms race continues in its current form, making holding on to Nvidia shares a smart decision. After all of the quantum computing investment hype, I think it’s time for investors to take a break from this sector and focus on some companies that have actual money flowing into them, rather than quantum computing-specific businesses like IonQ.

Nvidia has been the dominant force in the global semiconductor industry thanks to its graphics processing units (GPUs), which have played a critical role in enabling the proliferation of artificial intelligence (AI) applications. The demand for Nvidia’s GPUs has been so solid in the past three years that Nvidia has now become the world’s largest company.

Nvidia continues to rule the AI data center GPU market, facing very little threat from its peers so far. Analysts are expecting its top line to jump by an impressive 58% in the current fiscal year to more than $206 billion. That’s quite impressive for a company of Nvidia’s size. The stock registered respectable gains of 34% on the market this year based on the healthy growth that the company continues to deliver.

However, Nvidia’s stock market performance has been overshadowed by Broadcom (AVGO -1.24%). Broadcom has appreciated 48% this year and looks set to end 2025 on a high note following recent developments. In fact, it won’t be surprising to see Broadcom stock outperforming Nvidia next year as well. Let’s see why that may be the case.

Image source: Nvidia.

Custom AI chips are expected to witness stronger demand in 2026

So far, the majority of AI model training and inference has been carried out by Nvidia’s GPUs. GPUs are general-purpose computing chips with massive parallel computing power, making them ideal for quickly training AI models and moving them into production. OpenAI chose Nvidia’s A100 data center GPUs to train its popular chatbot ChatGPT three years ago.

Nvidia built upon its first-mover advantage and controlled an estimated 92% of the AI data center GPU market at the end of last year. However, the latest deal struck between OpenAI and Broadcom indicates that Nvidia’s influence over the AI chip market could wane. OpenAI will buy custom AI accelerators worth a whopping 10 gigawatts (GW) from Broadcom starting in the second half of 2026.

The deployment is expected to be completed by the end of 2029. This is a massive deal for Broadcom considering that it reportedly costs around $10 billion to build a 1 GW data center. Around 60% of the investment that goes into building a data center is allocated toward chips and other computing hardware, which would put Broadcom’s potential addressable market from each gigawatt of OpenAI’s deployment at $6 billion.

So, Broadcom could be sitting on a potential revenue opportunity worth $60 billion from this deal over the next three years. Broadcom’s custom AI processors have already been in terrific demand as hyperscalers and AI giants such as OpenAI are gravitating toward these chips because of the advantages they enjoy over GPUs.

Custom AI processors are designed for performing targeted tasks, such as AI inference. As a result, they are not only more power-efficient at running those workloads but also enjoy a performance advantage since they don’t need to perform any other tasks. Hence, deploying custom AI processors can help save costs for hyperscalers.

Shipments of application-specific integrated circuits (ASICs) meant for deployment in AI data centers are expected to increase by 45% in 2026, compared to the expected growth of 16% in GPUs. Broadcom is in the best position to make the most of this growth opportunity as it leads the ASIC market with an estimated share of 70%.

Moreover, the new deal with OpenAI along with another $10 billion contract with an unnamed customer that the company announced last month should ensure outstanding growth in Broadcom’s AI revenue next year.

Broadcom’s AI revenue could now increase at a faster pace

Broadcom is on track to end the current fiscal year with almost $20 billion in AI revenue, an increase of 64% from the previous year. The company reported a record revenue backlog of $110 billion at the end of the fiscal third quarter (which ended on Aug. 3). That backlog is likely to have moved higher following the recent deals struck by the company.

Don’t be surprised to see Broadcom’s revenue jumping at a faster pace than the 33% growth that Wall Street is expecting next fiscal year, which would be a nice improvement over the 23% growth it is expected to deliver in the current one. There is a good chance that its revenue growth in the long run could be better than expectations as well.

AVGO Revenue Estimates for Current Fiscal Year data by YCharts

Broadcom was already anticipating a serviceable addressable market worth $60 billion to $90 billion based on the three AI customers it was serving until earlier this year. That addressable market is now much bigger following the OpenAI contract, which opens up the possibility of stronger growth and more upside for Broadcom investors.

About a year ago, Nvidia (NVDA 0.86%) was facing one of its biggest moments ever. The artificial intelligence (AI) chip giant was launching its new Blackwell architecture, a system that was being met with “insane” demand as CEO Jensen Huang told CNBC at the time. The company announced Blackwell in March 2024 and the fourth quarter of the year was the first to include Blackwell revenue.

Blackwell was to be the first release of a new routine for Nvidia: launching chip or entire platform updates on an annual basis. Since that time, this new architecture has helped Nvidia’s earnings roar higher, with Blackwell data center revenue climbing 17% in the most recent quarter from the previous one. In the report, Huang said, “The AI race is on, and Blackwell is the platform at its center.” Meanwhile, Nvidia stock has reflected all of this, advancing 40% so far this year.

