Nvidia stock NVDA fell 2.5% on Thursday, tracking a broader decline in semiconductor stocks, even as the company announced new artificial intelligence partnerships and products aimed at expanding its presence in Japan.
The stock traded at $207.27 in midday trading, broadly in line with the wider chip sector.
The PHLX Semiconductor Index was also down 2.5%.
The announcements come as investors continue to question the sustainability of Big Tech spending on AI infrastructure, prompting Nvidia to broaden its customer base beyond its largest US cloud computing clients.
Nvidia said it will provide AI chips and computing infrastructure for foundational AI models to Noetra, a government-backed Japanese AI initiative backed by companies including SoftBank, Sony, and Honda.
Under the initial deployment, Noetra will install 13,750 Nvidia Vera central processing units and 27,500 Nvidia Rubin graphics processing units, providing 140 megawatts of data center capacity.
The companies did not disclose the financial terms of the agreement.
While the deployment is modest compared with the hundreds of thousands of chips Nvidia sells to its largest US customers, the company has identified sovereign AI as a growing business.
Nvidia said revenue from sovereign AI—government-backed efforts to develop independent artificial intelligence capabilities—more than tripled year over year to more than $30 billion in fiscal 2026.
The company said it expects further growth from the segment.
Separately, Nvidia announced collaborations with several Japanese companies focused on physical AI, which encompasses robotics, autonomous driving, and other real-world AI applications.
The company introduced two new supercomputing modules, the T3000 and T2000, based on its Thor computing architecture.
Nvidia said the modules are designed to support mass-market robotics.
On Wednesday, Nvidia also unveiled Cosmos 3 Edge, a new artificial intelligence model for robots and vision AI agents.
According to the company, Cosmos 3 Edge is a world model designed to help AI systems perceive and navigate physical environments in real time.
Nvidia said world models can learn from a broader range of inputs than large language models. The launch follows the introduction of Cosmos 3 in May.
The announcements coincide with Chief Executive Jensen Huang's two-day visit to Japan, where Nvidia is expanding its physical AI ecosystem.
According to the company, Fujitsu, Hitachi, and Kawasaki Heavy Industries intend to join a coalition aimed at advancing physical AI technologies in Japan.
“The next frontier of AI is in the physical world, and this is a once-in-a-generation opportunity for Japan,” Huang said in a Wednesday statement. “Japan invented modern manufacturing. Now, it has the opportunity to reinvent it for the age of intelligent industries.”
Nvidia's latest initiatives build on broader investment in Japan's AI ecosystem.
The company's partnerships come months after Microsoft announced a $10 billion investment in Japan to expand AI infrastructure and strengthen cybersecurity.
SoftBank has also increased its investments in artificial intelligence and is seeking to partner with Microsoft and Sakura Internet to advance AI development in the country.
According to the International Trade Administration, Japan's artificial intelligence market is expected to reach $27.9 billion by 2029.
The agency attributed the projected growth to the Japanese government's efforts to promote AI adoption across industries and the willingness of domestic companies to pursue international partnerships.
Bank of America vidí v síťových čipech NVIDIA další byznys za 20 miliard USD. Ve čtvrtletí tento segment vzrostl na 14,8 miliardy USD, meziročně o 199 %.
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NVIDIA (NASDAQ:NVDA | NVDA Price Prediction) has spent the last two months digesting a strong Q1 earnings report, with the back half of fiscal 2027 looking constructive. Bank of America has flagged Nvidia’s networking silicon as the next multi-billion-dollar business inside the data center, and our model agrees the market is not fully pricing it in.
Our 24/7 Wall St. price target for NVDA is $261.11, implying 23.28% upside from $211.80. Our recommendation is buy, with high confidence.
24/7 Wall St. Price Target Summary Metric Value Current Price $211.80 24/7 Wall St. Price Target $261.11 Upside 23.28% Recommendation BUY Confidence Level 90% A Summer Reset That Reopened the Runway NVDA is up 7.55% in the past week and 13.7% year to date, though shares sit roughly 28% below the $236.26 52-week high.
Q1 FY2027, reported on May 20, 2026, delivered: revenue of $81.615 billion grew 85.23% year over year, non-GAAP EPS came in at $1.87 versus $1.7738 consensus, and management guided Q2 to $91.0 billion. Data center networking alone was $14.8 billion, up 199% year over year. That is the line item Bank of America keeps circling.
Why Bulls See $300 and Beyond The bull case rests on three levers. First, networking scaled from roughly $7.25 billion in Q2 FY26 to $14.8 billion last quarter; Bank of America’s $20B business framing is not aggressive at that trajectory.
