Nvidia odhaduje, že globální kapitálové výdaje na datová centra dosáhnou do roku 2030 3 až 4 biliony USD ročně. Firma z toho těží díky rostoucím investicím do AI infrastruktury.
Nvidia (NVDA 1.39%) is the world's largest company by market cap, and many investors are a bit worried that its stock may have reached a point where it can't grow fast for much longer. I think that's just not true, and expect that several tailwinds will push the stock to new heights over the next few years.
The biggest of those tailwinds is the tech sector's soaring spending on the data center build-out. If this trend keeps up as Nvidia projects, then it should be a great stock to own in the coming years.
Image source: Getty Images.
Nvidia isn't alone in its projections On multiple occasions, Nvidia has made the bold assertion that global data center capital expenditures will reach $3 trillion to $4 trillion annually by 2030. For reference, the big four AI hyperscalers plan to spend around $650 billion on capex this year. That total doesn't include companies like OpenAI, Anthropic, xAI, or anything in China. So, the figure for the data center sector as a whole is likely several hundred billion dollars more. Next year, Nvidia expects the hyperscalers to spend around $1 trillion. It likely already has many of the orders for the AI processors they want on hand, giving it a privileged degree of insight into the pace of the growth trend.
Additionally, suppliers like Taiwan Semiconductor Manufacturing have already told investors to expect major growth for several more years, which is why they are spending big on increasing their production capabilities this year. One of the AI hyperscalers, Alphabet, told investors during its Q1 conference call that they should expect "significantly" higher capital expenditures in 2027 than the $180 billion to $190 billion it plans to spend in 2026.
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There simply isn't enough AI computing power to meet demand, and with everyone in the AI industry convinced that more computing power will solve problems, spending will trend that way, benefiting Nvidia. But just how much can Nvidia's stock rise by 2030?
Nvidia has major upside potential For simplicity's sake, let's assume that 2026's total data center expenditures globally will total $900 billion. That means that spending will increase by about fourfold in 2030. But how much of that growth will Nvidia capture?
There are two trends, each pulling in a different direction. One that is pulling in Nvidia's favor is that data centers are being built all across the world. Right now, that includes a lot of land costs, permitting, infrastructure, and other things necessary to get a data center operational. However, a significant number of the chips that will eventually go into these facilities haven't been purchased yet. So, it's safe to assume that as we get closer to 2030, a larger slice of the capex pie will be devoted to chips.
On the flip side, many companies are starting to develop custom AI chips so that they don't have to rely so heavily on Nvidia's products. While the hyperscalers will never completely get away from Nvidia's powerful general-purpose GPUs, the application-specific integrated circuits they are designing can provide significant cost-performance benefits when deployed for the narrow AI workloads they are optimized to handle.
As a result, in the future, custom chips are likely to account for a growing percentage of the AI data center processors being sold. So Nvidia's market share will shrink.
NVDA Net Income (TTM) data by YCharts.
Overall, I expect these two countervailing trends to nearly cancel each other out. If that proves to be the case, Nvidia should be able to increase its revenue and earnings fourfold between now and 2030. If Nvidia's earnings quadruple and it trades at that time at 20 times earnings (a pretty cheap valuation), that would give the company a $12.8 trillion market cap. That would be a 172% gain from today's stock price to about $530 per share.
Normally, to beat the market, a stock would have to double in less than seven years. Based on these premises, Nvidia could do that easily, making it a no-brainer stock to buy.
Nvidia spouští program, v němž si rychle rostoucí AI startupy vymění přístup k výpočetnímu výkonu za podíl na budoucích tržbách. Mezi první partnery patří Sharon AI a Firmus Technologies.
Chipmaker Nvidia says it is entering revenue-sharing agreements with fast-growing start-ups, in a move which will see customers swap access to compute power for a slice of future profits.
The artificial intelligence chip leader says its new partnership program, announced Thursday, offers fast-growing AI startups token credits to power their development. Cloud-based AI firms, model builders and other enterprises will share both product and cloud revenue with Nvidia, which is positioning itself as an intermediary helping startups gain direct access to full-stack computing powered by Nvidia chips.
In its announcement, Nvidia named two initial partners who will provide the compute power behind the scheme. Australia-based Sharon AI will deploy up to 40,000 Nvidia GPUs, while Singapore AI infrastructure company Firmus Technologies says it is building a data center in Batam, Indonesia, which is expected to scale to 360 megawatts and house up to 170,000 Nvidia GPUs.
Nvidia's move illustrates the critical importance of access to scarce compute power for AI-oriented startups, with GPUs likened to oil and even reportedly tied to futures contracts as users grapple with fluctuations in cost and issues around availability. Meanwhile, AI firms have increasingly entered into revenue and equity-sharing sharing agreements with chipmakers in order to circumvent liquidity issues afflicting the sector.
OpenAI has inked a number of deals that have seen it buy shares or entertain investments from partners including Amazon and AMD, CNBC reported in January.
Nvidia earlier this month said it was aiming to raise debt which sources said could amount to at least $20 billion. The firm intends to use the proceeds from the offering for general corporate purposes, including repayment and refinancing of existing debt.
Nvidia sází na robotiku jako na další velkou příležitost a fyzická umělá inteligence jí už za posledních 12 měsíců přinesla přes 9 miliard USD tržeb. Nový Halos for Robotics má posílit její softwarovou a bezpečnostní vrstvu pro humanoidy.
HomeInvestingYour Digital SelfYour Digital SelfNear-term revenue belongs to the motion and sensor companies supplying the industry’s buildoutJuly 1, 2026, 12:13 p.m. ET
Nvidia CEO Jensen Huang has called humanoid robots a “multitrillion-dollar economic opportunity.” Photo: Getty Images/iStockphotoJensen Huang has taken to calling robotics and physical AI the next trillion-dollar opportunity for Nvidia NVDA, and the market takes the company’s CEO at his word. Nvidia’s physical-AI revenue has run past $9 billion over the trailing 12 months, up from $6 billion the year before, and analysts now treat robots as its second act.
Nvidia’s ambition is to do for robotics what its CUDA platform did for accelerated computing. Huang has called humanoid robots a “multitrillion-dollar economic opportunity.” Nvidia’s newly announced Halos for Robotics safety stack sharpens the point: The company is building the software, compute and safety layer around humanoids, not trying to own the entire machine. Nvidia wants the operating layer underneath — and if physical AI scales the way factory automation has, it will get it.
NVIDIA uvedla za 1. čtvrtletí FY2027 tržby 81,615 miliardy USD a upravený zisk na akcii (EPS) 1,87 USD, oba údaje nad odhady. Firma zároveň čeká ve 2. čtvrtletí tržby 91 miliard USD.
I bought NVIDIA again last Friday, and I plan to buy it again this week if the selloff holds. That makes five additions in eight weeks for me, and the case for the next one has only gotten stronger. NVIDIA (NASDAQ:NVDA | NVDA Price Prediction) is down 13% in June and 7.55% over the past month, sitting at $194.97 while the company is printing the strongest fundamentals it has ever produced. That gap is why my finger keeps finding the buy button.
The thesis is simple. I am buying the only company selling the picks and shovels for what Jensen Huang calls “the largest infrastructure expansion in human history.” The institutional rotation out of semiconductors leaves NVIDIA’s business intact while lowering the price I pay to own it.
The Numbers That Keep Me Adding Start with Q1 FY2027. Revenue came in at $81.615 billion, up 85.23% year over year, beating consensus by 3.16%. Non-GAAP EPS landed at $1.87 versus the $1.7738 estimate, the fourth consecutive earnings beat. Net income grew 210.63% YoY to $58.321 billion. Free cash flow hit $48.554 billion, up 85.41%. Non-GAAP gross margin held at 75.0%, versus 60.8% a year ago. Those are platform margins, and they are widening.
Growth is accelerating. Quarterly revenue growth moved from 55.6% to 62.5% to 73.2% to 85.2% across the last four quarters. Forward guidance calls for $91.0 billion in Q2 revenue, and that number assumes zero Data Center compute revenue from China.
Then there is the capital return. The board raised the quarterly dividend from $0.01 to $0.25 per share and approved an additional $80.0 billion buyback authorization on top of $38.5 billion still outstanding. NVIDIA returned roughly $20.0 billion to shareholders in Q1 alone. At a forward P/E of 22 with revenue compounding above 80%, that math works for me.
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The Moat I Cannot Find Anywhere Else NVIDIA has Meta committed to millions of Blackwell and Rubin GPUs, OpenAI signed up for at least 10 gigawatts of NVIDIA systems, Anthropic at 1 gigawatt, and CoreWeave building 5+ gigawatts of AI factories by 2030. Data Center networking revenue grew 199% YoY, proof that the full-stack platform is being adopted alongside the GPUs. The $119.0 billion in supply commitments tells me management sees demand years out.
The Risk I Refuse to Ignore China is gone from the Q2 outlook. Zero Data Center compute revenue assumed, against $4.6 billion in H20 shipments in the year-ago quarter. Insiders also sold heavily in June, including coordinated dispositions by CEO Jensen Huang, CFO Colette Kress, and three other executives at $207.41 on June 17. I sat with both facts. The China hole is real, and the company guided to $91 billion anyway. The insider sales follow pre-set 10b5-1 plans at prices above where I am buying today. The thesis holds.
Why the Buy Button Stays Active The five-year return on NVIDIA is 878.06%. The ten-year is 16,943.1%. Those are history. I am buying the cash flows underneath them at a forward multiple of 22, with a 25x dividend hike fresh in the account and an $80 billion buyback at my back. The rotation handed me a price. I intend to use every dollar of it.
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NVIDIA přeuspořádala vykazování na dvě platformy, Data Center a Edge Computing, aby lépe zachytila růst trhů s AI. Firma tím ukazuje širší základnu budoucích tržeb mimo tradiční cloud.
Key Takeaways NVDA now reports two platforms: Data Center and Edge Computing, aligning with expanding AI markets.ACIE highlights AI factory opportunities across industries and countries beyond traditional cloud providers.Edge Computing adds Gaming, AI PCs, robotics, automotive, AI-RAN and physical AI growth avenues. NVIDIA Corporation's (NVDA - Free Report) new business structure underscores expanding AI growth opportunities, supporting the case for stronger long-term revenue potential. The company has reorganized its reporting into two major platforms — Data Center and Edge Computing — to reflect its current and future growth drivers. Within the Data Center, NVIDIA now separately reports Hyperscale, and AI Clouds, Industrial & Enterprise (ACIE), giving investors greater visibility into fast-growing AI markets beyond traditional cloud providers.
