Assetmark Inc. grew its holdings in NVIDIA Corporation (NASDAQ:NVDA – Free Report) by 1.3% during the first quarter, according to the company in its most recent filing with the Securities and Exchange Commission. The firm owned 5,856,371 shares of the computer hardware maker’s stock after acquiring an additional 73,458 shares during the period. NVIDIA comprises approximately 2.1% of Assetmark Inc.’s holdings, making the stock its 4th biggest holding. Assetmark Inc.’s holdings in NVIDIA were worth $1,021,351,000 as of its most recent SEC filing.
Other hedge funds and other institutional investors have also recently bought and sold shares of the company. Diversified Enterprises LLC lifted its holdings in NVIDIA by 44.2% in the fourth quarter. Diversified Enterprises LLC now owns 127,604 shares of the computer hardware maker’s stock worth $23,798,000 after purchasing an additional 39,129 shares during the period. ASR Vermogensbeheer N.V. increased its holdings in shares of NVIDIA by 1.8% in the fourth quarter. ASR Vermogensbeheer N.V. now owns 3,169,377 shares of the computer hardware maker’s stock valued at $591,086,000 after buying an additional 54,877 shares in the last quarter. Storen Legacy Partners LLC purchased a new stake in shares of NVIDIA during the fourth quarter valued at $1,350,000. Weaver Capital Management LLC lifted its stake in NVIDIA by 5.5% during the fourth quarter. Weaver Capital Management LLC now owns 85,216 shares of the computer hardware maker’s stock valued at $15,893,000 after buying an additional 4,439 shares in the last quarter. Finally, Arrowstreet Capital Limited Partnership boosted its stake in NVIDIA by 3.6% in the 4th quarter. Arrowstreet Capital Limited Partnership now owns 26,652,420 shares of the computer hardware maker’s stock worth $4,970,704,000 after purchasing an additional 936,506 shares during the period. 65.27% of the stock is owned by institutional investors and hedge funds.
Insider Activity In other NVIDIA news, Director Mark A. Stevens sold 885,000 shares of NVIDIA stock in a transaction on Thursday, June 18th. The shares were sold at an average price of $210.17, for a total transaction of $186,000,450.00. Following the completion of the sale, the director owned 5,207,271 shares of the company’s stock, valued at approximately $1,094,412,146.07. The trade was a 14.53% decrease in their position. The transaction was disclosed in a legal filing with the Securities & Exchange Commission, which is accessible through the SEC website. Also, Director Stephen C. Neal sold 15,500 shares of the company’s stock in a transaction dated Wednesday, June 3rd. The shares were sold at an average price of $215.73, for a total value of $3,343,815.00. Following the completion of the sale, the director owned 116,135 shares of the company’s stock, valued at $25,053,803.55. This represents a 11.77% decrease in their position. The SEC filing for this sale provides additional information. Insiders have sold 1,901,125 shares of company stock valued at $410,583,015 over the last 90 days. 3.94% of the stock is owned by company insiders.
NVIDIA Price Performance NASDAQ:NVDA opened at $197.01 on Wednesday. The company’s 50-day moving average price is $206.86 and its two-hundred day moving average price is $195.98. NVIDIA Corporation has a 12 month low of $164.07 and a 12 month high of $236.54. The firm has a market cap of $4.77 trillion, a PE ratio of 30.17, a price-to-earnings-growth ratio of 0.38 and a beta of 2.21. The company has a quick ratio of 2.85, a current ratio of 3.44 and a debt-to-equity ratio of 0.04.
NVIDIA (NASDAQ:NVDA – Get Free Report) last posted its quarterly earnings data on Wednesday, May 20th. The computer hardware maker reported $1.87 EPS for the quarter, topping analysts’ consensus estimates of $1.76 by $0.11. The company had revenue of $81.61 billion for the quarter, compared to analyst estimates of $78.42 billion. NVIDIA had a return on equity of 96.94% and a net margin of 62.97%.The business’s revenue was up 85.2% on a year-over-year basis. During the same quarter in the previous year, the firm earned $0.81 earnings per share. On average, equities analysts anticipate that NVIDIA Corporation will post 8.79 EPS for the current fiscal year.
NVIDIA declared that its board has authorized a stock buyback program on Wednesday, May 20th that allows the company to buyback $80.00 billion in outstanding shares. This buyback authorization allows the computer hardware maker to purchase up to 1.5% of its stock through open market purchases. Stock buyback programs are typically an indication that the company’s management believes its stock is undervalued.
NVIDIA Increases Dividend The company also recently disclosed a quarterly dividend, which was paid on Friday, June 26th. Shareholders of record on Thursday, June 4th were issued a dividend of $0.25 per share. The ex-dividend date of this dividend was Thursday, June 4th. This represents a $1.00 annualized dividend and a yield of 0.5%. This is a positive change from NVIDIA’s previous quarterly dividend of $0.01. NVIDIA’s dividend payout ratio (DPR) is currently 15.31%.
Analysts Set New Price Targets NVDA has been the subject of a number of research reports. Zacks Research upgraded NVIDIA from a “hold” rating to a “strong-buy” rating in a research report on Monday, July 20th. Rosenblatt Securities reissued a “buy” rating and set a $325.00 target price on shares of NVIDIA in a research report on Thursday, May 21st. The Goldman Sachs Group reissued a “buy” rating and issued a $285.00 price target (up from $250.00) on shares of NVIDIA in a research report on Wednesday, May 20th. BTIG Research initiated coverage on NVIDIA in a research report on Wednesday, April 15th. They set a “buy” rating for the company. Finally, Mizuho set a $300.00 price target on shares of NVIDIA in a research report on Thursday, May 21st. Three equities research analysts have rated the stock with a Strong Buy rating, forty-eight have issued a Buy rating and two have given a Hold rating to the company’s stock. Based on data from MarketBeat.com, the stock has an average rating of “Buy” and an average target price of $304.26.
Check Out Our Latest Report on NVIDIA
Key Headlines Impacting NVIDIA Here are the key news stories impacting NVIDIA this week:
Positive Sentiment: CEO Jensen Huang is emphasizing robotics and “physical AI” as the next major growth market, spanning autonomous machines, vehicles, factories and data centers. The company’s expanded Agent Toolkit, PhysicsNeMo and CUDA-X libraries are also being adopted by Cadence, Siemens, Synopsys, Samsung and Silvaco, supporting a broader software-and-platform ecosystem beyond GPU sales. NVIDIA robotics growth article Positive Sentiment: New strategic relationships with Safe Superintelligence, OpenAI, NAVER and other infrastructure partners could increase demand for NVIDIA’s Vera Rubin and Blackwell systems. Analysts remain broadly bullish, with reported price targets well above current trading levels. NVIDIA Safe Superintelligence investment article Neutral Sentiment: NVIDIA is reportedly discussing a potential backstop of up to $250 billion for OpenAI’s Ohio data-center project, alongside a much larger overall infrastructure plan. The arrangement could lock in substantial future chip demand, but it would also expand NVIDIA’s role from supplier to financier and expose it to OpenAI’s creditworthiness and project-execution risks. NVIDIA OpenAI financing article Negative Sentiment: Investors remain concerned that vendor-backed AI infrastructure spending represents circular financing rather than organic customer demand. Reports that NVIDIA could guarantee OpenAI-related obligations helped trigger a broad chip-stock selloff, while rising default-insurance costs have intensified balance-sheet concerns. NVIDIA default insurance costs article Negative Sentiment: Taiwanese authorities reportedly detained an NVIDIA employee in a probe involving alleged diversion of Super Micro AI servers to China. Although no wrongdoing by NVIDIA has been established, the investigation raises additional export-control, legal and reputational risks. Intensifying Chinese competition and weakness across Asian chip stocks are adding pressure to the sector. Taiwan NVIDIA employee investigation article NVIDIA Profile (Free Report)
NVIDIA Corporation, founded in 1993 and headquartered in Santa Clara, California, is a global technology company that designs and develops graphics processing units (GPUs) and system-on-chip (SoC) technologies. Co-founded by Jensen Huang, who serves as president and chief executive officer, along with Chris Malachowsky and Curtis Priem, NVIDIA has grown from a graphics-focused chipmaker into a broad provider of accelerated computing hardware and software for multiple industries.
The company’s product portfolio spans discrete GPUs for gaming and professional visualization (marketed under the GeForce and NVIDIA RTX lines), high-performance data center accelerators used for AI training and inference (including widely adopted platforms such as the A100 and H100 series), and Tegra SoCs for automotive and edge applications.
Recommended Stories Five stocks we like better than NVIDIA These 3 Stocks Have Soared in 2026—Can They Keep Climbing? Hasbro’s Earnings Beat Shows Why This Is No Longer Just a Toy Story Rambus: Another AI Phoenix Ready to Rise From the Ashes of Correction Chips & Clips: Memory Tariffs Rewire Tech Supply Chains Want to see what other hedge funds are holding NVDA? Visit HoldingsChannel.com to get the latest 13F filings and insider trades for NVIDIA Corporation (NASDAQ:NVDA – Free Report).
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Nvidia (NVDA +0.42%) stock investors are concerned about circular financing arrangements proliferating.
*Stock prices used were the afternoon prices of July 26, 2026. The video was published on July 28, 2026.
Parkev Tatevosian, CFA has positions in Nvidia. The Motley Fool has positions in and recommends Nvidia. The Motley Fool has a disclosure policy. Parkev Tatevosian is an affiliate of The Motley Fool and may be compensated for promoting its services. If you choose to subscribe through his link, he will earn some extra money that supports his channel. His opinions remain his own and are unaffected by The Motley Fool.
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Comparison between State Street SPDR Portfolio MSCI Global Stock Market ETF (SPGM -0.07%) and iShares MSCI Emerging Markets ETF (EEM -1.98%) hinges on whether an investor wants targeted, higher-cost emerging markets exposure or broad, low-cost global diversification.
These two funds provide access to international equities but with significantly different geographic scopes. One targets developing economies exclusively, while the other serves as a diversified core holding for stocks across both established and developing nations worldwide.
Snapshot (cost & size)MetricEEMSPGMIssueriSharesSPDRShare price$63.62 (as of 2026-07-27)$84.34 (as of 2026-07-27)Expense ratio0.72%0.09%1-yr return (as of 2026-07-27)31.00%21.10%Dividend yield1.80%1.80%Beta0.740.92AUM$28.6 billion$1.7 billionBeta measures price volatility relative to the S&P 500; beta is calculated from monthly returns over the available fund history (up to five years). The 1-yr return represents total return over the trailing 12 months. Dividend yield is the trailing-12-month distribution yield as of the close of trading on July 27.
The State Street SPDR Portfolio MSCI Global Stock Market ETF is substantially more affordable, carrying an expense ratio of 0.09% compared to 0.72% for the iShares fund. Both ETFs currently provide a matching trailing-12-month dividend yield of 1.80%.
Performance & risk comparisonMetricEEMSPGMMax drawdown (5 yr)(35.00%)(25.90%)Growth of $1,000 over 5 years (total return)$1,381$1,677What's insideThe State Street SPDR Portfolio MSCI Global Stock Market ETF (SPGM) provides exposure to stocks across the globe. Sector weights include technology at 31%, financial services at 17%, and industrials at 13%. With 2,923 holdings, the top positions include Nvidia Corp (NVDA +0.42%) at 4.1%, Apple Inc (AAPL +1.02%) at 3.8%, and Microsoft Corp (MSFT +1.15%) at 2.3%. The fund was launched in 2012. State Street SPDR Portfolio MSCI Global Stock Market ETF has paid $1.54 per share over the trailing 12 months, which on its recent ~$84.34 share price works out to a 1.80% yield.
The iShares MSCI Emerging Markets ETF (EEM) focuses exclusively on developing economies. Its allocation includes technology at 46%, financial services at 18%, and consumer cyclical stocks at 7%. Top holdings include Taiwan Semiconductor Manufacturing at 15.1%, Samsung Electronics at 8.1%, and the South Korean listing of SK Hynix at 7.6%. The fund was launched in 2003. It currently reports 1,190 holdings. iShares MSCI Emerging Markets ETF has paid $1.11 per share over the trailing 12 months, which, on its recent ~$63.62 share price, works out to a 1.80% yield.
Which fund is the better buy?These two funds provide similar exposure to equity markets around the world, but they have key differences that investors should consider before investing.
Stylistically, both funds are heavily weighted toward large-cap stocks, with the iShares MSCI Emerging Markets ETF (EEM) holding 92% of its assets in large caps, while the level is 78% for the State Street SPDR Portfolio MSCI Global Stock Market ETF (SPGM). Both are also less weighted in their top 10 than you find in other ETFs, with EEM allocating 37% of its portfolio to its top 10, while SPGM dedicates 21% of its assets to its top 10.
The major difference between them is the geographic exposure they provide to investors. SPGM is two-thirds U.S.-listed equities, 31% developed, non-U.S. markets, and the balance emerging markets. EEM has about 50% of its holdings in non-U.S. developed markets and just 1% in U.S. stocks. Just about 49% of the fund is in emerging markets.
If none of those differences tips the scale for investors, then performance should. EEM is benefiting from the outsize growth of non-U.S. markets in recent years, a trend to be expected given its focus on less-developed markets. It has returned 26% year-to-date, compared with about 12% for SPGM, and it also has the superior 1-year performance detailed earlier. EEM also outperforms SPGM over the 3-year time frame, with annualized returns of 22.9% versus 20.2%. Long-term however. SPGM has bested EEM, returning 11.4% and 13.1% in the 5-year and 10-year look-backs compared to 5- and 10-year gains of of 6.9% and 9.6%, respectively, for EEM.
The recent performance of EEM is appealing, but the long-term gains of SPGM, plus its lower expense ratio, make it the better fund for 2026.
For more guidance on ETF investing, check out the full guide at this link.
Nvidia (NVDA +0.42%) hasn't been the workhorse stock it normally is in 2026. This year, it has risen around 11%, just barely outpacing the S&P 500, up just over 8%. That's not the market-crushing performance investors have come to expect from the world's largest company. Fortunately for investors, I think Nvidia's time is coming. The stock is trading at a shockingly low valuation right now, and it could be one of the best buying opportunities in years.
Let's take a look at Nvidia's valuation and see why right now is the perfect time to load up on shares.
Image source: Nvidia.
Nvidia's valuation has reached must-buy levels When valuing a fast-growing company like Nvidia, the forward price-to-earnings (P/E) ratio is often used over the trailing one because it gives investors an idea of where it's heading rather than where it has been. Still, regardless of which ratio you use, Nvidia's stock looks quite attractive.
NVDA PE Ratio data by YCharts
Nvidia's trailing P/E ratio of 31.7 is the lowest it has been during the artificial intelligence trend, which began in 2023. It's also close to several of its big tech peers. Companies like Apple and Amazon trade for 40.3 and 27.8 times trailing earnings, respectively. Nvidia is growing far faster than either of them, with its year-over-year growth rate clocking in at 85%.
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From a forward earnings perspective, 23 times forward earnings is barely more expensive than the S&P 500, which trades at 21.1 times forward earnings. However, with the AI build-out expected to last several more years, this market-average price tag on Nvidia's stock makes it seem like an absolute steal. It's not often you can buy a stock that's trading at essentially the same price tag as the broader market that's expected to grow revenue at a 42% growth rate the following year.
This means that none of next year's expected success is priced into Nvidia's stock, and it could be primed for major upside in the second half of 2026. So, if you've been holding onto Nvidia shares in anticipation of incredible returns, my advice is to hold on just a little longer, as they could be on the way.
We're starting to hear more reports from AI hyperscalers of increased spending in 2027, and Nvidia itself has already forecast $1 trillion or more in data center capital expenditures from them. That would indicate substantial growth, making Nvidia a must-buy now, as none of that growth has been priced into Nvidia's stock.
Keithen Drury has positions in Amazon and Nvidia. The Motley Fool has positions in and recommends Amazon, Apple, and Nvidia. The Motley Fool has a disclosure policy.
The stock market can be an incredible wealth-building machine for patient investors. Over the last 30 years, the S&P 500 (^GSPC +0.37%) index has delivered a compound annual return of 10.5%, which would have turned an investment of $10,000 into almost $208,760. Many individual stocks have performed even better, albeit with more volatility along the way.
