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Nvidia (NASDAQ:NVDA | NVDA Price Prediction) shares caught quite the bid higher when Elon Musk surprisingly announced that his space empire, Space Exploration Technologies (NASDAQ:SPCX), would show loyalty to the great Jensen Huang by going exclusive with Nvidia’s AI chips.
Why the big commitment? To put it simply, Elon Musk said that “they are the best.” And he’s certainly not wrong, especially as the Vera Rubin era looks to change the world once again.
For investors, the big question is: why bother committing to one firm or another for AI chips? Doesn’t it make more sense to leverage rivals against each other for a shot at better prices?
In my view, I think SpaceX’s loyalty could come with some unspoken perks, especially as Nvidia faces intense demand for its latest and greatest. Indeed, it only makes sense to prioritize firms with the deep pockets and loyalty whenever the line starts going out the door.
SpaceX’s Nvidia exclusivity could pay off in a big-time way In my humble opinion, a simple gesture of loyalty can go a long way. And for SpaceX, it feels like it’s secured a spot at, or at least very close to, the front of the line for the next era of cutting-edge GPUs. Add Nvidia’s support for its orbital AI data center endeavors into the equation, and perhaps the partnership between the two titans in tech is just getting started. At the end of the day, it’s far better to have two of the brightest minds in tech tackling the same problems.
While it was initially shares of Nvidia that shot higher on the news, I do think that the ensuing rally in SpaceX shares was more than warranted. Just like that, the stock is more than $11 above the IPO price of $135 per share. Given the massive bounce off the lows, it feels like SpaceX remains a very dangerous stock to go short, even if the price of admission bakes in a lot — maybe even too much. As the Musk-Huang relationship expands further from here, I do think that both companies stand to benefit greatly.
As for losers of such a deal, Advanced Micro Devices (NASDAQ:AMD) immediately comes to mind. It’s the number-two player in the GPU race, and shares have outperformed Nvidia by leaps and bounds in the past year, more than doubling to a 162% gain, while Nvidia stock rose just 23% (close to a market return).
It’s not great news for Advanced Micro Devices, but Lisa Su need not worry Of course, Lisa Su’s chip empire is a serious challenger on price. But with a nearly $2 trillion space titan now off the market, Advanced Micro Devices needs to consider its next move, especially if there are more firms that will be willing to make similar commitments to improve relations, gain priority access, and maybe a bit more. If Nvidia can’t keep up with demand, Advanced Micro Devices still stands to post more wins of its own as it marches ever closer to that $1 trillion market cap milestone.
Any way you look at it, SpaceX going exclusive with Nvidia is bad news for Advanced Micro Devices, especially when you consider how much more the space titan could spend on AI hardware, as its CapEx looks to surge further in this unprecedented AI data center buildout.
Personally, I don’t think Advanced Micro Devices needs to force exclusive deals. If anything, concentrating on the value provided in an era where efficiency and ROIs matter, I think, could be the edge that helps Lisa Su’s firm continue to ride higher.
One area where Advanced Micro Devices could gain loyalty, I believe, is via structured equity deals and collaborations within the data center. Naturally, customers are going to want to stick with vendors that have skin in the game.
Of course, Nvidia has a ton of bets across the AI scene, from frontier AI labs to connectivity plays and everything in between. As Advanced Micro Devices looks to put some of its cash to work, I do think it’s bound to follow a similar playbook.
The bottom line All considered, I think Advanced Micro Devices is not at all in trouble after the latest SpaceX-Nvidia exclusivity announcement. If anything, it makes me even more bullish on Lisa Su’s firm as they look to make the best response. While I could be wrong, I still think Advanced Micro Devices shares will outpace Nvidia for the year ahead.
In my view, the SpaceX exclusivity deal is a subtle jab, not a knockout blow. Not even close.
Contact [email protected] for any questions or corrections.
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Jensen Huang doesn’t rattle easily. The CEO of NVIDIA (NASDAQ:NVDA | NVDA Price Prediction) has spent the past three years narrating an AI buildout that has pushed his company to a $5.18 trillion market cap. So when he turns visibly defensive, investors should pay attention.
On a recent Prof G Markets segment, China analyst Alice Han and host Ed Elson dissected a tense exchange between Huang and podcaster Dwarkesh Patel. Huang warned that if China’s DeepSeek optimized its next-generation models for Huawei silicon before NVIDIA hardware, “that is a horrible outcome for our nation,” adding that AI models running best on non-American chips “is bad news for us.” Elson called it “the first time I’ve seen him as defensive.”
What Huang Is Really Worried About The fear is structural. If DeepSeek, whose V4 model already handles a 1 million token context window on par with Gemini and the leading U.S. labs, shifts its training stack to Huawei accelerators, NVIDIA loses the network effect that has made CUDA the default substrate of global AI. Han noted DeepSeek’s funding will likely be “state-led” rather than venture-backed like Anthropic or OpenAI, and that hardware access remains the critical bottleneck.
Huang made the same case on NVIDIA’s Q1 FY2026 call: “The question is not whether China will have AI, it already does. The question is whether one of the world’s largest AI markets will run on American platforms.” He pegged the China AI accelerator TAM at roughly $50 billion, a market NVIDIA has effectively been locked out of. The H20 ban already forced a $4.5 billion inventory write-down, and Q1 FY2027 guidance of ~$78.0B explicitly assumes zero China Data Center compute revenue.
The Numbers Behind the Anxiety NVIDIA’s underlying business has not blinked. Q4 FY2026 revenue hit $68.13 billion, up 73% YoY, with Data Center Networking alone climbing 263% YoY on NVLink demand for GB200/GB300 racks (8-K filing). Full-year FY2026 revenue reached $215.94 billion. Wall Street’s consensus target sits at $269.17, with 48 Buy ratings and nine Strong Buy ratings against just two Hold ratings. Forward P/E is 24x.
Shares are up 22.12% over the past year and 18.44% year to date through Aug. 12.
What To Watch Reddit’s r/stocks community is already debating the threat directly, with one heavily-engaged thread asking “how do TPUs not pose a threat to GPU” drawing 221 comments. Han flagged that U.S. export policy has gone “off, on, off, on,” leaving NVIDIA strategically exposed. Huang’s defensive posture suggests the China question is no longer hypothetical, and the next earnings cycle will reveal whether the Vera Rubin roadmap and Grace Blackwell momentum can outrun a parallel Chinese AI stack.
Contact [email protected] for any questions or corrections.
Nvidia (NVDA +3.03%) shares are up 1,390% since the artificial intelligence boom began in January 2023, and Wall Street still thinks the stock is undervalued. Among 65 analysts, the median target price is $300 per share, implying 37% upside from the current share price of $218.
Nvidia shareholders recently got good news from Wall Street. Consensus earnings estimates have recently been revised higher, such that analysts now expect earnings to increase at 44% annually over the next three years. In March, the consensus estimate said earnings would increase at 33% annually over that period.
What changed? Wall Street analysts once again underestimated how much money hyperscalers would spend on AI infrastructure. Here are the important details.
Image source: Getty Images.
Nvidia dominates the market for AI infrastructure across GPUs, CPUs, and networking equipment Nvidia is a full-stack accelerated computing company that develops graphics processing units (GPUs), central processing units (CPUs), and networking equipment, supported by a robust ecosystem of software tools. That approach lets the company optimize performance and power efficiency in ways most competitors cannot, which explains why Nvidia systems are the gold standard in artificial intelligence.
Most readers probably know that Nvidia GPUs account for a large percentage of data center accelerator sales (around 90%, according to HPC Wire). But readers may be less familiar with the company's prowess in other categories. Nvidia recently became the largest networking company in the world, and it's on pace to become the largest CPU supplier by the end of this year.
Of course, there's been a lot of talk about application-specific integrated circuits (ASICs), chips purpose-built for specific workloads like artificial intelligence. Some investors are worried that custom silicon will eventually displace Nvidia. But those fears are unwarranted. ASICs perform certain tasks more cheaply than Nvidia GPUs, but they are less flexible and lack the robust software development ecosystem that backs Nvidia chips.
"Nvidia isn't going anywhere anytime soon," according to Meera Pandit, global market strategist at J.P. Morgan. "Only Nvidia chips can handle any AI workload. Custom hardware is a safe and efficient bet for known workloads like inference, but there's an obsolescence risk as AI evolved."
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Wall Street raised its hyperscaler capital expenditure (capex) spending forecast for 2026 Currently, 26% of hyperscaler capital expenditures (capex) go straight to Nvidia's bottom line, according to research from J.P. Morgan. That astonishing metric underscores the essential role Nvidia plays in the AI infrastructure market. And assuming the company maintains its pricing power and market share, earnings growth should more or less match capex growth going forward.
Here's the good news for shareholders: Wall Street has consistently underestimated how much hyperscalers will spend on AI infrastructure. "At the start of both 2024 and 2025, consensus estimates implied capex growth of roughly 20% for the year," writes Goldman Sachs. "In reality, it exceeded 50% in both years."
The same thing happened in 2026. Last June, the consensus estimate said capex spending among the five largest hyperscalers -- Alphabet, Amazon, Meta Platforms, Microsoft, and Oracle -- would total $361 billion this year. But Wall Street has since raised its forecast by over 100%, such that the consensus estimate now says their capex spending will total $733 billion in 2026.
Similarly, investors have reason to think Wall Street is making the same mistake with 2027. The consensus estimate currently says capex spending among the top five hyperscalers will grow 28% to $939 billion next year. But that would be a major slowdown compared to capex growth of 56% in 2024, 73% in 2025, and the projected capex growth of 90% in 2026.
Here's the big picture: Wall Street currently expects capex spending among the five largest hyperscalers to grow at 41% annually through 2028. Meanwhile, the consensus estimate says Nvidia's earnings will increase at 44% annually over the same period. It makes sense that those figures are roughly equivalent.
However, if analysts are underestimating hyperscaler capex, which is plausible given their track record, it stands to reason that they are also underestimating Nvidia's future earnings. And if earnings grow faster than expected over the next few years, the efficient market hypothesis predicts the stock price will rise. That makes Nvidia a worthwhile long-term investment.
I keep buying NVIDIA (NASDAQ:NVDA | NVDA Price Prediction), and the buy button has become a habit. Every quarter sharpens the case for adding shares. This is my highest-conviction position because the world is rewiring itself around AI compute, and Jensen Huang’s company is the toll booth on the road everyone is paving.
AI is moving from single-shot chatbots to continuous, multi-step agentic workflows that multiply compute and memory demands on every data center. Huang put it bluntly on the last call: “The buildout of AI factories, the largest infrastructure expansion in human history, is accelerating at extraordinary speed.” Reasoning models chew through a hundred to a thousand times more tokens than a one-shot query. Every token routes through NVIDIA silicon.
The Receipts I Keep Coming Back To Q1 FY2027 revenue landed at $81.615 billion, up 85.23% year over year, with Data Center at $75.246 billion (+92%). Data Center Networking at $14.8 billion, up 199% shows the full-stack moat in the P&L. NVLink, Spectrum-X, and InfiniBand are the plumbing agentic AI needs, and customers are paying for the whole rack.
Profitability: Non-GAAP gross margin of 75.0%, ROE of 101.5%, ROIC of 92.2%, and net debt/EBITDA of 0.006. Free cash flow was $48.554 billion in a single quarter. That balance sheet funds the next architecture cycle without asking for permission.
Capital return signals management sees runway ahead. The quarterly dividend rose from $0.01 to $0.25, and the board added an $80 billion buyback authorization on top of the $38.5 billion already outstanding. Companies that think the story is ending do not do that.
Why NVIDIA Over the Obvious Alternative The name a reader reaches for first is Advanced Micro Devices (NASDAQ:AMD). I own some, but my incremental dollar lands here. The reason is the networking line. A GPU competitor can match a chip. Matching CUDA, NVLink Fusion, Spectrum-X, and the software stack that runs in every cloud and every frontier model is a different problem. Even Intel (NASDAQ:INTC) chose to co-develop custom data center and PC products with NVIDIA using NVLink. When your rival plugs into your interconnect, that is the moat announcing itself.
The Risk I Refuse to Wave Away China export controls are real. Q1 saw no H20 shipments to China, and Q2 guidance of $91.0 billion, plus or minus 2%, explicitly assumes zero China Data Center compute. Add $119 billion in supply commitments and hyperscaler concentration near 50% of Data Center revenue, and concentration risk is real. Demand outside China absorbs supply faster than TSMC can print wafers. The roadmap from Blackwell Ultra to Vera Rubin gives multi-year visibility into a product cycle customers have already committed capital toward.
Why the Buy Button Stays Active At $224.09 and a P/E near 45, This is a premium multiple, paid for a company earning $1.87 a share off a 5-for-5 beat streak while building the operating system for the next industrial revolution. As long as agentic AI multiplies tokens, and NVIDIA remains the only place they can run at scale, my next contribution goes to the same ticker.
Contact [email protected] for any questions or corrections.
Nvidia (NVDA +3.03%) continues to be a dominant force in the artificial intelligence (AI) boom, thanks largely to its industry-leading graphics processing units (GPUs). But another type of technology is becoming increasingly important to the company's growth.
Nvidia generated a record $14.8 billion in data center networking revenue in its fiscal 2027 first quarter (which ended April 26), up 199% year over year. Networking revenue rose from $8.6 billion in its fiscal 2024 to $13 billion in its fiscal 2025 and to $31.4 billion in its fiscal 2026. Its opportunity in the space could become even larger as AI clusters scale further and require increasingly powerful networking infrastructure to connect many thousands of accelerator chips together.