The new reporting framework highlights how NVIDIA's revenue base is becoming increasingly diversified. While hyperscalers remain a major contributor, the company is seeing rising demand from AI cloud providers, enterprise customers, industrial AI deployments and sovereign AI initiatives. Management noted that ACIE captures opportunities in AI factories across industries and countries, reinforcing that future growth will come from a broader range of customers rather than a single market.
Beyond the Data Center, the revamped Edge Computing platform expands NVIDIA's addressable market. It includes Gaming, AI PCs, workstations, robotics, automotive, AI-RAN and other physical AI applications, creating additional growth avenues outside the data center. The company also highlighted strong demand across hyperscalers, model builders, AI cloud providers and enterprise customers, validating its decision to realign the business around these expanding AI ecosystems.
NVIDIA’s recent announcements further validate its new reporting framework. Continued investments in AI factories, agentic AI, robotics and physical AI demonstrate that the company is expanding into several high-growth AI markets. By aligning its reporting structure with these emerging opportunities, NVDA provides investors with greater visibility into future revenue drivers. Supporting this view, the Zacks Consensus Estimate projects fiscal 2027 revenues of $385.4 billion, representing a strong 78.5% increase year over year.
Can Rivals Match NVIDIA's New AI Growth Blueprint?As NVDA reshapes its business around the expansion of AI infrastructure and data centers, Advanced Micro Devices (AMD - Free Report) and Qualcomm (QCOM - Free Report) are evolving their operations to compete for the same long-term growth opportunities.
Advanced Micro Devices is NVIDIA's closest AI infrastructure rival, shifting its business toward Data Center and AI with EPYC CPUs, Instinct GPUs and hyperscaler partnerships. AMD leverages an open ecosystem, expanding AI software and rack-scale platforms to capture cloud demand. However, AMD still trails NVIDIA in CUDA ecosystem strength, AI software maturity and market leadership despite robust AI revenue momentum.
Qualcomm is expanding beyond smartphones by prioritizing edge AI, data-center CPUs, AI accelerators and custom silicon for hyperscalers. QCOM benefits from power-efficient AI, strong CPU expertise and diversified markets spanning automotive and IoT. However, QCOM lacks NVIDIA's scale in AI training infrastructure, software ecosystem and hyperscale deployments, leaving QCOM focused primarily on edge and inference AI.
NVDA’s Share Price Performance, Valuation & EstimatesNVIDIA shares have returned 4.5% in the past six-month period, underperforming the broader Zacks Computer and Technology sector’s 15.7% growth.
NVDA’s Six-Month Price Performance
Image Source: Zacks Investment Research
From a valuation standpoint, NVDA appears overvalued, trading at a forward price-to-sales ratio of 10.69, higher than the industry average of 9.96. The company carries a Value Score of D.
NVDA’s Valuation
Image Source: Zacks Investment Research
The Zacks Consensus Estimate for NVIDIA's fiscal 2027 and 2028 earnings per share is pegged at $8.69 and $11.67, respectively, reflecting robust year-over-year growth of 90.3% in fiscal 2027 and 34.2% in fiscal 2028. Notably, earnings estimates for both fiscal years have moved higher over the past 30 days, indicating improving analyst confidence.
Image Source: Zacks Investment Research
NVIDIA currently carries a Zacks Rank #3 (Hold). You can see the complete list of today’s Zacks #1 Rank (Strong Buy) stocks here.
Nvidia letos přidává jen asi 5 %, zatímco index PHLX Semiconductor Index roste o 94 %. Investoři sledují, zda nová platforma Vera Rubin obnoví její dominanci v AI infrastruktuře.
Nvidia NVDA stock rose on Tuesday. Shares of Nvidia were up 1.5% at $197.96 in early trading.
Despite the gain, Nvidia has significantly underperformed the broader semiconductor sector.
The stock is up roughly 5% year to date, compared with a 94% gain for the PHLX Semiconductor Index.
The muted performance marks a sharp contrast to Nvidia's dominant run over the past several years and would represent the stock's weakest first-half showing since 2022.
Investor attention is increasingly focused on whether Nvidia's upcoming Vera Rubin platform can restore the company's position as the undisputed leader in AI infrastructure.
The central challenge facing Nvidia is no longer limited to competition from rival graphics processor makers.
While Advanced Micro Devices remains a key competitor, the market has expanded to include custom chip developers and companies focused on central processing units, including Intel.
As artificial intelligence spending accelerates, major technology companies are increasingly distributing infrastructure budgets across a wider range of suppliers rather than concentrating purchases with a single vendor.
The key question for investors is whether Nvidia's next-generation hardware can establish a sufficiently large performance advantage to justify continued dominance in AI deployments.
Nvidia's relative underperformance has become one of the more notable developments in the semiconductor sector this year.
After several years of outsized gains, many investors appear to have taken profits and rotated into other areas of the AI supply chain, including memory chipmakers and emerging AI infrastructure companies.
Intel shares have climbed approximately 250% this year, while Advanced Micro Devices has gained about 152%.
The iShares Semiconductor ETF has advanced roughly 102% over the same period.
The shift suggests investors increasingly believe much of Nvidia's expected growth has already been reflected in the stock price, even as demand for advanced AI hardware remains strong.
Sentiment has also been weighed down by concerns over export restrictions affecting sales to China and broader questions about how long Nvidia can sustain the extraordinary growth rates it has delivered in recent years.
At the same time, Nvidia is expanding its focus beyond traditional AI infrastructure and into robotics and physical AI.
The company is ramping up hiring for its robotics operations in China, advertising more than a dozen positions across Beijing, Shanghai, and Shenzhen, according to a recruitment post published on its official WeChat account.
The openings cover embodied intelligence, simulation, implementation, and solutions.
Nvidia said the robotics team aims to build a "leading robotics platform and ecosystem to help developers and companies create autonomous machines," with the goal of accelerating the deployment of robots from research environments into real-world applications.
The recruitment drive highlights Nvidia's growing emphasis on physical AI, which combines artificial intelligence models with robotics systems that can perceive, reason, and interact with the physical world.
According to the job descriptions, employees will work on technologies including the Project GR00T humanoid robot foundation model, the Cosmos physical simulation world model, and Nvidia's GPU-accelerated computing platforms.
Nvidia oznámila tržby za 1. čtvrtletí fiskálního roku ve výši 81,6 miliardy USD, meziročně o 85 % více, a čistý zisk vzrostl o 211 % na 58,3 miliardy USD. Firma zároveň schválila další zpětný odkup akcií za 80 miliard USD nad rámec zbývajících 38,5 miliardy USD z předchozího programu.
Over the last five years, Nvidia (NVDA +1.30%) has been the quintessential millionaire-maker stock -- returning roughly 950% compared to the S&P 500's relatively modest gain of 74%. The company's powerful graphics processing units (GPUs) are the workhorses of the generative artificial intelligence (AI) industry. And its advantages in scale and technology have helped it stay ahead of the competition.
That said, Nvidia's stock price growth is beginning to stall as investors balk at its huge size and pivot to other sides of the AI infrastructure opportunity. Let's dig deeper to see if the company has what it takes to break out of its slump and continue generating market-beating returns.
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Business is still booming The generative AI megatrend shows no signs of slowing anytime soon. In fact, it may be heating up. Analysts at Evercore and Bank of America expect big tech's AI-related capital spending to exceed $1 trillion in 2027 -- up from around $800 billion to $900 billion this year. Most of this money is going to advanced hardware needed to run massive data centers.
Nvidia's chips remain highly relevant, which is reflected in the company's first-quarter earnings results. Revenue jumped 85% year over year to $81.6 billion, which is an incredible number for a business that is already so large. And as in previous quarters, overall growth was driven by growth in the company's data center segment, which recently announced exciting new offerings such as the Vera Rubin Platform, designed to facilitate the rise of agentic AI by removing processing bottlenecks.
Many industry watchers believe agentic AI represents the next phase of the technology. Unlike earlier AI systems, it is designed to independently plan and make decisions with limited human oversight, making it ideal for helping automate a variety of industries. And if the technology takes off as expected, it could help Nvidia maintain its elevated growth rate.
Management is returning value to shareholders Nvidia's success isn't limited to its top line. The company's technological edge gives it strong pricing power and operating leverage. Net income soared 211% year over year to $58.3 billion, and management is getting increasingly serious about returning much of it directly to shareholders.
As of May, Nvidia has increased its cash dividend from just $0.01 per share to $0.25 per share (a yield of around 0.5%). More importantly, management authorized an additional $80 billion in stock repurchases on top of the $38.5 billion remaining from its previous program.
Image source: Getty Images.
Investors tend to love buybacks because they reduce the number of a company's shares outstanding, giving every investor a higher claim on the company's future earnings and cash flow. They tend to encourage stock price growth and, unlike dividends, they aren't taxed as regular income, which can make a tremendous difference over the long term.
Nvidia's huge push toward buybacks marks a sharp divergence from other technology giants like Amazon, Microsoft, and Micron Technology, which are instead plowing cash back into AI-related capital expenditures like data centers or expanded production capacity. Nvidia's strategy is arguably less risky because it relies on internally generated cash instead of debt or dilution like some of the alternatives in the tech industry.
With a market cap of $4.72 trillion, Nvidia isn't a millionaire-maker stock anymore because, even in the best-case scenario, rapid multibagger growth seems unrealistic from such a high level. The company's sky-high margins will also eventually come down as customers substitute in-house solutions for Nvidia products and rivals catch up technologically.
That said, with a forward price-to-earnings (P/E) multiple of just 22.7, most of these challenges are already priced into Nvidia's valuation. And management's aggressive buyback policy will benefit shareholders over the long haul. Investors should view Nvidia stock as a value-oriented pick in the AI industry instead of a big growth opportunity.
Nvidia rozšiřuje tým pro Space-1, svůj první výpočetní systém pro vesmír. Nová role má pomoci vytvořit software pro orbitální datová centra a provoz na nízké oběžné dráze.
Nvidia CEO Jensen Huang. Bloomberg/Getty Images Nvidia's AI ambitions are officially out of this world this year, and they haven't come back down to Earth.
The AI chip giant is adding to the team behind Space-1, its first computing system designed for space. In recent weeks, the chip giant posted a second job tied to orbital data centers.
The role — for a system software principal architect — will help build software for Space-1, which the chip giant unveiled at its GTC event in March.
Space data centers have emerged as a potential way to get around growing constraints on land, power, and cooling on Earth. Companies like SpaceX are racing to make the idea a reality, while skeptics argue the costs still outweigh the benefits.
During a recent earnings call, Nvidia CEO Jensen Huang said the economics around space computing are poor today but will improve over time.
The principal architect job post follows another role shared earlier this year for an orbital data center system architect. While that position focuses on designing the overall system — from computing hardware to satellites to connectivity systems — the new post focuses on making Space-1's software work in practice.