But for young investors in their 20s, taking a little more risk for the opportunity to earn higher returns can be a worthwhile trade-off. If I were that age today, I'd buy these three stocks with the intention of holding them for the next 30 or 40 years until retirement.
Image source: Getty Images.
1. Nvidia Since going public in 1999, Nvidia (NVDA +0.44%) stock has returned a mind-boggling 831,900%. That translates to a compound annual return of almost 40% over the last 27 years, four times higher than the average annual gain in the S&P 500 over the same period.
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Nvidia created the world's first graphics processing unit (GPU) in the late 1990s, which redefined 3D graphics for personal computers. Today, it makes the best GPUs for data centers, which are designed to handle artificial intelligence (AI) training and inference workloads. Demand is outstripping supply for those chips, and the company's new Vera Rubin generation will only widen the imbalance.
This gives Nvidia the power to dictate prices, which is partly why its revenue soared by 65% to a record $215.9 billion during fiscal 2026 (ended Jan. 25). According to Wall Street's average estimate (provided by Yahoo Finance), the company's revenue could top $393 billion in the current 2027 fiscal year.
Although AI is Nvidia's primary growth driver today, the company is well-positioned to become a top supplier of chips and components for emerging technologies such as autonomous vehicles and robots. Earlier this year, CEO Jensen Huang said the market for humanoid robots alone could top $40 trillion over the long term, dwarfing the current AI data center opportunity.
As a result, while it's unlikely Nvidia stock will maintain a 40% annual return from here because of the company's sheer size, I think it still has the potential to outperform the broader market over the next 30 or 40 years.
2. Amazon Amazon (AMZN -0.08%) stock went public in 1997, and it has since climbed by a staggering 309,230%, or a compound annual rate of 32%. So, like Nvidia, it has obliterated the broader market.
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Amazon is an incredibly diverse technology company. Amazon.com is the biggest e-commerce platform in the world, while Amazon Web Services (AWS) dominates the cloud computing industry, and Amazon Prime Video has become a leading streaming platform for movies and television shows. The company is using AI across all of its businesses to unlock new revenue streams, improve efficiency, and create a better customer experience.
For example, Amazon has built an AI shopping assistant for its e-commerce website, which helps customers compare products and make purchase decisions. It has also deployed over 1 million AI-powered robots in its fulfillment centers to speed up its logistics processes. Further, the AWS platform operates some of the best data centers for AI development, which it rents to other businesses for a fee. This has become one of the most profitable practices in the company's history.
Amazon has never rested on its laurels. I think the company's willingness to aggressively enter new, high-growth industries whenever the opportunity arises will be the reason it continues to beat the broader market over the long term.
3. The Vanguard S&P 500 ETF I want to finish with an asset that even legendary investor Warren Buffett recommends. It isn't a stock in the traditional sense; it's an exchange-traded fund (ETF) that tracks the S&P 500 index: the Vanguard S&P 500 ETF (VOO +0.35%). I know I said younger investors can afford to take more risk, but this could be the ideal asset for those who want to take the tried-and-tested path to stock market returns.
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The Vanguard S&P 500 ETF holds 500 stocks across 11 sectors of the economy, making it highly diversified. But since it's weighted by market capitalization, the largest companies in the fund have a greater influence over its performance than the smallest. Given the size of companies like Nvidia, it's no surprise that the technology sector accounts for more than one-third of the value of the ETF's entire portfolio.
That means investors will have ample exposure to the AI boom and every other technological revolution, while also owning a slice of companies in the more defensive sectors of the economy, like financial services and consumer staples, which will help minimize volatility.
The Vanguard S&P 500 ETF is one of the most cost-effective index funds investors can buy. It has an expense ratio of just 0.03%, so annual fees would amount to just $3 per $10,000 invested. As a result, this could be the ultimate set-it-and-forget-it purchase for young investors of all experience levels.
Jessica Inskip (@jessicainskip) has her sights entirely on the Mag 7 for today's Big 3. She highlights Apple (AAPL) and its product suite as a key growth driver in macroeconomic uncertainty, Meta Platforms (META) as a major breakout candidate following months of consolidation, and Nvidia (NVDA) as it expands AI capabilities.
Just before last weekend kicked off, Nvidia (NVDA +0.44%) and SK Hynix (SKHY -8.33%) finished some business, signing the largest memory deal in history. As part of the partnership, SK Hynix's subsidiary, SK Telecom, will build a 2-gigawatt AI cloud data center in Korea using Nvidia's Vera Rubin Platform. Meanwhile, SK Hynix will supply Nvidia with high bandwidth memory (HBM) going forward, while the two companies will work together to co-develop future generations of AI memory.
One of the biggest bottlenecks in the AI infrastructure build-out right now is memory, especially HBM. To reduce latency and improve power efficiency, graphics processing units (GPUs) and other AI chips need to be packaged with HBM. Meanwhile, the need for HBM is only growing as inference increasingly focuses on fast memory access rather than raw compute power.
Image source: The Motley Fool.
However, increasing HBM capacity is a challenge. It requires access to the same EUV (extreme ultraviolet lithography) machines that manufacture GPUs and other advanced logic chips, and the supply for these machines is limited, since the only company that makes them is ASML. At the same time, HBM needs upward of 3 times the wafer capacity of regular DRAM, adding another challenge if one wants to rapidly increase supply. HBM also must be manufactured in massive clean rooms, which can take years to build.
My prediction is that this deal will play an important role in both stocks being big winners over the next few years.
Nvidia: Securing its future Nvidia has long been the dominant player in the AI infrastructure build-out, and its partnership with SK Hynix will only make it stronger. The company has already locked down the training market, as most foundational AI code was written on its CUDA software platform and optimized for its GPUs, giving it a wide moat in this area.
Locking up a massive amount of HBM supply, meanwhile, will help secure its leadership position, especially as the inference market becomes a larger share of the pie. Nvidia's "acquisition" of Groq and its language processing units (LPUs) is already helping it separate the two phases of inference, enabling faster responses. First, its GPUs (packaged with HBM) handle the prefill phase and understand user prompts, while its LPUs, with SRAM (static random-access memory) built directly onto these chips, handle the decode phase, reducing latency and helping deliver faster answers.
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In an HBM market that is very capacity-constrained, having access to such a large amount of capacity while also being able to offload some work to SRAM-based LPUs is a massive supply-chain advantage. Between its Groq deal and this major HBM supply partnership, Nvidia looks well positioned to remain the dominant player in AI infrastructure and to be a strong player in the inference market going forward. That should be a big growth driver for the stock in the years ahead.
Trading at a forward P/E of just over 15 times analyst estimates for fiscal 2028 (ending January 2028) and given its advantages, this is a top AI stock to buy.
SK Hynix: Adding visibility SK Hynix's deal with Nvidia is a massive windfall. The Korean company has been Nvidia's biggest supplier of HBM, and this partnership helps cement its status and will be a huge revenue growth driver in the coming years.
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The DRAM maker has been working to establish long-term contracts, and this is a major one that will give its business greater visibility. It also helps tie its fortunes to one of the largest and fastest-growing companies in the world, which helps it de-risk a multiyear capital expenditure expansion. It will likely leave other chipmakers scrambling to secure HBM supply, as Broadcom has already done with Samsung, which will keep overall DRAM capacity tight and prices high for the foreseeable future.
With the stock trading at a forward P/E of under 6, the added visibility that this deal creates could easily lead to some multiple expansion. As such, now is a great time to scoop up shares following this huge multiyear deal.
Imagine an enterprise app that analyzes company financial filings.
Today, the app gathers earnings releases and relevant market data. It sends that information to a closed model like Claude through an API, waits for a response, and presents the resulting analysis to the user.
The model may run on thousands of expensive accelerators. But none of that changes the enterprise app's hardware stack. From the developer's perspective, the app simply waits for the model to respond.
Now change the assignment.
Instead of simply producing an analysis, the model must write and run code to complete the work. If the code fails, it must inspect the error, revise its approach, and try again.
The app can no longer treat the model's response as text. It needs somewhere safe to run what the model created. Otherwise, the generated code could damage the application or compromise the systems around it.
That shift turns AI from an application integration problem into an infrastructure problem. The enterprise must create isolated computing environments, control what each one can access, preserve work between attempts, and shut them down when the task is complete.
It is a new execution workload that could force enterprise apps to adopt a different CPU architecture.
Nvidia (NVDA +0.44%), Advanced Micro Devices (AMD -7.40%), Intel (INTC -5.25%), Arm Holdings (ARM -7.63%), and the largest cloud providers are already making different bets on what that architecture should look like. The investment question is whether enterprise agents create enough executable work to turn those bets into a meaningful new hardware market.
AI agents may require isolated environments where generated code can run without putting the surrounding application at risk. Image source: The Motley Fool.
Sandboxes Turn Security Into an Economics Problem AI-generated code cannot safely run inside the main application.
It may contain errors, consume excessive resources, attempt prohibited network calls, or access data it should not see. The enterprise therefore needs a sandbox: an isolated environment with controlled access to computing resources, files, networks, and credentials.
One sandbox is manageable. Thousands of agents, each potentially needing several sandboxes, create a new infrastructure layer.
Virtualization is only one part of the challenge. The platform must isolate each sandbox, limit its resources, control its access to files and networks, preserve its state when needed, and shut it down when the work is complete.
Containers and microVMs offer different levels of isolation, but the larger goal is the same: Keep generated code from harming the application without making every task too slow or expensive.
That turns security into an economic trade-off.
Every second spent starting an environment extends task completion time. Every unused gigabyte reduces the number of sandboxes a server can support. Every environment that remains active after the work ends ties up capacity.
The winning system will not merely run code quickly. It will create, manage, pause, resume, and destroy isolated environments efficiently.
Amazon (AMZN -0.08%) has made this requirement explicit with AWS Lambda MicroVMs, which are designed to run user-generated or AI-generated code inside isolated, stateful environments.
Amazon is not alone. Microsoft (MSFT +2.01%) and Alphabet (GOOGL +2.62%) (GOOG +2.45%) are also adding isolated agent-execution environments to their cloud platforms. The products differ, but the direction is consistent: The major hyperscalers are preparing for applications that need to run generated work safely.
This is becoming an industry infrastructure category, not an AWS-only experiment.
The Real CPU Question Is Task Economics Agent workloads can place unusual pressure on a server.
A traditional enterprise app may run a stable group of long-lived services. An agent platform can create large numbers of temporary environments with unpredictable resource needs.
One task may require several sandboxes. One sandbox may be compiling code while another runs a script or starts a database. Some environments may disappear quickly. Others may remain available while the agent inspects the result and decides what to do next.
Peak benchmark performance does not capture that workload well.
The more useful questions are operational:
How many sandboxes can one server support? How quickly does each task finish? Does performance hold up when every core is busy? How much memory does each environment consume? How many completed tasks does the system produce per dollar and per watt? Those measurements can favor different processor designs.
A high-core-count CPU may support more environments at once. A CPU with stronger performance per core may finish each blocking step sooner. A cloud provider may accept lower peak performance if its custom processor reduces the total cost of operating the service.
State adds another layer.
An agent may install dependencies, create files, and produce intermediate results over several attempts. Rebuilding the environment after every model response would repeat work and add latency.
The system must preserve enough state for the agent to continue without keeping every sandbox active forever.
Agent execution is therefore not just a processor benchmark. It is a systems problem involving CPUs, memory, storage, networking, virtualization, identity, and scheduling.
The CPU matters because it determines how quickly the work runs and how densely environments can be packed. The surrounding system determines whether that performance becomes an economic advantage.
Generated Code Rewards Compatibility An agent platform may not know what software it will be asked to run.
Generated code may depend on an older library, a native extension, or an internal enterprise tool. That uncertainty increases the value of compatibility.
Arm-based processors now support much of the modern cloud software stack. Containers and managed runtimes can also hide many architectural differences. But compatibility becomes harder to dismiss when the workload itself is generated dynamically.
That creates the central trade-off in the CPU market: Specialization can improve speed and efficiency, but compatibility reduces the chance that the generated workload fails to run.
Some sandboxes will also use GPUs for highly parallel work. But the environment still needs a CPU to run the operating system, manage files and networks, install software, execute application logic, and launch any accelerated work.
The likely future is heterogeneous. The CPU remains the default foundation for the sandbox.
Nvidia Is Betting on More and Faster Workers Nvidia is making the clearest argument that agent execution deserves its own CPU architecture.
Think of CPU cores as workers. More cores allow the processor to handle more tasks at once. Faster cores help each worker finish its assignment sooner.
Vera aims to do both.
The processor has 88 custom Olympus cores, giving it more workers to run tasks in parallel. Each core also uses a 10-wide decode engine, helping every worker process more instructions per cycle and finish its assignment faster.
Nvidia says Olympus delivers up to 50% higher instructions per cycle than Grace. Vera also supports up to 1.2 terabytes per second of memory bandwidth, helping keep those cores supplied with data as more sandboxes run at the same time.
The faster-worker advantage matters because an agent often cannot move forward until its current step finishes. More workers do not necessarily shorten a script, compilation, or test that depends heavily on one core. A faster worker can.
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Nvidia is betting that the best agent CPU needs enough cores to run many sandboxes and strong enough cores to finish each blocking step quickly.
Nvidia is also positioning Vera beyond its own GPU systems. It plans to sell stand-alone Vera CPU racks and make the processor available through enterprise and cloud server partners.
That gives Nvidia a path into deployments that do not require customers to buy a full accelerator platform.
The trade-off is compatibility.
An enterprise using a closed-model API may have no Nvidia hardware in its existing stack. Nvidia must prove that Vera's combination of more workers and faster workers creates enough economic value to justify moving workloads away from established x86 systems.
Its architecture explains why Vera could win. Independent benchmarks still need to prove that advantage across real enterprise code, virtualization, software migration, and pricing.
AMD Is Betting on More Workers Per Rack AMD sees the same workload and makes a different bet.
If CPU cores are workers, AMD's Venice architecture aims to fit far more workers into each server and rack.
The EPYC 9006 generation supports up to 256 cores and 512 threads per socket. It also includes 16 channels of DDR5 memory and PCIe 6 connectivity, giving those workers more capacity to move data and communicate with the rest of the system.
AMD says Venice can scale beyond 36,000 cores in a liquid-cooled rack. That is the heart of its argument: Agent platforms will benefit most from running more sandboxes and completing more total tasks across the rack.
But AMD is not ignoring individual worker speed. The EPYC portfolio includes high-frequency processors for tasks that depend more heavily on one core, and AMD says Venice will extend those options.
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That gives AMD a broader pitch: Use many workers for parallel sandboxes, faster workers for blocking tasks, and the same x86 tools enterprises already use.
The compatibility advantage matters because an enterprise may not know which libraries, binaries, or internal systems generated code will need. A company can place agent sandboxes on EPYC without changing the architecture already running much of its software.
AMD is betting that agent execution creates a new workload without requiring a new ecosystem.
The trade-off is specialization.
A broad x86 portfolio may run more types of work, but Vera could still finish certain sequential tasks faster if its wider cores deliver the per-core advantage Nvidia claims.
AMD does not need EPYC to win every agent task. It needs more completed work per rack, better portability, and lower migration risk to matter more than Vera's specialized performance.
Intel Is Betting on the Existing Workforce Intel sees agent execution as another major workload that enterprises can place on the x86 infrastructure they already use.
In the worker analogy, Intel's advantage is familiarity. Enterprises already have the workers, tools, software, and operating processes built around Xeon.
That matters when generated code may depend on older libraries, native extensions, or internal systems. Moving those workloads to a new architecture can introduce compatibility problems before the agent completes any useful work.
Intel is also adding more workers through Xeon 6+ processors built for high-density, scale-out workloads. The company positions its Efficient-core designs around fitting more cores into each rack while lowering the power and space required for each task.
Intel therefore has a two-part argument: Keep the familiar workforce, then fit more of those workers into the same data center.
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That makes Intel's approach closer to AMD's than Nvidia's. Both x86 vendors emphasize compatibility and density. AMD currently has the sharper forward story through Venice, while Intel has the broader installed base.
Intel also describes Xeon as an "action CPU" for agentic systems, responsible for the general-purpose work around tools, enterprise software, and execution. But some of Intel's agentic messaging involves coordinating accelerator-heavy AI systems rather than the isolated enterprise sandboxes examined here. That evidence should not be allowed to carry the argument.