Now, it’s logical to wonder where Nvidia will be as this story progresses, for example, 24 months after the Blackwell launch. Here’s what history says.

Image source: Nvidia.

Nvidia’s path in AI

First, though, let’s consider Nvidia’s path in the AI market so far. The company has always been a graphics processing unit (GPU) powerhouse, but in its earlier days, it mainly sold these high-performance chips to the gaming market. As it became clear that their uses could be much broader, Nvidia developed the CUDA parallel computing platform to make that happen — and then, as the potential of AI emerged, Nvidia didn’t hesitate to put its focus on this exciting market.

That proved to be a fantastic move as it helped Nvidia secure the top spot in the AI chip market — and the quality and speed of its GPUs has kept it there. All of this has resulted in several quarters of double- and triple-digit revenue growth as well as high profitability on sales — gross margin has generally surpassed 70% in recent times.

To keep this leadership going, Nvidia committed to ongoing innovation, with the promise of updating its chips once a year. The company kicked this off with the launch of Blackwell about a year ago, then released update Blackwell Ultra a few months ago. Next up on the agenda is the Vera Rubin system, set for release late next year.

From platform to platform

All of these platforms operate together seamlessly, so customers don’t have to wait for a specific one and instead can get in on Nvidia’s current system and easily move forward with the latest innovations when needed. Still, as mentioned earlier, demand from big tech customers for the latest systems has been great — they want to win in the AI race and to do so aim to get their hands on the best tools as soon as possible.

So, where will Nvidia be 24 months after the Blackwell launch? The clues so far suggest revenue will continue to climb in the double-digits — and Wall Street’s average estimates call for a 33% increase in revenue next year from this year’s levels. And as Rubin is released, demand is likely to increase for that system as customers’ interest in gaining access to the latest AI technology continues.

But what about Nvidia’s stock price? History offers some clues. Prior to this time, Nvidia’s major recent releases happened every two years. We can look back to the launch of the Ampere platform on May 14, 2020, and the release of Hopper on Sept. 20, 2022. And each time, over the next 24 months, Nvidia stock soared in the triple digits. It climbed 120% in the two years following the Ampere release and more than 700% following the release of Hopper.

NVDA data by YCharts

What history says

History shows Nvidia stock is on track for a triple-digit gain two years after the Blackwell launch. If we use the starting point as the first quarter of Blackwell revenue — this quarter ended on Jan. 26, 2025 — we can see the stock has climbed about 30% so far. But Nvidia still has plenty of time to post more Blackwell sales and potentially see its shares advance in the triple-digits from their level earlier this year through the first month of the 2027 calendar year.

To illustrate, a 100% gain from early 2025 levels would bring the stock price to $284, and that would result in $6.9 trillion in market cap by the start of 2027. This fits into a scenario I wrote about recently, predicting Nvidia will reach $10 trillion in market value by the end of the decade.

Of course, it’s impossible to guarantee this outcome — any negative geopolitical or economic news, or even an unexpected problem like a decline in tech spending could hurt Nvidia’s revenue and stock performance. But, if these potential risks don’t materialize, history could be right — and Nvidia stock may find itself significantly higher 24 months after the Blackwell launch.

The artificial intelligence (AI) megatrend has dominated the stock market over the past three years, and with massive AI spending projections stretching out through 2030 and beyond, that doesn’t look likely to change anytime soon. Two of the most successful stock picks in that part of the tech sector in recent years have been Palantir (PLTR 0.11%) and Nvidia (NVDA 0.86%). They aren’t competitors, as they operate on different sides of the AI value chain. Nvidia is a largely hardware provider, while Palantir makes software.

Both have made their long-term investors a ton of money, but the question is, which one provides the better investment opportunity from here? Let’s break that question down and consider it by category.  

Business model

Nvidia makes the world’s leading graphics processing units (GPUs), and its wares are by far the most popular parallel-processor chips for powering and training AI models. Nvidia has enjoyed solid market dominance over the past few years, but rising competition from AMD (NASDAQ: AMD) and Broadcom (NASDAQ: AVGO) could challenge that. Additionally, the AI infrastructure buildout won’t last forever. There will eventually be a time when companies aren’t racing to add high volumes of computing capacity, but instead mostly replacing processors as they reach the end of their useful lifespans.

Palantir sells its customers artificial intelligence-powered data analytics platforms, and it has a large client base in both the commercial and government spaces. Palantir’s software enables those with decision-making authority to act quickly and with the most up-to-date information possible. Furthermore, it also offers automation tools that can task AI agents with jobs that humans have traditionally done, freeing up employees to do work that requires original thinking.

Even after the initial stages of the AI revolution are over, the use cases for AI will continue to grow. Palantir’s software is also a subscription service, so for customers to continue using it, they must pay their Palantir bills every year, while data center operators may be able to put off replacing their Nvidia GPUs for a while. This makes Palantir’s business model more sustainable, giving it the edge here.