The person hired will design the software that runs the system so it can withstand radiation and extreme temperature swings and be managed remotely.
Space-1 harnesses Nvidia's latest Vera Rubin AI chip platform and is designed for low-Earth orbit missions.
The system software role requires previous experience building AI infrastructure and systems in space. It offers a base salary of $272,000 to $431,250, which doesn't include Nvidia's coveted equity awards.
While the technology is still in its early stages, Nvidia's latest job postings suggest the chipmaker is moving from conceptual planning to building the systems needed to make it work.
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Geoff Weiss is a senior reporter on Business Insider’s tech team, where he writes about AI startups and Y Combinator, the intersection of AI and the media industry, and workplace dynamics within top AI labs and chip companies.Previously, Geoff was on the media desk, covering YouTube and Netflix, and themes like the intersection of Hollywood and the creator economy. His work on Netflix’s video podcasting ambitions and Mr Beast’s lessons for Hollywood won second and first prize, respectively, at the 2025 LA Press Club Awards.Prior to joining Business Insider, Geoff was the senior editor of Tubefilter and a staff writer at Entrepreneur. He graduated from New York University with a degree in English Literature.He can be reached at [email protected], on Signal @geoffweiss.25, and on LinkedIn. Have a tip? Use a personal email address and a nonwork device; here's our guide to sharing information securely.Selected stories:Nvidia crushed its quarter — and CEO Jensen Huang said in a leaked all-hands that 'the market did not appreciate it'Nvidia will foot the bill for Trump's new visa fees. Here's what CEO Jensen Huang told staff.Massive AI salaries and RTO are fueling a real estate boom in San Francisco: 'It's going to rain money'The AI talent wars are ricocheting across startups. Here's how they're competing with Big Tech.
Firmus Technologies uzavřela strategické partnerství s Nvidií, aby menším AI firmám levněji zpřístupnila výpočetní výkon. Dohoda zahrnuje 170 000 GPU od 1. čtvrtletí 2027 a očekávané tržby až 30 miliard USD za prvních šest let.
The NVIDIA logo in this illustration taken June 11, 2026. REUTERS/Dado Ruvic/Illustration/File Photo Purchase Licensing Rights, opens new tab
SYDNEY, June 29 (Reuters) - Australian AI infrastructure company Firmus Technologies said on Monday it had signed a strategic partnership with Nvidia Corp (NVDA.O), opens new tab to help provide emerging AI firms with more cost-effective access to computing power.
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Firmus said the deal would see it buy Nvidia infrastructure and sell Nvidia‑powered cloud services to "AI Native" customers, among others, in an agreement that would earn the U.S.-listed chip giant product revenue and a share of cloud revenue.
The deal will deliver 170,000 Graphics Processing Units (GPU) from the first quarter of 2027 to the start of 2028, that will be located in Batam, Indonesia.
Firmus said it expected to earn up to $30 billion in revenue during the first six years of the deal, based on customer commitments.
The Australian-founded company said the deal would make it easier for smaller and developing AI firms to access the technology's infrastructure.
"We have worked to figure out how to close the gap between the cost benefits that the large guys have access to, which they do because they have great credit ratings, and the guys that are up and comers," Firmus co-chief executive Tim Rosenfield told Reuters. "This is actually a really material way to level the playing field a little bit to give the next a chance to compete with the big guys."
Nvidia has participated in Firmus' previous capital raisings making it an investor in the Australian firm, according to Firmus.
Firmus said in April it had raised $1.35 billion over the previous six months, giving it a $5.5 billion post-money valuation. It has appointed investment banks to work on a potential initial public offering, according to people familiar with the matter.
Rosenfield declined to comment on Firmus' IPO preparations.
Reporting by Scott Murdoch; Editing by Kate Mayberry
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Scott Murdoch has been a journalist for more than two decades working for Thomson Reuters and News Corp in Australia. He has specialised in financial journalism for most of his career and covers the Australian financial services sector and superannuation. He is based in Sydney.
Nvidia čelí riziku, že zpomalení kapitálových výdajů velkých technologických firem omezí objednávky čipů. Klíčovým varováním je blížící se vlna odpisů, která může stlačit jejich zisky. Velké technologické firmy jako Meta, Alphabet, Amazon, Microsoft a Oracle loni dohromady utratily 412 miliard dolarů.
The beating heart of the artificial intelligence (AI) boom is, without a doubt, Nvidia (NVDA 1.42%). The chipmaker's graphics processing units (GPUs) -- the specialized chips that do the heavy math behind AI -- power the data centers that train and run ChatGPT, Claude, and the vast majority of AI models.
It's no surprise, then, that Nvidia has managed a multiyear win streak nearly unmatched in the modern era. In its fiscal 2022, the company booked $26.9 billion in revenue. Over the last 12 months, it booked nearly 10 times that -- $253.5 billion.
The stock has followed suit, up more than 600% since January 2022.
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That kind of run can make an investor nervous. As unstoppable as Nvidia looks, there are real risks here, and most of them have been talked to death -- customer concentration, fierce competition, the physical limits of the AI build-out. But the one I think matters most still flies under the radar.
Nvidia's fortunes depend on big tech's spending spree The AI boom is being fueled, in large part, by the capital expenditures (capex) -- the money a company sinks into long-term assets like buildings and equipment -- of just a handful of firms. Big tech names like Meta, Alphabet, Amazon, Microsoft, and Oracle are spending on a scale we've never seen. Last year alone, these five shelled out a combined $412 billion -- well over twice the total just two years prior.
That capex is the lifeblood of the AI economy. It flows to the construction firms building the data centers, the neoclouds operating them, and, most critically, to chipmakers like Nvidia.
So if that spending slows, Nvidia is in trouble. That much is obvious. What's not obvious is why it might.
Why big tech's profits look better than they really are Investors have stomached the enormous spending these past few years for one simple reason: They've watched big tech's earnings grow right alongside it. You see earnings per share (EPS) -- a company's profit divided across its shares -- jump 100%, and you stop worrying about the bill. Why fret about spending when profits are exploding?
Here's the thing: There's a lag in the system, and that profit growth could soon look a lot smaller than it does today.
When Meta spends $50 billion on Nvidia chips, that doesn't hit the books as an expense all at once. It counts as capex, and Meta can spread the cost over time. Say, $10 billion a year for five years.
That's depreciation: spreading the cost of a big purchase across the years a company expects to use it. There's nothing shady about it. It's the same thing every business with trucks or factories has always done.
What's different is the scale and the timing. A company often doesn't start the depreciation clock until the equipment actually goes into service -- and given how long it takes to build an AI data center, that can be a long wait.
Image source: Nvidia.
The depreciation wall is coming We're in a stretch where revenue is climbing while the true cost of all those chips hasn't fully shown up in earnings yet -- a "golden window where everybody looks good," as one Morgan Stanley analyst put it. That period won't last. A wall of depreciation is coming, and when it lands, it could drag down big tech's reported earnings.
And that's when investors may start to care about the spending. Faced with shrinking earnings, the Metas and Amazons of the world could trim those massive capex plans. Fewer dollars spent means fewer chips ordered, and fewer chips is bad news for anyone holding Nvidia.
Nvidia's stock could fall before its sales do Now, bulls will tell you Nvidia's order book is booked solid -- CEO Jensen Huang says he expects a $1 trillion backlog by the end of the year -- so there's not a real risk to Nvidia's sales coming any time soon.
I don't discount that, but stock prices are based on where investors think things are headed. Which means that Nvidia shares can take a hit well before Nvidia's actual order book does. All that's required is for investors to believe big tech is likely to scale back in the coming years.
What investors should watch for The real questions are when this happens and how big the hit will be -- and, I'll be honest, no one knows. You can see the uncertainty in Wall Street's own forecasts. Analysts' revenue targets for big tech over the next few years are fairly tight. Their depreciation estimates are all over the map.
None of this makes Nvidia a bad company -- it's a great one, selling every chip it can make. But Nvidia relies on capex spending continuing to expand. That could slow once investors start to see the true cost of that spending show up in income statements. For my money, the depreciation wall is a big reason I'd think twice before buying Nvidia shares today.
NVIDIA má objednávky na dodávky za 145 miliard USD, které mají zajistit výrobu čipů pro další čtvrtletí i rok 2027. Firma tím podporuje výhled na 1 bilion USD tržeb z Blackwell a Rubin do roku 2027.
A woman takes a picture at the NVIDIA booth during the China International Supply Chain Expo (CISCE) in Beijing on June 25, 2026. (Photo by Pedro PARDO / AFP via Getty Images)
AFP via Getty Images
This article was written by Doug Nathman, with research by his team at Trefis.
While investors concentrate on NVIDIA's staggering growth rate, an even more revealing figure resides in its supply commitments, illustrating a calculated strategy to satisfy demand that skeptics argue may not be viable.
Following a remarkable ascent, NVIDIA (NVDA) shares have cooled. The stock price has dipped below recent peaks, and discussions have transitioned from celebration to doubt. Is it possible for any corporation, even one at the forefront of the AI surge, to sustain this growth rate? While many analysts are examining the latest earnings figures or its trailing multiple, a crucial piece of information for an optimistic perspective is not found on the income statement at all.
The figure is $145 billion. This amount signifies NVIDIA’s overall supply, comprising existing inventory and, more critically, its future purchase commitments.
What Does $145 Billion In Commitments Represent?This amount signifies much more than merely a stockpile of chips stored away; it embodies a substantial, strategic commitment to future production. These pledges secure the necessary manufacturing capacity and raw materials required to create its upcoming generation of processors. Management has affirmed that this is a calculated initiative, reflecting the enhanced demand visibility we possess and a choice to secure capacity farther in advance than is normally standard. In a sector where a single shortage of components can disrupt production, NVIDIA is investing now to ensure it can manufacture the products it anticipates selling over the next several quarters, and even extending into the year 2027.
How This Assures Future RevenueThe underlying principle is straightforward: one cannot sell what cannot be produced. The primary physical limitation on NVIDIA's expansion is not demand, but rather the intricate supply chain necessary for its AI accelerators. By securing $145 billion worth of supply, the company is establishing the groundwork for its forecasts. This strategy is proactive, acting as the concrete basis for management's proclaimed confidence in achieving $1 trillion in Blackwell and Rubin revenue through 2027. That projection appears abstract until one observes the nine-figure commitments being undertaken to ensure the components needed for chip production.