The relevant investment question is narrower: Can Intel turn its existing workforce into a competitive agent-execution platform, or will enterprises use the new workload as a reason to move toward AMD, Nvidia, or custom Arm processors?
Intel does not need to invent an entirely new architecture to participate. Xeon only needs to offer enough density, performance, and cost efficiency that compatibility remains more valuable than migration.
The risk is that familiarity becomes a defensive advantage rather than a growth engine.
Nvidia is offering faster workers. AMD is offering a larger x86 workforce per rack. The hyperscalers can design the workforce and workplace together. Intel must prove that the workforce already in place can still complete the job at a competitive cost.
The Hyperscalers Are Betting on the Whole Workplace Amazon, Microsoft, and Alphabet do not need to sell their processors to outside server customers.
They use custom CPUs to improve the economics of their own clouds.
In the worker analogy, the hyperscalers control more than the workforce. They also control the building, tools, security, scheduling, and operating systems around it.
That vertical integration can matter as much as the CPU itself.
AWS can combine Graviton with Nitro, Firecracker, storage, networking, and billing. Microsoft can connect Cobalt to Azure, GitHub, identity, and enterprise software. Google can pair Axion with Kubernetes-based agent infrastructure and the rest of Google Cloud.
The cloud provider can optimize the entire environment around one goal: Complete more agent tasks at a lower total cost.
That creates a different business model from merchant silicon.
Nvidia and AMD can turn agent demand into processor revenue. A successful hyperscaler CPU may instead lower infrastructure costs, improve cloud margins, support more customer workloads, or allow the provider to reduce prices.
The hyperscaler does not need to prove that its workers are the fastest. It needs to prove that the whole workplace produces completed work more efficiently.
That advantage is especially relevant for sandbox fleets, where CPU performance is only one part of the cost. Isolation, start-up time, state management, networking, storage, and utilization all affect the final economics.
This also creates a threat to merchant CPU vendors.
If developers buy a managed sandbox service rather than choosing the underlying processor, AWS, Microsoft, or Google can decide which CPU runs the workload.
Custom silicon can therefore make agent execution cheaper for the cloud provider and harder for Nvidia, AMD, or Intel to capture directly.
Arm Supplies the Blueprint Arm sits underneath much of this competition.
In the worker analogy, Arm provides the blueprint used to design the workforce. AWS Graviton, Microsoft Cobalt, Google Axion, Nvidia Vera, and other processors can all use Arm's instruction set while building different cores, memory systems, and server designs around it.
That gives Arm broader exposure than an individual chip vendor.
AMD and Intel need their own processors to win deployments. Arm can benefit when several competing Arm-based processors gain share at the same time.
The company is also moving further into finished data-center silicon. That could create more direct revenue, but it also complicates Arm's relationship with customers that license its technology.
For investors, the cleaner thesis is still the architecture shift.
If agent execution moves more enterprise workloads toward Arm, the company can benefit whether Nvidia sells a specialized CPU or the hyperscalers use custom processors inside their own clouds.
Arm does not need to own the workers or the workplace. It can win by supplying the blueprint used to build both.
The Market May Support Several Winners There may be no universal agent CPU. Different workloads may reward different approaches.
Nvidia may win where faster workers shorten blocking tasks. AMD may win where more workers per rack increase total throughput. Intel may remain competitive where enterprises value familiar tools and existing infrastructure. The hyperscalers may win where controlling the whole workplace lowers the cost of each completed task.
Arm can benefit from several of those outcomes by supplying the blueprint.
The market is deciding which advantage matters most:
Speed per task
Sandboxes per server
Cost per completed task
Compatibility
Portability
Power efficiency
Integration with the surrounding cloud
Different customers may reach different answers. That makes segmentation more likely than one architecture replacing the others.
The Market Still Needs Proof Processor vendors are preparing for a new execution market. That does not prove enterprises will create one.
The strongest evidence will come from actual consumption:
The percentage of agents that execute generated code
Sandboxes created per completed task
CPU time consumed per task
Cost per completed task
These measurements matter more than surveys showing that enterprises are experimenting with agents.
A company can deploy hundreds of conversational assistants without creating meaningful CPU demand. The hardware market changes only when agents perform enough executable work to consume measurable computing capacity.
The same evidence can support a bottom-up estimate of the market:
Active execution agents × tasks per agent × sandboxes per task × execution time × compute cost
That calculation must separate agents that merely wait for responses from LLM APIs from agents that require isolated execution.
The distinction may determine whether this becomes a modest extension of existing cloud computing or a meaningful new hardware market.
The estimate will probably be smaller than broad forecasts for agentic AI. Even as a coder working in this space, it is still hard in July 2026 to see isolated agent execution becoming mainstream. But it measures a critical part of the AGI bet: giving increasingly capable models a safe environment in which to act, test their work, and try again.
The winning architecture must ultimately prove one of three things: more work from each worker, more workers in the same rack, or lower costs across the whole workplace.
Investors Are Underwriting Different Outcomes The companies in this market offer different forms of exposure.
Nvidia, AMD, and Intel monetize the workers.
Nvidia is betting that wider, faster cores can finish blocking agent tasks sooner. AMD is betting that Venice can complete more work across each rack while preserving x86 compatibility. Intel is betting that enterprises will continue using the workforce and tools already in place.
Arm monetizes the blueprint. It can benefit when several competing companies build Arm-based processors, even if no single chip dominates the market.
Amazon, Microsoft, and Alphabet monetize the workplace. Their custom processors can lower cloud costs, improve margins, support more customer workloads, or make their services more competitive.
That distinction matters.
Merchant processors offer portability across clouds and data centers. Custom cloud processors offer deeper integration and potentially lower service costs.
One model turns agent demand into direct processor revenue.
The other turns silicon into an internal operating advantage.
The Skeptical Case Could Still Win The bullish thesis can fail in three main ways.
First, most enterprise agents may never execute arbitrary code. They may retrieve documents, update records, send messages, or call controlled APIs. Those actions create orchestration demand but may not require isolated sandboxes at scale.
Second, existing infrastructure may absorb much of the work. What vendors describe as a new agentic CPU market could partly be familiar cloud computing with a new label.
Third, the workplace may matter more than the worker.
Developers may choose a sandbox service based on security, lifecycle management, observability, and ease of use while remaining indifferent to the processor underneath it. In that outcome, the cloud providers could capture more value than the merchant CPU vendors.
Specialized processors may also struggle if general-purpose CPUs are already good enough. Faster execution has limited value when most of the task is spent waiting on storage, a database, another API, or the next model response.
The likely result may be segmentation rather than displacement.
Agent execution could still create new CPU demand. But custom cloud silicon may absorb much of the benefit before it reaches outside chip vendors.
The Next AI Infrastructure Market Is About Doing Enterprise AI has so far been easier to add than to rebuild around. An app calls a model, waits for a response, and continues running on familiar infrastructure. Agents could break that pattern.
Once the model creates executable work, the enterprise needs somewhere safe for that work to happen. It must isolate the code, control access, preserve state, manage multiple sandboxes, and finish the task at an acceptable cost.
No company has won because the market itself remains unproven.
The signal to watch is not how many enterprises say they are experimenting with agents. It is how often those agents create isolated environments, how many environments each task requires, how long those environments run, and how much computing capacity they consume. That data will reveal whether the market needs faster workers, more workers, or a better-run workplace.
The enterprise has learned how to rent intelligence.
The next hardware opportunity begins when it has to give that intelligence somewhere safe to work.
Dave Altavilla recaps AMD Inc.'s (AMD) Advancing AI 2026 conference and his biggest takeaways on the event. He argues AMD's Helios rack offers "all the pieces" to compete with Nvidia (NVDA) as CEO Lisa Su sets her sights on creating a full AI platform.
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As has been the case with iPhone releases since the dawn of time, there is a swirl of rumors about hardware and software. Apparently, in September, Apple (NASDAQ: AAPL | AAPL Price Prediction) will release a high-end version of the iPhone 18. Or maybe some versions of the iPhone 18 won’t be released until spring 2027. Or maybe Apple will release the expensive iPhone 18 Pro, iPhone 18 Pro Max, and the Ultra (which will be foldable) in three months. Or something.
What the market and investors are really waiting for is not hardware. It is the AI upgrades of Siri and Apple Intelligence, with full integration with Google Gemini. Apple management says this integration will solve its problems of being slow to the AI market. It is paying Alphabet (NASDAQ: GOOG) $1 billion a year. That seems cheap, but Google gets its AI in what may eventually be hundreds of millions of Apple products.
Based on everything Apple has said, its iOS 27, which will be in full release this fall, will be its AI superstar. If it is broadly accepted, investors can breathe a sigh of relief. Apple will finally have a horse in the AI race. With its massive hardware distribution, it will jump to a level of distribution close to, or above, the market leaders like OpenAI’s ChatGPT, Claude, or Grok.
Every iPhone generation has a better camera, a better and faster chip, a lighter and more durable case, a shorter charge time, and longer battery life. None of these will be enough for Wall St. Apple recently moved ahead of Nvidia (NASDAQ: NVDA) as the world’s most valuable company. It only holds that spot if Apple Intelligence and Siri are consumer AI home runs.
Apple’s AI software probably cannot pull ahead of the most advanced consumer-centric AI downloads. And it does not have to. It has to be slightly better than good enough.
After Apple failed to release an AI-powered iPhone 17 and an iOS AI-powered system last year and early this year, and after many of its top AI engineers left for rivals, Apple has sat on the AI sidelines for a year. However, it still has enough fans to stay in the global lead of smartphone unit sales and, perhaps, enough to impress investors.
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ToplineApple on Tuesday became the second company in history to be valued at $5 trillion, joining Nvidia as the iPhone maker’s shares have surged in recent weeks, becoming the world’s largest firm by market capitalization.
The iPhone maker recently regained its ranking as the world’s most valuable company.
AFP via Getty Images
Key FactsShares of Apple rose as much as 1.8% to $342.89 shortly after trading opened, pushing the company’s market capitalization just above $5 trillion for the first time, before paring back gains to be largely unchanged.
Apple ranks ahead of Nvidia ($4.7 trillion) as the world’s largest company by market value after surpassing the AI giant on Monday, and ahead of Alphabet ($3.9 trillion) and Microsoft ($2.9 trillion).
Nvidia and Apple have climbed at varying rates so far this year: Apple’s stock has jumped nearly 25%, while shares of Nvidia—down 1.4% on Tuesday—have risen just 2.6%.
surprising factThe pace at which companies have grown has accelerated in recent years: Apple became the first $1 trillion company in 2018, the first $2 trillion company in 2020 and the first $3 trillion firm in 2022. Nvidia then became the first to reach both $4 trillion and $5 trillion, as booming demand for AI products quickly swelled the valuation of many tech firms.
tangentApple on Tuesday announced U.S. customers would soon be able to lease an iPhone for up to two years starting at $17.99 per month. The program, named Upgrade, is in partnership with the buy-now, pay-later firm Klarna and will be offered at Apple’s physical and online stores. That comes after the firm raised starting iPad and Mac prices by at least $100, including some models with price tags bumped by more than $1,000, citing a global memory crunch.
key backgroundApple long held the title as the world’s most valuable company before being unseated by Nvidia in 2024, and later falling behind Microsoft. The iPhone maker held the top spot for market capitalization for most of the previous decade after first surpassing Exxon in 2011, and then the firm periodically traded spots with Microsoft. Apple, like its mega-cap competitors, has accelerated its spending on AI products over the last year, though its spending projections are just a fraction of others. Apple’s capital expenditures totaled $12.7 billion in fiscal 2025, whereas Alphabet plans to spend $205 billion this year, and Microsoft and Amazon bumped their annual spending plans to as much as $190 billion and $145 billion, respectively.
further readingForbesApple Briefly Unseats Nvidia As World’s Largest CompanyBy Ty Roush
Nvidia shares traded little changed on Tuesday after recovering from early losses, although the stock remained below the psychologically important $200 level.
Investors looked to balance an increasingly attractive valuation against concerns over artificial intelligence financing and upcoming Big Tech earnings.
The stock had fallen sharply in the previous session, losing 5% and surrendering its position as the world's most valuable listed company to Apple.
Despite the recent weakness, Nvidia's valuation has become increasingly attractive.
The stock closed Monday on a forward price-to-earnings ratio of 18.16, its lowest level since April 2015, according to Dow Jones Market Data.
Monday's decline came amid a broader selloff in semiconductor stocks following reports that a Chinese company had begun mass-producing key chipmaking equipment.
Investor sentiment was also weighed down by a Wall Street Journal report that Nvidia is discussing a roughly $250 billion financing guarantee for OpenAI to support a large data centre project in Ohio.
The arrangement would help OpenAI secure more favourable financing terms while supporting long-term demand for Nvidia's artificial intelligence chips.
The report sparked concerns among some investors that financing arrangements between Nvidia and AI customers could resemble the circular investment structures seen during the dotcom era.
Morningstar said it does not believe the reported financing discussions undermine the long-term investment case for Nvidia.
The research firm maintained its $280 fair value estimate for the company and said the shares remain undervalued despite concerns surrounding financing-backed AI infrastructure projects.
The target represents an around 40% upside from the current market price.
Morningstar said demand for artificial intelligence computing continues to expand rapidly, with AI hosting providers remaining constrained by available computing capacity rather than customer demand.
The firm also pointed to AMD's recent increase in its server CPU market forecast as evidence that demand for agentic AI continues to strengthen, supporting the need for additional AI infrastructure over the coming years.
Morningstar said its understanding is that Nvidia already provides financing backstops to some cloud infrastructure providers in exchange for sharing portions of future AI hosting revenue.
According to the firm, a similar arrangement with OpenAI would represent a much larger transaction but would remain consistent with Nvidia's broader strategy of expanding the AI ecosystem and supporting long-term demand for its hardware.
Investor attention has now shifted to quarterly results from major technology companies, which are expected to provide fresh insight into the pace of artificial intelligence investment.
Microsoft, Meta Platforms, and Amazon are scheduled to report earnings this week, with investors expected to closely monitor capital expenditure guidance as an indicator of future demand for Nvidia's processors.
Beyond overall spending levels, investors will also look for commentary on the types of AI hardware companies intend to deploy.
Several large technology companies have increasingly developed custom processors with partners such as Broadcom for specific workloads.
While those chips are designed to complement rather than fully replace Nvidia's graphics processing units, investors continue to monitor whether greater adoption of custom silicon could gradually reduce reliance on third-party suppliers.
Robotics is moving out of the lab and into the real economy. Speaking at YC Startup School, NVIDIA CEO Jensen Huang made a striking claim about the timing of the next great AI wave. Asked about robotics, he told the audience: “I would say the ChatGPT moment of robots happened a couple of years ago already.” Paired with Huang’s estimate that physical AI opens a $50 trillion market opportunity, the comment reframes robotics as a wave already breaking, not one still waiting offshore.
The Moment Huang Says Changed Everything Huang traced the shift back to generative video work inside NVIDIA (NASDAQ:NVDA | NVDA Price Prediction) labs. “A couple of years earlier, inside our labs, we were driving a simulator completely generated by video, completely generated by neural networks,” he said. The breakthrough came when he connected generated video with physical movement: “If I could generate video of a hand picking up a glass, why can’t I cause a robot to do the same?”
That insight, he said, launched NVIDIA’s push into “a world foundation model, an AI that understands the laws of physics and how the world works.” That strategy now spans Cosmos world foundation models and Isaac GR00T robot foundation models, alongside the DRIVE Hyperion autonomy platform used by Hyundai, Kia, Uber, BYD, Geely, Isuzu, and Nissan.
The Numbers Behind the Thesis The financials say the buildout is real. NVIDIA’s Q1 FY2027 revenue hit $81.615 billion, up 85.23% year over year, with Data Center revenue reaching $75.246 billion, up 92% YoY, and non-GAAP gross margin at 75.0%. Total supply commitments now stand at $119.0 billion, compared with $95.2 billion in the prior quarter, a signal Huang is putting cash behind his conviction. On the company’s last earnings call, he described the AI factory buildout as “the largest infrastructure expansion in human history.” Investors have bought in, though cautiously. Shares are up 12.3% over the past year.