Winner: Palantir

Growth rates

Both companies are growing at similar rates, although Nvidia’s sales have decelerated on a percentage basis, while Palantir’s continue to gradually accelerate.

NVDA Revenue (Quarterly YoY Growth) data by YCharts.

Whether Palantir will take the lead on growth or not, only time will tell, but with massive demand for AI services still out there, each will likely maintain a relatively rapid growth rate for the foreseeable future, leading me to view them as fairly evenly matched by this criterion.

Winner: Tie

Valuation

From a valuation standpoint, the comparison isn’t particularly close. Palantir’s stock has delivered incredible returns alongside Nvidia, but a large chunk of Palantir’s share price gains has come from its valuations rising to outsized levels, and that condition is not sustainable.

NVDA PE Ratio (Forward) data by YCharts.

Nvidia trades at a comparatively cheap 42 times forward expected earnings, while Palantir’s ratio tops 275. For comparison, if Nvidia had the same forward P/E as Palantir, it would be worth over $30 trillion, versus the $4.6 trillion it’s actually worth.

This shows that Palantir is overvalued. It will have to deliver years of sales and earnings growth to return the stock to a more reasonable level, even if it simply moves sideways from here. If we set Nvidia’s current valuation of 42 times forward earnings as that “more reasonable” level, and Palantir’s revenue rises at a 50% compound annual growth rate while it maintains a 35% profit margin, it would take over five years’ worth of growth to bring its P/E down to the target. And again, that assumes the stock doesn’t rise during those five years.

That means that Nvidia has basically a five-year head start on Palantir’s long-term stock performance. Given that AI spending is projected to grow rapidly over the next five years, Nvidia shares should easily outperform Palantir moving forward, as Palantir will spend most of the next five years growing into its already expensive valuation. Which is why, despite the two companies’ similar growth rates and Palantir’s more attractive business model, it’s not the AI stock I’d suggest buying now.

Overall winner: Nvidia

Nvidia (NVDA 0.86%) has grown to become the largest company in the world, but the question on many investors’ minds is if the company has more upside ahead in the coming years. The answer looks to be yes.

Powering the AI infrastructure ecosystem

Nvidia is much more than just a chipmaker that makes graphics processing units (GPUs). It is the company whose ecosystem is most responsible for powering the current artificial intelligence (AI) revolution that is taking place.

Nvidia’s biggest advantage starts with its CUDA software platform, which it developed to allow its chips to be easily programmable for tasks outside their original purpose of speeding up graphics rendering in video games. While it took time for other markets to develop, the company smartly gave CUDA away for free to universities and research labs that were doing early work on AI.

This led to nearly all foundational AI code being written on its software and optimized for its chips. Since rewriting code and retraining developers for another platform would be both costly and time-consuming, this has created a huge moat for the company. This can be seen both in the company’s market share and growth. Last quarter, it held a more than 90% market share in the GPU space, while its data center revenue climbed to $41.1 billion, up from just $10.3 billion two years ago.

Nvidia’s moat does not end with CUDA, though. It developed its NVLink interconnect to allow its GPUs to act as a single unit. That keeps customers from mixing in AI chips from other vendors in an AI cluster. Meanwhile, its 2020 purchase of Mellanox gave it a networking component that allows it to provide end-to-end AI factories. Last quarter, its data networking revenue nearly doubled to $7.3 billion, showing how important this has become to the company.

The company is not stopping there. Its up to $100 billion investment in OpenAI gives it a stake in one of the companies at the forefront of AI models and helps give one of its largest customers financing to buy or rent its chips. While OpenAI has struck deals with other chip companies, no one else is getting an equity stake in the ChatGPT maker.

AI infrastructure spending, meanwhile, is showing no signs of slowing. Nvidia estimates that the total addressable market for AI hardware and systems could climb from roughly $600 billion today to as much as $4 trillion in the next several years. Nvidia is bound to get more than its fair share of this spending directed its way.

Image source: Getty Images.

Nvidia’s two-year outlook

Nvidia has indicated that it has the ability to continue to grow revenue at a 50% compound annual growth rate (CAGR) over the next few years. The revenue consensus for its current fiscal year ending in January is around $206.5 billion. At that pace of growth, its 2027 revenue (essentially its fiscal year 2028 ending in January) would be around $465 billion.

If the company’s adjusted operating expenses were to rise by an average of 7% quarter over quarter during this stretch and its gross margin remained around 73%, and we apply a 15% tax rate on its operating income, Nvidia could generate nearly $260 billion in adjusted earnings by 2028 (fiscal 2029), or $10.50 per share, at its current share count of 24.5 billion. Place a 25 times-to-30 times price-to-earnings ratio (P/E) multiple on the stock, and its share price would be between $265 and $315 in two years.

Here is a basic model of what its revenue and earnings growth would look like.