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The Resolution To The Major Concern?The foremost risk looming over the stock is its sustainability. The stock is currently facing pressure precisely because the market is questioning the duration of this level of growth. The company’s price-to-earnings multiple of 30.3, although high in relative terms, lies toward the lower end of its own 10-year spectrum of 19.6 to 143.1, indicating that investors are reluctant to factor in future growth at a rate comparable to the past. These purchase commitments represent a direct and significant response to that apprehension. A corporation that fears an approaching cyclical peak would not engage in long-term supply agreements of this magnitude. This indicates that management perceives a demand trajectory that justifies the undertaking of risk to secure capacity well in advance.
Of course, a commitment does not equate to a sale. The ultimate benchmark is converting that secured supply into revenue. However, for investors attempting to evaluate the resilience of NVIDIA’s market position, this $145 billion figure offers a concrete, forward-looking metric that the headline growth rates do not convey.
Typically, one figure does not drive a decision independently, but recognizing which number is crucial and the rationale behind it constitutes a significant portion of the challenge. Arriving at the aforementioned figure required looking beyond the surface level of fear to what was genuinely occurring beneath—an analysis that is difficult to perform once and exceedingly challenging to replicate consistently.
The Trefis High Quality (HQ) Portfolio is constructed on executing precisely that, continuously, across 30 quality enterprises, and then maintaining them with rule-based discipline so that no single entity dominates your outcome. You acquire a selection of well-researched advantages rather than a sole all-or-nothing gamble, with a proven record of surpassing a benchmark that aggregates the three major indices – the S&P 500, S&P Mid-cap, and Russell 2000. If a figure like this one merits action, that form of disciplined quality deserves serious consideration.
Nvidia vykázala tržby 81,61 miliardy USD za Q1 FY27 a těží z CUDA. Cerebras sice nabízí až 21násobně rychlejší inference, ale pro celý rok čeká provozní marže v rozmezí -28 % až -32 %.
NVIDIA (NASDAQ: NVDA | NVDA Price Prediction) and Cerebras Systems (NASDAQ: CBRS) just delivered earnings that frame the same question from opposite ends. Nvidia posted another blowout quarter built on its CUDA software stack. Cerebras, fresh off its May IPO, showed jaw-dropping inference speed yet guided full-year operating margins negative. The moat is developer gravity.
One Sells Platforms. The Other Sells Speed. Nvidia’s Q1 FY27 hit $81.61 billion in revenue, up 85.2% YoY, with Data Center alone reaching $75.25 billion on 92% growth. Networking soared 199% as InfiniBand, NVLink and Spectrum-X locked customers deeper into the stack. Jensen Huang told investors NVIDIA is “the only platform that runs in every cloud, powers every frontier and open source model, and scales everywhere AI is produced”, and the numbers back the claim.
Cerebras’ first report as a public company landed differently. Q1 GAAP revenue reached $193.4 million, up 94% YoY, with cloud services growing 178%. A multi-year, $20 billion-plus OpenAI inference deal covering 750 megawatts anchors near-term growth. Yet management guided full-year operating margins to negative 28% to negative 32%. Speed sells. Scaling it economically is harder.
Software Gravity Beats Wafer-Scale Throughput Independent benchmarks show Cerebras’ wafer-scale design delivering a 21x speed advantage over Nvidia hardware for latency-sensitive, low-batch inference. The catch is that every major LLM framework and enterprise developer stack is natively optimized for Nvidia architecture out of the box, while Cerebras requires specialized compilation and custom engineering support for anything off the well-trodden path.
Lens NVIDIA Cerebras Core Bet CUDA full-stack platform Wafer-scale inference speed Q1 Gross Margin 75.0% non-GAAP 44.6% GAAP Anchor Customers Meta, OpenAI, Anthropic, Google OpenAI, AWS, G42 Biggest Vulnerability OpenAI’s Jalapeño custom chip Negative operating margins Nvidia’s $119 billion in supply commitments and $80 billion added to its buyback authorization signal management is doubling down on the platform. Cerebras raised $5.6 billion at IPO and is funneling it into data center capacity for OpenAI’s decode workloads while AWS Trainium 3 handles prefill. That is a focused inference bet riding on one customer’s roadmap.
The Next Test Is Whether Developers Defect Two catalysts matter into the back half of 2026. For Nvidia, the OpenAI Jalapeño chip, built with Broadcom, is the most credible threat to CUDA stickiness. NVDA shares are already down 8.79% over the past month, even with the stock up 27.01% YoY. For Cerebras, the bar is executing the OpenAI ramp without further margin slippage. Q2 core gross margin guidance of 36% to 38% telegraphs how steep the infrastructure build will be.
Why The Setup Still Favors Nvidia For AI infrastructure exposure with a self-funding moat, Nvidia remains the cleaner expression of the thesis. The 75% gross margin, $48.55 billion in quarterly free cash flow, and the developer install base are tough to dislodge in a single product cycle. Cerebras has the faster chip and a marquee anchor customer. A forward P/E of 23 on NVDA already prices in some software erosion. If CUDA defections spread beyond OpenAI, my view changes.
Nvidia má forwardové P/E jen 21,5 a její ukazatel P/E klesl na 30,09, nejníže od roku 2019. Firma zároveň chystá systém Vera Rubin, který má snížit náklady na inference až o 90 %.
Nvidia (NVDA 1.86%) had a market capitalization of $360 billion at the beginning of 2023, which was right before the artificial intelligence (AI) boom started gathering momentum. The company has since sold millions of its graphics processing units (GPUs) for data centers, which are the primary chips used in AI training and inference workloads, propelling its market cap to $4.8 trillion.
But despite a 13-fold increase in value over the last three years, Nvidia stock is still cheap by one of Wall Street's most widely used valuation metrics. In fact, here's why the stock could more than double from here.
Image source: Nvidia.
Nvidia is about to launch its most powerful chips yet Nvidia's dominance in the market for AI data center chips started in 2022 with its H100 GPU, which was built on its Hopper architecture. The company has since launched Blackwell and Blackwell Ultra GPUs, the latter of which can deliver up to 50 times more performance than the H100 in certain configurations.
Blackwell Ultra GPUs are currently the most sought-after AI chips in the industry, but Nvidia is about to extend its advantage with its new Vera Rubin system, which will ship in the second half of this year. It includes the Rubin GPU, the Vera central processing unit (CPU), and a series of updated networking components. Nvidia says the platform is so powerful that developers can train AI models using 75% fewer GPUs compared to Blackwell.
Vera Rubin can also reduce inference token costs by up to 90% (inference tokens include the text, images, and symbols generated by an AI model in response to a query). In other words, Nvidia's new system will make AI substantially cheaper to use, which could make providers like OpenAI and Anthropic more profitable, driving more demand for chips as a result.
During a conference call with investors on May 20, Nvidia CEO Jensen Huang said every frontier AI company intends to adopt Vera Rubin at launch, which wasn't true for the Blackwell platform. Therefore, he expects it to be far more successful than its predecessor.
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Nvidia's revenue and earnings continue to soar Nvidia generated $215.9 billion in total revenue during its fiscal year 2026 (ended Jan. 26), which was up 65% from the prior year. Its data center business accounted for $193.7 billion of that revenue, and it grew by 68%.
Both of those growth rates accelerated in the first quarter of fiscal 2027 (ended April 26). The company generated $81.6 billion in total revenue and $75.2 billion in data center revenue, which represented year-over-year increases of 85% and 92%, respectively, highlighting the sheer momentum in AI-related hardware sales.
Since demand currently exceeds supply for GPUs, Nvidia is able to dictate prices, which is significantly boosting its profit margins. As a result, Wall Street expects the company's generally accepted accounting principles (GAAP) earnings to soar by 91% to $9.36 per share during fiscal 2027 (according to Yahoo! Finance), which could have very positive implications for its stock price.
The price-to-earnings (P/E) ratio is one of the most widely used valuation metrics on Wall Street. If a stock has a P/E ratio of 10, investors are effectively paying $10 for every $1 of the company's earnings. Faster-growing companies tend to attract higher P/E ratios; investors are willing to pay more for their earnings because those companies will, in theory, earn their money back more quickly.
That's why the Nasdaq-100 index, which is full of high-growth technology companies, trades at a P/E ratio of 34.4, whereas the more diversified S&P 500 trades at a P/E ratio of 25.2.
Nvidia's P/E ratio recently fell to 30.09, which was the lowest level since 2019. Moreover, it was a substantial discount to its average P/E of 71.2 over that seven-year period.
NVDA PE Ratio data by YCharts
In other words, Nvidia stock would have to more than double just to trade in line with its long-term average P/E ratio. I'm not suggesting that will happen immediately, but based on the company's projected earnings for fiscal 2027 (which I highlighted earlier), its stock trades at a forward P/E ratio of just 21.5. That means even if its stock doubles over the next six or seven months, its P/E would rise to just 43, which would still be far below its long-term average.
No matter which way you slice it, Nvidia stock looks extremely cheap right now, especially ahead of what could be the biggest product launch in its history. As a result, it could be a great buy right now.
Nvidia chce, aby banky odhalovaly podvodné sítě napříč účty, zařízeními a transakcemi, ne jen podezřelé platby. Její AI blueprint má fungovat v reálném čase během platebního toku.
Banks have spent decades building fraud systems that see one transaction at a time. A charge either looks suspicious or it doesn’t. Fraud rings built their business model around that gap, spreading activity across thousands of payments using stolen cards, mule accounts, shared devices and synthetic identities so no single transaction trips a filter.
The Nilson Report projects that global card fraud losses will reach $403 billion over the next decade, with the U.S. accounting for roughly 42% of those losses despite representing just 26% of total card volume worldwide, according to a press release.
Nvidia’s AI blueprint for financial fraud detection is built around a different idea. Rather than asking whether a single transaction looks suspicious, the system asks whether the people, devices and accounts involved in a transaction are connected to suspicious activity elsewhere. A $47 purchase at a gas station may look completely normal on its own. It looks different if the phone used to approve it also shows up in 60 other disputed charges across three states that week. Or the same card was opened using an address tied to a known mule account.
That is the blind spot fraud rings count on. PYMNTS Intelligence found that unauthorized-party fraud — driven by credential theft and account takeovers — now makes up 71% of all fraud incidents and dollar losses at U.S. financial institutions, up from 48% in 2024. Organized rings move fast precisely because they know the window before detection closes.
Why Transaction-Level Scoring Fails Against Organized Rings Most bank fraud systems today use a technique called gradient-boosted modeling, a scoring engine that looks at a transaction’s characteristics and decides whether it resembles past fraud. Did the purchase happen in an unusual location? Was the amount out of range for this customer? Did the card get used twice in five minutes in different cities? Those are useful signals for catching individual bad actors.