Image source: Getty Images.
Networking is becoming a major growth engine Modern AI systems increasingly depend on high-performance networking as well as raw computing power. Training and running increasingly sophisticated models requires massive amounts of data to be moved rapidly among large numbers of accelerators and data storage devices. If the network cannot keep up, communication can become a bottleneck that reduces GPU utilization and slows AI workloads.
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Nvidia's NVLink technology connects GPUs inside powerful AI rack systems, while Spectrum-X Ethernet connects servers and racks across larger data centers. As AI systems scale, the company has more opportunities to sell networking and interconnect technology alongside its computing hardware.
According to research firm IDC, Nvidia captured 21.5% of data center Ethernet switching revenue in the first quarter of 2026, making it the market leader.
Custom AI chips are strengthening the networking opportunity Custom AI chips are a growing competitive threat to Nvidia's GPUs. But the NVLink Fusion rack-scale platform could cushion the company against that threat by allowing some custom processors to work alongside its networking and infrastructure technologies. That gives it another way to benefit from the rising AI infrastructure spending, even in cases when it doesn't supply the AI accelerators.
Nvidia has also expanded its partnership with custom chip designer Marvell Technology (MRVL +2.25%). Under the partnership, Marvell will provide custom accelerators and the networking hardware needed to connect those processors at high speeds, while Nvidia will supply technologies including NVLink high-speed interconnect technology, Spectrum-X switches, ConnectX network adapters, and BlueField data processing units.
Nvidia's networking business will not benefit from every custom AI chip. Customers can still choose competing networking technologies, and its networking gains may not fully compensate for the loss of lucrative GPU sales to rival chipmakers.
Competition is also significant, with market research firm IDC estimating Arista Networks' share of the data center Ethernet switching market at 20.7%, marginally below Nvidia's 21.5% share.
Still, Nvidia is trying to sell more of the technology that goes into each AI data center, rather than relying so heavily on its GPUs.
Networking could help support a $7.5 trillion market capitalization for Nvidia Nvidia is trading now at around 24.1 times Wall Street's fiscal 2027 earnings estimate of about $9 per share (as of Aug. 12). Analysts currently expect its earnings to increase to approximately $12.90 per share in fiscal 2028.
If Nvidia delivers on those expectations and continues to trade at roughly the same forward valuation, its market capitalization could approach $7.5 trillion, compared to roughly $5.3 trillion today. However, valuation compression would limit its upside even if earnings rise.
Still, networking is no longer a peripheral business for Nvidia. As AI factories become larger and more communication-intensive, Nvidia's ability to sell more of the infrastructure surrounding its chips could become an increasingly important part of its next phase of growth.
I know, I know: Nvidia (NVDA +3.03%) is already the largest company in the world, with a current market cap of $5.4 trillion. If its stock rises to about $250 per share, it would make Nvidia the first $6 trillion company in history.
To put that in perspective, at $6 trillion, Nvidia would be worth more than Amazon, Meta Platforms, Tesla, and Netflix combined.
But given how much Nvidia's revenue and earnings have grown, and how much CEO Jensen Huang has done to ensure the company's long-term dominance, it's actually kind of amazing that the company isn't already trading at $250 per share ... or more.
Here's the simple math that explains why I'm predicting a $6 trillion market cap for Nvidia by the end of the year.
Image source: Nvidia.
All about value Over the last three years, Nvidia's revenue, profits, and share price have all soared, but its valuation has actually dropped. Its price-to-earnings (P/E) ratio, which stood at about 100 times trailing earnings three years ago, has now dropped to 34. Its price-to-sales (P/S) ratio, which was at about 35 times sales, has tumbled to 22 over the same time frame.
And that's just on a trailing basis. If we look at the company's projections for revenue and net income, Nvidia is currently trading at 25 times forward earnings and a mere 14 times sales. Both its trailing and forward P/E ratios are much lower than those of less-successful chipmakers Intel and Advanced Micro Devices, and are even lower than Apple's.
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In Nvidia's most recent quarter, revenue was up 85% year over year, and net income was up 211%, beating expectations. The spending boom in artificial intelligence (AI) shows no signs of slowing. Although Nvidia's share price is up just 22.5% over the past year, investors should soon realize how much of a bargain Nvidia is at its current price.
That's why I'm predicting we'll see Nvidia's stock hit $250 per share and a total market cap of $6 trillion before the end of December.
John Bromels has positions in Amazon, Apple, Meta Platforms, Netflix, Nvidia, and Tesla. The Motley Fool has positions in and recommends Advanced Micro Devices, Amazon, Apple, Intel, Meta Platforms, Netflix, Nvidia, and Tesla. The Motley Fool has a disclosure policy.
When Jensen Huang flew to Tokyo last month and signed seven Japanese industrial giants into Nvidia's (NVDA +3.03%) new physical AI coalition, he was locking in a massive, long-lived stream of demand for Nvidia's chips and software, and that is something I think investors should really pay attention to.
Nvidia CEO Jensen Huang. Image source: Nvidia.
"Physical AI" refers to AI that controls robots, factory lines, and machines in the real world instead of just chatbots on a screen. In mid-July, Nvidia announced that companies like Fujitsu, FANUC, Yaskawa Electric, and Kawasaki Heavy Industries, along with Hitachi, NEC, SoftBank, Sony, and Kubota, intend to build on its Cosmos, Isaac, Metropolis, and Jetson platforms as part of a "Cosmos Coalition" focused on physical AI. Put simply, these are some of Japan's biggest names in robotics, manufacturing, and communications agreeing to standardize on Nvidia's stack as they build the brains for next-generation industrial automation.
Behind the coalition sits an even larger national project. Nvidia is partnering with Noetra, a Japanese AI consortium backed by Sony, SoftBank, Honda, and dozens of other firms, to build what it calls the world's first national infrastructure for physical AI. The centerpiece of that effort will be a Vera Rubin AI factory that will feature 13,750 Vera CPUs and 27,500 Rubin GPUs, delivering about 140 megawatts of compute capacity to train and deploy physical AI models. Japan's industry ministry has framed this as the computing backbone for its FRONTia program, and expects that it will help the country hit its goal of capturing 30% of the global AI robotics market by 2040.
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What about Nvidia shareholders? On top of that, Prime Minister Sanae Takaichi's government has laid out a plan to mobilize more than 370 trillion yen ($2.3 trillion) in combined public and private investment by 2040 across physical AI, semiconductors, and data centers. Noetra's own roadmap calls for roughly 1 trillion yen ($6.3 billion) of sovereign AI spending over five years to develop domestic foundation models for robots and industrial AI. When you add up the national AI factory, the robot makers building on Cosmos, and Japan's broader tech investment targets, you are talking about demand that lives comfortably in the trillion-dollar range over the coming decades.
For Nvidia shareholders, the important part is not just that these orders exist. It is that they represent multiyear infrastructure-level commitments that are hard to unwind. FANUC and Yaskawa are not going to rip out their control platforms every cycle. A sovereign AI factory is not built for a single experiment. By turning physical AI into a coalition and tying it to Japan's long-term industrial strategy, Huang is trying to make Nvidia's chips and tools the default choice for robots and factories in one of the world's most advanced manufacturing economies.
That is what confirmed demand really means here. It is not a one-off spike in GPU sales. It is governments and industrial giants literally planning their futures around Nvidia's hardware and software, which gives its shareholders much more visibility into where revenue and profit margins might come from years down the line.
Obsah:
00:41 AI cyklus jede dál
01:57 Návratnost investic
04:43 IPO Anthropic a OpenAI
06:02 Boj o kapitál
07:59 Compute jako nová třída aktiv
13:45 Univerzální Nvidia
21:29 Pozitivní AI obrázek
Výsledková sezóna nepřinesla jediný zásadní signál, který by zpochybňoval pokračování investičního cyklu kolem umělé inteligence. AI investiční příběh se tak po další výsledkové sezóně nejen nezhoršil, ale v některých ohledech vypadá ještě přesvědčivěji než před několika měsíci. Branislav Soták zůstává přesvědčený, že poptávka po výpočetním výkonu stále převyšuje nabídku a že současný cyklus investic do umělé inteligence má prostor pokračovat. „Za celou výsledkovou sezónu si momentálně nedokážu vybavit jediné vysloveně špatné číslo. Samozřejmě jsme místy viděli slabší reakce akcií na výsledky, ale jednotlivé indikace o stavu AI cyklu prakticky všechny ukazují, že bude pokračovat,“ říká Soták.
Kdo na AI skutečně vydělává?
Jednou z klíčových otázek současného cyklu zůstává monetizace. Podle Sotáka se paradoxně jako rizikovější část AI ekosystému profilují společnosti na jeho konci – takzvané frontier AI laboratoře, které vyvíjejí nejpokročilejší modely. Patří sem například OpenAI nebo Anthropic. Ekonomika samotných modelů je navíc pod tlakem konkurence. Open-source modely ze Západu i z Číny tlačí ceny dolů a část výpočetní zátěže se přesouvá k volně dostupným a méně výkonným modelům. To podle Sotáka znamená, že zisková marže se zatím ve větší míře přesouvá jinam. „Zatím ten profit podle všeho zůstává v hardwaru,“ říká.
Výsledková sezóna přesto přinesla pozitivní signály i ze softwarové části trhu. Soták jako výrazného vítěze zmiňuje Microsoft, přičemž velmi dobrá čísla představil také Palantir. Hodnota se tak podle něj začíná ukazovat i u firem, které vlastní infrastrukturu nebo vrstvu pod samotnými jazykovými modely.
IPO Anthropic ano, u OpenAI je Soták opatrnější
Pozornost investorů se bude soustředit také na budoucí IPO společností Anthropic a OpenAI. U první z nich je Soták výrazně optimističtější. „Anthropic je nejrychleji rostoucí firmou a podle všech indicií dokáže růst dokonce profitabilně i na frontier vrstvě, která je poměrně drahá. Pokud se dostane na trh, jeho IPO velmi pravděpodobně bude úspěšné,“ míní.
U OpenAI je naopak opatrnější. Problém podle něj není pouze v managementu, ale především v ekonomice podnikání. Firma sice rychle roste, její růst je ale velmi nákladný a spotřebovává prakticky všechny generované tržby. „OpenAI stále funguje se ztrátou a myslím, že k bodu zvratu má ještě poměrně daleko. Tady bych takovým optimistou nebyl,“ říká.
Na scénu vstupuje „compute“ jako nová třída aktiv
Případná dvě velká IPO navíc přicházejí v době, kdy se o kapitál uchází stále více projektů. Konkurence na kapitálových trzích roste nejen kvůli obrovskému americkému rozpočtovému deficitu, ale také kvůli makroekonomickému vývoji v Japonsku a financování samotné AI infrastruktury. Právě zde Soták vidí jeden z nejzajímavějších posunů posledních týdnů: Nvidia společně s velkými finančními institucemi, mezi něž patří Goldman Sachs, BlackRock či Blackstone, oznámila záměr mobilizovat až 500 miliard dolarů institucionálního kapitálu pro financování výpočetního výkonu. Výpočetní výkon by se tak mohl stát samostatně investovatelnou třídou aktiv. To může podle Sotáka zásadně změnit dostupnost a cenu kapitálu pro výstavbu datacenter.
„Třetí strany budou schopné investovat do výpočetního výkonu jako do nezávislé třídy aktiv. To je velmi zajímavé z hlediska dostupnosti kapitálu i nákladů financování,“ říká. Argumentem je podle něj i velikost potenciálního kapitálu. David Solomon z Goldman Sachs v této souvislosti upozornil, že jen v amerických money-market fondech je zaparkováno přibližně 9 bilionů dolarů, zatímco americký akciový trh má kapitalizaci kolem 100 bilionů dolarů. Kapitálu tedy podle Sotáka na trhu pravděpodobně je dostatek, jde především o to vytvořit mechanismus, který jej nasměruje do nové třídy aktiv.
V budoucnu si přitom lze představit standardizované finanční produkty navázané na výpočetní výkon – například forwardy či futures na kapacitu datacenter. „Mohou vzniknout standardizované produkty a otevřít se nový trh, který těm, kdo tuto infrastrukturu financují, zajistí větší dostupnost kapitálu a kapitál také zlevní,“ říká.
Současně ale upozorňuje, že finanční inženýrství samo o sobě neřeší otázku návratnosti. Právě zde vzniká paralela s hypoteční krizí, která je s podobnými finančními konstrukcemi historicky spojována. „Zatím tak daleko ještě nejsme. Finanční trhy jsou od toho, aby efektivně alokovaly kapitál, a většinu času to dělají poměrně dobře,“ konstatuje Soták. Riziko podle něj vzniká ve chvíli, kdy se na produktivní aktiva začne nabalovat příliš mnoho spekulace.
Zatím podle něj ale trh spíše vytváří novou investiční infrastrukturu než spekulativní bublinu. A první výsledky naznačují, že financování skutečně zlevňuje. CoreWeave například podle posledních výsledků zaznamenal meziroční pokles procentních nákladů na obsluhu dluhu.
Nvidia získává další výhodu
Nový způsob financování může být důležitý také pro samotnou Nvidii. Pokud se budou datacentra financovat jako samostatná produktivní aktiva, bude záležet na tom, jaký hardware v nich bude instalován. A právě zde má Nvidia podle Sotáka silnou pozici. Její čipy jsou univerzální a podporují širokou škálu modelů. Nad hardwarem navíc stojí softwarová vrstva CUDA, která umožňuje výkon dále optimalizovat.