Data source: Estimates based on author’s calculations.

All this means that while its stock has been a huge winner already, Nvidia’s stock still has plenty of upside potential over the next two years and beyond.

Nvidia (NVDA 1.04%) has hit it out of the park quarter after quarter when reporting earnings, but that hasn’t made investors blasé about the artificial intelligence (AI) giant’s next update. Instead, investors wait with just as much anticipation each time around — and even wonder if, this time, they’ll see a slowdown in what’s been a whirlwind growth story.

As investors count the days until the next report — and in this case, it’s set for Nov. 19 — they look for clues about Nvidia’s AI business, one that’s generated record revenue in recent years. Nvidia, as the world’s biggest AI chip designer, delivered $130 billion in revenue in the latest fiscal year — that’s compared to $27 billion just two years earlier.

Now, one particular clue — and one investors truly can count on — comes from Taiwan Semiconductor Manufacturing (TSM -1.68%), a key Nvidia partner. TSMC, the world’s largest chip manufacturer, just announced big news for Nvidia stockholders. 

Image source: Getty Images.

How Nvidia and TSMC work together

Before we get to this fantastic news, though, we’ll take a quick look at Nvidia’s business and how the company works with TSMC. Nvidia for many years built its business around designing chips for the gaming market, but as AI surfaced as a growth opportunity, the company turned its attention there. And, as they say, the rest is history.

Today, Nvidia dominates this market with its high-powered chips as well as related products and services from enterprise software to networking systems. This has helped earnings and the stock price soar — Nvidia shares have climbed more than 1,100% over the past five years.

It’s important to note that though Nvidia is a chip designer, it’s not a chipmaker. Nvidia doesn’t actually manufacture its AI chips, known as graphics processing units (GPUs), and instead turns to TSMC for that job. TSMC has more than 500 customers across segments of the market, including the world’s chip leaders — from Nvidia to Broadcom and Advanced Micro Devices.

A deep look at the industry

On top of this, since the actual production of advanced chips becomes more and more complex with each chip innovation, TSMC starts work with customers two to three years prior to a new project. “Therefore, we probably get the deepest and widest look possible in the industry,” CEO C.C. Wei said during the company’s earnings call this week.

All of this means TSMC has a very clear picture of what’s happening in today’s AI market and what lies ahead. And this brings me to the news the company delivered this week — news that’s a big deal for Nvidia stockholders.

TSMC reported a 39% increase in profit and a 30% increase in revenue in the recent quarter, beating analysts’ estimates. Importantly, Wei said TSMC continues to see a “strong outlook” from customers and “received very strong signals from our customers’ customers. … Our conviction in the AI megatrend is strengthening.” Wei added that semiconductor demand “will continue to be very fundamental.”

Confirming the trend

All of this is incredible news for Nvidia’s shareholders as it confirms the trends the chip designer has spoken of in recent quarters and its prediction for growth in demand. In Nvidia’s most recent earnings report, back in August, CEO Jensen Huang predicted that AI infrastructure spending may jump to $4 trillion by 2030. TSMC’s report this past week offers us reason to be optimistic about that possibility and suggests that Nvidia is already starting to reap the rewards.

As customers seek GPUs, chip designers must turn to TSMC for production — and it’s likely that TSMC’s revenue gains reflect demand for Nvidia’s chips since Nvidia is the market leader.

All of this means there’s reason for investors to be optimistic about Nvidia’s upcoming earnings report and the messages it will deliver regarding future demand for its GPUs. That’s incredible news for Nvidia stockholders — and makes the stock a great one to buy and hold today.

One of the first investors to buy Nvidia (NVDA 1.04%) for the artificial intelligence (AI) boom was Stanley Druckenmiller at his Duquesne Family Office investment fund. At the end of 2023, it was one of his largest positions, a year where the stock more than tripled for investors, putting it on the path to become the largest company in the world by market capitalization.

Then, in 2024, Druckenmiller began to sell down his stake in Nvidia. By the end of last year, he had completely exited his position. What has he been buying instead? Last quarter, Duquesne bought two other trillion-dollar AI stocks: Taiwan Semiconductor Manufacturing (TSM -1.68%) and Microsoft (MSFT -0.43%).

Let’s see whether you should follow Druckenmiller and buy these two stocks for your portfolio today.

Image source: Nvidia.

Nvidia’s semiconductor supplier

Some readers may already know this, but Nvidia does not manufacture its advanced computer chips itself. It only designs them. The key manufacturing supplier of Nvidia chips is Taiwan Semiconductor Manufacturing, or TSMC for short. TSMC only makes computer chips for third parties and is known as a semiconductor foundry. These include Nvidia, but also the likes of Apple, Broadcom, and other technology giants.

With the insatiable demand for computer chips from the growing AI market, TSMC has been doing quite well in recent quarters. Last quarter, revenue grew 44.4% year over year to $30 billion. Not only is TSMC one of the largest businesses in the world, but one of the fastest growing.