They are much less useful against a coordinated ring. A ring using 500 stolen card numbers can keep each card’s activity well within normal-looking ranges, making individual transactions appear routine. The Nilson Report found that card-not-present transactions represent the highest-risk category in every world region, precisely because they are easiest to execute at scale with stolen credentials, according to the release.
Nvidia’s blueprint addresses that gap by adding a layer that maps relationships across the data. The technique, graph neural networks, works by building a picture of how transactions, accounts and devices connect to each other, then looking for clusters that share suspicious links. It feeds those relationship signals into the existing scoring model as additional context, so a transaction that scores low on its own can still be flagged if it sits inside a connected cluster of high-risk activity.
PYMNTS reported that Block Chief Risk Officer Brian Boates has pushed banks to move away from reviewing fraud after the fact toward stopping it in the moment. “It’s one thing to find the bad actors after the fact,” Boates said. “But what’s much more effective is investing in more real-time technology.” PYMNTS Intelligence found that 68% of financial institutions have increased fraud detection spending year over year as the problem outpaces older systems.
Real-Time Decisions Inside Live Payment Flows The challenge with relationship-based analysis is speed. Mapping connections across millions of accounts and transactions takes significant computing power. Doing it fast enough to stop a payment before it clears, typically within a few hundred milliseconds, requires infrastructure most banks have not yet built.
The Nilson Report noted that worldwide card fraud losses totaled $33.41 billion in 2024, and that AI tools have helped the industry build its best fraud-fighting models to date, even as organized crime continues to adapt.
Nvidia’s blueprint uses its Dynamo-Triton inference server to run those relationship checks at payment speed. The system produces a fraud score for each transaction alongside an explanation of which signals drove it, so a fraud investigator can see not just that a transaction was flagged, but that it was flagged because the device matched three others in an active dispute cluster, or because the billing address had been used to open four accounts in the past week. The blueprint runs on Amazon Web Services and Hewlett Packard Enterprise, with Dell Technologies support planned, Nvidia said.
For all PYMNTS AI coverage, subscribe to the daily AI Newsletter.
Nvidia letos zaostává, ale byznys dál prudce roste: tržby v 1. čtvrtletí vzrostly o 85 % na 81,6 miliardy USD a upravený čistý zisk o 139 % na 45,5 miliardy USD.
For much of the AI boom, Nvidia (NVDA 1.86%) has been the stock market darling.
The stock started soaring shortly after the release of ChatGPT in Nov. 2022 as it was primed to benefit from demand for its GPUs, which are used for AI training.
Since then, the stock has gained more than 1,000%, and Nvidia has become the most valuable company in the world, with a market cap of nearly $5 trillion.
However, in 2026, chip stock investors seemed to have moved on from the industry leader, piling into the new chip sector bottlenecks, including memory chip stocks like Micron and Sandisk, which are experiencing a shortage, and CPU stocks like Intel, AMD, and Arm Holdings, which are expected to benefit from increasing demand for AI inference.
As a result, Nvidia's performance has been downright pedestrian this year. At nearly the halfway point of 2026, Nvidia stock is up just 4%, compared to an 8% gain in the S&P 500, and a 9% increase in the Nasdaq Composite. The iShares Semiconductor ETF, which tracks the sector, has more than doubled this year due to breakout gains from Intel, Micron, and other stocks, rather than Nvidia.
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While Nvidia stock is slumping, down 17% from its peak in May, the business performance remains excellent. Revenue jumped 85% in the first quarter to $81.6 billion, and adjusted net income rose 139% $45.5 billion. Nvidia's net income is on track to top $200 billion this year, easily making it the most profitable company in the world. To put that number into perspective, only a few dozen companies make that much in annual revenue. $200 billion is similar to the GDP of countries like Ukraine and Qatar.
Based on its trailing adjusted earnings per share of $5.84, the stock now has a price-to-earnings ratio of 33, which is modestly more expensive than the S&P 500, at 26.
Image source: Nvidia.
Where Nvidia starts to look like a bargain The trailing valuation isn't the best way to look at Nvidia. After all, this is a company that just grew revenue by 85% and more than doubled its net income. You have to factor in its growth and its direction.
Below is the consensus EPS forecast for Nvidia for the next three years.
Fiscal year endingEPS consensusJan. 2027$8.69Jan. 2028$11.67Jan. 2029$15.76 Source: Nasdaq.com
Nvidia reported $4.77 in adjusted EPS last year, so analysts expect EPS to nearly double this year and to more than triple over the next three years.
Based on fiscal 2029 estimates, the stock looks ridiculously cheap, trading at just 12 times expected earnings. That's a valuation normally reserved for no-growth or slow-growth stocks in sleepy industries like banking and manufacturing.
Nvidia, on the other hand, has been one of the most disruptive companies of the decade and is still growing like wildfire.
Is Wall Street right? It's worth remembering that the numbers in the chart above are just forecasts, and the further out they go, the more inaccurate they become. A lot could change between now and Jan. 2029.
However, investors should also be aware that analysts have significantly underestimated the sustainability of the AI boom and Nvidia's growth.
The chart below shows how Wall Street's estimates for Nvidia's next fiscal-year revenue have changed.
NVDA Revenue Estimates for Next Fiscal Year data by YCharts
Through much of 2025, Wall Street thought Nvidia would bring in around $250 billion in revenue for the current fiscal year (fiscal 2027). Instead, Nvidia is on track for close to $400 billion in revenue this year. That's a huge miss; Wall Street simply did not expect the company's growth rate to reaccelerate, which it has in recent quarters.
Why Nvidia looks so undervalued The best explanation for why the stock is trading at just 12 times fiscal 2029 earnings is that investors don't believe these profits are sustainable over the long term. According to that argument, semiconductors are historically cyclical, and when the massive AI capex build-out slows down, so will demand for Nvidia chips.
The debate over whether there's an AI bubble has been brewing for nearly a year now, and there's no clear answer. Last night's earnings report from Micron showed that there's still a huge shortage in memory chips, which seems bullish for companies like Nvidia. While Nvidia is a customer of Micron, the memory shortage means that demand for AI chips like Nvidia's would be even higher if there were sufficient memory supply. In other words, Nvidia's revenue could be even higher than what it is now. Nonetheless, Nvidia stock fell on the news.
At some point, there will likely be a peak in the AI chip cycle, and depending on valuations, there will be a pullback in some stocks. If that happens, some observers will surely say the AI bubble has burst.
However, that risk seems more than priced into Nvidia stock at this point, and Wall Street has thus far been too conservative, underestimating its growth. While the fiscal 2029 EPS forecast is probably wrong, there's a good chance that it's wrong because it's too low, rather than too high.
Nvidia NVDA stock fell on Thursday, giving up premarket gains as investors weighed growing competition in the artificial intelligence chip market despite another wave of enthusiasm across the broader AI sector.
The stock was down 1.3% at $196.76 in early trading after closing 0.5% lower in the previous session.
The decline came even as memory-chip stocks advanced following stronger-than-expected results from Micron Technology, which helped lift sentiment across parts of the semiconductor industry.
Several of Nvidia's major peers also traded lower. Shares of Advanced Micro Devices and Intel were in the red alongside the AI chip leader.
While Nvidia continues to dominate the market for artificial intelligence accelerators, investors are increasingly paying attention to efforts by major technology companies to reduce their dependence on the company's hardware.
The latest development came on Wednesday when OpenAI and Broadcom unveiled a custom artificial intelligence chip called Jalapeño.
The processor marks OpenAI's first entry into AI silicon development and will be used primarily for inference workloads, the computational process of delivering AI responses to users through ChatGPT and other applications.
According to OpenAI President Greg Brockman, the chip was developed rapidly with assistance from the company's own AI systems.
"The degree to which our models have been able to accelerate it was very surprising to us," Brockman said during an interview with CNBC.
Brockman said the chip was designed from end to end in approximately nine months.
The project highlights a broader trend across the artificial intelligence industry as leading technology companies and AI developers seek greater control over their computing infrastructure.
The OpenAI partnership further strengthens Broadcom's position in the growing market for custom AI chips.
Broadcom has emerged as one of the major beneficiaries of the generative AI boom by helping hyperscalers and frontier AI laboratories develop application-specific processors tailored to their own workloads.
Shares of Broadcom have risen about 10% this year and have increased nearly sevenfold since the end of 2022 as demand for AI infrastructure has surged.
The company has become a key partner for organizations looking to supplement or partially replace standard AI hardware deployments with custom-designed silicon.
Meanwhile, Qualcomm recently announced supply agreements involving Microsoft and Meta Platforms, adding to investor concerns that large technology companies are diversifying their AI hardware strategies.
Nvidia remains the industry leaderDespite the growing number of competitors, there is little evidence that Nvidia has lost meaningful business.
The company's graphics processing units remain the preferred option for many artificial intelligence training workloads, and major technology companies continue to commit substantial spending toward Nvidia-based infrastructure.
Many hyperscalers and AI developers have already announced plans to deploy Nvidia's next-generation Vera Rubin platform, which is expected to play a central role in future AI data center buildouts.
Nevertheless, investors appear increasingly focused on the long-term implications of custom chip development.
NVIDIA vykázala v Q1 FY27 tržby 81,61 miliardy USD, meziročně o 85 % více, a tržby divize Data Center vzrostly na 75,25 miliardy USD. Společnost zároveň schválila další zpětný odkup akcií za 80 miliard USD.
Mid-year is when serious investors stop trading the headlines and start thinking about the next decade. June 2026 has handed long-term buyers a useful gift: meaningful pullbacks in some of the most important AI platforms despite fundamentals that keep getting stronger. Three names stand out as platform-scale businesses already monetizing AI at scale, with runways that extend well beyond this quarter or even this year.
The setup matters. Goldman Sachs Asset Management’s 2026 outlook frames the central question this way: growth based on long-term transformative investments may be masking the true nature of the underlying real economy, and getting the AI capex call right is the key factor for 2026. The three picks below are levered to that capex cycle from three different angles: the chip layer, the cloud layer, and the application/ad layer.
NVIDIA (NVDA) NVIDIA (NASDAQ:NVDA | NVDA Price Prediction) trades at $199.45, roughly 27% below its 52-week high of $236.26. That is a meaningful entry discount on a business that just printed Q1 FY27 revenue of $81.61 billion, up 85% year over year, with Data Center revenue of $75.25 billion and networking up 199%.
The bull case is straightforward. Hyperscaler AI capex is locked in, and NVIDIA is the toll booth. CEO Jensen Huang called it “the largest infrastructure expansion in human history”, and the numbers back him: $119.0 billion in total supply-related commitments, 75% non-GAAP gross margins, and a board that just authorized an additional $80 billion buyback and raised the dividend from $0.01 to $0.25 per share quarterly. Analyst consensus is 95% bullish with a $298.93 target price.