Ještě důležitější je podle něj skutečnost, že Nvidia je ochotna poskytnout záruky za část financování. Pokud by nebyla dostatečná poptávka po nově vybudovaných kapacitách, Nvidia by podle oznámení převzala reziduální hodnotu části hardwaru. To přímo míří na jeden z hlavních argumentů medvědů kolem AI. Ti upozorňují, že hardware může zastarávat rychleji, než se investice vrátí.
Praxe ale podle Sotáka začíná ukazovat něco jiného. Hyperscaleři původně počítali s užitečnou životností GPU serverů kolem tří let, dnes ji řada z nich prodlužuje až na šest let. CoreWeave navíc uzavřel kontrakt na cluster postavený na čipech Nvidia A100 z roku 2020, který má trvat až do roku 2029. „To znamená, že i devět let po uvedení a instalaci čipu si tento hardware stále najde ekonomické využití. To poměrně výrazně nabourává tezi o rychlé depreciaci a negativním dopadu na profitabilitu,“ upozorňuje Soták.
Dalším argumentem je vývoj cen za pronájem GPU výkonu. U čipů H100 podle Nvidie vzrostla cena zhruba z 1,70 dolaru za GPU hodinu v roce 2025 na 2,40 dolaru. U novějšího Blackwellu se ve stejném období cena zvýšila přibližně z 5,30 na 7 dolarů. Podle Sotáka to podporuje tezi, že AI datacentrum není pouze rychle zastarávající hardware, ale může představovat produktivní aktivum, jehož výnosnost se díky růstu poptávky, cenové síle a technologickému pokroku zvyšuje.
Nvidia zůstává první volbou
Pokud jde o samotné investice do polovodičového řetězce, Soták v současnosti nevidí důvod hledat složitější alternativu. „Pokud se bavíme o poměru očekávaného nebo viditelného růstu a ceny, byla by to v tuto chvíli Nvidia. Moc bych nespekuloval s jinými jmény a volil bych lídra,“ říká. Nvidia je podle něj výjimečná tím, že má expozici na více částí dodavatelského řetězce. A zatímco se často hovoří o jednotlivých úzkých hrdlech, jejich význam je nakonec odvozen od samotné poptávky po výpočetním výkonu. Tu Nvidia stále ve velké míře obsluhuje.
Nová generace Vera Rubin by navíc měla podle Sotáka nabíhat do výroby rychleji než Blackwell. „Tempo růstu, které je enormní z té velké báze, na které Nvidia je, se pravděpodobně ani v dohledné době výrazně nezpomalí,“ domnívá se.
Příležitosti vidí ale i v síťové a optické infrastruktuře. Výsledky společností Lumentum a Coherent by měly přinést další indikaci o síle této poptávky. Rychlejší datová centra podle Sotáka totiž narážejí na fyzikální limity měděných spojů, což podporuje přechod k optickým technologiím. Valuace těchto firem jsou ovšem podle něj oproti Nvidii na jiné úrovni.
AI cyklus zůstává v dobré kondici
Celkový obrázek po výsledkové sezóně je tak podle Sotáka pozitivní. A možná ještě pozitivnější než na jejím začátku. Důležitá je přitom nejen síla jednotlivých firem, ale skutečnost, že AI komplex má dnes výrazný vliv na celý akciový trh. Když se v červenci AI segment otřásl, otřásl se podle Sotáka i celý trh. „Celková zpráva o stavu AI cyklu je z mého pohledu i po této výsledkové sezóně velmi pozitivní a možná pozitivnější, než byla na jejím začátku,“ uzavírá.
The much-anticipated initial public offering (IPO) of Space Exploration Technologies (SPCX +9.65%) and its aftermath have been a roller-coaster ride for investors. While shares initially surged, they are now down by 41% from the all-time high of roughly $226 they reached in mid-June, and below where they opened on their first day of trading. But is the stock on track for more downside or a long-term rebound? What might the next five years have in store?
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Space is no longer the key growth driver When it was still a privately held company, SpaceX became known for its industry-leading rocket-launch business. It developed some of the world's largest and most powerful rockets, capable of transporting high-value payloads and even humans to space. It also developed a leading satellite-based broadband internet solution called Starlink that brought wireless connectivity to the most remote areas on Earth.
Both of these businesses are still important. In the second quarter, the space and connectivity segments combined represented just over 67% of SpaceX's total revenue. However, the company's burgeoning AI business is likely to be the bigger story over the next few years.
In February, SpaceX purchased CEO Elon Musk's social media and AI company xAI in an all-stock transaction that valued it at $250 billion. The deal gave the combined entity access to xAI's frontier large language model, Grok, and to the company's enormous hardware resources. These include the Colossus supercomputing facilities, which boast over 1 million Nvidia H100 graphics processing unit (GPU) equivalents.
Is AI an opportunity or a mistake? SpaceX's pivot to AI gives it substantial new revenue opportunities. The benefits of this are already beginning to show. For example, Q2 revenue soared 92% year over year to $7.81 billion, helped by an eye-popping 248% increase in sales from the company's AI segment as clients clamor for access to its hardware.
SpaceX has signed a series of high-profile deals, including one that will see Anthropic renting out the computing capacity of roughly 325,000 Nvidia GPUs from its Colossus data centers for $1.25 billion each month. The company has a similar deal with Alphabet's Google worth $920 million per month. In the best-case scenario, these contracts could net SpaceX an eye-popping $26 billion in annual revenue, practically ensuring high-double-digit percentage top-line growth for the next few quarters.
Image source: Getty Images.
SpaceX's leadership also has plans to keep the company dominant over the longer term. It is working alongside Musk's electric vehicle maker, Tesla, to build a massive semiconductor manufacturing facility called Terafab, which is expected to eventually produce 1 terawatt (TW) of AI compute capacity per year (more than the current global supply), with the chips to be divided between the two companies.
While that ambitious chip manufacturing plan sounds great, it won't come cheap. The capital investments SpaceX and Tesla will need to put into the first phase of Terafab are expected to be $16.8 billion. Furthermore, a regulatory filing in May revealed that the total capex required could soar to $119 billion if all the planned additional phases are completed. This represents more than a tenth of a trillion dollars in capital that could have been used for other projects or returned to investors via stock buybacks or dividends. The success or failure of this project will have an immense effect on the company's stock performance.
What will the next five years look like? Over the next five years, SpaceX looks likely to continue experiencing breakneck top-line growth as it scales up its AI infrastructure business. That said, the boom almost certainly won't last forever, because the companies that are currently spending the largest sums on computing power are already shifting toward designing their own chips. Rising competition in the AI processor space will likely bring down growth and margins across the industry.
While SpaceX's price-to-sales (P/S) ratio has plunged from roughly 116 in June to 61 today, it still looks very elevated compared to the S&P 500's average P/S ratio of 3.8. Investors might want to wait for more information before considering a long-term position in the stock.
In this video, I will cover CoreWeave and Nebius' latest earnings reports and explain why Nvidia (NVDA +3.03%) is still the king of AI despite the competition. Watch the short video to learn more, consider subscribing, and click the special offer link below.
*Stock prices used were from the trading day of Aug. 11, 2026. The video was published on Aug. 12, 2026.
Neil Rozenbaum has positions in CoreWeave and Nebius Group. The Motley Fool has positions in and recommends Nvidia. The Motley Fool has a disclosure policy. Neil is an affiliate of The Motley Fool and may be compensated for promoting its services. If you choose to subscribe through his link, he will earn some extra money that supports his channel. His opinions remain his own and are unaffected by The Motley Fool.
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The GraniteShares 2x Long AMD Daily ETF (NASDAQ:AMDL) gives you a simple way to double down on one of the semiconductor industry’s biggest potential winners. The fund seeks twice the daily performance of Advanced Micro Devices (NASDAQ:AMD | AMD Price Prediction), turning every gain (as well as every loss) into something much larger. That sounds attractive as AMD continues to grow its AI business. The catch is that buying AMDL does not just double your exposure to AMD. It also doubles your exposure to the company’s biggest challenge: catching Nvidia (NASDAQ:NVDA), which still dominates the AI accelerator market.
AMD’s AI Growth Is Real — But Nvidia Is Still the Standard AMD has plenty of momentum. Second-quarter revenue reached a record $11.54 billion, up 50% year over year. Data Center revenue more than doubled to $6.72 billion as demand for EPYC processors and Instinct AI accelerators continues to grow. Management also guided for roughly $13 billion in third-quarter revenue, ahead of Wall Street expectations. Those numbers solidify AMD as a legitimate AI infrastructure company rather than simply a CPU manufacturer.
The challenge is scale. Nvidia generated more than $81 billion of revenue in a single quarter, with its Data Center business continuing to dwarf AMD’s. Nvidia also benefits from its CUDA software ecosystem, networking products, and integrated AI platform that many enterprise customers have already standardized on. While AMD continues to win customers and gain market share, investors are ultimately betting on how quickly that gap can narrow. If AMD’s AI business grows slower than expected, AMDL shareholders will feel that disappointment twice as much.
How AMDL’s 2X Daily Leverage Changes the Investment AMDL seeks to deliver 200% of AMD’s daily return, not twice AMD’s long-term performance. That distinction matters. Because the fund resets its leverage every trading day, returns become path dependent. During strong, sustained rallies, leverage can amplify gains beyond what many investors expect. However, during volatile periods, daily compounding can steadily erode returns even if AMD ultimately finishes near where it started (a phenomenon known as volatility decay).
That risk is especially relevant for AMD. The stock frequently experiences large moves following earnings reports, AI product announcements, hyperscaler contract wins, and developments involving its largest competitor, Nvidia. Those swings become significantly larger inside AMDL. Investors should also remember that the fund carries a substantially higher expense ratio than simply owning AMD shares (current expense ratio = 1.07%), making it better suited for tactical positioning than long-term buy-and-hold investing.
Key Fund Statistics Before investing, it is worth understanding exactly how AMDL is structured. Unlike owning AMD directly, investors are purchasing a leveraged product designed to achieve a specific daily objective. Key fund metrics are included in the table below.
Metric AMDL Inception Date March 4, 2024 Investment Objective 2× Daily AMD Performance Net Assets $1.05B Expense Ratio 1.07% YTD Total Return +236.27% (Compared to +125.70% for AMD) 1-year Total Return +330.02% (Compared to +180.37% for AMD) Since Fund Inception +104.98% (Compared to +135.37% for AMD) Max Historical Drawdown -88.63% What This Means for You AMD continues to execute well. Revenue growth remains impressive, the Data Center business is expanding rapidly, and the company is steadily becoming a larger player in the AI infrastructure space. If AMD continues to gain market share, AMDL can magnify those gains.
However, this ETF also magnifies AMD’s biggest uncertainty. Nvidia remains the industry’s dominant force, and even small disappointments in AMD’s execution can translate into outsized negative swings for AMDL investors. For traders with a strong short-term conviction on AMD, the leverage can be attractive. For long-term investors, owning AMD shares directly is likely the more predictable way to benefit if the company’s AI strategy continues to succeed.
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Michael Intrator, co-founder and chief executive officer of CoreWeave. Bloomberg/Getty Images AI cloud company CoreWeave just offered fresh evidence in one of the biggest debates hanging over the AI boom: How long can AI chips stay useful and keep generating revenue?
The AI cloud company recently signed a contract to rent out Nvidia A100 GPUs well into 2029, CoreWeave Chief Financial Officer Nitin Agrawal told analysts late Tuesday. Nvidia introduced the A100 in 2020.
That means customers are committing to use these chips for running AI about nine years after their launch.
This matters because investors have been fiercely debating how quickly AI hardware loses its economic value. Critics and short sellers have argued that rapid advances from Nvidia could make older chips obsolete within two or three years. If that happened, companies spending billions of dollars on AI infrastructure might have to write down those investments much faster, hurting profits.
CoreWeave's latest deal suggests the opposite may be happening.
"We recently signed an A100 contract that extends into 2029 at an attractive price," Agrawal said. CoreWeave is also "largely sold out" of older generations of Nvidia chips, he added.
I first raised this depreciation risk before CoreWeave went public. Since then, evidence has increasingly suggested that useful GPU lives may be longer than feared. CoreWeave shares have surged since the initial public offering and jumped 20% on Wednesday.
Rental-market data backs up the company's comments. Silicon Data, which tracks GPU prices, says A100 rental rates have held up well after a strong rebound in 2026.
"We are still learning when it comes to the question of economic lifespan of GPUs. It certainly doesn't appear to be 2-3 years as some seem to casually assume," Silicon Data wrote in a post on X on Tuesday.
There are good reasons older GPUs can remain useful.
The newest chips are important for building the most advanced AI models. Once those models are created, companies have many other computing jobs that don't require the latest hardware. Older GPUs can be repurposed for these less demanding tasks and continue generating revenue.
Erwan Menard, a senior vice president at AI infrastructure company Crusoe, told me last year that GPUs can move from one type of work to another as they age. Lambda executive Matt Rowe has said their effective lives can stretch to seven or eight years.
GPUs inevitably break and have to be replaced. That cuts the useful life of a fleet of GPUs. However, observers worrying about depreciation often overlook warranty contracts, Rowe told me late last year. These warranties typically last five years, so if GPUs fail, they are replaced with new ones, extending the life of the overall GPU fleet.