The Memory Beneficiary Every physical AI model needs memory. Micron Technology (NASDAQ:MU) posted Q3 FY2026 revenue of $41.46 billion, up 345.7% year over year, with gross margin expanding to 84.6%. CEO Sanjay Mehrotra said results “reflect the strategic value of memory in the AI era.” Q4 guidance calls for $50.0 billion in revenue. The stock is up 189.5% year to date.
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The Smaller, Riskier Plays Serve Robotics (NASDAQ:SERV) runs roughly 2,000 delivery robots powered by NVIDIA Jetson Orin compute, with Q1 revenue of $2.98 million (up 577.5% YoY) and 2026 guidance near $26 million, quite a jump. Yet the stock trades at $4.68, down 55.2% year to date, versus an analyst target of $18.45.
Arbe Robotics (NASDAQ:ARBE) builds 4D imaging radar and is integrating with NVIDIA’s DRIVE Hyperion platform. Q1 2026 revenue was $0.5 million, and shares sit at $0.64 against an analyst target of $2.50.
If Huang is right that the robotics ChatGPT moment is already behind us, the picks-and-shovels names are showing it first. The smaller autonomy plays remain lottery tickets on whether the $50 trillion tally is closer to self-fulfilling prophecy than hyperbole.
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With Apple (NASDAQ:AAPL | AAPL Price Prediction) reclaiming the world’s most valuable public company crown at a $337.47 share price and NVIDIA (NASDAQ:NVDA) sitting just behind at $196.03, the question retirement-focused investors are asking is simple: which one belongs in the core of a portfolio built to last 20 or 30 years? Both are mega-caps. Both print cash. Only one fits the classic retirement mandate of income plus capital preservation. Let’s settle it on three dimensions that actually matter to retirees.
Dimension 1: Income and Capital Return (Winner: AAPL) Retirees need reliable payouts. Apple yields 0.31% against NVIDIA’s 0.02%, and Apple just raised its dividend 4% to $0.27/quarter alongside a fresh $100B buyback authorization. NVIDIA only recently moved its payout from $0.01 to $0.25/quarter and added an $80B repurchase. Impressive, but the track record is thin. Apple returned roughly $32B to shareholders in a single quarter and executed $90.71B in FY25 buybacks. That’s a capital-return machine with more than a decade of dividend hikes behind it. Retirees compounding distributions want the operator who has already proven the discipline. Apple wins cleanly.
Dimension 2: Growth Trajectory (Winner: NVDA) NVIDIA posted Q1 FY27 revenue of $81.62B, up 85.2% year over year, with net income of $58.32B, a 210.6% jump. Data Center revenue alone hit $75.25B (+92%), and management guided Q2 to $91.0B with 75.0% gross margins. Apple’s most recent quarter was strong by its own standard, with revenue up 16.6% to $111.18B and iPhone revenue of $56.99B, but that’s a rounding error next to NVIDIA’s trajectory. On valuation-adjusted growth, NVIDIA trades at a P/E of 40 versus Apple’s 44. You are paying less for dramatically more growth. NVIDIA wins on this axis.
Dimension 3: Volatility and Risk Profile (Winner: AAPL) This is where retirement portfolios live or die. NVIDIA’s business is concentrated: Data Center is roughly 92% of revenue, hyperscaler customers account for around half of that segment, and the company carries $119B in supply commitments plus zero H20 shipments into China from export restrictions. Retail sentiment reflects the debate. A 3,600-upvote wallstreetbets thread revived Michael Burry’s short thesis, and concentration-risk narratives are pulling sentiment scores as low as 22. Insiders have been net sellers, with 26 recent transactions including large CEO and CFO dispositions in June. Apple’s revenue base is diversified across iPhone, Services (a record $30.98B), Mac, and a 2.5B active-device installed base spanning every geography with double-digit growth. Apple’s debt-to-equity of 1.52 is higher than NVIDIA’s 0.073, but its earnings stream is materially less cyclical. For a portfolio that must survive drawdowns, Apple is the lower-variance asset.
The Verdict For a retirement-focused investor, Apple wins. Two of the three dimensions that define retirement suitability, income durability and volatility control, land firmly with AAPL. NVIDIA is the superior growth compounder and arguably the more exciting stock, but concentration in one end-market, hyperscaler dependency, insider selling, and a dividend yield that rounds to zero disqualify it as a retirement anchor. The 18.72% one-month move in AAPL heading into the July 30 earnings call, Tim Cook’s final one, introduces short-term chase risk, and historically Apple has averaged a -1.09% one-day post-earnings move even on beats. For retirees weighing entry timing, staged accumulation historically reduces single-day event risk around earnings. But over a 10 to 20 year retirement horizon, Apple is the correct answer. NVIDIA fits a satellite growth sleeve for retirees who can stomach a -9.34% 30-day post-earnings drawdown.
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Index Dow Jones +1,21 % na 52844,2 b. S&P 500 +0,41 % na 7443,89 b. Nasdaq Composite +0,11 % na 24958,68 b.
Na americké burze pokračuje výprodej technologických titulů, ke kterým se dnes přidává i sektor energií. Pokračují obavy z přehřátí trhu v oblasti umělé inteligence, což ale vyvažuje pozitivní sentiment z poklesu cen ropy a optimismus ohledně čtvrtletních zisků.
Index Nasdaq momentálně připisuje 0,11 %, S&P 500 roste o 0,41 %, a index DJI posiluje o 1,21 %,
Je zřejmé, že nálada na trhu s akciemi společností zabývajících se umělou inteligencí se dále zhoršuje. Dnes zejména souvislosti se zprávami, že společnost Nvidia zvažuje poskytnutí finanční podpory ve výši 250 miliard dolarů pro OpenAI, čímž by se propojení obou společností ještě více prohloubilo a zesílily by se obavy ze vzájemně propojeného financování. Další ranou technologickému sektoru jsou informace, že čínská konkurence snižuje náskok amerických společností v oblasti umělé inteligence, a že dokonce vyvinula i prototyp vlastního litografického stroje na výrobu čipů, což v této oblasti podkopává vyhlídky na budoucí zisky amerických společností.
Pokračuje také záplava kvartálních výsledků u známých společností jako Visa, Boeing, Ford či PayPal. Výsledkům zatím vévodí společnost Coca-Cola, která zvýšila svůj celoroční výhled poté, co zveřejnila výsledky za druhé čtvrtletí, které předčily očekávání. V centru pozornosti jsou i očekávané výsledky společnosti SK hynix Inc., které navodí atmosféru o vývoji na trhu s paměťovými čipy v době, kdy se šíří obavy ohledně sázek na efektivitu umělé inteligence.
Ceny ropy mezitím pokračují v poklesu poté, co USA a Írán zastavily aktivní boje a prezident Trump uvedl, že obě strany vedou diplomatická jednání. Cena bitcoinu dnešní den poklesla o více než 1,5 % a obchoduje se těsně nad hranicí 63 700 USD za token, což je nejnižší úroveň za posledních deset dní. I zde je patrný sentiment z propadu akcií společností působících v oblasti umělé inteligence, nejistota ohledně dalšího rozhodnutí Fedu o měnové politice a přetřásající zpoždění přijetí legislativy týkající se kryptoměn v Kongresu.
Index S&P 500 +0,41 % na 7443,89 b. Nejsilnější sektory S&P Změna Nejslabší sektory S&P Změna Nezbytná spotřeba +2,6 % Energie -1,5 % Zdravotní péče +2,2 % Informační technologie -0,7 % Základní materiály +2,1 % Průmysl -0,3 % Nejsilnější akcie S&P Změna Nejslabší akcie S&P Změna IQVIA Holdings (IQV) +13 % Corning (GLW) -15 % Sherwin-Williams (SHW) +8,4 % Sandisk Corp (SNDK) -13 % Fair Isaac Corp (FICO) +8,2 % Coherent Corp (COHR) -11 % FactSet Research Systems (FDS) +7,8 % Dell Technologies (DELL) -9,5 % Nucor Corp (NUE) +7,3 % Lumentum Holdings (LITE) -9,4 %
David Rojko-Kovačík
Fio banka, a.s.
Prohlášení
After enjoying a stock market recovery through most of July, Nvidia (NASDAQ: NVDA) took a nosedive late in the month, effectively leaving investors who took the June decline as a buying opportunity flat.
Indeed, if a trader purchased $1,000 worth of NVDA shares one month ago, they would have been acquiring the equity roughly at $194.97. At the latest closing bell, Nvidia stock was changing hands at $196.51, meaning the late June investment would have risen $7.90 to $1,007.90.
If the Tuesday, July 28, pre-market is taken into account, the position would turn into a slight loser given NVDA shares’ press-time price is $194.85 – $0.12 below the Monday, June 29 close.
Nvidia stock price one-month chart. Source: Google Why Nvidia stock plunged in late July Nvidia’s performance through July can largely be attributed to the ongoing concerns regarding the financial health of companies involved with the artificial intelligence (AI) ‘boom.’
Specifically, NVDA stock’s drop coincided with Google’s (NASDAQ: GOOGL) latest earnings report, which showed rising capital expenditures (CapEx) and diminishing margins and led to an immediate investor backlash.
The reaction was driven by the debate over return on investment (ROI) from AI infrastructure, which came into focus in late May as Uber (NYSE: UBER) began questioning the worth of its adoption of the technology, as well as by Microsoft’s (NASDAQ: MSFT) changes to GitHub Copilot pricing.
Subsequent developments have done relatively little to alleviate the situation since, though they could represent the costs of providing AI decreasing, they can also be read as some of the biggest players in the sector making an emergency extension of subsidies to avoid losing customers.
Additionally, Nvidia’s most recent drop came shortly after the blue-chip chipmaker entered a $250 billion data center backstop agreement with OpenAI. The move reignited discussions over circular financing in the AI industry and over the semiconductor giant possibly investing in its own customers so they can afford to remain its customers.
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The semiconductor sector has spent the past two years proving that artificial intelligence can overcome almost any market headwind. Export restrictions, supply shortages, and geopolitical tensions have repeatedly created volatility, yet demand for AI infrastructure has continued to outpace expectations.
That resilience is being tested again after Taiwanese prosecutors detained an Nvidia (NASDAQ:NVDA | NVDA Price Prediction) employee as part of an ongoing investigation into the alleged smuggling of restricted AI servers to China by employees of Super Micro Computer (NASDAQ:SMCI). The headline grabbed investors’ attention immediately, but the details paint a much different picture than the market’s initial reaction might suggest.
The Supermicro Probe Is Expanding Taiwan’s Keelung District Prosecutors Office detained an Nvidia employee identified only by the surname Chang this morning after authorities searched his home and workplace on July 24. Prosecutors allege Chang was involved in falsifying business documents connected to shipments of AI servers containing Nvidia chips that were ultimately destined for China despite U.S. export restrictions.
The investigation originally centered on Super Micro Computer servers allegedly exported through falsified documentation. Yet prosecutors have consistently maintained that neither Nvidia nor Supermicro itself is the target of the investigation. Instead, authorities are investigating the actions of specific individuals involved in the alleged scheme. Supermicro reiterated earlier this month that Taiwanese authorities confirmed the company itself is not the subject of the investigation.
That distinction is easy to overlook, but it is probably the most important fact investors should remember.
Why Nvidia’s Situation Looks Different From Supermicro’s Markets rarely wait for legal proceedings to conclude. When news of the Supermicro investigation first surfaced, its shares plunged 33% in a single trading session. The stock eventually fell from $30.79 before the scandal broke to as low as $19.48, a decline of 36.7%. Since then, confidence has gradually returned. Supermicro closed Monday at $29.81, recovering almost all of those losses, although the shares were down nearly 4% in premarket trading this morning following news of the Nvidia employee’s detention.
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Nvidia’s stock also fell about 5% Monday, but the broader semiconductor sector was already under pressure. Sandisk (NASDAQ:SNDK), for example, dropped roughly 11%, while Micron Technology (NASDAQ:MU) is down 5.5% today, suggesting investors were responding to a wider chip selloff rather than this investigation alone.
The difference between the two companies comes down to leadership and scope. Supermicro’s founder became implicated during the investigation, creating uncertainty around corporate oversight. Nvidia faces no comparable situation today. Had CEO Jensen Huang been detained, investors would likely be evaluating a very different risk profile. Instead, current reporting points to a single employee allegedly acting within a broader investigation rather than evidence of companywide misconduct.
Key Takeaway In short, investors should resist treating Nvidia as “the next Supermicro.” Granted, any criminal investigation involving an employee creates uncertainty, and that uncertainty may linger until Taiwanese prosecutors complete their probe. Markets also dislike headlines linking Nvidia to export-control violations given the company’s dependence on international AI demand.
That said, the facts available today do not indicate Nvidia itself is under investigation. The company’s competitive position, AI chip roadmap, customer relationships, and financial outlook remain unchanged by the detention of one employee.
Ultimately, this appears to be a legal risk surrounding individuals rather than Nvidia’s business model. Unless investigators uncover evidence that expands beyond a rogue employee, smart investors will view the situation as one worth monitoring — not one that fundamentally changes the long-term investment case for the AI chip leader.
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SummaryNvidia Corporation is rated Buy, with skepticism and competitive risks already fully priced into its compressed 23x forward P/E multiple.NVDA's business doubled year-over-year, with Q1 2026 revenue at $81B and net profit at $58.3B, while shares have traded flat for six months.Gross margin stability above 70% in the upcoming report will signal continued pricing power and absence of destructive price wars.Accelerating AI infrastructure capex and robust enterprise demand are expected to drive NVDA’s next leg of growth, outweighing near-term competitive threats. Antonio Bordunovi/iStock Editorial via Getty Images
The shares of Nvidia Corporation (NVDA) — the leader of the semiconductor industry and the main locomotive of the technological sector of recent years — have effectively been trading sideways in a wide range in
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Analyst’s Disclosure: I/we have no stock, option or similar derivative position in any of the companies mentioned, and no plans to initiate any such positions within the next 72 hours. I wrote this article myself, and it expresses my own opinions. I am not receiving compensation for it (other than from Seeking Alpha). I have no business relationship with any company whose stock is mentioned in this article.
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I keep buying NVIDIA (NASDAQ:NVDA | NVDA Price Prediction) because it turns the world’s largest capital spending cycle into cash faster than I can decide where to redeploy the dividend. Every dollar hyperscalers pour into AI factories flows across NVIDIA’s fabless model as top-line revenue without dragging concrete, power, or square footage onto its balance sheet. That is the machine I keep funding.
The receipts back the story. Free cash flow went from $27.0B in fiscal 2024 to $60.9B in fiscal 2025 to $96.7B in fiscal 2026. Then Q1 FY2027 landed $48.55B in free cash flow in a single quarter, on revenue of $81.61B, up 85.2% year over year. Data Center revenue alone hit $75.25B, a gain of 92%, with the networking piece rising 199%. That is operational leverage doing exactly what a fabless architect is supposed to do: capture customer capex as revenue while research and administrative overhead stays comparatively fixed.
Balance Sheet Math That Lets Me Sleep The second reason I keep adding is the shape of the returns under the cash. Operating margin sits at 60.4%, return on invested capital at 92.2%, gross margin at 71.1%, and net margin at 55.6%. Debt-to-equity is 0.073 and interest coverage is 503x. A company earning those returns on that little leverage funds its growth from cash flow alone, which is what I want compounding inside a long-term account.
The third reason is what management now does with the money. In May 2026 the board lifted the quarterly dividend from $0.01 to $0.25, a 25x step-up, and authorized an additional $80B buyback on top of $38.5B remaining. NVIDIA returned roughly $20.0B to shareholders in Q1 FY27 alone, after returning $41.1B across fiscal 2026. The yield is still nominal at about 0.02%, so I own this for compounding book value rather than income.
Why This One Over the Obvious Alternatives Friends ask why I keep choosing this over Advanced Micro Devices (NASDAQ:AMD) or Broadcom (NASDAQ:AVGO). My answer lives in the margin structure. NVIDIA’s 55.6% net profit margin and 92.2% ROIC reflect pricing power over the full accelerator stack, from silicon to NVLink to CUDA-X, that merchant GPU and custom silicon businesses have not replicated at scale. When one company throws off $96.58B of free cash in a year on a fabless cost base, the alternative has to clear a very tall bar to earn the same dollar of my capital.