The risk: Q2 FY27 guidance of $91.0 billion ± 2% excludes China data center compute entirely, and export restrictions remain the single largest swing factor on the outlook. Buyers here are paying for the rest-of-world AI build, not Beijing.
Amazon (AMZN) Amazon (NASDAQ:AMZN) sits at $237.27, 12% below its $278.56 52-week high. The AWS reacceleration story is finally showing up in the numbers: Q1 2026 AWS revenue of $37.59 billion grew 28%, the fastest pace in 15 quarters, at a 38% operating margin.
The platform story has three legs now. AWS is reaccelerating with landmark compute commitments from OpenAI, Anthropic, and Meta. The custom silicon business (Graviton, Trainium, Nitro) crossed a $20 billion annual revenue run rate, growing triple digits year over year. And advertising hit $17.24 billion in Q1, up 24%, on a trailing-twelve-month base above $70 billion. CEO Andy Jassy framed the moment: “We’re in the middle of some of the biggest inflections of our lifetime.” Analyst sentiment is 94% bullish with a $312.99 consensus target.
The risk is the capex bill. Amazon is guiding to roughly $200 billion in 2026 capex, which has already compressed TTM free cash flow to $1.2 billion, down 95% year over year. Long-term debt has climbed to $119.1 billion. Investors buying today are funding an infrastructure cycle whose returns won’t be obvious for years.
Meta Platforms (META) Meta Platforms (NASDAQ:META) is the most contrarian pick of the three. Shares trade at $560.74, down 15% year to date and 19% over the past twelve months. That weakness has happened alongside Q1 2026 revenue growth of 33% and ad revenue of $55.02 billion growing 33%, with ad impressions up 19% and price per ad up 12%.
The bull case rests on three pillars. First, the engagement base: 3.56 billion Family of Apps daily active people, with Morningstar pegging the network at close to 4 billion monthly active users. Second, profitability: operating income of $22.87 billion grew 30%, and the company expects full-year 2026 operating income to exceed 2025 levels. Third, valuation: Morningstar rates Meta 31% undervalued against an $850 fair value estimate as of June 8, 2026, and analyst consensus sits at 89% bullish with an $827.32 target price. CEO Mark Zuckerberg framed the strategy bluntly: “We’re on track to deliver personal superintelligence to billions of people.”
The risk is the spend behind that ambition. 2026 capex guidance was raised to $125-145 billion, Reality Labs lost $4.03 billion in Q1 alone, and EU/US regulatory and youth-litigation overhangs have not gone away. Sentiment trackers register the chill: Meta’s composite prediction score sits at 43.84, neutral with a 7-day change of -15.42.
What to Watch From Here The thread connecting these three is platform durability. NVIDIA owns the silicon, Amazon owns the cloud rails plus a fast-growing chip line, and Meta owns the largest attention surface on the planet. Each is plowing record capital into AI. The earnings prints over the next two quarters, capex absorption, AWS growth rate sustainability, and Meta’s ad pricing trajectory, will tell investors whether the spend is producing the durable economic moats the bull case requires.
Nvidia zítra vyplatí první vyšší dividendu; 100 akcií nyní přinese 25 USD za čtvrtletí, tedy 100 USD ročně. Firma letos plánuje nasměrovat 50 % volného peněžního toku na odkupy akcií a dividendy.
Nvidia (NASDAQ: NVDA) is paying its first boosted dividend tomorrow, June 26, 2026, marking the commencement of its new share buyback strategy announced in March.
As part of the new program, the chipmaker plans to deploy 50% of its free cash flow toward stock buybacks and dividends this year as it restarts manufacturing tied to the new orders.
Prior to the hike, 100 shares earned only a symbolic sum – $1 per quarter at the old $0.01 rate, to be precise. Now, the same investment nets $25 per quarter, or $100 annually if the new payout is maintained.
As such, tomorrow’s Nvidia stock dividend represents an increase of no less than 2,400% from the previous one issued in April, according to DivvyDiary data.
Nvidia dividends calendar. Source: DivvyDiary A new milestone in Nvidia dividend history For context, with 24.22 billion Nvidia shares outstanding as of press time, more or less $6.055 billion will be distributed to shareholders.
These new initiatives put Nvidia more in line with the broader industry, as, for example, Meta (NASDAQ: META) is reportedly planning between $115 billion and $135 billion in capital expenditures as well.
The last time management increased the payout was in June 2024, when they lifted it from $0.004 to $0.01. Currently, the chipmaker offers an annual payout of $0.28 per share, which is a dividend yield of 0.14% (verseus the industry average of 1.37%).
One day, before the historic Nvidia dividend payout date, the shares are up 1.2% in-premarket, the optimism generated by both tomorrow’s shareholder reward and a broader rally in global chip shares following Micron’s (NASDAQ:MU) strongest quarter on record.
Featured image via Shutterstock
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Nvidia se poprvé stala největším dodavatelem podle tržeb na trhu ethernetových switchů pro datová centra. V 1. čtvrtletí 2026 měla tržby 2,1 miliardy USD a podíl 21,5 %.
Nvidia CEO Jensen Huang Chris Jung/NurPhoto via Getty Images Nvidia's dominance in AI is moving beyond chips.
For the first time, the company became the top vendor by revenue in data center Ethernet switches — the networking gear that helps connect AI chips inside data centers, according to market research firm IDC.
This market is growing fast because cloud giants and other large businesses are pouring hundreds of billions into building out AI data centers. IDC research vice president Paul Nicholson called Nvidia's ascension "one of the most significant vendor landscape shifts IDC has tracked in enterprise networking."
In the first quarter of 2026, Nvidia generated $2.1 billion in data center Ethernet switch revenue — a 21.5% share of the market. That's up from 4% in the first quarter of 2024, said IDC senior research manager Brandon Butler.
Nvidia has pushed ahead of rivals like Arista Networks, which held a 20.7% share of the data center Ethernet switch market in the first quarter of this year. Other major players include Cisco, Huawei, and HPE.
The data center Ethernet switch market totaled $10 billion in the first quarter, according to IDC, growing 61% from a year earlier.
IDC attributed Nvidia's growth in networking revenue to its Spectrum-X product, "a tightly integrated system" that's designed to work closely with its AI chips, Butler said.
Butler said Nvidia's approach appeals to cloud giants looking to build quickly and avoid piecing together parts from multiple vendors. The trend also reflects a broader shift of companies buying networking and computing products together, IDC said.
The chip giant has increasingly highlighted networking as a major growth driver. At a shareholder meeting on Wednesday, Nvidia CEO Jensen Huang said Spectrum-X is "now larger than all other Ethernet networking peers combined."
The comments echoed Nvidia's most recent earnings call in May, when chief financial officer Colette Kress said the company's broader data center networking revenue had tripled to $15 billion from the previous year.
Nvidia's networking business traces back to its 2019 acquisition of Mellanox, which gave the company a foothold in data center networking before the AI boom took off.
Nvidia's lead isn't guaranteed. Cloud giants are increasingly looking to diversify their supplier base, Butler said, while businesses may lean on existing relationships with networking providers as they ramp up their infrastructure.
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Geoff Weiss You're currently following this author! Want to unfollow? Unsubscribe via the link in your email.
Geoff Weiss is a senior reporter on Business Insider’s tech team, where he writes about AI startups and Y Combinator, the intersection of AI and the media industry, and workplace dynamics within top AI labs and chip companies.Previously, Geoff was on the media desk, covering YouTube and Netflix, and themes like the intersection of Hollywood and the creator economy. His work on Netflix’s video podcasting ambitions and Mr Beast’s lessons for Hollywood won second and first prize, respectively, at the 2025 LA Press Club Awards.Prior to joining Business Insider, Geoff was the senior editor of Tubefilter and a staff writer at Entrepreneur. He graduated from New York University with a degree in English Literature.He can be reached at [email protected], on Signal @geoffweiss.25, and on LinkedIn. Have a tip? Use a personal email address and a nonwork device; here's our guide to sharing information securely.Selected stories:Nvidia crushed its quarter — and CEO Jensen Huang said in a leaked all-hands that 'the market did not appreciate it'Nvidia will foot the bill for Trump's new visa fees. Here's what CEO Jensen Huang told staff.Massive AI salaries and RTO are fueling a real estate boom in San Francisco: 'It's going to rain money'The AI talent wars are ricocheting across startups. Here's how they're competing with Big Tech.
Nvidia stále dominuje v AI: pohání 81 % z top 500 nejrychlejších superpočítačů na světě, tedy více než 400 systémů. I přes rostoucí konkurenci si drží jasné vedení.
Nvidia (NVDA 0.93%) has built an artificial intelligence (AI) empire, offering graphics processing units (GPUs) that power essential tasks like the training of AI models and providing a wide range of related products and services. All of this has sent earnings soaring in recent years -- and the stock price has followed.
Customers flock to Nvidia for these top AI products, and the company has consistently remained No. 1 in the AI chip market. In recent times, Nvidia says it also aims to lead in central processing units (CPUs), a market that's been dominated by Intel and Advanced Micro Devices. This represents a $200 billion opportunity, and Nvidia has said it's on track to accomplish this goal thanks to its first stand-alone CPU, launching later this year.
All of this sounds fantastic, but it's important to remember that Nvidia faces increasing competition from a variety of companies. Will this leader continue to dominate in AI? One number offers a strikingly clear answer.
Image source: Getty Images.
A history of GPU expertise First, let's start with a quick summary of the Nvidia story so far. The company has a long history of GPU expertise, with this chip first serving the gaming market. Nvidia still makes GPUs for gaming, but it has progressively expanded the uses of these high-powered chips over the years. Through the CUDA parallel computing platform, GPUs may be programmed for other needs, and the area of AI has proven to be particularly valuable.
Today, sales of GPUs to data center customers generate the lion's share of Nvidia's revenue. And this doesn't include chips only, but related products such as networking tools, so that Nvidia offers complete AI systems. The company has also designed offerings specifically suited to various industries -- for example, AI platforms that assist healthcare companies with drug discovery.
All of this has helped Nvidia's revenue climb in the double and triple digits in recent years, and it reached a new record of more than $215 billion in the latest fiscal year. In the first quarter of this year, earnings continued to climb, with revenue rising 85% to $81 billion, and net income advancing more than 200% to $58 billion.
So it's not surprising that Nvidia's stock price has also skyrocketed, climbing 900% over five years.
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Nvidia faces competition These points all offer us reason for optimism about the future, but we shouldn't ignore the fact that Nvidia faces growing competition. Fellow chip designers, such as AMD, or new-to-the-market players like Cerebras Systems, aim to take market share. And even some of Nvidia's customers might represent a threat as they're designing their own chips. Amazon is a good example. The company has seen such demand for its own chips that it may even consider creating a separate chip business.