As one of the only companies that can manufacture advanced semiconductors at scale, TSMC has been able to sell its computer chips to customers like Nvidia with fat profit margins. Last quarter, operating margin was close to 50%, which is unheard of for a manufacturing business.

At today’s stock price, TSMC trades at a price-to-earnings ratio (P/E) of 34. While this is slightly expensive, it is much better than Nvidia’s P/E ratio of 51. When you consider that both stocks will benefit from the growing demand for AI computer chips, it is no surprise that Duquesne sold its stake in Nvidia and owns TSMC today instead.

Microsoft’s opportunity in AI

Microsoft is a large customer of Nvidia as the company accelerates its buildout of cloud computing data center infrastructure to power the AI revolution. It has a relationship with OpenAI, the leading private AI company that is spending hundreds of billions of dollars on infrastructure. In 2025 alone, Microsoft is planning to spend $80 billion on capital expenditures to help catch up with AI demand.

Its cloud revenue is benefiting massively from the growth in AI. Its Azure cloud computing division grew revenue 34% year over year last quarter to $75 billion, making it the second-largest cloud business in the world apart from Amazon Web Services (AWS). Overall revenue is growing well due to Microsoft’s diversified assets in personal computing, Office 365 subscriptions, and other services such as LinkedIn. Revenue was up 17% year over year last quarter, with operating income up 22% (both in constant currency). Expanding operating margins to 45% makes Microsoft one of the most profitable businesses in the world.

Like TSMC, Microsoft trades at a much cheaper P/E ratio than Nvidia, at 37.5 as of this writing. With steady growth, margin expansion, and a clear line of new demand for Azure for AI solutions, Microsoft looks like a solid buy-and-hold stock for investors over the next decade and beyond.

At the end of the second quarter, TSMC was 4.3% of the Duquesne stock portfolio, according to its 13F filing, increasing its position by 27% more shares in the period. Microsoft was a completely new buy for the fund, but it is already a 2.5% position. Both stocks have done well throughout the second and third quarters, but can still be good long-term buys for investors looking for inspiration from super investors like Druckenmiller.

The artificial intelligence (AI) revolution is transforming every corner of the global economy. Nvidia, the company at the center of this revolution, continues to be a Wall Street favorite for all the right reasons. As an undisputed leader in accelerated computing, the company’s hardware and software power much of the world’s AI infrastructure buildout.

Shares of Nvidia have already surged over 43% so far in 2025. However, despite the massive demand for its Blackwell architecture systems, software stack, and networking solutions, the stock may grow quite modestly in future months. With its market capitalization now exceeding $4.6 trillion and shares trading at a premium valuation of nearly 30 times forward earnings, much of the optimism is already priced in.

Memory giant Micron (MU 6.12%), on the other hand, is still in the early stages of its AI-powered growth story. Shares of the company have surged nearly 128% in 2025, which highlights the increasing investor confidence in its high-bandwidth memory and data center portfolio. Yet, Micron could still offer investors higher returns in 2026, while riding the same AI wave. Here’s why.

Image source: Getty Images.

Lower customer concentration risk

Wall Street has been highlighting one significant underappreciated risk for Nvidia. Nvidia’s revenues depend heavily on a few hyperscaler customers, with two accounting for 39% and four accounting for 46% of its revenues in the second quarter of fiscal 2026 (ending July 27, 2026). Many of these hyperscaler clients are developing proprietary chips, which may offer a price-performance optimization in their specific workloads. This may reduce their dependence on Nvidia’s chips in future years.

Micron’s revenue base is significantly more diversified than Nvidia’s. The company’s largest customer accounted for 17% of total revenue, while the next largest contributed 10% in fiscal 2025 (ending Aug. 28, 2025). The company has earned over half of its total revenues from the top 10 customers for the past three years. The company has a reasonably broad customer base, including data center, mobile, PC, automotive, and industrial markets.

Hence, compared with Nvidia, Micron’s lower concentration risk makes it more resilient in the current economy.

HBM demand and AI memory leadership

Micron’s high-bandwidth memory (HBM) products, known for their superior data transfer speeds and energy efficiency, are being increasingly used in data centers. HBM revenues reached nearly $2 billion in the fourth quarter of fiscal 2025, translating into $8 billion annualized run rate.

Management expects Micron’s HBM market share to match its overall DRAM share by the third quarter of fiscal 2025. The company now caters to six HBM customers and has entered into pricing agreements covering most of the 2026 supply of HBM third-generation extended (HBM3E) products.

Micron has also started sampling HBM fourth-generation (HBM4) products to customers. The company expects the first production shipment of HBM4 in the second quarter of calendar year 2026 and a broader ramp later that year.

Beyond HBM, Micron’s Low-Power Double Data Rate (LPDDR) memory products are also seeing strong demand in data centers. The data center business has emerged as a key growth engine, accounting for 56% of Micron’s total sales in fiscal 2025.