The issue of GPUs' useful lives has become more important as Wall Street pours money into AI infrastructure. Nvidia this week announced partnerships with Apollo, BlackRock, Blackstone, Brookfield, Goldman Sachs, and KKR aimed at mobilizing more than $500 billion over time.
Those investments depend in part on AI hardware retaining its value for years.
An A100 still attracting customers into 2029 is a powerful test of that assumption, and, so far, an encouraging one.
Sign up for BI's Tech Memo newsletter here. Reach out to me via email at [email protected].
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Alistair Barr You're currently following this author! Want to unfollow? Unsubscribe via the link in your email.
Alistair Barr is the author of Business Insider's Tech Memo newsletter and the driving force behind the company's AI Insider franchise. Sign up here. Before that, he was Business Insider's Global Tech Editor and the Big Tech team leader at Bloomberg, following a reporting career at The Wall Street Journal, USA Today, Reuters, and MarketWatch. Alistair covers all things Big Tech, along with startups and venture capital. He writes analysis and columns about topics including AI, cloud computing, data centers, semiconductors, online search, e-commerce, EVs, robotics, and autonomous vehicles.
Artificial Intelligence Cloud Computing Earnings More AI
Nvidia (NVDA +2.84%) may have been one of the greatest stock investments in the history of the market, but that doesn't mean its winning streak can go on forever. It often happens that by the time a stock gets the wider market's notice for a great run-up, its most thrilling gains are already behind it. But that doesn't mean that widely known and popular stocks can't still create shareholder value.
Image source: Nvidia.
So what's happening with Nvidia? It has been following the general trajectory of the S&P 500 for most of the year, and as of this writing, it's up 20% versus 14% for the broader index. That's a fair beat, but it's not on par with the massive gains it's delivered in the past. Let's see what might be on the table for the chip stock in the coming weeks and months.
The gold standard for AI chips Nvidia became a household name after the artificial intelligence (AI) megatrend exploded, but it was a successful business and an excellent investment well before that. In 2021, when AI was still a futuristic concept to most non-techies, Nvidia was a leader in video game hardware, and its stock more than doubled.
ChatGPT was released toward the end of 2022, and Nvidia's graphics processing units (GPUs), originally designed to improve the rendering of video game graphics, quickly became the gold standard for providing the parallel processing power required by generative AI. Since then, Nvidia stock has skyrocketed. Moreover, there's a fairly clear pattern for how Nvidia stock performs through the end of July and what happens through the remainder of the year.
If 2026 follows the general pattern of the past five years, it's likely to end the year higher than it's trading right now, but not by that much. That's been the pattern for the past four years -- with most of the stock's price action occurring in the first seven months. 2021 was an exception -- most of Nvidia's gains came closer to the end of that year.
The epicenter of AI Over the past four years, AI has changed tremendously, with a vast array of large language models and agentic AI services, but Nvidia is still the linchpin. It provides chips and whole infrastructure ecosystems for hyperscaler clients, and it's deeply embedded into their systems -- a condition that creates high barriers to entry for would-be competitors. For its fiscal 2027 second quarter, which ended July 26, management is guiding for 95% revenue growth year over year.
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However, the stock's gains have been slowing down, even as the business speeds up. Nvidia is already the most valuable company in the world by market cap, and Wall Street is being very deliberate about its stock. Even if it beats expectations for fiscal Q2, which is likely, the market's reaction could be muted.
Nvidia (NVDA) is expanding its role in the artificial intelligence industry by helping finance the infrastructure needed to support growing demand, with a $500
NVIDIA (NVDA), the chip giant powering the AI boom, jumped approximately 2.5% in Wednesday morning trading after unveiling an ambitious plan that could throw ev
NVIDIA Corporation (NVDA) shares rise 84,714% since 2000’s first institutional outlier signal.
In this article:NVDA
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NVDA’s computer graphics processors, chipsets, and related software are at the forefront of AI, which is why it partnered with financial giants to establish a $500 billion AI infrastructure financing platform to attract third-party capital for AI projects. In its first-quarter fiscal 2027 earnings, the company showed $82 billion in total revenue (an 85% year-over-year gain) of which $75 billion came from data centers, a 74.9% GAAP gross margin, and issued quarterly revenue guidance of $91 billion (plus or minus 2%).
It’s no wonder NVDA shares are up 17% so far this year – and they could rise more. MoneyFlows data shows how Big Money investors are again betting heavily on the stock.
NVIDIA, a Big Money Favorite Institutional volumes reveal plenty. In the last year, NVDA has enjoyed strong investor demand, which we believe to be institutional support.
Each green bar signals unusually large volumes in NVDA shares. They reflect our proprietary inflow signal, pushing the stock higher:
NVDA shares are up 18.8% in a year thanks to institutional support. Source: www.moneyflows.com Plenty of technology names are under accumulation right now. But there’s a powerful fundamental story happening with NVIDIA.
NVIDIA Fundamental Analysis Institutional support and a healthy fundamental backdrop make this company worth investigating. As you can see, NVDA has had strong sales and earnings growth:
Also, EPS is estimated to ramp higher this year by +42%.
Now it makes sense why the stock has been generating Big Money interest. NVDA has a track record of strong financial performance.
Marrying great fundamentals with MoneyFlows software has found some big winning stocks over the long term.
NVIDIA has been a top-rated stock at MoneyFlows for years. That means the stock has unusual buy pressure and growing fundamentals. We have a ranking process that showcases stocks like this on a weekly basis.
It’s up 84,714% since its first appearance on the rare Outlier 20 report in June 2000 – it’s had 113 total appearances. Institutions keep buying. The blue bars below show when NVDA was a top pick in the last five years – Big Money support matters:
Bursts of outlier institutional inflow signals have sent NVDA shares from below $50 to over $200 in the last five years. Source: www.moneyflows.com Tracking unusual volumes reveals the power of money flows.
This is a trait that most outlier stocks exhibit…the best of the best. Big Money demand drives stocks upward.
NVIDIA Price Prediction The NVDA action isn’t new at all. Big Money buying in the shares is signaling to take notice. Given the historical gains in share price and strong fundamentals, this stock could be worth a spot in a diversified portfolio.
Disclosure: the author holds no position in NVDA at the time of publication.
If you are a Registered Investment Advisor (RIA) or are a serious investor, take your investing to the next level and follow our free weekly MoneyFlows insights.
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Lucas is a well-versed equity investor and educator. He currently is co-founder of research and analytics firm, MAPsignals.com, which focuses on finding outlier stocks by following the Big Money.
As Nvidia Corp. (NASDAQ: NVDA) stock price rallied over 17% between July 29, 2026, and August 12, more Wall Street analysts expect the company’s share to hit a new all-time high (ATH) over the next 12 months.
On August 12, James Schneider, an expert at Goldman Sachs Group Inc. (NYSE: GS), reiterated a ‘Buy’ rating for Nvidia stock. Schneider also maintained the bank’s 12-month price target for NVDA at $285, suggesting a potential 27.66% upside.
Ahead of Nvidia’s quarterly earnings report on August 26, 2026, the firm expects investors to focus on the details of the company’s recently announced $500 billion financing platform with its partners. Additionally, Schneider said that investors should be interested in the shape of the Rubin product ramp in the second half, future gross margin trends, and potential upside from agentic AI to central processing units (CPUs).
Wall Street signals bullish sentiment for Nvidia stock Earlier on Wednesday, Christopher Rolland, an analyst at Susquehanna, reaffirmed a ‘Buy’ rating for Nvidia. He maintained the firm’s 12-month price target for this company at $275, signaling a possible 23.05% uptick.
As such, 37 analysts surveyed by TipRanks have set an average price target for NVDA at $309.94, which represents a likely 38.92% growth trajectory. Worth noting that the highest 12-month price target for NVDA share price is $500, while the lowest is $250.
Over the past six months, NVDA stock price has surged more than 20%, currently retesting a strong supply level at approximately $223.25. As a result, the company had a market capitalization of $5.3 trillion.
NVDA’s 6-month chart. Source: Finbold If Nvidia’s stock price continues its established macro uptrend, these analysts’ targets of a new ATH in the next 12 months could be realized.
Featured image via Shutterstock
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HomeIndustriesComputers/ElectronicsTech StocksTech StocksInvestors are concerned that Alphabet faces a fresh threat from Nvidia’s plans to help fund the AI buildout alongside major Wall Street playersAug. 12, 2026, 2:19 p.m. ET
Alphabet’s artificial-intelligence capabilities have received intense scrutiny in recent weeks as its latest Gemini model experiences delays. Now, another cornerstone of the company’s AI strategy — its in-house hardware — is coming under question thanks to Nvidia’s latest AI financing plans.
After falling 4% on Monday, Alphabet shares GOOGL GOOG shares were down 0.3% in Tuesday’s trading. To some investors, Nvidia’s NVDA $500 billion partnership with Wall Street firms to fund AI-infrastructure development poses a significant headwind to Alphabet’s custom chips, according to Jefferies buy-side analyst Jeffrey Favuzza. By making Nvidia infrastructure available through favorable financing options, the deal could make custom silicon options less attractive for customers.
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Key Takeaways NVIDIA is partnering with six financial firms to mobilize more than $500B of third-party capital.The financing effort aims to ease AI factory funding hurdles and support expansion of computing capacity.NVDA posted 85% revenue growth in fiscal Q1 2027, while Q2 revenues are expected to reach $91 billion. NVIDIA Corporation (NVDA - Free Report) is taking a major step to accelerate the AI infrastructure buildout by partnering with six leading financial institutions to create financing platforms that could mobilize more than $500 billion of third-party capital over time. The partnerships involve Apollo, BlackRock, Blackstone, Brookfield, Goldman Sachs and KKR.
The initiative could become an important growth catalyst because financing has emerged as a key hurdle for customers seeking to build large AI factories. By connecting customers with long-term capital, NVIDIA aims to make it easier for AI labs, enterprises and AI cloud providers to expand computing capacity. This could translate into stronger demand for NVIDIA’s graphics processing units (GPUs), networking products and software.
The strategy also creates a potentially longer revenue runway. NVIDIA describes its compute as an asset that can remain useful across different customers and workloads, with its CUDA software ecosystem helping extend its economic life. This flexibility could make NVIDIA-based infrastructure more attractive to investors and operators financing large projects.
The $500 billion figure represents capital that financing platforms aim to mobilize, not revenues or funding directly provided by NVIDIA. Still, if the initiative successfully lowers financing barriers, it could expand the number and scale of AI factories using NVIDIA technology. This would strengthen hardware demand while increasing software adoption, potentially supporting NVIDIA’s long-term revenue growth.
In the first quarter of fiscal 2027, NVIDIA’s revenues surged 85% year over year to $81.62 billion. Management’s expectations of $91 billion in revenues for the second quarter indicate year-over-year growth of approximately 95%. The Zacks Consensus Estimate for fiscal 2027 revenues is currently pegged at $387.93 billion, calling for a nearly 80% year-over-year increase.
Could Rivals Challenge NVIDIA’s AI Financing Edge?NVIDIA’s financing strategy could widen its lead, but Advanced Micro Devices, Inc. (AMD - Free Report) and Broadcom Inc. (AVGO - Free Report) are building strong alternatives for customers investing in AI infrastructure.
Advanced Micro Devices’ Data Center business generated $6.72 billion in second-quarter 2026 revenues, up 107% year over year, driven by EPYC CPUs and Instinct GPUs. The company is also expanding large-scale partnerships, including a plan with Meta to deploy up to 6 gigawatts of Instinct GPUs. Advanced Micro Devices and Tata Consultancy Services are co-developing a 200MW deployment of the AMD "Helios" open rack-scale AI architecture in India.
Broadcom is taking a different route by focusing on custom AI accelerators and networking. Its approach allows large technology companies to build chips tailored to specific workloads, potentially reducing reliance on general-purpose GPUs. This could become important as AI infrastructure spending expands and customers look for multiple ways to finance and deploy computing capacity. In the second quarter of fiscal 2026, Broadcom’s revenues soared 48% year over year to $22.19 billion.
NVIDIA, however, has a notable advantage in the financing initiative. The recent collaboration with top financial institutions will potentially make NVIDIA-based AI factories easier to fund.
Advanced Micro Devices and Broadcom can compete through alternative hardware and infrastructure solutions, but NVIDIA’s combination of technology, CUDA software and access to large pools of capital could strengthen its position as AI spending enters another major investment cycle.
NVIDIA’s Price Performance, Valuation and EstimatesShares of NVIDIA have risen around 16.6% year to date, underperforming the Zacks Computer and Technology sector’s gain of 17.7%.
NVIDIA YTD Price Return Performance
Image Source: Zacks Investment Research
From a valuation standpoint, NVDA trades at a forward price-to-earnings ratio of 19.91, below the sector’s average of 21.53.
NVIDIA Forward 12-Month P/E Ratio
Image Source: Zacks Investment Research
The Zacks Consensus Estimate for NVIDIA’s fiscal 2027 and 2028 earnings implies a year-over-year increase of approximately 90.6% and 38.3%, respectively. Estimates for fiscal 2027 and 2028 have been revised upward over the past 30 days.
Image Source: Zacks Investment Research
NVIDIA currently carries a Zacks Rank #2 (Buy). You can see the complete list of today’s Zacks #1 Rank (Strong Buy) stocks here.
Nvidia stock NVDA rose early Wednesday as investors appeared to take some comfort from a new financing initiative involving six of Wall Street’s biggest investment firms.
Shares rose around 3% to about $223 in early trading.