Now, let's consider our question: Will Nvidia continue to dominate in AI as the competition mounts and customers are served with more and more options?
One particular number offers a strikingly clear answer. Almost nine of every 10 systems new to the world's fastest supercomputer list are built on Nvidia, according to the latest rankings. This clearly shows that customers continue to turn to Nvidia -- so even though there is plenty of business for rivals to succeed too, so far this hasn't come even close to threatening Nvidia's leadership position.
The data revealed that Nvidia powers 81% -- or more than 400 -- of the world's top 500 fastest supercomputers. This is an increase of 17 systems from the last report, according to Nvidia. The list is updated twice a year.
Moving forward, Nvidia's new presence in CPUs may help it gain even more ground, as it now offers another key element, particularly in the phase of agentic AI. CPUs are the main chips that help guide AI agents as they take action to handle a problem on behalf of humans.
All of this means that, though Nvidia faces competition, customers still see the value of choosing this leader -- and the company's focus on innovation should keep this going. And that's excellent news for investors who've chosen to buy and hold Nvidia for the long term.
NVIDIA už podle článku nepotřebuje čínské datacentrové compute tržby, protože její datacentrový, AI, networking a platformový byznys roste silně mimo Čínu. V 1. čtvrtletí tržby stouply o 85 % a výhled činí 91 mld. USD.
SummaryNVIDIA is a Buy as its base case no longer depends on Chinese data center compute revenue.NVDA’s data center, AI, networking, and platform businesses are compounding strongly ex-China, with Q1 revenue up 85% and robust $91B guidance.China now represents high-value optional upside, not a key valuation pillar; partial reopening or compliant chip sales would further boost upside.Downside risk is limited, with base and bull cases supporting 43–70% upside; key risks are AI buildout slowdown and Rubin ramp delays. Robert Way/iStock Editorial via Getty Images
I am not buying NVIDIA (NVDA) because I hope China will reopen someday. In fact, my argument is almost the opposite: I am buying NVDA because it no longer needs Chinese data center compute revenue
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Nvidia v prvním čtvrtletí fiskálního roku 2027 zvýšila tržby segmentu datových center na rekordních 75,2 miliardy USD, meziročně o 92 %. Firma těží z poptávky po Blackwellu a novém CPU Vera Rubin.
Chipmaker Nvidia (NVDA 0.93%) stands at the center of the artificial intelligence (AI) infrastructure supercycle. The world's most valuable company supplies essential hardware and software that enables the training, inference, and scaling of ever more sophisticated AI models.
Insatiable demand for the company's Blackwell GPU architecture, record capital spending by the hyperscalers, and the debut of its new Vera Rubin architecture, which expands its reach into CPUs, all point to the company enjoying sustained acceleration amid the ongoing data center build-out.
Taken together, Nvidia has the conditions for meaningful revenue growth complemented by even further earnings expansion. This combination should support a meaningful upward rerating of Nvidia stock over the next year.
Image source: Nvidia.
Nvidia's data center business is accelerating again Nvidia's most recent quarterly results underscore a clear reacceleration from the data center business. During the first quarter of its fiscal 2027 (which ended April 26), data center revenue reached a record $75.2 billion -- up 92% year over year. This performance reflects robust demand across hyperscalers as well as a broadening customer base that includes frontier AI labs, large enterprises, and sovereign entities. The increase in data center sales signals that growth momentum is strengthening again after a brief period of more measured expansion.
Management's guidance for the fiscal second quarter points to further sequential progress, which should reinforce investors' confidence in the trajectory of the broader AI infrastructure build-out. To me, these trends suggest that Nvidia's growth reacceleration is not occurring in isolation; rather, it is being fueled by aggressive capital expenditure plans from the largest cloud providers, which continue to scale up their AI infrastructure at a rapid pace.
Looking further out, analyst projections indicate that hyperscaler capital spending in 2027 could surpass $1 trillion. When extended across the broader ecosystem -- including memory, networking, and power -- the cumulative investment in AI-related infrastructure is expected to reach several trillion dollars over the coming years.
As the dominant supplier of the accelerated computing platforms that sit at the core of these deployments, Nvidia is positioned to capture a meaningful share of this spending. The combination of reaccelerating quarterly results and management's multiyear visibility into customer budgets offers a compelling reason to anticipate continued data center expansion through next year and beyond.
Nvidia is quietly becoming a full-stack solution Nvidia has taken a decisive step beyond designing GPUs with the introduction of its Vera CPU platform. This hardware is purpose-built for the emerging era of agentic AI. The company launched the Vera CPU earlier this year and has already delivered the product to leading AI laboratories and cloud providers.
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By delivering a high-performance CPU optimized for the same CUDA software ecosystem that has long powered its GPUs, Nvidia can deepen its control of the full AI compute stack. Vera pairs with Nvidia's GPUs, thereby reducing friction within integrated AI systems. This strategy should help accelerate Nvidia's data center business even further as the company captures sales within an additional pocket of the AI chip value chain.
Where will Nvidia stock be in one year? These secular growth drivers -- Blackwell adoption, hyperscaler infrastructure spending, and the new Vera CPU -- are converging at a time when Nvidia's forward price-to-earnings (P/E) multiple sits well below the levels it usually traded at during earlier phases of the AI revolution.
NVDA PE Ratio (Forward) data by YCharts.
With earnings poised to expand from the data center segment, Nvidia's current valuation leaves it meaningful room for valuation expansion. Even a conservative rerating to between 24 and 27 times Nvidia's expected fiscal 2028 earnings per share (EPS) of $12.73 could propel its stock price well above $300 -- implying more than 50% upside from current trading levels.
Investors who focus on the durability of these catalysts rather than short-term noise around the growing levels of competition in the AI accelerator space or the sensitive macroeconomic environment will benefit from Nvidia's operational outperformance. Eventually, its valuation multiples will normalize toward levels consistent with the company's leading role in the AI infrastructure build-out.
Philippe Laffont went on CNBC this morning with a framework that skips the usual bitcoin-versus-gold debate and lands somewhere more concrete. “Is there going to be a $10 trillion company in 10 to 15 years? I think yes,” the Coatue Management founder said, walking through the arithmetic. Global market cap sits near $120 to $140 trillion today, and if it grinds to $200 trillion over the next decade, a company worth 5% of the world would clear $10 trillion. The mechanism he keeps pointing at is agentic AI, which he called “one of the bigger ideas, at least in my investment career.”
The shorthand for agentic AI is software that does work rather than answers questions. Laffont described it as “the ability to have thousands of people working for you” overnight, and said the productivity gains were already showing up “even in our own office.” That framing matters because the companies closest to his $10 trillion finish line are the ones selling the picks and shovels for that buildout, plus the hyperscalers consuming them.
NVIDIA is the obvious candidate NVIDIA (NASDAQ:NVDA | NVDA Price Prediction) carries a market cap of roughly $4.8 trillion as of this week, which puts it about halfway to Laffont’s threshold without needing any heroic assumptions about market expansion. The Q1 FY27 report from May 20, 2026 showed revenue of $81.61 billion, up 85.2% year over year, with the data center segment alone at $75.25 billion. Jensen Huang called the AI factory buildout “the largest infrastructure expansion in human history.”
The stock itself trades around $199, up 5.6% year to date and 35% over one year. Forward earnings change hands at roughly 23 times, which is not a stretched multiple if revenue keeps compounding at the current pace. Loop Capital analyst Ananda Baruah already raised his target to $350, which implies an $8.5 trillion valuation.
The hyperscalers are funding the entire thing Microsoft (NASDAQ:MSFT), Alphabet (NASDAQ:GOOGL), Amazon (NASDAQ:AMZN), and Meta Platforms (NASDAQ:META) are writing the checks that turn into Nvidia revenue. Microsoft’s AI business hit a $37 billion annual run rate, up 123% year over year, with commercial remaining performance obligations at $627 billion. Alphabet guided 2026 capex to $175 billion to $185 billion, and Google Cloud backlog nearly doubled quarter over quarter to roughly $460 billion. Moreover, Amazon plans about $200 billion in 2026 capex and its custom chips business is now running above a $20 billion annual rate. Meta lifted its 2026 capex range to $125 billion to $145 billion.
These are the dollars feeding what Jensen Huang described on the earnings call as “Agentic AI has arrived, doing productive work, generating real value and scaling rapidly across companies and industries.” Laffont’s framework rests on that loop continuing for another decade.
The near-term price action disagrees Most other mega-cap stocks are up by double digits, though some are treading water. Prediction markets on Polymarket are pricing in a 98.8% probability that Nvidia closes lower today, and only a 23.5% chance the stock closes above $210 by month-end.
That gap between Laffont’s decade-long thesis and the week-to-week price action is the actual investment question. He told CNBC that “the longer dated capital is very, very important because I’m trying to figure out the index of the future ten years out,” which is partly why Coatue is pushing into private markets. He floated OpenAI, Anthropic, and SpaceX as candidates for the eventual $10 trillion crown, none of which sit in a public index today.
For investors who only have public-market access, the working assumption embedded in Laffont’s view is that one of the five names above keeps pulling the chain on agentic AI revenue. The hard part is that the company most likely to triple from here is also the company most exposed if hyperscaler capex ever moderates.
Nvidia CEO Jensen Huang told shareholders on Wednesday that if a commercial opportunity conflicts with U.S. national security, the company would prioritize American interests.
"National security comes first," Huang said in a session shortly after the company's annual stockholder meeting concluded.
He added that if a company wanted to smuggle Nvidia's chips or systems into countries with export restrictions — such as China — they would have challenges getting it working because Nvidia wouldn't provide support or repairs.
"Advanced AI data centers are massive integrated systems that require trusted hardware, software, networking, and continuing support," Huang said. "Trying to cobble together data centers with some smuggled products is a dead end."
Huang's remarks come as Washington regulators and the Trump administration are increasingly wary that exporting AI software and hardware to China and other nations is a threat to national security.
Earlier this month, Anthropic, which uses Nvidia chips, shut down Fable 5 and Mythos 5 after the U.S. government ordered it to disable access to its most advanced models.
Nvidia's chips have had export controls placed on them since 2022, which forced the company to produce China-specific chips for the region that complied with U.S. government benchmarks. But last year, the U.S. cleared the company's H200 chip — the same model used by U.S. companies — for export to the region.