The Real Risk, Named Plainly The risk I respect is China. Guidance already assumes zero Data Center compute revenue from China, and the company absorbed a $4.5 billion H20 inventory charge earlier in the cycle. That is real money and a real ceiling on the addressable market. My thesis survives because FY2026 free cash flow still grew 58.7% with that door effectively closed. Any workable reopening becomes upside I am paying nothing for at today’s P/E near 41 and P/FCF near 51.
What keeps the buy button live is the forward runway. CEO Jensen Huang framed it directly: “The buildout of AI factories, the largest infrastructure expansion in human history, is accelerating at extraordinary speed.” Q2 FY27 guidance calls for $91.0B in revenue at a 75.0% non-GAAP gross margin, and management has committed to an annual product cadence extending through 2028, with the Vera Rubin platform already announced behind Blackwell. As long as NVIDIA keeps converting hyperscaler capex into free cash on this trajectory, my order gets refilled.
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Wall Street watches a company's quarterly report closely to understand as much as possible about its recent performance and what to expect going forward. Of course, one figure often stands out among the rest: earnings.
Life and the stock market are both about expectations, and rising above what is expected is often rewarded, while falling short can come with negative consequences. Investors might want to try to capture stronger returns by finding positive earnings surprises.
The ability to identify stocks that are likely to top quarterly earnings expectations can be profitable, but it's no simple task. Here at Zacks, our Earnings ESP filter helps make things easier.
The Zacks Earnings ESP, ExplainedThe Zacks Earnings ESP, or Expected Surprise Prediction, aims to find earnings surprises by focusing on the most recent analyst revisions. The basic premise is that if an analyst reevaluates their earnings estimate ahead of an earnings release, it means they likely have new information that could possibly be more accurate.
Now that we understand the basic idea, let's look at how the Expected Surprise Prediction works. The ESP is calculated by comparing the Most Accurate Estimate to the Zacks Consensus Estimate, with the percentage difference between the two giving us the Zacks ESP figure.
Bringing together a positive earnings ESP alongside a Zacks Rank #3 (Hold) or better has helped stocks report a positive earnings surprise 70% of the time. Furthermore, by using these parameters, investors have seen 28.3% annual returns on average, according to our 10 year backtest.
Stocks with a ranking of #3 (Hold), or 60% of all stocks covered by the Zacks Rank, are expected to perform in-line with the broader market. Stocks with rankings of #2 (Buy) and #1 (Strong Buy), or the top 15% and top 5% of stocks, respectively, should outperform the market; Strong Buy stocks should outperform more than any other rank.
Should You Consider Nvidia?The final step today is to look at a stock that meets our ESP qualifications. Nvidia (NVDA - Free Report) earns a #1 (Strong Buy) 29 days from its next quarterly earnings release on August 26, 2026, and its Most Accurate Estimate comes in at $2.10 a share.
By taking the percentage difference between the $2.10 Most Accurate Estimate and the $2.09 Zacks Consensus Estimate, Nvidia has an Earnings ESP of +0.52%. Investors should also know that NVDA is one of a large group of stocks with positive ESPs. Make sure to utilize our Earnings ESP Filter to uncover the best stocks to buy or sell before they've reported.
NVDA is part of a big group of Computer and Technology stocks that boast a positive ESP, and investors may want to take a look at Fortinet (FTNT - Free Report) as well.
Fortinet is a Zacks Rank #1 (Strong Buy) stock, and is getting ready to report earnings on July 29, 2026. FTNT's Most Accurate Estimate sits at $0.76 a share one day from its next earnings release.
Fortinet's Earnings ESP figure currently stands at +1.56% after taking the percentage difference between its Most Accurate Estimate and its Zacks Consensus Estimate of $0.75.
NVDA and FTNT's positive ESP figures tell us that both stocks have a good chance at beating analyst expectations in their next earnings report.
Find Stocks to Buy or Sell Before They're ReportedUse the Zacks Earnings ESP Filter to turn up stocks with the highest probability of positively, or negatively, surprising to buy or sell before they're reported for profitable earnings season trading. Check it out here >>
On Friday, July 25, the legendary ‘Big Short’ trader Michael Burry disclosed he has increased his bet against the semiconductor giant Nvidia (NASDAQ: NVDA) while the stock was changing hands at roughly $210.28.
The move added to the $186 million short position he originally assumed in the third quarter (Q3) of 2025, before deregistering Scion Asset Management, and came amidst the latest NVDA downturn that ignited on July 22.
By press time on Tuesday, July 28, Burry’s bearish bet appears to be paying off as Nvidia equity opened the day’s session at $193.45, extending the weekly losses to 6.15% and pushing its monthly performance into the red.
Nvidia stock price one-month chart. Source: Google Still, the options purchased last year are likely yet to turn profitable for the short trader unless they were purchased at the very end of Q3. Indeed, Nvidia stock was changing hands between $170 and $190 for most of the time frame and only crossed above $200 in the final days of October, 2025.
Michael Burry’s increase of the bet against Nvidia is in line with his long-standing view of the instability of the artificial intelligence (AI) ‘boom.’
Why Michael Burry is betting against Nvidia stock and the AI ‘boom’ In recent months, the legendary investor has been sounding the alarm regarding the debt private credit providers have accumulated, and that is mostly linked to the chip leases and the data center buildout.
According to Burry, the trend could turn into a contagion that risks the wider economy, especially in the context of rising long-term bond yields.
Notably, though the ‘Big Short’ trader has faced extensive criticism in recent months for staying bearish through the ‘boom,’ he is far from the only one sounding the alarm.
Data center construction has, despite the massive capital expenditure (CapEx) it is consuming, apparently not been going according to plan, with the numerous delays, cancellations, and a severe mismatch between the number of announced groundbreakings and completions.
Furthermore, Nvidia’s recent $250 billion backstop agreement with OpenAI reignited concerns over circular financing, with some of the company’s greater critics raising the question of whether the chipmaker is funding its own customers so they can remain its customers.
Together, the developments also contribute to the concerns that much of the hardware that the world’s biggest semiconductor company sold might be slowly depreciating, unplugged and in warehouses, all the while the new Vera Rubin platform needs to exceed Blackwell sales.
However, it is notable that the bearishness is far from universal and that the majority of companies involved with AI – including Nvidia – remain in the green year-to-date (YTD) and that NVDA shares still command the confidence of Wall Street.
Nvidia is not the only short position Michael Burry increased in July Elsewhere, the world’s largest blue-chip chipmaker was not the only short position Michael Burry increased in late July.
Also on Friday, the ‘Big Short’ investor disclosed raising his bets against Micron (NASDAQ: MU), Caterpillar (NYSE: CAT), and the iShares Semiconductor ETF (SOXX).
Burry’s Tesla (NASDAQ: TSLA) and Palantir (NASDAQ: PLTR) short positions, reportedly, remain intact as well.
Just a few years ago, it would have sounded far-fetched to suggest that Nvidia could become the world's most valuable company. Then came the artificial intelligence (AI) revolution.
Its graphics processing units became the engine powering modern AI and demand exploded as tech giants raced to build ever-larger AI models.
Still, companies that create the most value at the beginning of a technology revolution aren't always the ones that create the most value in the end. That's why Alphabet (GOOGL +2.13%) deserves investors' attention.
Although Nvidia dominates the infrastructure powering AI today, Alphabet could become one of its biggest long-term beneficiaries. If the AI race shifts from building intelligence to using it profitably, Alphabet has a credible path to becoming the world's most valuable company.
Image source: Getty Images.
As of July 27, Nvidia and Alphabet have market capitalizations of $4.8 trillion and $4 trillion, respectively. With a difference of about 20%, it's not difficult to envision a future in which the latter overtakes the former in market capitalization.
The first phase of AI belongs to Nvidia Every major technological revolution begins with infrastructure. The internet needed networking equipment. Cloud computing requires huge data centers. Smartphones depend on advanced semiconductor manufacturing.
AI is following the same pattern. Every company building frontier AI models needs enormous computing power, and Nvidia has become the clear industry leader. Hyperscalers are collectively investing hundreds of billions of dollars to expand their AI infrastructure, creating an extraordinary demand environment for Nvidia's chips.
But here's the thing: History also shows that infrastructure companies don't always capture the largest share of long-term value. Once the underlying technology becomes widely available, investors often shift their attention to the companies that use it to solve real-world problems and generate recurring profits.
That transition could become the next chapter of the AI boom.
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Alphabet already has what most AI companies want Many AI companies face the same challenge: They need customers.
Alphabet already has them. Billions of people use Google Search, YouTube, Android, Chrome, Gmail, Google Maps, and Google Workspace every day. Few companies have a distribution network of this scale, and even fewer have the data and user engagement to continuously improve their AI models.
That gives Alphabet an advantage that is easy to overlook. It doesn't need AI to persuade people to use its products. Instead, AI can be added to the products people already rely on.
Smarter Search could improve the user experience while helping advertisers reach customers more effectively. AI-powered tools can make Workspace more valuable to businesses. Google Cloud can attract enterprise customers looking to build AI applications. Even YouTube has opportunities to improve content discovery, advertising, and creator tools through AI.
None of these initiatives needs to become a trillion-dollar business on its own. Together, they could meaningfully increase these businesses' earnings.
The biggest prize isn't building AI; it's monetizing it Building a powerful AI model is impressive. But turning that technology into sustainable profit is much harder. This is where Alphabet's business model stands out.
Rather than betting on a single AI product, the company can embed AI across multiple businesses that millions of consumers and enterprises already pay for. Every incremental improvement can increase engagement, improve productivity, strengthen customer loyalty, or enhance monetization.
That's a powerful flywheel. Alphabet doesn't need AI to reinvent the company. It simply needs AI to make an already exceptional business even stronger. If management executes well, the financial impact could compound for years.
The big question Can Alphabet really overtake Nvidia? It's certainly possible, but it's far from guaranteed.
Nvidia remains the clear leader in AI chips, and demand for its products continues to exceed supply in many areas. The company is also innovating rapidly and has built an ecosystem that competitors will struggle to replicate.
But market leadership isn't determined solely by who builds the best technology. It's determined by who captures the most economic value. If AI spending gradually shifts from building infrastructure to deploying AI across billions of everyday interactions, Alphabet could emerge as one of the biggest winners.
Its unmatched distribution, multiple monetization engines, and extraordinary cash generation give it advantages that few companies can match.
What does it mean for investors? Nvidia has been the defining investment of AI's infrastructure phase. But Alphabet could become the defining investment of AI's monetization phase.
That doesn't mean Alphabet will automatically become the world's most valuable company. Predicting the future of AI is impossible, and Nvidia could continue extending its lead for many years.
That will happen if Alphabet turns AI into the greatest amount of long-term economic value.
Tech investors keep seeing and hearing the same headlines about tech companies making their own chips and diversifying away from Nvidia (NVDA -4.97%)'s high-priced products. Initially, it's easy to see why such a scenario may appear to be a troubling one, given that tech giants have the resources to invest in their own chipmaking abilities.
However, these aren't exactly new developments. And there are also many other chipmakers out there, including Broadcom and Advanced Micro Devices, that offer alternatives. But the actual numbers don't really back up the worries that Nvidia is in any serious trouble, at least not yet, anyway. Both its growth rate and its market share remain strong.
It also raises the question of whether the stock, which is among the most valuable in the world and has a market cap of around $5 trillion, could still be a bargain buy.
Image source: Getty Images.
Nvidia continues to dominate the data center market Tech companies are spending big money on data centers, requiring the latest and greatest chips in their build-out efforts. What's remarkable is that even with a growing number of options out there, companies still go to Nvidia. That's evident with a remarkable stat from Futurum Group, which finds that Nvidia dominates the market for data center GPUs, with more than 95% market share.
It's an astounding figure that highlights just how crucial the company's chips are. And Nvidia's growth rate certainly corroborates that, as the business has been doing more than fine in its most recent quarters.
NVDA Revenue (Quarterly YoY Growth) data by YCharts
Is Nvidia's stock a bargain buy? Although Nvidia's market cap, which is often around $5 trillion, may seem high, the company's impressive revenue and profit growth highlight just how reasonably priced the stock is right now. Based on analyst projections, it's trading at less than 24 times its future earnings. By comparison, the average stock on the S&P 500 trades at 21 times its future profits. That means it's trading at only a slightly higher premium than the average stock within the broad index.
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In the long run, Nvidia has potentially even more opportunities to tap into, even if competition does end up cutting into its growth. The massive profits and cash flow it's generating now and in recent years can enable it to invest heavily in the future in new technologies and acquisitions to drive even further growth. That's why, as a long-term investment, it may be a great addition to any portfolio.
David Jagielski, CPA has no position in any of the stocks mentioned. The Motley Fool has positions in and recommends Advanced Micro Devices, Broadcom, and Nvidia. The Motley Fool has a disclosure policy.
Jim Cramer opened Mad Money on July 27, 2026 with a warning that pulled directly from his own trading history. “A spectre is haunting this market. The spectre of the year 2000,” he told viewers, before turning to the deal that has become the flashpoint of the current AI cycle: NVIDIA‘s (NASDAQ:NVDA | NVDA Price Prediction) reported financing arrangement with OpenAI.
Cramer’s concern centers on Nvidia guaranteeing $250 billion worth of financing for OpenAI data centers. His view is that the structure mirrors the vendor financing arrangements that helped detonate the telecom equipment sector during the dot-com collapse. “Makes sense given that OpenAI is one of their big customers,” he said. “But there is history. Boatloads of it. And it is very negative.”
The Vendor Financing Trap Cramer Says He Lived Through The core lesson Cramer pulled from 2000: “What we learned in 2000 is that you don’t lend to customers who buy your goods. They might default and your earnings get smashed.” Back then, telco equipment suppliers booked huge revenue by financing customer purchases, only to watch their stocks take decades to revisit previous highs after customers defaulted.
His argument is that OpenAI’s profile fits the risk pattern. OpenAI is not investment grade and is known to be burning significant cash. It has not gone public and its ability to pay is uncertain. That, Cramer contends, is exactly the profile investors ignored during the last cycle.
He extended the critique to the broader customer base. “So many of the buyers of Nvidia AI chips had tremendous balance sheets a year ago. That’s no longer the case now. Some desperately need more money to finish their data center buildouts, and it might not be available,” he said. Cramer noted his own hedge fund exited 2000 tech stocks about a week before the peak by watching buyer balance sheets turn grotesque.
The Numbers Behind the Warning Nvidia itself remains a financial juggernaut. The company reported Q1 FY2027 revenue of $81.615 billion, up 85.2% year over year, with Data Center revenue of $75.246 billion and non-GAAP EPS of $1.87 against a $1.77 consensus. Non-GAAP gross margin held at 75.0%. The board authorized an additional $80.0 billion in buybacks and lifted the quarterly dividend from $0.01 to $0.25. Details are in the company’s Q1 FY27 8-K filing.
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CEO Jensen Huang has framed the moment as generational, calling the “buildout of AI factories” the largest infrastructure expansion in human history. Yet the company’s total supply-related commitments have reached $119.0 billion, with multi-year cloud service commitments of $30.0 billion, capital obligations that anchor Cramer’s concern about counterparty risk.
The Market Is Already Reacting Cramer argued the tape is confirming the risk. Nvidia stock fell 10 points despite positive news, and supplier stocks finished dramatically lower on Friday despite huge deal announcements. NVDA closed at $196.51 on July 27, down 4.99% on the session and 3.33% for the week.
Cramer also flagged JP Morgan strategist Michael Lewis recently comparing the current moment to the dot-com era, concluding they are “too close for comfort.” The macro backdrop added fuel: oil fell 9% in one session, helping move interest rates down and stocks up, the kind of tape rotation that historically masks deeper structural concerns.
Reddit sentiment mirrors that tension. The single most engaged NVDA post of the week, with 4,824 upvotes and 622 comments, argued that “34% of the S&P is 10 stocks making the same bet.”
Cramer’s Bottom Line Cramer emphasized he still regards Nvidia as an exceptional company. His objection is to the financing pattern. “I saw the movie. I was in a movie. Bottom line, I don’t want the sequel. Nvidia shouldn’t make these guarantees, even if it has all the money in the world. Just history. That’s all. Just history,” he said. Investors will want to keep an eye on the stock as Q2 FY2027 guidance of $91.0 billion in revenue collides with deepening scrutiny of who is financing whom.