The MoUs announced Monday bring together Apollo Global Management, BlackRock, Blackstone, Brookfield Asset Management, Goldman Sachs, and KKR to help mobilize more than $500 billion of third-party capital for AI infrastructure projects.
The arrangement gives Nvidia's customers access to a much larger pool of capital without requiring the chipmaker to fund the entire buildout itself.
The participating financial firms will independently evaluate individual projects and determine how much capital to commit.
That distinction matters because investors have increasingly questioned whether Nvidia’s financing arrangements could create a form of circular financing, in which the company helps customers obtain funding to buy Nvidia's own chips, supporting demand that might otherwise be weaker.
Nvidia's direct financial exposure under the new structure appears more limited than some investors had initially feared.
Morningstar said Nvidia will not provide cash to the financing platform and may instead provide support for the residual value of assets in certain cases.
Nvidia CEO Jensen Huang said the company could provide a "residual-value support mechanism for up to 25% of an opportunity," assessed on a project-by-project basis.
That potentially limits the amount of risk Nvidia takes onto its own balance sheet while allowing outside investors to finance a much larger portion of the AI infrastructure buildout.
Circular financing concerns remainThe financing structure nevertheless comes at a sensitive time for the AI industry.
Hyperscalers, including Alphabet, Amazon, Meta, and Microsoft, have been taking on substantial debt to fund data centers, computing capacity, and AI development.
The growing capital requirements have pushed credit markets to pay closer attention to whether the expected returns from AI infrastructure will justify the spending.
Nvidia has faced additional scrutiny because it has increasingly provided financial support to companies that purchase its hardware.
The company was previously reported to be discussing guarantees of as much as $250 billion to support OpenAI's lease and debt financing for a large data-center project in Ohio.
Those arrangements have raised concerns that financing could help sustain demand for Nvidia's chips even before AI infrastructure generates sufficient cash flow to support the investment.
The new Wall Street partnership is intended to address some of that concern by moving much of the funding responsibility to independent financial institutions.
Analysts remain bullish on Nvidia stockMorningstar maintained its $280 fair value estimate for Nvidia and said the financing partnerships do not change its positive view of the company's long-term growth prospects.
The research firm said Nvidia is using its position at the center of the AI ecosystem to bring additional capital into infrastructure development while expanding access to its chips.
Nvidia remains the dominant supplier of GPUs, networking equipment, and software used to build large-scale AI systems.
The company has also increasingly sought to support the broader ecosystem around its hardware as demand expands beyond the largest cloud providers.
Morningstar continues to view Nvidia's shares as undervalued, arguing that the company's medium- and long-term growth prospects remain underappreciated.
Wall Street’s AI conversation has become fixated on Nvidia Corp‘s (NASDAQ:NVDA) newest chips. CoreWeave, Inc. (NASDAQ:CRWV), however, used its second quarter earnings call to make a different point: older GPUs may have far more earning power than investors think.
The cloud infrastructure provider revealed it recently signed a customer contract for Nvidia’s A100 GPUs that extends through 2029—nearly a decade after the chip debuted.
More importantly, management suggested this isn’t an exception but evidence that AI infrastructure can continue generating attractive returns long after its first deployment.
CoreWeave Sees Long-Term Value in Older Nvidia GPUsThe clearest indication came from CFO Nitin Navin, who highlighted the longevity of one of the company’s latest deals. “We recently signed an A100 contract that extends into 2029 at an attractive price. As a reminder, this SKU was introduced in 2020,” Navin said.
CEO Michael Intrator expanded on that point, arguing the contract offers a glimpse into how AI infrastructure could be monetized over a much longer period than many investors currently assume.
“The fact that we have been able to go ahead and sell a GPU whose architecture was from 2020 in a contract that was fully priced out to 2029 really provides some insight into what the future is going to look like,” Intrator said.
Those comments challenge a common assumption in the AI infrastructure market—that each new generation of Nvidia chips quickly renders older hardware economically obsolete.
Instead, CoreWeave is signaling that mature GPUs can continue attracting customers if the workload and pricing remain attractive.
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CoreWeave’s GPU Strategy Goes Beyond the First ContractThe company also hinted that older hardware could generate revenue more than once.
Navin said every time an existing GPU is renewed or redeployed after its initial contract, the revenue comes on top of returns already earned during the original lease. “Every resale or renewal is incremental on top of the returns already earned within the initial term,” he said.
Intrator added that managed inference—a business the company expects to surpass $250 million in annual recurring revenue by the end of 2026—offers another avenue for putting GPUs coming off contract back to work rather than leaving them idle.
For investors, the takeaway extends beyond a single A100 contract. If CoreWeave can consistently renew, redeploy or repurpose older GPUs into new customer agreements and inference workloads, the economic life of its infrastructure could prove much longer than many expect.
That would allow the company to generate additional returns from assets already on its balance sheet. A dynamic that could become increasingly important as the AI market moves beyond the race for the latest chips and toward maximizing the value of existing GPU fleets.
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Nvidia Corp. (NASDAQ:NVDA) shares moved higher Wednesday as investors focused on continued AI infrastructure spending, broader semiconductor momentum and the company’s upcoming earnings report.
The company’s stock rose almost 3% as investors looked ahead to the company’s quarterly earnings report on Aug. 26, 2026. The move came as S&P 500 futures gained 0.3%, supporting risk appetite for mega-cap technology stocks.
AI Infrastructure Demand Supports Chip StocksIntel Corp. (NASDAQ:INTC) kept investor attention on AI infrastructure after increasing its equity offering to $20 billion and expecting about $19.7 billion in net proceeds.
Intel said it plans to use the funds for general corporate purposes, including working capital and capital expenditures, and expects 2026 capital spending to exceed $20 billion.
CoreWeave Inc. (NASDAQ:CRWV) and Super Micro Computer Inc. (NASDAQ:SMCI) also reported strong backlogs and continued data-center spending, reinforcing demand for AI infrastructure.
Heavy AI hardware investment by major cloud and technology companies continues to support demand for Nvidia’s chips.
Earnings & Analyst OutlookThe countdown is on: Nvidia Corp is set to report earnings on August 26, 2026 (confirmed).
EPS Estimate: $2.07 (Up from $1.04 YoY) Revenue Estimate: $91.82 Billion (Up from $46.74 Billion YoY) Valuation: P/E of 33.3x (Indicates premium valuation relative to peers) Analyst Consensus & Recent Actions: The stock carries a Buy rating with an average price forecast of $325.74. Recent analyst moves include:
Wells Fargo: Overweight (Maintains Forecast to $315.00) (Aug. 11) Keybanc: Overweight (Raises Forecast to $330.00) (July 14) China Renaissance: Initiated with Buy (Forecast $319.00) (June 5) Top ETF Exposure Franklin Focused Dynamic Growth ETF (NASDAQ:FFOG): 9.99% Weight Xtrackers Net Zero Pathway Paris Aligned US Equity ETF (NYSE:USNZ): 9.73% Weight iShares Nasdaq Top 30 Stocks ETF (NASDAQ:QTOP): 9.96% Weight Significance: Because NVDA carries such a heavy weight in these funds, any significant inflows or outflows for these ETFs will likely force automatic buying or selling of the stock.
Price ActionNVDA Stock Price Activity: Nvidia shares were trading higher by 2.66% at $223.21 at the time of publication on Wednesday, according to Benzinga Pro data.
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CoreWeave (CRWV), an AI cloud provider that rents out Nvidia (NVDA) chips, rose 15.64% premarket after reporting second-quarter revenue of $2.58 billion, up 112
Last month, American tech giants came together to urge policymakers not to place "premature restrictions" on open-weight AI models, even if they're from China. Now, two of those companies are making a concerted effort to compete by introducing their own open offerings.
Meta and Nvidia both released artificial intelligence models this week that are available for developers to download for free via the open-source ecosystem, a contrast to the popular proprietary models from OpenAI and Anthropic.
Open-source AI has become a contentious topic from Silicon Valley to Washington, D.C., with critics raising concerns about the potential national security risks of Chinese models, and of the AI training practice called distillation, which can be viewed as a form of intellectual property theft. Meanwhile, most of the industry's leading players contend that restricting use of the models would be to our own detriment and would place too much power in the hands of too few companies.
"The age of AI can be one of prosperity," the consortium of tech companies wrote in an open letter on July 24. "With the right choices, open weight AI can expand opportunity, strengthen competition, extend American technological leadership, mitigate risk, and ensure that the benefits of this extraordinary technology are shared broadly across our economy."
As for distillation, they call it "a widely used technique for model improvement, evaluation, and validation."
watch now
Meta on Monday released Muse Glimmer as part of a strategy to release its most powerful AI models to the open-source community. CEO Mark Zuckerberg said the company would open the weights for its latest AI model, Muse Spark 1.2. Weights refer to the calculations and rules that determine how the AI works and behaves.
A day later, Nvidia debuted Nemotron 3.5 Lightning. The model stems from the company's Nemotron 3 family of models released in December. The chipmaker said its models are "truly open source," because the company publishes the related "training datasets, techniques, and model weights" for developers to inspect.
Both companies still have to prove there's an audience for their offerings in a market featuring popular models from Chinese AI labs like Moonshot AI and DeepSeek, as well as Alibaba's Qwen.
Box CEO Aaron Levie, one of the signatories of last month's letter, is optimistic. He said Zuckerberg's plan for Muse Spark 1.2 is a "very big deal" because it's a powerful model that rivals top foundation models from Anthropic and OpenAI. The models this week from Meta and Nvidia are smaller and intended to run on laptops for tasks like powering on-device digital agents.
"There's a very firm flag in the ground that America will have near-frontier open-source models," Levie said.
Meta has tried this route in the past with Llama. That was Zuckerberg's initial entry into the foundation AI market, but the release of Llama 4 in April 2025 left developers unimpressed. Meta followed by spending billions of dollars to overhaul its AI unit, installing Scale AI CEO Alexandr Wang as the division's leader.
Recently, Wang's group has been rolling out proprietary models under the Muse branding to try and develop new revenue streams.
'Tremendous amount of potential'Levie said that companies put off by using Chinese open-weight AI models would be more inclined to experiment with Meta's upcoming variant.
"You probably wouldn't be able to put a non-domestic open-source model in a major government agency, as an example, and you wouldn't be able to use it at very large banks most likely," Levie said. "If you think about the kind of use cases that now Muse can be used in, it actually opens up a tremendous amount of potential."
Still, Meta in particular faces some headwinds as it pursues yet another open-source strategy. Umesh Sachdev, CEO of business AI startup Uniphore, said Meta burned bridges with third-party developers when it shifted from open weight to proprietary AI models.
"I think it's going to take more than a 3,500 worded article from Zuck to convince developers," Sachdev said regarding Zuckerberg's accompanying manifesto this week. "The emotion of my developers at Uniphore, they almost feel betrayed."
But Sachdev said he's rooting for domestic companies to succeed, "because more competition will drive down token cost, and will drive up innovation, and it's always good for consumers."
It's a sentiment shared by Forrester analyst Charlie Dai. He called Meta's latest move "strategically important because it restores a major U.S. frontier AI vendor to the open ecosystem."
"Developers and enterprises will likely welcome Meta's shift back toward open weights because it improves transparency, customization, deployment flexibility, and data sovereignty," Dai said. Now, the company must "prove it can cultivate a durable ecosystem beyond releasing competitive models," he said.
WATCH: Meta's new AI model is a "positive development for the ecosystem."
Blackwell has been Nvidia's most advanced graphics processing unit (GPU), but Vera Rubin has begun deployment. The GPU market is already massive and only expected to grow.
Analyst’s Disclosure: I/we have a beneficial long position in the shares of NVDA either through stock ownership, options, or other derivatives. I wrote this article myself, and it expresses my own opinions. I am not receiving compensation for it (other than from Seeking Alpha). I have no business relationship with any company whose stock is mentioned in this article.
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AI is the most important tech advance in human history, and perhaps the greatest investment of all time. One only has to talk to the hundreds of millions of people who use it (or perhaps billions) and the army of companies around the world that say it will transform the way their employees work and pave a golden road to profits. It has also made untold numbers of people richer via ownership of its stock and the constellation of AI-related companies that surround it. Many of these have been helped by investments from Nvidia (NASDAQ: NVDA | NVDA Price Prediction), or loans that will make them grow faster. If AI is the world’s most important technology development, Nvidia sits in the middle of its future.
After dozens of deals, it has financial relationships and ownership in Anthropic, OpenAI, Intel (NASDAQ: INTC), Coreweave, Nokia, Synopsys (NASDAQ: SNPS), Marvell (NASDAQ: MRVL) and at least half a dozen others.
AI data centers are the heartbeat of AI’s future. Nvidia has just pulled off a coup as it set up a partnership with some of the world’s largest financial companies to set up a $500 billion facility to build out more of this infrastructure. The group includes Apollo, BlackRock, Blackstone, Goldman Sachs (NYSE: GS) and several smaller companies. Goldman Sachs is the world’s premier investment bank. BlackRock is the world’s largest money manager. And Nvidia will backstop some of the deal, just in case other investors fall short. As Bloomberg reports, “Executives indicated that it will focus on debt financing to provide access to computers for Nvidia’s largest customers and that there are already many deals in the works that would qualify toward this commitment.” This means that much of this money will return to Nvidia as revenue, which is central to many of its other investments. “Round-tripping” of revenue or not, it helps to guarantee Nvidia’s 60%-plus top-line quarterly growth.