Read more CNBC tech newsAmazon's Zoox unveils redesigned robotaxi ahead of upcoming expansionOpenAI unveils first chip as part of Broadcom deal in effort to 'build the full stack'South Korean chipmaker SK Hynix plans to raise $29 billion via Nasdaq listing as soon as July 10Alphabet added to Dow Jones Industrial Average, replacing VerizonHuang said that the U.S. government approved those licenses, but Nvidia has yet to generate any revenue from the chips and that Nvidia doesn't know whether China will allow imports of its products. About 9% of Nvidia's fiscal 2026 revenue came from China, including Hong Kong, a smaller proportion than in 2025 and 2024.
Huang told stockholders during the meeting that the question of AI return-on-investment "has been answered."
He said that when AI output is useful, such as generating code, then operating an Nvidia system to generate tokens, or bits of AI output, becomes profitable and means companies need more computing power. He noted that GitHub saw pull requests nearly triple this year because of AI.
"Nvidia systems may not be the cheapest to purchase, but Nvidia generates the lowest cost tokens, the highest token throughput, and the most revenues," Huang said.
He reiterated that Nvidia plans to return 50% of the company's free cash flow to investors through share repurchases and dividends over the next few years.
Nvidia generated over $96 billion in free cash flow in its fiscal 2026.
"Nvidia offers investors a unique combination of exceptional growth, strong margin, and free cash flow execution, and rising capital returns," Huang said.
At the annual meeting, shareholders approved the company's executive compensation plan in an advisory capacity and re-elected all 10 board members. One outside shareholder proposal to change company bylaws so that all shareholder votes would win with a simple majority passed.
NVIDIA dál zrychluje růst: tržby datového centra dosáhly 75,25 miliardy USD a firma čeká ve 2Q FY27 tržby 91 miliard USD. Zároveň zvýšila dividendu z 0,01 na 0,25 USD na akcii a schválila další odkup akcií za 80 miliard USD.
I keep buying NVIDIA (NASDAQ:NVDA | NVDA Price Prediction) because every quarter the company reports, the math behind my thesis gets stronger. That is the whole confession. I have been adding on every pullback this year, including the 4.13% drop on June 23 that pushed shares back to $200.04, and I plan to keep doing it through the back half of 2026. Here is why.
The core thesis in human terms Jensen Huang calls what is happening right now “the largest infrastructure expansion in human history.” I think he is right, and I think NVIDIA sits at the toll booth. Every hyperscaler, sovereign, neocloud, and enterprise that wants to train or serve a frontier model has to come through this company’s stack. That is a structural position I want to own for the next decade.
Three reasons the thesis holds Reason one: the growth curve is accelerating. Revenue growth has gone +55.6% in Q2, +62.5% in Q3, +73.2% in Q4, and +85.2% in Q1 FY27. Data Center revenue hit $75.25 billion last quarter, up 92% year over year, with networking inside that segment growing 199%.
Management guided Q2 FY27 to $91 billion, and they have beaten the prior two guides by billions. Total supply commitments now sit at $119 billion. That is locked-in demand visibility.
Reason two: margins and cash returns are doing the work. Non-GAAP gross margin printed at 75%. Free cash flow last quarter was $48.55 billion, up 85.41%. The board raised the dividend from $0.01 to $0.25 per share and authorized an additional $80 billion buyback on top of $38.5 billion still available.
Roughly $20 billion came back to shareholders in a single quarter. That is a capital return program I want compounding alongside my position.
Reason three: the moat keeps widening. The customer list reads like the entire AI economy: Meta committing to millions of Blackwell and Rubin GPUs, OpenAI on 10 gigawatts, Anthropic on 1 gigawatt, CoreWeave on 5+ gigawatts by 2030.
Four straight EPS beats, with last quarter at $1.87 against a $1.7738 consensus. And the valuation looks reasonable for this growth rate: forward P/E of 24, PEG of 0.642, against a market cap near $5.05 trillion.
The real risk China. NVIDIA shipped zero H20 compute products to China last quarter, against $4.6 billion in the year-ago quarter. The Q2 FY27 guide assumes no Data Center compute revenue from China at all. That is a real hole in the business that export restrictions could keep open indefinitely.
What keeps me buying anyway: the company guided to $91 billion with that revenue already zeroed out, and growth is still accelerating. The thesis holds even with China taken to zero.
What keeps the buy button active Wall Street consensus target sits at $298.93 from 58 buys against 1 sell. Forward P/E of 24. A dividend that just jumped 25x. A buyback authorization with no expiration. An installed base running every cloud and every frontier model.
I own NVIDIA because the AI factory buildout is a multi-year story and the company collecting the toll is also returning cash and compounding margins while it grows. I will keep buying for as long as the receipts say I should.
Nvidia se drží nad hranicí 200 USD, zatímco investoři řeší ocenění a slabší výkon vůči širšímu polovodičovému trhu. Zájem podporuje i prudký růst cen jejích AI čipů na čínském černém trhu, které za posledních šest měsíců více než zdvojnásobily.
Nvidia NVDA shares edged higher on Wednesday as the chipmaker stabilized following a broader semiconductor-sector selloff, with market participants assessing whether the stock is establishing a new trading range.
Despite recent volatility, the stock has largely held above the psychologically important $200 level since breaking out of its previous range in April.
The move comes as investors weigh Nvidia’s relative underperformance against the broader semiconductor sector.
The stock is up 7.3% so far this year, compared with a roughly 90% gain for the PHLX Semiconductor Index over the same period.
Still, technical and valuation signals suggest some support for the stock at current levels.
Nvidia has only briefly fallen below $200 in recent months and has tended to rebound on dips around that level.
The company is trading at a forward price-to-earnings ratio of 19.34 times, according to FactSet, slightly below the S&P 500 average of 20.77 times.
Analysts suggest this valuation could attract investors looking for relative value, potentially limiting further downside.
Nvidia is also returning significant capital to shareholders through dividends and buybacks, distributing about 50% of free cash flow.
Based on expected free cash flow of $195.35 billion in 2026, the company could return more than $97 billion to investors.
However, expectations for a sustained breakout remain tied to product cycle developments.
Investors are watching the rollout of Nvidia’s next-generation Vera Rubin chips, which are expected to enter the market in the second half of the year.
Market participants say the company will need to demonstrate continued dominance in artificial intelligence hardware to drive the next leg higher.
Nvidia’s AI chips have seen sharply higher prices on China’s black market, more than doubling over the past six months, according to a Financial Times report.
The increase comes amid tighter US enforcement of export controls restricting access to advanced semiconductors.
The DGX B300 server, which contains eight Blackwell graphics processing units, has risen in price to more than 8 million yuan ($1.1 million), up from around 4 million yuan, based on interviews with Chinese chip traders.
The system typically sells for about $400,000 in the United States.
Similarly, the RTX 6000 Pro workstation chip, used in large language model development, has increased from roughly 50,000 yuan at the start of the year to as much as 130,000 yuan, according to the report.
Both products are subject to US export restrictions on sales to China.
The surge in unofficial pricing follows a series of enforcement actions.
In March, a Supermicro co-founder, along with a Taiwan-based employee and a contractor, was charged with allegedly smuggling $2.5 billion worth of Nvidia AI servers to Chinese customers in what is described as the largest US enforcement case related to AI chip exports.
Wall Street zvýšila cílovou cenu pro Nvidia na 295 USD, což znamená 42% potenciál růstu. Firma zároveň dál získává podíl v AI infrastruktuře, zejména v inferenci, sítích a CPU.
Nvidia (NVDA 0.38%) has been one of the biggest winners from the artificial intelligence (AI) infrastructure build-out. The stock has advanced more than 1,300% since January 2023. But most Wall Street analysts still believe Nvidia is deeply undervalued.
In fact, the consensus target price has increased from $265 per share to $295 per share in the last 90 days, according to LSEG. That implies 42% upside from the current share price of $209.
Here's what investors need to know.
Image source: Getty Images.
Nvidia is gaining market share in AI inference workloads Nvidia graphics processing units (GPUs) are the industry standard in artificial intelligence (AI) accelerators, chips that assist CPUs by handling repetitive mathematical tasks. Nvidia accounts for more than 80% of AI accelerator sales, but some analysts expected the company to lose significant market share as the industry shifted toward inference.
To elaborate, AI training is a discrete event in which models learn to perform certain tasks, but AI inference is a continuous process wherein models are used to generate outputs. Inference accounts for about two-thirds of AI workloads today, up from about one-third in 2023, and the shift will only intensify in the future as more models are deployed.
Companies like Alphabet and Amazon have designed custom AI accelerators in an effort to reduce their dependence on Nvidia GPUs. In certain scenarios, those custom chips are actually more efficient, but Nvidia's inference market share still increased eight percentage points to 74% over the past year, according to The Information.
Why? GPUs are general-purpose accelerators, while custom chips are designed for specific workloads. That makes them very efficient in certain situations, but it also means they are much less flexible (i.e., they run fewer algorithms). Venture Beat explains, "If a new AI technique is invented tomorrow, a GPU will run it immediately." That is not necessarily true for custom AI accelerators.
Beyond that, Nvidia has a competitive advantage in its vertically integrated business. The company not only designs GPUs but also CPUs, networking, and software that together form a turnkey solution for AI infrastructure. That translates into cost savings for customers. "Nvidia compute is not just the highest performance AI infrastructure, it is the most economic," says CEO Jensen Huang.
Nvidia is gaining market share in other categories of AI infrastructure While Nvidia is best known for its GPUs, the company is actually gaining share in other AI infrastructure categories. Networking revenue has at least doubled in each of the last three quarters, and it nearly tripled in the most recent quarter, because customers want tightly integrated systems. Nvidia recently became the largest networking company in the world.
Meanwhile, demand for Nvidia's next-generation Vera CPU is already immense ahead of its launch later this year. Vera is twice as efficient as x86-based alternatives (CPUs designed by AMD and Intel). CFO Colette Kress recently told analysts, "We have visibility to nearly $20 billion in total CPU revenue this year, setting us up to become the world-leading CPU supplier."
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AI infrastructure spending is projected to quadruple by the end of the decade To summarize, Nvidia is gaining share within the inference category of the AI accelerator market. That's important because inference has already surpassed training in terms of workload volume, and it will become an even larger part of the market in the future.
Meanwhile, Nvidia is also gaining share in networking equipment and CPUs as customers prioritize tightly integrated systems. Collectively, that puts the company in a good position. CEO Jensen Huang thinks AI infrastructure spending could hit $4 trillion annually by 2030, up from about $1 trillion today. Grand View Research has published similar numbers.
Here's the big picture: Multiple industry experts expect AI infrastructure spending to grow by 36% annually through the end of the decade. Nvidia is gaining share across multiple categories in that market, suggesting its earnings could grow even faster than 36% annually. That makes the current valuation of 32 times earnings look cheap. Patient investors should feel comfortable buying a small position today.