Hence, Micron seems well-positioned to capture a significant share of the AI-powered memory demand in the coming years.

Valuation

Micron appears to offer a stronger risk-reward proposition than Nvidia, even in the backdrop of accelerated AI infrastructure spending. The company currently trades at 12.3 times forward earnings, significantly lower than Nvidia’s valuation. Hence, while Nvidia’s premium valuation already assumes near-perfect execution and continued dominance, Micron still trades like a cyclical memory stock. This disconnect leaves room for modest valuation expansion to account for Micron’s improving revenue mix toward high-margin AI memory products.

Wall Street sentiment is also increasingly positive for Micron. Morgan Stanley’s Joseph Moore recently upgraded the stock from equal-weight or neutral to overweight and raised the target price from $160 to $220. UBS has reiterated its “Buy” rating and increased the target price from $195 to $225. Itau Unibanco analyst has initiated coverage for Micron with a “Buy” rating and target price of $249.

Analysts expect Micron’s earnings per share to grow year over year by nearly 100% to $16.6 in fiscal 2026. If the current valuation multiple holds, Micron’s share price could be around $204 (up 6% from the last closing price as of Oct. 9), with limited downside potential. But if the multiple expands modestly in the range of 14 to 16 times forward earnings, shares could fall in the range of $232 to $265, offering upside of 20% to 37.8%.

On the other hand, there remains a higher probability of valuation compression for Nvidia, leaving less room for growth. With diversified customers, increasing AI exposure, and reasonable valuation, Micron may prove to be the better semiconductor pick in 2026.

Nvidia (NVDA -4.84%) last reported earnings on Aug. 27. That was another blowout report from the artificial intelligence (AI) chip leader. Revenue soared 56% year over year in its fiscal 2026 second quarter, and sales of its AI platform Blackwell to data center clients grew by 17% from the prior quarter.

Yet Nvidia stock has only moved about 2% higher since that report as I write this on Oct. 7. That’s not because investors weren’t impressed with the company’s results. It’s because it has made a habit of beating expectations. Investors anticipated that it would do so again, and sent Nvidia stock soaring by nearly 20% in the weeks leading up to that report.

Nvidia is scheduled to report its fiscal third-quarter results on Nov. 19, and it’s possible that a similar scenario will play out this time around. That would make now the time to buy the stock — if you’re looking at the short term — ahead of its next run higher as investors jump in closer to the report date.

Image source: Nvidia.

Don’t get complacent on Nvidia

Expectations will once again be high. For its fiscal 2026 third quarter, management has guided investors to expect about 15% sequential growth, or 54% year-over-year sales growth. That forecast is even more remarkable considering that it doesn’t include any potential H20 chip shipments to China.

Investors shouldn’t yawn at those numbers. After this many quarters of similarly incredible growth rates from the GPU leader, it’s possible that the market is starting to take them for granted. But investors shouldn’t forget just how much cash flow that growth will result in. That cash should eventually make its way back to shareholders through buybacks, dividends, or share price growth.

The lesson for investors is not to sleep on Nvidia. Expectations may be high, but this is not a story stock. Its revenues and cash flow are real. The next healthy slice of short-term gains for the stock might be arriving in the next few weeks, leading up to Nvidia’s Q3 earnings report. But this is a stock that it makes sense to own for the long term. That makes buying Nvidia stock now a smart move either way.

In late August, I was listening to Nvidia‘s (NVDA -4.84%) earnings call for its fiscal second quarter (ended July 27). When Colette Kress, CFO of the artificial intelligence (AI) tech leader, gave quantifiable data about the company’s sovereign AI business, I thought, “Finally!” as such data is only rarely shared.

Nvidia’s sovereign AI business is growing like gangbusters. It appears to be the biggest growth engine of the company’s AI-driven data center platform, which accounts for the bulk of Nvidia’s total revenue. Yet, it gets little coverage in the financial press.

“Sovereign entities” are those that are independent and have total or at least significant control within their borders. This includes many nations, U.S. states, and the European Union (EU).

Image source: Getty Images.

Nvidia “on track to achieve over $20 billion in sovereign AI revenue this year”

From Kress’ remarks on last quarter’s earnings call:

Sovereign AI is on the rise as the nation’s ability to develop its own AI using domestic infrastructure, data, and talent presents a significant opportunity for NVIDIA Corporation. NVIDIA Corporation is at the forefront of landmark initiatives across the UK and Europe. …

We are on track to achieve over $20 billion in Sovereign AI revenue this year, more than double that of last year.

I’ll put the $20 billion in context below.

Kress said that the EU plans to invest 20 billion euros to establish 20 AI factories in France, Germany, Italy, and Spain. This will include five gigafactories, and it will increase its AI compute infrastructure by 10-fold.