Nvidia has a path toward being the world’s largest company by revenue. In its most recent quarter, it had revenue of $81 billion, which grew 85% year over year. That means Nvidia’s revenue run rate is close to $330 billion. And, it said in the current quarter, revenue will be $91 billion. In the upcoming fiscal year, at its current growth rate, its revenue could be $630 billion. Amazon topped the Fortune 500 based on revenue at $714 billion, but its growth rate is 19%. Give Nvidia two or three years, and it could sit atop the Fortune list.
The business world has never seen a company like Nvidia. One could argue that Microsoft was more important in the late 20th century and the beginning of this one. The operating system sector has faded. Google’s search business was a huge step forward, but Nvidia has largely replaced it. Apple is built on one product.
Nvidia’s market cap is $5.4 trillion. That is based on its role as the arms merchant to the AI industry. As it provides money for core assets like data centers, that role grows. It grows more and it becomes the AI sector’s banker.
Despite a bit of sideways movement, recently Nvidia’s stock is up 977% in the last five years. To reach a market cap of $10 trillion, it does not have to come close to that pace.
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Nvidia CEO Jensen Huang. Bloomberg/Getty Images Majestic Labs cofounder Sha Rabii knows what it's like to build AI infrastructure in an industry dominated by Nvidia.
Rabii spent years leading custom silicon inside Google and Meta before launching his own AI hardware startup.
When Rabii considers Nvidia's biggest competitive advantage, he doesn't point to its brilliant engineers, leading technology, or well-established sales channels.
"Where they're kind of unmatched is in the giant bag of cash they're sitting on top of," Rabii said.
Nvidia had more than $80 billion in cash and marketable investments as of April, when it last reported earnings, and generated another $50 billion in operating cash flow that quarter. While other Big Tech giants have comparable stashes, Nvidia doesn't shoulder the same massive data-center construction costs.
Even after returning billions to shareholders, it leaves it with an enviable problem: how to put its riches to work.
"What better use of the rest of the cash to invest and grow and strengthen the ecosystem around their products?" said Bernstein analyst Stacy Rasgon.
On Monday, Nvidia unveiled a new way to turbo-charge the power of its cash hoard by bringing in at least $500 billion of outside capital to finance far more Nvidia-powered AI infrastructure than what it's already funding. This new initiative includes some of the biggest firms on Wall Street, including Apollo, Blackstone, and Goldman Sachs.
The company is also in talks to guarantee an OpenAI data center project worth hundreds of billions of dollars. It's providing financial backstops to neoclouds, or specialized AI cloud providers, to buy its graphics processing units (GPUs) — the chips used to run AI.
It's also making long-term commitments to secure scarce components, and investing in and supporting AI startups through its NVentures and Inception programs. If one bet takes off, Nvidia hits the lottery on both the investment and future chip sales.
The result is a self-reinforcing cycle: Nvidia's technological dominance generates cash, and that cash is increasingly becoming a moat of its own.
Nvidia's scale has boosted its financing playbookVendors using their balance sheets to help customers buy their products isn't a novel strategy, said Bernie Margulies, who works on GPU financing at American Compute. The practice is spreading more broadly.
AMD has previously backstopped chips for customers, while Broadcom recently partnered with Apollo and Blackstone on an AI-infrastructure financing platform. Neither rival can match Nvidia's scale, said D.A. Davidson analyst Gil Luria, calling the chipmaker's financial might a different "order of magnitude."
In addition, Meta agreed to purchase up to $15 billion of computing capacity from the neocloud Nebius, while Google has backed Anthropic's data-center projects.
Historically, Nvidia hasn't needed to do this, Margulies said.
As the AI buildout explodes, Nvidia helps finance projects that might not otherwise get built. Margulies said this could also be read as an effort to keep customers from experimenting with alternatives, like AI chips built by AMD or Google.
Alex Yeh, CEO of the neocloud GMI Cloud — which has a backstop agreement with Nvidia — said the deals help the chip giant build an "alliance" with neoclouds and AI startups as its biggest cloud customers develop their own chips.
They can also unlock massive orders for AI chips.
Yeh said that without Nvidia stepping in, he wouldn't have been able to take on the AI startup Fireworks as a customer, with which GMI has a nine-figure deal.
Likewise, Rabii said financing is a complication for one of Majestic's target markets: neoclouds. If a customer wanted to buy billions of dollars of Majestic hardware, his startup couldn't backstop the financing the way Nvidia can.
"Nvidia's real moat today is how freaking expensive it is to build data centers," Rabii said. Instead, he said he's betting Majestic's power-efficient chips will convince customers to choose its systems.
Nvidia is looking beyond its own balance sheetNvidia's growing financial ties have fueled concerns about circular financing.
Margulies said he isn't particularly concerned, though the strategy "does cause a lot of investors to be worried." If Nvidia loses market share and has to pay out on its backstops, "it'll be brutal," he said.
Michael Reid, CEO of Australian neocloud Megaport, which does not have a backstop agreement with Nvidia, said overall demand for GPUs provides another safeguard. If one customer falters, the neocloud could rent the capacity to another.
Nvidia CEO Jensen Huang said on X that the company's latest Wall Street partnerships are designed to address concerns about circular financing. Analysts said that tapping outside capital means Nvidia doesn't have to shoulder as much of the financial risk.
"They're sharing the reward, but they're also sharing the risk," said D.A. Davidson's Luria.
In this vein, the chipmaker's next financial moat may be access to money that isn't even its own.
Have a tip? Contact this reporter via email at [email protected] or Signal at @geoffweiss.25. Use a personal email address, a nonwork WiFi network, and a nonwork device; here's our guide to sharing information securely.
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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 is positioned as a durable, differentiated AI compute leader, with new $500B funding platforms set to deepen its CUDA moat. Current valuation rests on delivering ~40% FY28 earnings growth, with a 12-month base case price target of $275 and a Buy rating. Q2 earnings strength is expected, but broadening demand beyond hyperscalers and prudent credit management are critical near-term signals.
In the rapidly expanding semiconductor ecosystem, Advanced Micro Devices (AMD +1.01%) and Nvidia (NVDA -0.02%) stand as pivotal players powering the compute backbone of artificial intelligence (AI). Nvidia dominates with its Blackwell and Rubin GPU architectures, which deliver industry-leading performance for large-scale training and inference workloads.
Meanwhile, AMD contributes complementary technology via its Instinct MI-series accelerators and Epyc processors, offering high-performance CPUs and GPUs that hyperscalers integrate for cost-effective AI clusters.
Hyperscalers such as Microsoft, Amazon, Alphabet, and Meta Platforms rely on both companies extensively -- deploying Nvidia GPUs for AI acceleration while leaning on AMD's CPU and GPU offerings for broader data center efficiency and diversification away from single-supplier risk. Yet when the valuations are examined side by side, only one of these AI chip stocks emerges as the clear buy right now.
Image source: The Motley Fool.
Assessing the valuation discrepancy between Nvidia and AMD The chart below illustrates the forward price-to-earnings (P/E) ratios for Nvidia and AMD. The trends reveal a striking divergence: AMD currently trades at a forward P/E of 63, while Nvidia sits at 24. Over the displayed time period spanning mid-2024 through today, Nvidia's forward P/E has largely existed in a band between roughly 20x and 40x, whereas AMD's ratio has climbed sharply in more recent months.
Data by YCharts.
AMD's premium appears counterintuitive. Competitive pressures from custom ASICs developed by hyperscalers -- Google's TPUs, Amazon's Trainium and Inferentia chips, and Microsoft's Maia -- appear to be intensifying primarily against Nvidia, whose GPUs face substitution risk as cloud providers seek to lower infrastructure costs and assert greater control over their chip stack.
Therefore, some investors might actually expect Nvidia's valuation multiple to compress aggressively. However, these same dynamics do not apply to AMD, which commands an elevated valuation, while Nvidia's profile has stabilized to a more modest level.
This discrepancy suggests investors are pricing in catch-up potential for AMD's Instinct accelerators and accompanying software stack, even as the ASIC threat remains acute for Nvidia as the incumbent AI chip designer.
Comparing AMD's growth to Nvidia AMD's second-quarter financial results showed solid but comparatively measured expansion. The company reported total revenue of $11.5 billion, a 50% increase year over year. AMD's data center segment -- the primary AI growth driver -- generated $6.7 billion in sales, surging 107% year over year. Meanwhile, free cash flow grew modestly to $1.6 billion.
Nvidia has yet to report second-quarter results. But during the first quarter, Nvidia showed far greater scale and velocity relative to AMD. Total revenue reached $81.6 billion, up 85% year over year, with record data center revenue of $75.2 billion, climbing 92%. Lastly, Nvidia's free cash flow of $48.5 billion nearly doubled from the prior year.
AMD's absolute numbers remain a fraction of Nvidia's, and its overall growth rate lags its larger rival. Despite this slower trajectory and substantially smaller revenue base, AMD's valuation sits at 2.5 times Nvidia's, a valuation gap that seems difficult to justify based on growth and profitability metrics alone.
AMD vs. Nvidia: Which is the better stock to buy? The trends explored above illustrate a recurring pattern in which both Nvidia and AMD tend to rerate once their forward P/E ratios approach an elevated threshold. In prior cycles, AMD's forward P/E spiked above 50 or 60 only to experience subsequent normalization through multiples compression.
Nvidia has shown similar behavior, with its multiple rising and then settling into more sustainable ranges (which is happening right now). AMD's current levels position the stock for potential normalization in the near term, while Nvidia's relatively modest multiple leaves room for valuation expansion if its growth momentum persists.
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History suggests AMD shares could face selling pressure as its premium unwinds, even as Nvidia could accelerate into a new leg higher. Given Nvidia's superior scale, faster overall growth, significantly higher profitability, and more entrenched position in hyperscale AI ecosystems, I think the risk-reward balance favors investing in Nvidia at the moment. Investors seeking exposure to the ongoing AI semiconductor boom might be better served by buying Nvidia stock over AMD right now while the valuation gap remains this wide.
Inference has become the fastest-growing part of the artificial intelligence (AI) infrastructure market, and Bloomberg Intelligence projects it will double the size of the AI training market by 2032, reaching $1.3 trillion. With so much at stake, both leading chipmakers and upstarts are jockeying to grab a slice of this huge, fast-growing market.
Nvidia (NVDA -0.02%), Cerebras (CBRS +2.06%), and Advanced Micro Devices (AMD +1.01%) are all tackling this market in different ways. Let's see how these AI stocks stack up and why they could all be winners, given the size and growth of the inference market.
Image source: Getty Images.
1. Nvidia Already the winner in AI model training, Nvidia now has its sights on the inference market. The company's big move to capture share was its "acquisition" of Groq and its language processing units (LPUs). Inference is more about fast memory access and low latency than raw compute power, and LPUs help address this by having SRAM (static random-access memory) embedded directly on their chips.
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LPUs are particularly useful during the decode phase of inference, which is when large language models (LLMs) answer queries. As such, Nvidia now offers complete systems designed specifically for inference, where its graphics processing units (GPUs) handle the pre-fill phase (reading the prompt) while its LPUs handle the decode phase, thereby speeding up response times.
This is a nice solution and positions Nvidia to remain an AI infrastructure leader, even if it doesn't capture the same market share it does in training.
2. Cerebras Like Nvidia, Cerebras is tackling inference with SRAM-based chips. However, because SRAM is so bulky, instead of just embedding a small amount onto its chips and stringing them together, Cerebras has created huge wafer-sized chips that are five to six times faster than LPUs.
The physical size of Cerebras' chips comes with some trade-offs. They require specialized cooling and energy management solutions and, as such, are only sold or rented as part of the Cerebras CS-3 systems. They also come at a very premium price tag.
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However, the company has inked major deals with OpenAI and Amazon's AWS, and it recently announced a partnership with AMD that should help reduce the cost of ownership. The two companies will offer an inference solution in which AMD's Helios rack-scale solution will handle the pre-fill phase of inference, which it can do more cheaply, while Cerebras' Wafer-Scale Engine will perform the decode phase, which it can do more quickly. It's a nice way for companies to better compete with Nvidia's offerings.
Given the high cost of its systems, Cerebras has been more of a premium, niche solution, but it now looks set to become a major player in the humongous inference market.
3. AMD After losing out on the LLM training market to Nvidia, AMD has been aggressively pursuing the inference market to make sure it doesn't get left behind again. Its chiplet design is better suited for inference, as it allows its GPUs to be packaged with more high-bandwidth memory (HBM) and to act as part of an entire unit to reduce latency. Meanwhile, its partnership with Cerebras looks like a smart move to help it better compete with Nvidia's complete inference system.
However, the company has not stopped there. It recently acquired memory optimization company MEXT and chip start-up Taalas to boost its inference offering. Memory is one of the biggest AI bottlenecks right now, and MEXT's solution can offload seldom-accessed data from DRAM to unused flash and then, using predictive AI, can transfer it back into DRAM before an application even requests it. This can reduce the need for more expensive DRAM and help save costs.
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Meanwhile, Taalas has developed chips in which AI models are hardwired directly to bolster inference performance. Since the chips are model-specific, they aren't as flexible, but they are cheaper and much faster. The company plans to use them as part of a complete system where its GPUs would handle the pre-fill phase and Taalas' chips would handle the decode phase.
AMD is tackling inference from a couple of different angles, which should position it to capture a nice share of this huge market.
Even as NVIDIA Corp.’s (NASDAQ:NVDA) shares surge in August, cryptocurrency punters remain skeptical that the stock will finish the month at or above $250.