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ToplineProsecutors in Taiwan detained an Nvidia employee as part of an investigation into alleged smuggling of AI servers into China—which were powered by Nvidia’s advanced chips in violation of U.S. export controls—according to multiple reports on Tuesday.
Prosecutors in Taiwan detained an Nvidia staffer as part of a probe into smuggling of advances AI chips into China.
Getty Images
Key FactsIn a statement on Tuesday, Keelung District Prosecutors Office identified the suspect by his surname, Chang, and said he was summoned for questioning after investigators searched his residence and workplace last week.
The statement didn’t mention Chang’s employer’s name, but Bloomberg and Reuters reported they are an Nvidia employee and the search targeted the chipmaker’s Taipei office.
The statement added that after the questioning, the prosecutors determined there was a “strong suspicion of criminal activity” and Chang was detained amid concerns they could flee, destroy evidence or collude with accomplices.
The prosecutor’s statement does not accuse Nvidia or any other company of wrongdoing but notes that the detained employee is suspected of multiple criminal offenses, including falsification of documents.
Forbes has reached out to Nvidia for comment.
As part of the probe, Taiwanese authorities detained several individuals in May and June—including employees of server manufacturer Super Micro—whose co-founder was arrested and charged by the U.S. Justice Department earlier this year in a related case.
What Do We Know About The Super Micro Smuggling Case?In March, the DOJ announced it had charged three people, including Super Micro co-founder Yih-Shyan “Wally” Liaw, with one count of violating U.S. export control law, one count of conspiring to smuggle goods from the U.S. and one count of conspiring to defraud the U.S. The Justice Department alleged that the trio had conspired to illegally divert advanced servers assembled in the U.S. with sophisticated American AI chips to China. Liaw, who is a U.S. citizen, was one of the two people arrested. According to the prosecutors, the three men sold servers equipped with cutting-edge Nvidia AI chips—which are subject to export controls—to China through a Southeast Asian company. The alleged smuggling generated $2.5 billion in revenue for Super Micro. The server maker noted that it was not named as a defendant in the case and said the alleged conduct by the three individuals violated the company’s “policies and compliance controls.” The company also said it had placed Liaw and another staffer on administrative leave and severed ties with the contractor who was charged as part of the probe.
TangentIn a statement shared with Bloomberg, an unnamed Nvidia spokesperson said smuggling was a “nonstarter” for the company and the company sells its products to well-known partners to ensure compliance with export control rules. The spokesperson also said any diverted chips would receive “no service, support or updates.”
further readingSuper Micro Shares Plunge 25% After Co-Founder Charged In $2.5 Billion AI Chip Smuggling Plot (Forbes)
The semiconductor industry is shifting rapidly as artificial intelligence scales, leaving investors to choose between high-growth titans. Deciding between Marvell Technology (MRVL -2.38%) and Nvidia (NVDA -4.97%) requires weighing networking expertise against GPU dominance.
Marvell specializes in the infrastructure that moves and stores data, while Nvidia focuses on the processors that analyze and generate it. Both are essential to modern computing, but they offer different financial profiles for investors looking to capitalize on hardware demand.
The case for Marvell TechnologyMarvell Technology designs and sells essential data infrastructure solutions, focusing on networking, security, and storage products for data centers and 5G carriers. Its key commercial relationships include Amazon (AMZN -0.33%) for custom AI chip production and Nvidia for strategic infrastructure integration.
Because its top 10 customers account for nearly 82% of total net revenue, this level of customer concentration adds a layer of risk to the business. In fiscal 2026, revenue reached nearly $8.2 billion, up roughly 42.1% from the prior year.
Marvell reported net income of approximately $2.7 billion, marking a significant transition from net losses in previous years. As of its January 2026 balance sheet, the debt-to-equity ratio is roughly 0.3.
The current ratio is nearly 2, while free cash flow totaled nearly $1.4 billion for the year. Note that stock-based compensation accounted for roughly 33.8% of operating cash flow, thereby inflating reported cash generation, since SBC is a non-cash expense added back into the cash flow statement.
The case for NvidiaNvidia develops the hardware and software used for AI model training, scientific computing, and graphics. It maintains deep partnerships with system integrators to deploy infrastructure at scale among semiconductor stocks.
Its revenue is heavily concentrated among a limited group of large enterprise customers and cloud service providers. In fiscal 2026, revenue reached nearly $215.9 billion, an increase of 65.5% versus the previous year.
Net income was approximately $120.1 billion, resulting in a net margin of close to 55.6%. This figure reflects the percentage of sales remaining after all operating expenses, interest, and taxes are paid.
As of its January 2026 balance sheet, the debt-to-equity ratio is approximately 0.1. The current ratio stands at nearly 3.9, indicating strong liquidity to cover upcoming bills. Free cash flow for the fiscal year ended Jan. 25, 2026, was close to $96.7 billion.
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Risk profile comparisonMarvell Technology faces intense competition and a trend where customers like Amazon design their own proprietary chips, which could erode market share. Stringent U.S. export controls limit access to certain regions, while a heavy reliance on third-party foundries in Taiwan creates geopolitical vulnerability. The company must also successfully integrate recent acquisitions, such as Celestial AI, to maintain its product road map.
Nvidia deals with similar regulatory complexity regarding chip exports to China and competition from Advanced Micro Devices (AMD -5.09%) and Intel (INTC -0.70%). Major customers, including Microsoft (MSFT +1.95%), are increasingly insourcing AI chip designs to reduce costs. Additionally, the company faces supply chain dependencies on Taiwan Semiconductor Manufacturing (TSM -0.83%) and ongoing litigation regarding historical disclosures of its cryptocurrency-related revenue.
Valuation comparisonNvidia appears more attractive on a forward price-to-earnings basis, while Marvell Technology carries a higher premium relative to its future earnings estimates.
MetricMarvell TechnologyNvidiaForward P/E51.323.0P/S ratio22.223.3Valuation metrics sourced from Financial Modeling Prep (FMP) and may differ from other data providers.
Personally, the AI boom makes me nervous to invest in Nvidia, because that's fueling a lot of investor enthusiasm for the stock. (A boom doesn't look very different from a bubble.) Furthermore, The Wall Street Journal recently reported that Nvidia is weighing potentially $250 billion in financing for OpenAI's data center buildout. The issue here is that it basically looks like an ouroboros of AI money. Nvidia gives OpenAI the money, then OpenAI turns around and buys Nvidia's GPUs to build its data centers. This sort of deal is not the first of its kind amid the AI arms race, but it's very large and raises concerns about the almost circular economy developing in the sector.
The other thing I have a hard time getting a handle on is Nvidia's gargantuan market cap. It's a very simplistic view of things, but Marvell has a market cap under $200 billion, while Nvidia is valued at $4.8 trillion. Part of that is because Nvidia is posting massive growth, but that will be increasingly hard to replicate as it faces tough comparisons to its previous performance.
Marvell's forward P/E is on the pricier end of the scale, which I don't love, but it's not quite so steeped in the AI obsession that fuels investors' demand for Nvidia stock. I'd rather have Marvell in my portfolio, all things considered.
Picture a 53-year-old software project manager. She has been maxing her 401(k) for two decades, most of it in a low-cost S&P 500 index fund. The account has ridden a serious wave: the S&P 500 itself has gained roughly 241% over the last 10 years, before dividends. She has no pension. Only 14% of Gen X workers have a traditional pension, compared with 56% of boomers, according to CNBC, citing the National Institute on Retirement Security.
Here is the wrinkle. Her index fund is more concentrated than it looks. Seven stocks now make up over 30% of the S&P 500. Asher Rogovy, chief investment officer of Magnifina, reportedly estimates that 40% to 50% of the index’s value is tied to companies riding the artificial intelligence theme. Inside the fund, NVIDIA (Nasdaq: NVDA) alone represents about 8% of the index, with Apple (Nasdaq: AAPL) and Microsoft (Nasdaq: MSFT) close behind. She reads a message board thread from a peer worrying about the same thing: a retirement plan that quietly turned into an AI bet.
This is why Social Security matters more for her than it did for her parents. It is the one piece of her retirement income that arrives every month, receives annual inflation adjustments, and does not care what NVIDIA did last quarter.
The Two Social Security Features That Actually Move the Needle The first is the one she controls: when she claims. Claiming at 62 can cut a benefit by up to 30% for life, while waiting past full retirement age (FRA) adds about 8% per year until 70. On a $2,400 monthly benefit at FRA, claiming at 62 could mean roughly $1,680 a month instead. Waiting until 70 could push it toward about $2,976. That difference compounds across a 25-year retirement, and it is inflation-adjusted the whole way.
The second is built in. The 2026 cost-of-living adjustment (COLA) came in at 2.8%, tied to the CPI-W readings the Social Security Administration (SSA) uses to set annual raises. Private annuities can provide lifetime income, but matching Social Security’s combination of longevity protection, inflation adjustments, and federal backing is difficult and expensive.
Now the sharp twist. Social Security’s Old-Age and Survivors Insurance trust fund is projected to exhaust its reserves in the fourth quarter of 2032. At that point, continuing revenue would cover about 78% of scheduled benefits without Congressional action. Gen X begins retiring right into that window. Reform is possible, as it was in 1983, but the projection is what the trustees currently show.
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How Social Security Talks to the Rest of Her Money Her portfolio and her Social Security check are two very different animals. If a bad market hits in the first years of retirement, she faces what planners call sequence-of-returns risk: shares sold at depressed prices are gone and cannot participate in the recovery. After the dot-com peak, Amazon (Nasdaq: AMZN) took about a decade to reclaim its high. The company recovered. An investor forced to sell along the way did not recover those shares.
Social Security helps in a real way. Every dollar of guaranteed income is a dollar she does not have to withdraw from a falling portfolio. Pair that with a cash and short-term bond “war chest” covering two or three years of expenses, and she buys herself time to let stocks recover instead of locking in losses.
Delaying her claim while she still works or using taxable savings strategically during the gap years can raise the guaranteed floor for the rest of her life, including the benefit left to a surviving spouse.
What to Actually Do With This Separate the early-retirement money from the long-term portfolio. Bills in the first few years should not depend on whatever the AI trade is doing that month. Cash and short-term bonds can cover near-term withdrawals. An equal-weight fund, large-cap value sleeve, or gradual glide path can separately reduce concentration in the long-term portfolio. Those are two different jobs, and they need different tools. Treat the claiming decision like the pension it effectively is. For many workers without a pension, delaying Social Security is the highest-quality income upgrade available. Run the numbers for claiming at 62, 67, and 70 before deciding, and factor in a spouse’s benefit if there is one. The point is knowing which piece of retirement is guaranteed, which piece is not, and giving the guaranteed piece the weight it deserves, without needing to predict the market or Congress. Individual situations vary, and a small change in health, marriage status, or taxes can shift the right answer.
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Shares of Nvidia (NVDA -4.97%) sank on Monday following reports that the chipmaker was in discussions to guarantee financing for a colossal data center project.
Image source: Getty Images.
The costs of the AI buildout boom are mounting Nvidia is in talks to provide a $250 billion financial guarantee for a 10-gigawatt data center project in Ohio, according to The Wall Street Journal.
One of Nvidia's largest customers, artificial intelligence (AI) model builder OpenAI, is reportedly attempting to lease the site, which is being developed by a subsidiary of Japanese investment giant SoftBank.
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Nvidia is also reportedly evaluating a separate deal to finance OpenAI's purchase of its AI chips, which could amount to another $350 billion.
Red flags are waving News of these potential financing deals is making investors increasingly uncomfortable.
So-called circular financing deals occur when a supplier helps its customers pay for goods or services that they might not otherwise be able to afford.
At first, these arrangements can boost the supplier's sales. But over time, the supplier becomes increasingly tied to its customers' fate.
That's a legitimate concern for Nvidia and its shareholders. Despite its stunning growth, OpenAI remains deeply unprofitable. And competition among AI model developers intensifies by the day.
Joe Tenebruso has no position in any of the stocks mentioned. The Motley Fool has positions in and recommends Nvidia. The Motley Fool has a disclosure policy.
Nvidia has signed leases worth up to $50 billion for a data center in Texas that Hut 8 is building, the Financial Times reported on Tuesday, citing five people familiar with the deal.
Nvidia's (NVDA -4.97%) tepid returns of 19% over the past year may lead investors to think that the artificial intelligence (AI) pioneer's best days on the stock market are now behind it. After all, the PHLX Semiconductor Sector index has clocked way more impressive gains of 109% during this period.
However, it would be wrong to think that Nvidia stock has peaked following stellar returns that it has clocked in recent years. That's because the AI infrastructure boom that has supercharged Nvidia's growth over the past four years isn't ending anytime soon. More importantly, the company has been diversifying into new AI niches that should strengthen its growth over the long run.
So, don't be surprised to see Nvidia emerging from its lull and going on a terrific bull run that could take its stock price beyond $500 by 2029. Let's see how that's possible.
Image source: The Motley Fool.
AI-driven productivity gains should ensure strong demand for Nvidia's chips According to a survey of 578 respondents carried out by Info-Tech Research Group, 94% of developers using AI tools to develop software have reported higher productivity. Meanwhile, 83% of respondents have witnessed a drop in defects. Even consulting giant PwC estimates that companies using AI are experiencing 40% higher productivity compared to companies least exposed to this technology.
Not surprisingly, capital expenditures needed to set up AI infrastructure are anticipated to hit $1.4 trillion by 2028, according to Morgan Stanley. The investment bank estimates a cumulative $2.1 trillion outlay on AI capex between 2025 and 2027. Nvidia is poised to corner a significant chunk of this lucrative opportunity, given its 80% share of the AI chip market.
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The company is already anticipating $1 trillion in chip orders for its Blackwell and Vera Rubin systems in 2026 and 2027. That points to a major improvement over its $193.7 billion data center revenue in fiscal 2026 (which ended in January this year). Another immediate catalyst for Nvidia is its Vera server central processing unit (CPU), which the company believes will open a $200 billion total addressable market (TAM) opportunity.
The chip designer is projecting $20 billion in Vera CPU revenue this fiscal year, which is impressive considering that it has just started shipping this processor as a stand-alone product. Don't be surprised to see Nvidia's server CPU business get bigger over the next couple of fiscal years, considering that it is in solid demand from hyperscalers.
The math behind a $500 stock price Analysts are projecting an 88% increase in Nvidia's earnings per share to $8.99 in fiscal 2027. This will be followed by robust double-digit growth over the next two fiscal years.
Data by YCharts
Analysts, however, may be underestimating Nvidia's growth potential, especially considering its solid revenue pipeline for the next two years. However, this AI stock has the potential to jump significantly even if its earnings per share increase to $15.98 in fiscal 2029 (which will end in January 2029). A price-to-earnings ratio of 33 (in line with the Nasdaq-100 index) at that time suggests that Nvidia's stock price could reach $527. That's 2.5x where Nvidia stock is right now, making it a no-brainer buy as it trades at an attractive 31.7 times earnings despite its outstanding growth potential.
Item 1 of 3 Computer motherboard and chip appear in this illustration taken August 25, 2025. REUTERS/Dado Ruvic/Illustration
[1/3]Computer motherboard and chip appear in this illustration taken August 25, 2025. REUTERS/Dado Ruvic/Illustration Purchase Licensing Rights, opens new tab
SummaryCompaniesSK Hynix's U.S.-listed shares closed below their $149 listing priceChina's advances in chipmaking and AI fuel worries of stronger competitionSK Hynix shares drop 11%, Samsung shares slide nearly 10% in SeoulSEOUL, July 28 (Reuters) - South Korean chip stocks slumped on Tuesday, with Samsung Electronics (005930.KS), opens new tab and SK Hynix (000660.KS), opens new tab falling as much as 9.5% and 11.1%, respectively, as investors retreated from AI-related stocks amid mounting concerns over financing risks tied to AI infrastructure spending and intensifying competition from China.
SK Hynix's U.S.-listed shares had already slumped overnight, closing at $143.02, below their $149 initial public offering price.
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The benchmark KOSPI (.KS11), opens new tab was trading down around 8% as of 0120 GMT.
The sector-wide selloff followed a series of developments that renewed doubts about the sustainability of the AI-driven semiconductor rally.