A “gigafactory” means that the AI compute facility will contain the number of Nvidia’s graphics processing units (GPUs) — which dominate the market for AI chips — that require at least 1 gigawatt of power. For context, 1 gigawatt (or 1,000 megawatts) equates to about the power output of a large-scale nuclear power plant.

Nvidia CEO: “Nations are investing in AI infrastructure like they once did for electricity and the Internet.”

The above quote is from CEO Jensen Huang’s remarks on Nvidia’s fiscal first-quarter earnings call in May. Here are more Huang snippets from that call:

I was honored to join him [President Donald Trump, in May] in announcing a 500-megawatt AI infrastructure project in Saudi Arabia …

[In May,] we announced Taiwan’s first AI factory … Last week, I was in Sweden to launch its first national AI infrastructure. Japan, Korea, India, Canada, France, the UK, Germany, Italy, Spain, and more are now building national AI factories to empower startups, industries, and societies. … [N]ations are investing in AI infrastructure like they once did for electricity and the Internet.

All the countries that Huang rattled off as building sovereign AI infrastructure are using Nvidia’s GPUs and related technology. Talk about big customers!

Putting the sovereign AI business’ projected annual growth in context

For the current fiscal year (fiscal 2026, which ends in late January), Wall Street expects Nvidia’s revenue to be $206.5 billion, up 58% from $130.5 billion last fiscal year. If that estimate proves relatively accurate and the sovereign AI business brings in revenue of $20 billion, it will account for about 9.7% of total revenue. And Kress said “over $20 billion,” so the percentage could be higher.

Below are more stats for further context.

Data source: Nvidia. *Calculations by author.

The above are half-year stats, but they give you an idea of what a standout performer Nvidia’s sovereign AI business is. Given the annual projections Kress shared, this business probably generated first-half revenue in the ballpark of $8 billion, or 10% of the data center’s revenue, and likely grew 100%-plus year over year.

Why Nvidia’s sovereign AI strategy is particularly brilliant

Nvidia is not only selling its technology to sovereign entities, it’s also assisting them in their massive undertakings. These relationships should make Nvidia’s sovereign AI business especially “sticky.” Countries that are happy with Nvidia are likely to stick with Nvidia when they want to upgrade or expand their AI infrastructure.

The sovereign AI business should also lead to other opportunities for Nvidia. Companies, researchers, and technology students that use and become familiar with a country’s sovereign AI infrastructure will probably be more likely to buy Nvidia’s offerings if and when they need their own AI-enabling tech.

Nvidia has been the face of the artificial intelligence (AI) race since it began in 2023. However, there’s another competitor that’s looking to take over Nvidia’s leadership role: Broadcom (AVGO -0.26%).

While Broadcom has its fingers in many parts of tech, its most promising segment is its AI chip business, and it’s growing rapidly. Broadcom is already a $1.6 trillion company, but could it find its way near the top and become the next Nvidia? Let’s take a look.

Broadcom’s custom AI accelerators are a GPU alternative

Broadcom’s AI semiconductor division gets its revenue from two primary sources: Custom AI accelerators and connectivity switches. Broadcom’s connectivity switches, like the Tomahawk3, are used in data centers to stitch workloads back together after they have been split up to be processed among multiple computing units. This makes Broadcom’s connectivity switches vital for data centers, regardless of what computing unit is being used.

This product line has seen strong growth, but it’s nothing compared to the potential of Broadcom’s custom AI accelerator chips, which it calls XPUs. Broadcom’s XPUs are designed in collaboration with end users to ensure the architecture is suited for the workloads it will see. By designing a custom chip around a specific workload for each client, XPUs can have greater performance than Nvidia’s graphics processing units (GPUs). Additionally, because the end user is working directly with Broadcom, these units are far cheaper than anything from Nvidia.

The combination of better performance at a lower cost is a no-brainer, and that’s why companies like Alphabet and Meta Platforms have allegedly (Broadcom doesn’t reveal who its XPU clients are) invested heavily in their XPUs. Additionally, it announced that a new client placed an order for $10 billion worth of XPUs. This has been linked to OpenAI, the creator of ChatGPT, giving Broadcom the status of providing computing units for nearly all of the top generative AI models.

So, is Broadcom set to replace Nvidia?

Nvidia still has more to gain from the AI buildout than Broadcom does

The reality is that these AI hyperscalers know what their AI workloads will look like. However, cloud infrastructure companies, like Alphabet, Amazon, and Microsoft, must continue purchasing Nvidia GPUs because clients want flexibility. Furthermore, if one of the AI hyperscalers wants to try something different to run workloads in a new way, they’ll need the flexibility of a GPU.

So, Nvidia isn’t going away, but I’d expect Broadcom’s chips to become far more popular over the next few years. We’re already seeing that now, as Nvidia’s data center revenue rose 56% year over year while Broadcom’s AI semiconductor revenue rose 63%. Broadcom will need to maintain that quicker growth pace if it is to rise to be in true competition with Nvidia, but with how rapidly demand for XPUs is growing, I wouldn’t be surprised if that’s the case.