Polymarket Wagers on NVDAThe betting crowd on Polygon (CRYPTO: POL)-based Polymarket currently assigns only a 9% chance to the possibility, down from 50% a month ago.
The odds of NVDA ending above $260 also remained at 9%. Punters put the odds at 62% for a close above $210 on Aug. 31, and 87% for a close above $190. The prediction market was pricing a 99% probability that the stock would close above $140.
The stock closed at $200.75 on the last trading day in July, and has gained 8.34% month-to-date. It closed at $223.96 last week, but has since retraced.
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NVIDIA, often viewed as the definitive gauge of AI sector, is set to release its second-quarter results later on Aug. 26, making the month pivotal for the stock.
Analysts expect the company to report earnings per share of $2.07, up nearly 100% year-over-year. The firm is expected to report revenue of $91.82 billion, a 96% increase from the same quarter last year.
Investors are waiting to see if earnings beat expectations, and whether that catalyst is enough to push shares higher.
The stock carries a consensus “Buy” rating from 30 analysts, with an average price target of $313 and a third-quarter target of $323.
Price Action: NVIDIA shares rose 0.25% in after-hours trading after closing 0.02% lower at $217.50 during Tuesday’s regular trading session, according to data from Benzinga Pro. Year-to-date, the stock has rised 16.64%.
Benzinga Edge Stock Rankings indicate that NVDA maintains a stronger price trend across short-, medium-, and long-term timeframes, supported by elevated Value and Growth scores.
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Nvidia (NVDA -0.02%) signed memorandums of understanding Monday with six of Wall Street's largest investment firms to establish independent financing platforms -- vehicles meant to mobilize more than $500 billion of third-party capital for artificial intelligence (AI) infrastructure. The six are Apollo Global Management, BlackRock, Blackstone, Brookfield Asset Management, Goldman Sachs, and KKR.
The idea is to let lenders treat computing hardware the way they treat buildings or toll roads (an asset that produces revenue and can therefore secure debt).
Markets have run a version of this experiment before. In the late 1990s, telecom equipment makers lent their customers the money to buy their gear, and by the end of 2000, nine suppliers (including Lucent, Nortel, and Cisco) had extended about $25.6 billion, according to a McKinsey estimate.
Nvidia's new target is about 20 times that figure. The structure is different this time, and the difference matters. But the announcement leaves something open that may matter more.
Image source: Nvidia.
Compute as collateral The platforms are designed to create dedicated pools of outside capital for Nvidia's customers (the companies building AI data centers) so the next wave of hardware isn't paid for out of the buyers' own cash.
"This is really the first time that technology chips have become an investable asset class," CEO Jensen Huang told CNBC on Monday.
The market's response was cool. Shares slipped about 3% Monday and trade near $218 as of this writing.
Note what the plan is not: a response to weak demand. Nvidia's trailing-12-month revenue rose about 71% to $253 billion, and its net income roughly doubled from the year before, to about $160 billion. In the fiscal first quarter of 2027 (the period ended April 26, 2026), revenue grew 85% year over year, accelerating from the quarter before, and management guided for about $91 billion in the quarter it reports next. The sequence is still climbing.
The financing exists because the bill is starting to outgrow the buyers. Rating agencies have warned that record capital spending has begun squeezing the big AI spenders' free cash flow and pushing them toward heavier debt loads. In other words, the next $500 billion of hardware needs more money than the customers' own operations throw off.
The telecom precedent The last time an industry's suppliers arranged their customers' financing at anything like this scale, it ended badly. Network operators in the late 1990s demanded financing from equipment vendors as a condition of awarding contracts, and the vendors obliged with their own money.
When spending collapsed, 24 of the 30 largest publicly traded telecom carriers went bankrupt, and an estimated one-third to 80% of the suppliers' loan portfolios were lost. Lucent and Nortel were pushed to the brink of insolvency.
That history, to me, is the right measuring stick. Against McKinsey's count of what the era's nine biggest lenders had extended, more than $500 billion is roughly 20 times as much. Broader measures of the period's vendor lending run higher, which would shrink the multiple. On any measure, though, the new pool is far larger.
The difference is who carries the loans. Lucent's sat on Lucent's balance sheet, which is why its customers' failures nearly became its own. Nvidia isn't the lender here. The platforms are independent, and the money is Wall Street's.
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Who takes the loss? That is the part Monday's announcement doesn't finish explaining. The release describes the platforms as independent and the capital as third-party. It says nothing about who absorbs the damage when a borrower defaults.
The collateral case comes from Huang himself. Chips can be moved from one customer to another, he argues, and they keep improving through Nvidia's CUDA software. A lender could, in principle, take the hardware back and lease it to someone new.
Maybe so. But a repossessed chip is only worth what someone will pay for computing at that moment, and each new chip generation can cut the price of the one before it. If a borrower failed because AI demand cooled, the collateral would be cooling with it.
And financed demand is still demand. After all, hardware bought with borrowed money shows up in Nvidia's revenue exactly the way hardware bought with cash does. In the telecom collapse, that was arguably the demand that vanished first.
Ultimately, I think the platforms fix the failure that defined 2000 -- the vendor betting its own solvency on its customers' success. Nvidia's balance sheet stays out of the lending, as the release describes it, and the business it is financing demand for keeps posting extraordinary numbers.
What the structure can't change is what the money is for -- hardware that gets paid back out of AI revenue that mostly doesn't exist yet. The announcement doesn't say who takes the loss if that revenue falls short.
Jensen Huang built the world's most valuable company by pioneering the specialized computer chips behind the artificial intelligence boom.
To keep his vision for the future within reach, the Nvidia founder is now attempting a different kind of engineering: convincing Wall Street investors that those chips are long-term financial assets akin to commercial real estate or toll roads.
His bet hinges on outpacing AI developments in China.
This week, Nvidia unveiled agreements with six of the world's largest asset managers, BlackRock, Blackstone, Apollo, KKR, Brookfield and Goldman Sachs. The goal was to assemble a $500 billion pipeline to finance the construction of data centers and GPU clusters for companies that lack the credit rating or cash to buy millions of dollars of silicon outright.
Key to his plan, which Huang announced during a CNBC segment flanked by the leaders of all six Wall Street firms, is one crucial assumption: that Nvidia's graphics processing units will hold their value over time, behaving more like traditional hard assets than fast-depreciating consumer electronics.
"Nvidia's AI factory platform is really an investable asset, an infrastructure asset," Huang said. "The reason for that is because it's productive, it's revenue generating, it is fungible, it's used by just about every cloud service provider, it runs every AI model."
In standard asset-backed finance, a bank lends money because if a borrower defaults, the bank can repossess the asset — like a building, a warehouse or a cargo ship — and sell it to get their money back. Those physical assets have established secondary markets and can last decades.
But the productive lifespan of cutting-edge GPUs is far from settled.
While new chips power frontier model training, after a few years they are relegated to lower-margin inference work — a shift that directly impacts their resale and collateral value.
"Depreciation is the one key risk here," said Ben Emons, founder of FedWatch Advisors, who structured similar asset-backed loans for IndyMac before joining Pimco as a portfolio manager. Nvidia chips "could depreciate faster than expected," he said.
High-yield rates?In particular, Emons said he believes the single biggest threat to Nvidia's financing model comes from China, which is rapidly ramping up domestic compute capacity and could choose to flood the market with low-cost silicon in a price war.
If Chinese production pushes hardware prices into a freefall, the collateral backing hundreds of billions in private loans could erode far faster than the terms of the debt itself, leaving investors exposed to losses, according to Emons.
To compensate at least partly for that risk, Emons estimates investors will treat GPUs as high-depreciation equipment rather than real estate, demanding high-yield returns in the 11% to 17% range depending on where they sit in the capital structure.
On top of that, the borrowers are likely to be non-investment grade firms locked out of traditional debt markets, including AI startups and neoclouds, according to a Bank of America Securities note.
If those higher-risk borrowers go under, Wall Street fund managers will be forced to repossess and resell used chips into a potentially falling market.
Whatever risks China poses wouldn't be realized anytime soon. Huawei, the dominant provider of Chinese AI chips, has been on the U.S. Commerce Department's Entity List since 2019. And in May, the U.S. government said Huawei's Ascend AI chips violate U.S. export controls, preventing any American company from using the chips.
In the meantime, Nvidia remains by far the leading supplier of AI chips in the U.S., with upwards of 75% market share by most estimates.
And for now, the economics are still moving in Huang's favor. Driven by scarcity as hyperscalers race to build out capacity, rental rates for Nvidia's H100 chips rose from roughly $1.70 per GPU-hour in late 2025 to about $2.35 per GPU-hour this year, Huang noted.
Crucially, Nvidia argues its CUDA software layer — which enables developers to run AI workloads on its GPUs — continuously improves hardware performance after deployment, allowing older chips to stay productive and generate yield longer than traditional accounting models predict.
The future of the AI buildout, and hundreds of billions of dollars in investor money, may depend on who is right.
US investment giants including Apollo Global Management Inc., Blackstone Inc., BlackRock Inc. and Brookfield Asset Management are partnering with Nvidia Corp. to source $500 billion in financing for artificial intelligence infrastructure. Bloomberg's Ed Ludlow joins to discuss this as well as Intel raised $20 billion in an upsized share sale, a third more than it was targeting when it announced the deal Monday morning.
Nvidia (NVDA -0.02%) said yesterday that it has partnered with six of the biggest names on Wall Street to raise more than $500 billion in outside capital to fund the build-out of artificial intelligence (AI) data centers.
The agreements are memorandums of understanding (MOUs) -- preliminary handshake deals, not binding contracts -- meaning the $500 billion is a target, but not guaranteed at this point.
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Who Nvidia is partnering with and how the deal worksAccording to the company's Aug. 10 press release, Nvidia is teaming up with some of the largest asset managers and investment banks on the planet -- Apollo Global Management, BlackRock, Blackstone, Brookfield, Goldman Sachs, and KKR.
The group will create what Nvidia calls compute financing platforms that will pool capital to lend to Nvidia customers building AI data centers with its advanced graphics processing units (GPUs). The funding is meant to cover the chips themselves along with servers, networking gear, buildings, and power.
Nvidia said it has the option to guarantee up to 25% of any of the deals, helping the customers receive a better rate.
CEO Jensen Huang spoke to CNBC on Monday, saying that GPUs have become "revenue-generating assets" and could be financed the way investors finance toll roads or power plants. He said that the chips are productive, long-lived, fungible, and flexible, and claims that a single rack of chips could serve one customer after another over its working life.
How $500 billion fits into the bigger AI spending pictureA figure that large is impressive, but it’s in line with what the industry is already spending. Analysts at Bank of America estimate that the big hyperscalers -- think Amazon or Alphabet -- alone will spend a whopping $860 billion on AI capital expenditures in 2026 and an incredible $1.2 trillion in 2027. Nvidia controls something like 85% or more of the market for AI GPUs, which in turn are the most expensive part of an AI data center, so it collects the lion’s share of every dollar spent on the build-out.
Image Source: Getty Images
Why this deal may not be as bullish as it soundsWhile the deal taps additional capital to keep the AI build-out humming along, it comes at a time when many investors are wary of its sustainability. Given that the hyperscalers, who run core businesses that steadily bring in enormous sums of cash, have begun to turn to the bond market and major stock sales, Nvidia’s announcement of yet another funding source could be more concerning than it is reassuring for many.
And there’s a real question of how much demand for this financial product there will be. Unlike power plants, Nvidia’s GPUs have a much shorter useful life. That makes using them as collateral an iffy proposition for investors.
The bottom lineI understand why Jensen Huang is pitching this. The more funding that pours into the system -- whatever the source -- the more chips Nvidia sells. But I’m not convinced it’s good for the health of the market as a whole, and I would guess this news actually hits Nvidia stock rather than helps it.
For now, wait and see if this becomes a reality and if these MOUs become signed agreements.
Johnny Rice has no position in any of the stocks mentioned. The Motley Fool has positions in and recommends BlackRock, Blackstone, Brookfield Corporation, Goldman Sachs Group, KKR, and Nvidia. The Motley Fool has a disclosure policy.
NVIDIA Corp. (NASDAQ:NVDA) may still be the face of the artificial intelligence chip boom, but JPMorgan says the next phase of the semiconductor rally could spread much further across the industry.
• NVIDIA stock is trading at elevated levels. Where is NVDA stock headed?
The latest World Semiconductor Trade Statistics data show semiconductor fundamentals remain strong, with June industry sales reaching $152 billion and year-over-year growth accelerating to 134%, according to JPMorgan. More importantly, the strength is no longer confined to memory chips.
JPMorgan now sees the global semiconductor industry reaching $1.68 trillion in sales in 2026, up 111% year over year, followed by $2.25 trillion in 2027, a 34% increase.
That creates a much bigger opportunity for investors than the familiar Nvidia-led AI trade.
Semiconductor Growth Is BroadeningMemory remains the biggest driver of the industry’s growth. JPMorgan said memory accounted for roughly 77% of the year-to-date increase in semiconductor sales, with DRAM and NAND revenue continuing to benefit from higher pricing and shipment volumes.
But the bank is increasingly focused on what is happening outside memory.
Ex-memory semiconductor sales reached $63.5 billion in June, up 38% year over year and marking a third consecutive month of accelerating growth. Microcomponents, including microcontrollers, microprocessors and digital signal processors, were among the biggest sources of improvement.
The monthly data also show gains spreading across categories including analog chips, sensors and actuators.