SK Hynix, a key supplier of high-bandwidth memory (HBM) chips to Nvidia (NVDA.O), opens new tab, has been one of the biggest beneficiaries of the AI spending boom, making its shares particularly sensitive to shifts in investor sentiment toward the sector.
Analysts said the selloff reflected a combination of concerns over AI infrastructure financing, China's technological advances and rising competition from Chinese firms.
Han Ji-young, an analyst at Kiwoom Securities, said reports that Chinese companies were developing domestic deep ultraviolet (DUV) lithography equipment had reignited concerns that Chinese memory makers could accelerate capacity expansion, intensifying competition in the global memory market.
While details such as the companies involved, equipment performance and commercialization timelines had yet to be disclosed, the news had cooled investor sentiment as the investment narrative for semiconductor stocks had already weakened, he said.
Han added that investors were also becoming increasingly cautious ahead of a string of earnings reports due later this week.
"Despite stronger-than-expected earnings from Samsung Electronics earlier this month and Alphabet last week, semiconductor shares experienced sharp declines after the results," he said.
Separately, a Wall Street Journal report that Nvidia could provide a roughly $250 billion financial backstop for an OpenAI data-centre project sent Nvidia shares down nearly 5%, with investors questioning the extent to which the AI chip leader may be financing its own customers.
Further weighing on sentiment, the growing popularity of low-cost Chinese open-source AI models such as Kimi K3 raised questions about whether future AI workloads could prove less intensive than previously expected — meaning less demand for advanced AI chips and HBM.
Meanwhile, Chinese memory-chip maker CXMT's 688825.SS strong stock-market debut fuelled concerns about intensifying competition in the global memory industry.
The listing came after reports that Apple had been lobbying the Trump administration to allow the use of Chinese-made chips in some of its products, further unsettling investors already concerned about China's growing technological capabilities.
Reporting by Heekyong Yang; Editing by Kevin Buckland
Our Standards: The Thomson Reuters Trust Principles., opens new tab
The chipmaking giant is in talks with OpenAI to provide a $250 billion financial backstop for the project, which would be among the largest of the A.I. boom.
HomeIndustriesComputers/ElectronicsTech StocksTech StocksInvestors are fretting over a report that Nvidia could backstop an OpenAI data-center lease, in what would be the largest such arrangement yetJuly 27, 2026, 5:46 p.m. ET
As investors question the value of heavy artificial-intelligence spending, the specter of vendor financing once again hangs over the technology sector.
On Sunday, the Wall Street Journal reported that Nvidia NVDA is in talks to guarantee $250 billion in financing that would allow OpenAI to lease a data center being built in Ohio. The Ohio facility could cost over $500 billion and would be the largest data-center project announced to date, according to the Journal.
Nvidia is reportedly in talks to provide a $250 billion financing package for a giant OpenAI data center project in Ohio — days after CEO Jensen Huang voiced support for controversial “open source” AI models used increasingly by China.
Nvidia’s guarantees would help the ChatGPT maker lease a 10-gigawatt project — the largest the industry has yet seen, costing as much as $500 billion in total — that Japanese billionaire Masayoshi Son’s SoftBank is developing in southern Ohio through its energy subsidiary, according to a Wall Street Journal report on Sunday.
Nvidia CEO and founder Jensen Huang is in talks to provide OpenAI a financial backstop for a massive AI data center. AFP via Getty Images The AI pioneer has been in advanced talks to lease the site for several weeks, per the Journal report and Anthropic, Microsoft and Google have also spoken to Commerce Secretary Howard Lutnick about the project.
The potential deal has also reignited fears that Nvidia is singlehandedly propping up the AI boom. Financiers including Goldman Sachs traders and famed investor Michael Burry of “Big Short” have for months sounded the alarm that such agreements are “circular” in nature, where Nvidia finances and takes stakes in companies and projects that use its chips.
Meanwhile, Huang — in his first post ever on X late Friday — issued a letter rallying for controversial open-source models that was also signed by other tech titans including Microsoft, Meta, IBM and Palantir Technologies. The group – calling itself the Open Secure AI Alliance – called on lawmakers to avoid “premature restrictions on open models that stifle competition or drive innovation overseas.”
The missive by Huang was widely seen in tech circles as a landmark moment in the intensifying debate over open vs closed-source AI models that has roiled Silicon Valley and Washington.
On one side, Huang and other tech titans say models that aren’t solely controlled by one company speed the development of AI and prevent power from being overly concentrated. Opponents — most notably Anthropic and OpenAI — say releasing AI blueprints hands bad actors the keys to build AI tools that can be used for nefarious purposes.
OpenAI co-founder and CEO Sam Altman isn’t profitable and is hoping to secure financial backing from Nvidia for the $500 billion project. Getty Images Anthropic CEO Dario Amodei said in a 2023 testimony before the US Senate Judiciary Committee that open source AI was moving down a “very dangerous path” — a warning he has lately stepped up.
Altman, meanwhile, has also argued against open source AI – but last year OpenAI launched some tools with open source elements, known as open weights.
“It was clear that if we didn’t do it, the world was gonna be mostly built on Chinese open-source models,” Altman told CNBC last year.
Huang acknowledged in his letter that open-source AI models carry a risk but that in the long-run they will AI to create “innovation and prosperity.”
Sam Altman-led OpenAI has been in advanced talks to lease the data center site for several weeks. REUTERS “To be sure, open weights carry real and distinct risks. Once released, the weights are beyond the original developer’s control, and modified versions are difficult to trace or reverse,” Huang wrote in the alliance’s letter. “But the right response to this risk is not to prohibit open weights.”
The alliance group said Monday it’s developing and is aiming to deploy open-source AI tools that any company can use to thwart cyberattacks.
The Ohio project is a big bet for both Lutnick and the Trump administration. As part of Japan’s tariff agreement with the U.S., Tokyo committed $33 billion to build a natural-gas power facility on federal land that will be operated by SB Energy, a company controlled by SoftBank’s Son.
Lutnick, Son and Energy Secretary Chris Wright broke ground on the site – Built on a former uranium-enrichment site south of Columbus – in March. The U.S. will pay SB Energy to run the plant, while Japan and America will split power revenue until Japan recovers its investment. After that, the U.S. would receive 90% of the proceeds.
Microsoft and other tech giants have advocated to lawmakers for open-source AI models. ZUMAPRESS.com Other tech giants are exploring this model – Google, for instance, has backstopped some data centers for Anthropic.
Nvidia and other supporters of open-source have argued that proprietary tools from companies like Anthropic or OpenAI can similarly be misused and have their safeguards circumvented. But disseminating the AI capabilities widely with open-source tools will allow everyone to be able to defend themselves.
Nvidia’s backing of the data center project would allow the SoftBank-owned developer to raise debt at more favorable terms than it could if OpenAI had no financial backer since the Sam Altman-led startup is an unprofitable private company and thus has no investment-grade credit rating.
Nvidia already has $30 billion riding on OpenAI and is also discussing a deal to finance chip buying for OpenAI, which could total $350 billion, according to the Journal.
The proposed mega AI campus would consume roughly 10 gigawatts of electricity – enough to power several million homes – and take years to complete with the first phase expected to be finished in 2028.
NVDA stock is down on the report. See the chart and price action here. Nvidia would also discuss separately financing up to $350 billion of chip purchases tied to the same site, pushing total project costs past $500 billion and making it the largest data center ever proposed.
The arrangement would let SB Energy borrow against Nvidia’s balance sheet rather than OpenAI’s, since the ChatGPT maker still lacks an investment-grade credit rating.
The scale drew immediate pushback. Investor Michael Burry and commentator Ed Zitron flagged the guarantee as further evidence of a self-reinforcing loop, with Burry writing “around and around we go.”
Nvidia’s own filings show why: its first quarter fiscal 2027 10-Q caps total lease-guarantee exposure at $3.5 billion, meaning a $250 billion commitment would run roughly 71 times its current disclosed guarantee book.
This is the latest entry in a pattern stretching back nearly two years:
Each deal shares the same skeleton: Nvidia writes a check or backstops debt, and the recipient turns around and spends heavily on Nvidia silicon or Nvidia-powered cloud capacity.
Nvidia has consistently maintained it does not contractually require partners to buy its chips with the proceeds.
CEO Jensen Huang had suggested in March that the $30 billion OpenAI stake and $10 billion Anthropic commitment might mark the end of Nvidia’s largest AI equity checks, citing both companies’ expected IPOs.
The Ohio site talks suggest the chipmaker has instead found a new vehicle for the same dynamic, shifting from direct equity into loan backstops as OpenAI’s projected compute spending climbs toward $750 billion through 2030.
Terms remain unsettled, and people familiar with the talks caution the deal could still fall apart.
NVDA Stock Price Activity: Nvidia stock shed 4.99% on Monday to close at $196.51, according to data from Benzinga Pro.
Over the past month, NVDA has gained about 1.5% versus a 0.3% rise in the S&P 500 and is up roughly 4% year-to-date compared to the index’s 7.8% gain.
This content was partially produced with the help of AI tools and was reviewed and published by Benzinga editors.
Market News and Data brought to you by Benzinga APIs
Nvidia (NVDA - Free Report) closed the most recent trading day at $196.51, moving -4.99% from the previous trading session. The stock trailed the S&P 500, which registered a daily gain of 0.02%. On the other hand, the Dow registered a gain of 0.51%, and the technology-centric Nasdaq decreased by 0.18%.
Prior to today's trading, shares of the maker of graphics chips for gaming and artificial intelligence had gained 7.43% outpaced the Computer and Technology sector's loss of 4.21% and the S&P 500's gain of 0.77%.
The upcoming earnings release of Nvidia will be of great interest to investors. The company's upcoming EPS is projected at $2.09, signifying a 99.05% increase compared to the same quarter of the previous year. Our most recent consensus estimate is calling for quarterly revenue of $91.71 billion, up 96.2% from the year-ago period.
Regarding the entire year, the Zacks Consensus Estimates forecast earnings of $9.09 per share and revenue of $387.84 billion, indicating changes of +90.57% and +79.61%, respectively, compared to the previous year.
Investors should also note any recent changes to analyst estimates for Nvidia. These recent revisions tend to reflect the evolving nature of short-term business trends. With this in mind, we can consider positive estimate revisions a sign of optimism about the business outlook.
Based on our research, we believe these estimate revisions are directly related to near-term stock moves. Investors can capitalize on this by using the Zacks Rank. This model considers these estimate changes and provides a simple, actionable rating system.
The Zacks Rank system, which varies between #1 (Strong Buy) and #5 (Strong Sell), carries an impressive track record of exceeding expectations, confirmed by external audits, with stocks at #1 delivering an average annual return of +25% since 1988. Over the past month, there's been a 1.54% rise in the Zacks Consensus EPS estimate. Nvidia presently features a Zacks Rank of #1 (Strong Buy).
With respect to valuation, Nvidia is currently being traded at a Forward P/E ratio of 22.76. This expresses a discount compared to the average Forward P/E of 42.16 of its industry.
Meanwhile, NVDA's PEG ratio is currently 0.39. Comparable to the widely accepted P/E ratio, the PEG ratio also accounts for the company's projected earnings growth. The Semiconductor - General industry currently had an average PEG ratio of 0.87 as of yesterday's close.
The Semiconductor - General industry is part of the Computer and Technology sector. With its current Zacks Industry Rank of 6, this industry ranks in the top 3% of all industries, numbering over 250.
The Zacks Industry Rank assesses the strength of our separate industry groups by calculating the average Zacks Rank of the individual stocks contained within the groups. Our research shows that the top 50% rated industries outperform the bottom half by a factor of 2 to 1.
Be sure to use Zacks.com to monitor all these stock-influencing metrics, and more, throughout the forthcoming trading sessions.
Nvidia (NVDA), a leading developer of artificial intelligence chips, formed a coalition with several technology and cybersecurity companies to develop and share
Nvidia (NVDA -4.97%) announced Monday that it has formed the Open Secure AI Alliance, along with a group of roughly three dozen tech companies. The alliance will build and share open tools for protecting software and AI agents -- AI programs that act on their own. Space Exploration Technologies Corp. was among the founding members through its AI unit, SpaceXAI.
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What will the alliance do?The alliance’s core mission will be to “work to remediate and disclose vulnerabilities using open technologies.” Members include Microsoft, IBM, Palantir Technologies, and CrowdStrike.
Nvidia said it is contributing open model weights -- the trained numbers inside a model, published for all to see and free to use -- along with training data and research. It also posted a project which Nvidia says makes an AI agent's conduct easier to govern, audit, trace, and test. SpaceXAI said future Grok models will ship with open weights.
Why now?The timing follows a high-profile cyberattack in which an OpenAI model acting on its own -- no person was directing it -- hacked into the systems of Hugging Face, an open-source machine learning hub. Hugging Face said it contained the attack by running an open Chinese model on its own computers.
In Nvidia’s announcement of the alliance, the company stressed that "cyber defenders need open, frontier agentic systems for self-defense."
While the company didn’t name it directly, it’s clear that U.S. firms are wary of Chinese models -- many of which are open source -- becoming the go-to for cyber defense. But they are equally wary that the government will overstep and stifle competition domestically.
Treasury Secretary Scott Bessent floated sanctions last week for Chinese firms that use “distillation,” a process that creates new models from existing ones, more or less bypassing the incredibly expensive training phase that frontier models undergo.
More than 20 companies (including Nvidia) wrote to policymakers last week opposing "premature restrictions" on open weight models, saying it would “drive innovation overseas.“ SpaceX was not a signatory, but CEO Elon Musk took to X to share his support.
What it means for Nvidia investorsThis is unlikely to make a big difference to Nvidia’s bottom line for now, but long-term, the alliance could help Nvidia increase its importance in AI security, a layer that could further expand its footprint.
In the short term, the company is doing just fine. It reported $81.6 billion in quarterly revenue in May, up an incredible 85% from a year earlier. It guided the current quarter to $91 billion.
What it means for SpaceX investorsAgain, the impact on SpaceX in the short term is likely limited, but if the alliance is an indication of where the industry is headed -- moving from closed, proprietary models to open weight -- SpaceXAI could be in trouble.
Though it lags OpenAI and Anthropic, SpaceXAI is still first and foremost a frontier lab, and its business model relies on users paying for access. If cheaper -- or free -- models are available, it may prove difficult for the company to earn a return on the enormous costs involved in training Grok.
Johnny Rice has no position in any of the stocks mentioned. The Motley Fool has positions in and recommends CrowdStrike, International Business Machines, Microsoft, Nvidia, and Palantir Technologies. The Motley Fool has a disclosure policy.
Live Coverage Updates appear automatically as they are published.
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This live blog is being updated by Thomas Richmond, a 24/7 Wall St. contributor. You’ll get expert analysis of Navitas’ earnings.
Simply stay on this page, and new updates will appear below automatically. We expect Navitas to release earnings shortly after 4:05 p.m. ET.
5 minutes ago
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That wraps up our initial coverage of Navitas’s Q1 results. Thank you for stopping by!
53 minutes ago
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Navitas ended Q2 with $557.4 million in cash, up from $236.9 million at the end of 2025. That gives the company substantial funding to expand capacity and invest in its high-power product portfolio while its core business remains unprofitable.
One new opportunity is a 1.2-kilovolt JFET product line scheduled for release by early 2027. Navitas estimates the product could address an incremental $1 billion market across AI data centers, solid-state transformers, and energy-grid infrastructure.
The balance sheet provides time for that pipeline to mature. Navitas expects Q3 revenue of $13.5 million at the midpoint, representing 28% sequential growth and a return to year-over-year growth, while adjusted gross margin is projected to expand slightly to 39.7%.
55 minutes ago
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Navitas disclosed that it is shipping production samples of its gallium nitride and silicon carbide solutions for next-generation AI data centers targeting 800-volt architectures. Selected hyperscaler and XPU platforms are expected to begin ramping in 2027.
The company also deepened its collaboration with the NVIDIA MGX ecosystem, recently demonstrating an 800-volt-to-6-volt power delivery board. These higher-voltage architectures are designed to overcome the power bottlenecks created by increasingly dense AI computing racks.
Navitas reported an expanding backlog and record book-to-bill ratio as multiple customer programs moved toward production. The key question now is whether those samples and design engagements translate into material revenue when hyperscaler platforms begin ramping next year.