During its third-quarter fiscal year 2025 (ending Aug. 3) announcement, Broadcom predicted that it would generate $6.2 billion in AI semiconductor revenue during the fourth quarter, up from $5.2 billion in Q3. That’s rapid quarter-over-quarter growth, but it is still slower than Nvidia’s peak growth pace last year.

Time will tell how well Broadcom’s XPUs do, but I’d wager that Broadcom’s AI semiconductor division will grow faster than Nvidia for the foreseeable future. However, because Broadcom is far more diversified than Nvidia, it won’t deliver the same explosive growth. Despite its AI semiconductor revenue growing at a 63% pace, Broadcom’s overall revenue increased at a 22% pace during Q3. Nearly all of Nvidia’s revenue comes from data centers, and its 56% data center growth pace was identical to its overall revenue growth rate.

As a result, Nvidia still looks like the better stock pick here. It’s more exposed to the AI data center buildout trend, as long as that spending holds up. With AI hyperscalers all announcing record capital expenditure for 2026, I think it’s safe to assume that this trend will continue. Although Broadcom is an excellent pick, I still think Nvidia will outperform it through 2026.

Nvidia is arguably the king of Wall Street these days. As the maker of high-performing graphics processing units (GPUs) that power artificial intelligence (AI) programs and large language models, Nvidia’s stock price exploded in the last three years, up nearly 1,500%. The company now boasts a market capitalization of $4.6 trillion, making it the biggest company in the world by valuation, and it seems to be a lock to reach $5 trillion soon.

While Nvidia is having another solid year in 2025, boasting a 41% gain, there’s another AI stock that’s doing even better — one that’s essential to the success of Nvidia and nearly every other major chipmaker.

Better than Nvidia

Taiwan Semiconductor Manufacturing (TSM 3.46%), better known as TSMC, is the biggest semiconductor fabricator in the world. It doesn’t design chips, but it builds them in its fabrication plants for Nvidia and other customers, including Broadcom, Advanced Micro Devices, Apple, Tesla, and more.

TSMC stock is up 45% so far this year, beating Nvidia’s year-to-date gain, and just set a new all-time high. And it’s also a better valued stock, with price-to-earnings and price-to-sales ratios that are much more appealing than Nvidia.

TSM PE Ratio data by YCharts

Now for the icing on the cake. Nvidia’s CEO loves Taiwan Semiconductor and recently tipped his cap to TSMC. “They are a world-class foundry and support customers of diverse needs. You can’t overstate the magic that is TSMC,” Jensen Huang told reporters in September.

Image source: The Motley Fool.

What makes TSMC tick?

Taiwan Semiconductor’s biggest business is making 3-nanometer and 5nm chips. The company gets 60% of its revenue from making the chips.

TSMC is one of a select few fabricators that can make the highly sought-after 3nm chips at scale, and that’s a big deal. The smaller the transistors on chips, the more that companies such as Tesla and Nvidia can cram into them to make them more powerful. And TSMC already has plans to mass-produce its 2nm process this year.

TSMC also makes semiconductors used in smartphones, making 5G communication possible for a mass audience. 5G allows wireless users to access the internet at broadband speeds, which means you can do pretty much anything you need from your laptop, tablet, or phone, including streaming high-resolution videos or content, or work remotely.

The company gets a smaller portion of its revenue from Internet of Things devices such as smart home products and wearable technology. It also makes chips for electric vehicles, driver assistance programs, and vehicle information and entertainment systems.

Revenue in the second quarter was $30.07 billion, up 44.4% from a year ago, with an outstanding net profit margin of 42.7%. And the numbers are expected to be even better next quarter, when the company is projecting revenue between $31.8 billion and $33 billion.

TSMC is also expanding rapidly, investing $165 billion into creating fabrication plants and other facilities in Arizona. That’s important to help insulate Taiwan Semiconductor from the threat of tariffs or other economic headwinds as the U.S. government seeks to bring manufacturing to American soil.

Should you buy Nvidia or TSMC?

If you’re just picking one stock to buy now, my choice would be TSMC. The company has a 70% market share in the foundry market, according to market research firm TrendForce, giving it an enormous moat. And when you consider the semiconductor industry is a $600 billion business that’s projected to reach $1 trillion annually by 2030, the market opportunity for Taiwan Semiconductor is huge.

And it also has a dividend, which you don’t often see in an AI stock. Taiwan Semiconductor’s yield of 1.2% and payout of $3.34 per share won’t make you a millionaire, but it’s loads better than the skimpy $0.04 that Nvidia pays out annually.

All in, TSMC is a cheaper stock than Nvidia and is absolutely essential to the semiconductor and AI industries. But if you have room in your portfolio, you should invest in both. Together, TSMC and Nvidia are an unstoppable two-headed AI powerhouse that can anchor any portfolio.