That matters because it suggests AI infrastructure spending is beginning to create a broader semiconductor demand cycle rather than benefiting only the most obvious AI accelerators and memory suppliers.
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JPMorgan’s 6 Chip Stocks to WatchJPMorgan sees the strongest positioning across three parts of the semiconductor market.
For compute, JPMorgan picks Nvidia, Broadcom Inc. (NASDAQ:AVGO), Advanced Micro Devices, Inc. (NASDAQ:AMD) and Intel Corp. (NASDAQ:INTC). Nvidia remains the industry’s dominant AI accelerator supplier, while Broadcom and AMD offer exposure to custom AI infrastructure and competing compute platforms. Intel, meanwhile, gives investors exposure to CPUs and its increasingly important foundry and AI ambitions. For memory, JPMorgan favors Micron Technology, Inc. (NASDAQ:MU), as DRAM and NAND pricing continues to strengthen. For networking, JPMorgan again highlights Broadcom, alongside Marvell Technology, Inc. (NASDAQ:MRVL), as AI data centers require increasingly sophisticated connectivity to move data between processors and systems. That gives investors six ways to play the same underlying theme — but with very different exposures.
The AI Trade Is Getting BiggerThe most important takeaway may be that investors don’t necessarily need to pick the next Nvidia.
JPMorgan’s latest data suggest the AI infrastructure boom is creating demand across compute, memory and networking, while other semiconductor categories are beginning to recover as well.
JPMorgan also sees upside risk to its $1.68 trillion and $2.25 trillion industry forecasts because its model assumes largely seasonal growth across most categories.
For investors, that creates a broader semiconductor opportunity: Nvidia may have started the AI chip boom, but JPMorgan sees plenty of room for the rest of the industry to catch up.
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HomeIndustriesComputers/ElectronicsTech StocksTech StocksNvidia’s new partnerships with financial players help mitigate concerns that the company is too tightly linked to its customers, according to BofA and Morgan StanleyAug. 11, 2026, 2:36 p.m. ET
Some investors have worried about the tight financial relationships between Nvidia and its customers, but analysts say that newly announced partnerships should put those worries to rest for now.
The company NVDA announced Monday that it has formed strategic partnerships for “independent compute financing.” These are worth more than $500 billion and are meant to support artificial-intelligence infrastructure development over time. Six firms including Apollo Global Management APO, Blackstone BX and Goldman Sachs GS will provide the third-party capital, the chip maker said.
Nvidia Corporation is spearheading a $500B compute financing platform with major financiers, signaling a next step in AI infrastructure investment. Demand for rapid, energized data center capacity is in demand, with a premium on near-term, high-quality assets and creditworthy tenants like Microsoft. Texas is one focal point, with large-scale projects such as Riot Platforms' $10B, 20-year deal and IREN's 750 MW flagship site offering much-demanded capacity for the AI buildout.
Characteristics and Risks of Standardized Options: https://bit.ly/2v9tH6D. Nvidia (NVDA) doubled down on the AI trade, with CEO Jensen Huang announcing that the company aims to finance $500 billion in AI infrastructure with the help of six key financial firms.
Key Takeaways NVIDIA's $500B AI push could broaden the AI trade beyond technology stocks.Wall Street could play a bigger role in financing the AI infrastructure boom.Financial ETFs offer a diversified way to play AI's growing financing needs. Nvidia (NVDA - Free Report) announced on Monday that it had entered into memorandums of understanding with Apollo Global Management (APO - Free Report) , BlackRock (BLK - Free Report) , Blackstone (BX - Free Report) , Brookfield (BAM - Free Report) , Goldman Sachs (GS - Free Report) and KKR (KKR - Free Report) to establish financing platforms aimed at supporting its customers, as quoted on CNBC.
The chipmaker is advancing its effort to turn AI computing into a new asset class for Wall Street, collaborating with major asset managers on a $500 billion financing push. The initiative seeks to make AI compute infrastructure akin to commercial real estate, toll roads and other assets that can be financed against.
As quoted on the abovementioned article, the NVIDIA initiative could unlock more than $500 billion in third-party capital for AI infrastructure, helping hyperscalers, frontier AI labs and enterprises expand data-center capacity and purchase NVIDIA hardware. By connecting its customers with institutional credit, insurance funds and private capital, NVDA is helping shift some of the funding burden away from their balance sheets.
Speaking with CNBC, Jensen Huang, NVIDIA’s founder and CEO, stated that AI computing is emerging as a new investable asset class, as quoted on the abovementioned article. Huang contended that NVDA’s widely adopted and transferable hardware enables lenders to underwrite AI computing as a durable, revenue-generating asset with a long useful life. The chipmaker’s efforts seek to turn AI computing capacity into a long-term, financeable asset. However, skeptics remain.
How Asset Managers Fit Into the AI Financing PushThe AI narrative is increasingly expanding beyond technology to the financing of the infrastructure behind it. NVIDIA’s latest financing push highlights the growing role of financial institutions in funding the infrastructure needed to support AI’s rapid expansion.
The ETFs mentioned below could offer investors exposure to companies positioned to benefit from the broader AI financing boom. Potential beneficiaries include lenders benefiting from growing credit demand, asset managers collecting fees on rising capital deployment, private-credit firms financing AI infrastructure and investment banks and capital-markets firms supporting the financing and structuring of these projects.
Huang believes the next phase of AI infrastructure financing will be driven by Wall Street rather than corporate balance sheets, with leading financial institutions playing a central role in funding the industry's expansion, as quoted on another CNBC article.
As per the previously mentioned CNBC article, alternative asset managers have been increasingly deploying capital into digital infrastructure, using institutional and insurance capital to finance these projects. Firms like Apollo and Blackstone have already helped finance companies like Anthropic through debt and equity arrangements.
Larry Fink, BlackRock’s CEO, along with executives at Wall Street firms like Blackstone’s President Jon Gray and Goldman Sachs’s CEO David Solomon, on Monday, stated that AI compute is emerging as a critical asset class that could drive the next phase of global economic expansion.
According to Blackstone’s Gray, as quoted on the previously mentioned CNBC article, AI compute could eventually be treated as a “financeable asset class,” with lenders financing computing infrastructure much as mortgage lenders finance homes.
Additionally, BlackRock’s Fink described the initiative as the beginning of a “next future for financial engineering,” drawing a comparison to the development of mortgage-backed securities in the 1970s. While some funds have already been raised, Fink said BlackRock plans to raise substantially more capital going forward.
However, it is important to note that the immediate benefit from NVIDIA’s announcement is likely to be concentrated among the financial firms directly involved in the initiative, rather than representing a broad-based tailwind for the entire financial sector. Broader financial companies could benefit if NVIDIA’s financing model gains traction and AI infrastructure investment continues to accelerate.
ETFs for a Direct Play on Alternative Asset ManagersVanEck Alternative Asset Manager ETF GPZVanEck Alternative Asset Manager ETF seeks to track the performance of MarketVector Alternative Asset Managers Index, which measures the performance of alterative asset managers across private equity, venture capital, private credit, private real estate and private infrastructure.
The fund has significant exposure to leading alternative asset managers, including Blackstone, KKR, Apollo Global Management and Brookfield Asset Management, which account for approximately 12.9%, 9.8%, 7.3% and 4.7% of the fund, respectively.
GPZ charges an annual fee of 0.40% and has a one-month average trading volume of about 164,000 shares. The fund has also amassed an asset base of $257.3 million. GPZ has gained about 8.3% over the past month and was up around 0.7% on Monday.
Tema Listed Private Managers ETF PRVTTema Listed Private Managers ETF employs an active strategy, seeking to provide a diversified exposure to publicly traded alternative asset managers across private equity, private credit, venture capital and real assets globally. The fund charges an annual fee of 0.75% and has gathered an asset base of $0.5 million.
The fund has a basket of 28 securities, with no single holding accounting for more than 5.55% of its exposure. PRVT has an exposure of 54.33% to the United States, followed by Canada (14.1%) and the U.K. (13.54%).
ETFs for Diversified Access to the Financial SectorBroad-based financial ETFs offer investors a diversified way to capture potential benefits from the AI financing boom.
Investors can consider State Street Financial Select Sector SPDR ETF (XLF - Free Report) , Vanguard Financials Index Fund ETF Shares (VFH - Free Report) , Invesco KBW Bank ETF (KBWB - Free Report) , iShares U.S. Financials ETF (IYF - Free Report) and iShares U.S. Financial Services ETF (IYG - Free Report) .
Among the mentioned funds, XLF and VFH have a Zacks ETF Rank #1 (Strong Buy). Meanwhile, IYF and IYG have a Zacks ETF Rank #2 (Buy). XLF is the cheapest option among the mentioned funds, charging an annual fee of 0.08%. XLF is also the most liquid fund, having a one-month trading average of about 32.59 million shares.
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At $218.10, NVIDIA (NASDAQ:NVDA | NVDA Price Prediction) trades in a range where risk and reward are closely balanced. The chip giant sits at the intersection of the largest capital cycle in tech history and a growing debate over whether that movement is starting to look like a bubble. The same buildout powering NVIDIA’s growth is also feeding the case against it.
NVIDIA designs the accelerated computing platform that powers essentially every frontier AI model in production. The Data Center segment now represents 92% of total revenue, and the customer list reads like a who’s who of hyperscale AI: Meta, OpenAI, Google Cloud, Microsoft, Oracle, Anthropic, and xAI. The stock has climbed to a $5.42 trillion market cap on four consecutive earnings beats and margins near record highs.
Why the Musk Moonshot Could Push NVDA Toward $500 On SpaceX’s first earnings call, Elon Musk told investors he wants to scale data center capacity from roughly 1.4 gigawatts today to 10 gigawatts by year-end 2027. Research firm SemiAnalysis estimates the buildout at $50 billion per gigawatt annually, or $300 billion to $500 billion in 2027 capital spending alone, and considers the target achievable. Here’s the rub: Musk said SpaceX would work exclusively with NVIDIA, a decision SemiAnalysis ties to expected vendor-financing support.
That thesis is reinforced by the recent $500 billion financing partnership NVIDIA announced with Apollo, BlackRock, Blackstone, Brookfield, Goldman Sachs, and KKR to underwrite AI factory buildouts. Layer even $150 billion to $200 billion in incremental SpaceX orders onto NVIDIA’s accelerating trajectory, including Q2 guidance of $91 billion, up roughly 34% year over year, and the path to a $500 share price becomes a math problem.
Why the Same Moonshot Could Crack the Stock The problem is scale. A single customer proposing capex on par with AWS and Google combined, at a company far less profitable than either, is exactly the kind of concentration risk bears have salivated over. NVIDIA’s $119 billion pipeline in supply commitments already assumes the AI capex party continues. If SpaceX funding tightens or hyperscalers slow orders to digest capacity, the demand cliff is real.
Valuation leaves no room for error. Shares trade at roughly 34x trailing earnings and 26x forward, with net insider selling across 27 recent transactions. Bears also point to zero China Data Center compute in the Q2 guide and the reality that AMD (NASDAQ:AMD) is courting the same hyperscalers with its MI450 roadmap.
Why Patience Is Winning the Argument Today The fundamentals are extraordinary. Nvidia’s revenue grew 85.2% YoY last quarter to $81.61 billion, gross margin sits at 75.0%, and free cash flow hit $48.55 billion in a single quarter. Yet the stock has been range-bound, up just 3.12% over the past month even as guidance accelerated.
Investors want confirmation, not projection. They want to see the OpenAI 10GW, Meta multi-generation, and SpaceX gigawatt commitments convert to booked orders on schedule. Until then, buyers and sellers are canceling each other out.
What the Numbers Actually Say NVIDIA currently trades at $217.43. The Wall Street consensus target is $302.83, implying roughly 37.6% upside. Coverage is heavily skewed bullish, with 10 Strong Buy, 48 Buy, 2 Hold, and 1 Sell ratings.
Year to date, NVDA is up 16.6%, edging the S&P 500’s 13.36% gain but trailing AMD’s 121.4% surge as the market prices in a genuine second source. Polymarket traders assign a 51.5% probability that shares close August above $220 and just 9.5% above $250.
The Verdict on NVIDIA at $217.43 At $217.43, the risk/reward on NVIDIA looks balanced.
The setup cuts both ways. If SpaceX directs even a fraction of its projected $300 billion to $500 billion in 2027 capital spending toward NVIDIA, with support from the Apollo and BlackRock financing platform, revenue estimates get rewritten higher and a $500 share price becomes a serious 12- to 18-month conversation. If Musk’s gigawatt math slips, funding stalls, or hyperscalers pause to digest capacity, the same $119 billion in supply-related commitments that looks visionary today starts looking like demand risk.
The right posture is patience with clear triggers. Bullish confirmation would require firm procurement commitments for the SpaceX buildout and continued NVIDIA Data Center growth above 60% into fiscal 2028. Bearish confirmation would call for a hyperscaler capital-spending cut, a material Blackwell delay, or evidence that the $500 billion financing platform is struggling to place capital. Watch NVIDIA’s quarterly Data Center growth, gross margin, and the pace at which announced megadeals convert into bookings.
When a single customer’s buildout can move a $5 trillion stock by $80 in either direction, waiting for the picture to develop is the prudent call.
Contact [email protected] for any questions or corrections.
CNBC's Leslie Picker, Kristina Partsinevelos and Ed Yardeni, Yardeni Research president, joins 'Power Lunch' to discuss Nvidia's recent partnership with Wall Street.