56 minutes ago
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Navitas Semiconductor expects mobile and low-end consumer revenue to become insignificant by the end of 2026, completing its transformation into a high-power semiconductor company.
The transition is beginning to show up in the numbers. High-power revenue grew more than 50% year over year during Q2, helping total revenue climb 22% sequentially to $10.5 million despite remaining 27% below last year’s level. Adjusted gross margin also expanded 100 basis points year over year to 39.5%.
AI data centers and grid infrastructure are expected to generate more than one-third of Navitas’ sales by year-end. With management forecasting double-digit sequential growth throughout the second half, the company believes its shrinking consumer business has reached the point where high-power growth can finally outweigh the lost revenue.
1 hour ago
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Navitas Semiconductor delivered Q2 revenue of $10.5 million, topping the $9.97 million estimate, while adjusted EPS matched expectations at a $0.04 loss. Adjusted gross margin reached 39.5%, beating the 38.7% consensus and expanding 100 basis points year over year.
The bigger surprise came from guidance. Navitas expects Q3 revenue of $13.5 million at the midpoint, nearly 22% above the $11.1 million consensus and representing 28% sequential growth. Management also expects revenue to return to year-over-year growth as its high-power strategy gains traction.
By year-end, Navitas expects mobile and low-end consumer products to contribute an insignificant portion of sales, leaving nearly all revenue tied to high-power markets such as AI infrastructure and grid applications.
The $228.2 million GAAP loss looks alarming, but it included a $203.1 million noncash earnout-liability charge rather than a comparable deterioration in the underlying business.
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Navitas Semiconductor just reported Q2 fiscal 2026 earnings, with shares initially down 1% following the report.
Guidance:
Q3 revenue: $13.5 million at the midpoint Sequential growth: Approximately 28% Year-over-year growth: Expected to return in Q3 Quick Read:
Navitas expects a sharp sequential acceleration next quarter, but the initial stock reaction suggests investors wanted a stronger outlook or more immediate evidence of its AI-power ramp.
Cash and equivalents surged to $557.4 million from $236.9 million at year-end, while the new 1.2-kilovolt JFET product line adds an estimated $1 billion opportunity across AI data centers and grid infrastructure.
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Wall Street models Q2 revenue near $9.97 million and non-GAAP EPS of -$0.0422, but the Q3 outlook will drive the reaction. Chris Allexandre has framed Q4 2025 as the revenue floor, with sequential growth through 2026.
Management’s pattern is conservative: Navitas (NASDAQ:NVTS) beat its own Q4 2025 guide of $7.0M ± $0.25M and its Q1 2026 guide of $8.0M-$8.5M.
Bullish Guidance: A Q3 guide above $11.5 million, gross margin cresting 40%, and a named AI data-center design win.
Bearish Guidance: A flat-to-down Q3 guide, contracting margins, or accelerated burn against the $221.0 million cash pile.
History warns even 15.97% beats can trigger day-one drops when guidance disappoints.
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Top 5 Analyst Questions When do in-rack GaN DC-DC proof points convert to volume orders? Path to breakeven, given a high-30s revenue threshold? GlobalFoundries 8-inch pivot in 2027 milestones? Customer concentration as mobile winds down? SiC Gen 5 traction after 50% power density claims? Key Topics, Buzzwords, Red Flags: Key Topics: Q3 revenue framing, cash burn versus $221 million, Delta/Flex/Vertiv design-in cadence, Wolfspeed litigation posture. Buzzwords to Listen For: “Kyber,” “18.5-kilowatt PSU,” “$10,000 to $15,000 per megawatt” content, “solid-state transformer,” “production-intent samples.” Red Flags: Widening opex above $15.5 million, gross margin below 38.5%, deferred NVIDIA ramp language, fresh capital raise hints beyond the $500M ATM, or softer high-power growth versus Q1’s 50% sequential AI infrastructure gain. 1 hour ago
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Navitas (NASDAQ:NVTS) reports Q2 2026 after tonight’s close. Management guided revenue to $10.0M ± $0.5M, over 16% sequential growth, with non-GAAP gross margin at 39.25% ± 75 bps and operating expenses of $14.5M to $15.5M. Q1 delivered a -$0.04 non-GAAP EPS beat.
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Analysts are focused on high-power revenue mix (up roughly 35% YoY last quarter), margin trajectory, and cash burn against the $221.008M balance. Commentary on NVIDIA‘s (NASDAQ:NVDA | NVDA Price Prediction) 800-volt architecture and the GlobalFoundries (NASDAQ:GFS) U.S. GaN ramp could matter more than tonight’s headline numbers.
Shares trade at $11.47, down 40.39% over the past month but up 52.94% YTD. The stock has risen a strong 4.72% intraday, suggesting investors are bullish heading into earnings. Polymarket’s beat odds have slipped from 75.5% to 54.5% this week. Full-chain put/call sits at 0.32.
Revenue above $10.5M with firm Q3 guidance could spark a rebound, while a result below $9.5M or margin slippage risks retesting July lows.
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Guidance Will Drive NVTS’s Q2 Reaction Wall Street expects a modest Q2 loss near -$0.04, with management having guided revenue to $10.0 million ± $0.5 million and non-GAAP gross margin of 39.25% ± 75 basis points.
CEO Chris Allexandre has guided conservatively, beating four consecutive quarters on EPS. Tonight’s guidance is likely going to determine the stock’s reaction to earnings.
Investors want a Q3 revenue outlook, margin trajectory toward 40%+, updated cash burn against the $221 million balance, and color on NVIDIA 800V ramps and GlobalFoundries U.S. GaN timing.
Bullish: a Q3 guide above $12 million, margin at 40%+, named AI design-win ramps, and reduced burn.
Bearish: a flat or sub-$10 million guide, softer margins, elevated opex, and a pushed-out breakeven timeline.
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With shares down 40.39% over the past month, both the Bull and Bear camps have sharpened their arguments ahead of tonight’s earnings.
Bull Case AI power tailwind: The NVIDIA MGX engagement and a $3.5 billion 2030 SAM growing 60%+ CAGR anchor the pivot. Momentum returning: High-power revenue grew roughly 35% year-over-year, with Q2 guided to over 16% sequential growth. Balance sheet: $221 million cash, no debt funds the transition. Crowd’s vote: Polymarket odds sit at 55% for a beat. Bear Case Scale mismatch: A $10.0 million revenue guide against a $2.66 billion market cap leaves little cushion. Legal overhang: Wolfspeed’s five-patent infringement suit clouds the AI narrative. Dilution: A $500M ATM offering weighs on supply. Timing: GaN 800V production is targeted for 2027. 2 hours ago
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Navitas Semiconductor enters Q2 earnings with investors looking to see whether the company’s shift toward high-power applications can outweigh the continued wind-down of its mobile business and preserve sequential growth.
Gross margin progress toward the 39.25% guide and cash burn against a $221.01 million balance will frame the runway debate. However, commentary surrounding NVIDIA’s 800-volt architecture and the timing of the U.S. gallium nitride ramp with GlobalFoundries could matter even more than the quarterly results.
Navitas trades at roughly 66 times sales without a near-term path to GAAP profitability. That valuation prices in execution, as well as the company’s long-term potential. A beat paired with firm design-win commentary would reinforce the AI-power thesis.
A guidance cut or margin miss could reignite doubts over whether the projected $3.5 billion addressable market by 2030 represents a credible opportunity or an aspirational target.
Navitas Semiconductor (NASDAQ:NVTS) reports Q2 2026 earnings tonight at 4:05 PM ET after the bell. The GaN and SiC power specialist enters the report with shares down 40.39% over the past month yet up 52.94% year to date.
The Backdrop: Beat, Selloff, Recovery Last quarter, Navitas beat consensus on non-GAAP EPS at -$0.04 vs -$0.05, its fourth consecutive EPS beat. Revenue of $8.60 million grew 18% sequentially yet fell 38.7% year over year as the company exits mobile and consumer.
High-power markets grew roughly 35% year over year, and non-GAAP gross margin ticked up 30 basis points to 39.0%. Shares fell 4.96% on the earnings day, then recovered 26.92% within a week. Cash slipped from $236.86M to $221.01M. CEO Chris Allexandre framed the quarter as “a return to top-line sequential growth” driven by GaN and high-voltage SiC.
Consensus Estimates Metric Q2 2026 Guide YoY Change FY 2025 Actual FY 2026 Trend Revenue $10.0M ± $0.5M -31% $45.92M Sequential growth Non-GAAP Gross Margin 39.25% ± 75 bps Expansion 38.5% Gradual expansion Non-GAAP EPS ~-$0.04 Improving -$0.20 Narrowing loss The setup implies 16% sequential growth at the midpoint with modest margin expansion. Little cushion exists given how much of the story rests on the high-power ramp.
What I’m Watching: Design Wins, Cash, and Cadence Tonight, I’ll be watching four things on the call. First, the high-power mix percentage. It crossed a majority of revenue for the first time in Q4 2025, and investors will be looking for the specific number this quarter.
Second, NVIDIA 800V DC traction. CEO Allexandre highlighted a 20 kW 800V-to-6V DC-DC power delivery board at NVIDIA GTC and a 250 kW solid-state transformer with EPFL at APEC. Named design wins and supplier-selection timing matter more than any single revenue figure.
Third, cash burn cadence. The operating loss was -$27.77M. The current cash balance funds the transition, but any drift above the $14.5M to $15.5M OpEx guide tightens the math.
Fourth, GlobalFoundries US GaN. Availability is guided to late 2026. Any pull-in or slip changes the 2027 volume-production story.
Tonight, Polymarket puts the probability of a beat at 54.5%.
Earnings History Quarter EPS Surprise 1-Day Move 7-Day Move 30-Day Move Q1 2026 +15.97% -5.34% +26.92% +46.76% Q4 2025 +3.85% -3.74% -6.68% -16.19% Q3 2025 0% -5.74% -12.81% -9.37% Q2 2025 +0.4% -6.2% +2.81% -17.28% On average, shares moved +2.56% seven days after earnings over the past year.
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Tech giant Alphabet (GOOG +2.33%) (GOOGL +2.13%) has been investing aggressively in artificial intelligence (AI) infrastructure, and the company's latest quarterly report makes it clear that it will keep pumping more money into this technology.
Alphabet released second-quarter results on July 22 and announced that it is raising its 2026 capex guidance to a range of $195 billion to $205 billion. The company had earlier projected $180 billion to $190 billion in capex for 2026. The updated guidance points to a significant increase over Alphabet's 2025 capex of $91.4 billion.
This is great news for Nvidia (NVDA -4.97%). Let's see why.
Image source: Nvidia.
Alphabet sees AI demand exceeding supply, suggesting that it will procure more Nvidia chips Alphabet's Google Cloud revenue surged 82% year over year to $24.8 billion. What's more, the company's cloud backlog stood at a whopping $514 billion in Q2. CEO Sundar Pichai noted that demand for its AI models is outpacing supply, prompting management to ramp up capex to quickly convert its massive backlog into revenue.
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When Nvidia announced its next-generation Vera Rubin chip platform in January this year, Pichai pointed out that Alphabet will "bring the impressive capabilities of the Rubin platform to our customers." Importantly, Nvidia has started the volume production of Vera Rubin processors, and it plans to begin shipping them to customers this fall.
With Alphabet poised to significantly raise its spending this year, and possibly in the future as well, due to the huge backlog that it is sitting on, it is likely to purchase more of Nvidia's AI chip systems. So, there is a solid chance of an improvement in Nvidia's growth rate.
The semiconductor giant reported an 85% year-over-year increase in revenue in the first quarter of fiscal 2027 (which ended April 26), along with a 140% increase in earnings per share. Its guidance of $91 billion in revenue for the current quarter points toward a stronger year-over-year increase of 95%. However, it could do better than that as hyperscalers such as Alphabet significantly raise their spending to fulfill their AI-related cloud backlogs.
Analysts expect a solid bounce in Nvidia stock Nvidia's 12-month median price target of $300, according to 64 analysts covering the stock, suggests a potential jump of 45% over the coming year. However, it could do better. After all, its earnings per share are projected to increase by 88% in the current fiscal year to $8.99, according to consensus estimates on Yahoo! Finance.
That's well above the 24% jump in the S&P 500 index's earnings. So, Nvidia should ideally trade at a significant premium to the index, which has a forward earnings multiple of 21.1. Assuming Nvidia trades at 40 times earnings at the end of the fiscal year due to its market-beating earnings growth, its stock price could reach $360.
That's a potential gain of 74% from current levels, which is why investors can consider buying Nvidia stock right away as the aggressive spending by the likes of Alphabet on AI infrastructure will create a solid tailwind for the AI chip specialist.
Bloomberg's Ed Ludlow speaks with Nvidia CEO Jensen Huang amid renewed concerns about the AI industry's circular financing deals. Plus, Apple aims to take on Meta in the smart glasses department.
Nvidia (NVDA) has formed a long-term partnership with Safe Superintelligence, the AI laboratory founded by former OpenAI co-founder Ilya Sutskever, while also m
Apple passed Nvidia on Monday for the title of world's most valuable company, with the iPhone maker topping the artificial intelligence chip firm at market close for the first time since April 2025.
Shares of Nvidia fell 5% on Monday, giving the chipmaker a valuation of $4.77 trillion, as AI chip stocks in general declined as investors fret about large costs related to the AI buildout.
Meanwhile, Apple shares rose 1%, giving it a market cap of $4.95 trillion, ahead of the company's highly-anticipated earnings on Thursday.
Nvidia had held the top spot as the most valuable company since June 2025, when it took the crown from Microsoft, and it briefly held a $5 trillion capitalization in October.
So far in 2026, Nvidia's shares have only climbed 4% while Apple's are up 24%. Apple has outperformed the market as investors have rewarded its reluctance to spend heavily on capital expenditures for AI, preferring to rent capacity instead of building its own.
While Nvidia's sales are now in the third year of massive AI-driven growth, many investors have switched their focus from AI chips called graphics processing units to memory chips and other data center infrastructure that benefit from the AI boom, such as Micron Technology, SK Hynix, and Sandisk.
Apple will report fiscal third-quarter earnings on Thursday, in which the iPhone maker is expected to reveal for the first time some of the financial impacts from the AI-driven global memory chip shortage, which forced the company to raise Mac and iPad prices in June.
Apple and Nvidia stock chart.
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If the past few years have taught investors anything, it's that you shouldn't bet against Nvidia (NVDA -4.59%). Still, Advanced Micro Devices (AMD -6.43%) is creating quite a buzz with a string of wins and advances that pose a direct challenge to the dominance of its rival Nvidia. Can AMD actually dethrone Nvidia as king of AI chips?
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There are a lot of good things happening with AMD. The company is reportedly finalizing a deal with Anthropic to supply 2 gigawatts of AI computing capacity. AMD may also take an equity stake in Anthropic worth up to $5 billion.
Microsoft's Azure has also committed to using AMD's new Helios rack-scale platform. This pairs well with AMD's existing partnerships with OpenAI and Meta Platforms. Lastly, the autonomous driving company Turing is migrating 10% of its AI training workloads from Nvidia to AMD.
Image source: The Motley Fool.
AMD's new accelerators could potentially exceed Nvidia's performance in certain workloads by the end of the year.
While AMD is closing the gap in many ways, it still has a tremendous way to go before overtaking Nvidia. Jensen Huang's company still controls upwards of 80% of the AI accelerator market, while AMD's revenue accounts for between 5% and 7%. AMD isn't anywhere close to catching Nvidia's data center revenue, either. Nvidia reported $75 billion in data center revenue in the last quarter alone.
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For investors, it's important to note that AMD doesn't need to "dethrone" Nvidia to see meaningful growth in both revenue and market share. It's estimated that the total addressable market for AI accelerators will top $200 billion in 2026. AMD is a well-run company that Nvidia won't be able to keep down. The market is large and lucrative enough for both of them to achieve substantial growth in revenue and per-share earnings over the next several years.
AMD's stock has risen nearly 158% year to date as of July 23. Nvidia, on the other hand, has declined significantly since reaching a 52-week high in mid-May. Nvidia stock is up only 12% year to date as of this writing.
Catie Hogan has no position in any of the stocks mentioned. The Motley Fool has positions in and recommends Advanced Micro Devices, Meta Platforms, Microsoft, and Nvidia. The Motley Fool has a disclosure policy.