Second, supply commitments hit $119 billion, up from $50.3 billion two quarters ago, effectively pre-signing demand.
Third, capital return: an $80 billion buyback authorization landed in May on top of the $38.5 billion remaining.
Jensen Huang stated: “The buildout of AI factories, the largest infrastructure expansion in human history, is accelerating at extraordinary speed.” The Street’s $301.62 average target, backed by 48 Buy ratings, sits within reach if Blackwell 300 and Vera Rubin ramp cleanly (a scenario The Next Nvidia Playbook has been mapping).
What Could Go Wrong Q2 guidance explicitly excludes China data center compute, and forward revenue was zero from H20 shipments this quarter versus $4.6 billion a year earlier. A prolonged export freeze caps the top line. Beta of 2.211 means any hyperscaler capex pause hits NVDA harder than most.
Insiders have been net sellers across 26 recent transactions. The counterfactual: the $4.5B H20 charge that crushed year-ago margins is gone, gross margin expanded to 75%, and free cash flow of $48.55 billion in a single quarter absorbs macro noise. A bear case scenario lands near $227.02, still above current levels.
How NVIDIA Compares to AMD and Broadcom Advanced Micro Devices (NASDAQ:AMD) is the direct GPU competitor. AMD’s Q1 FY26 data center revenue of $5.78 billion grew 57% year over year, but NVDA’s data center segment is more than $75 billion in a single quarter. AMD trades at a trailing P/E near 206, making NVDA’s 32 multiple look pedestrian.
Broadcom (NASDAQ:AVGO) is the custom accelerator and AI networking counterpoint. AVGO printed $10.8 billion in AI semiconductor revenue last quarter, up 143%, and guided Q3 AI to $16.0 billion. It validates the size of the networking pie rather than shrinking NVDA’s slice.
Company Forward P/E Latest Qtr Rev Growth NVIDIA 24 85.2% AMD ~35 37.9% Broadcom ~40 47.9% The peer set makes our $261.11 target look conservative.
Our Take on NVIDIA at Current Levels Our 24/7 Wall St. price target of $261.11 is a buy at 90% confidence. Networking is real, compounding at triple digits, and the market is still valuing NVDA on compute alone.
The setup looks constructive if hyperscaler capex guides stay firm through the next TSMC report. The thesis weakens if China export policy tightens further and Q2 revenue prints below the $91 billion guide. Neither looks likely right now.
Here is where NVDA could trade if execution holds.
Year 24/7 Wall St. Price Target 2026 $235 2027 $266 2028 $301 2029 $341 2030 $386 These projections assume NVIDIA sustains data center dominance and networking scales as guided. Significant upside would come from an accelerated Vera Rubin cycle; downside from a sustained hyperscaler capex reset.
NVIDIA už nepočítá s žádnými tržbami z čínského datacentrového byznysu a místo toho tlačí nový CPU byznys. Firma tvrdí, že Vera CPU otevírá trh o velikosti 200 miliard USD.
Nvidia CEO Jensen Huang shakes hands with an attendee after the media Q&A session during Nvidia/Japan AI Ecosystem Reception in Tokyo on July 16, 2026. AI-powered robots for use in shipbuilding, the Japanese firm said on July 16 during a visit to Tokyo by the US chip giant's CEO Jensen Huang. (Photo by Philip FONG / AFP via Getty Images)
AFP via Getty Images
This article was written by Doug Nathman, with research by his team at Trefis.
The company has reduced its commentary regarding the multi-billion-dollar issue related to China that previously dominated their discussions, and what they are focusing on now indicates a substantial change in where the company's growth must stem from.
With NVIDIA (NVDA) stock still trading close to all-time highs following an impressive 62% surge over the past two years, it’s easy to lose sight of the significance behind record-setting figures. The latest quarter was consistent with this trend, showcasing data center revenue skyrocketing by 92% compared to the previous year. However, the most significant indicator for an investor isn’t always the most pronounced statistic. It’s the issue that was once a major headline matter and has now faded to a mere footnote. For NVIDIA, that issue pertains to China.
The Multi-Billion Dollar Issue That Became Less VisibleNot long ago, dealing with U.S. export regulations concerning its China-specific chips was a key narrative. Management was clear about the financial impact, indicating they were “unable to ship $2.5 billion in H20 revenue during the first quarter” of last year. It was a clearly articulated, significant obstacle. Currently, this topic is less frequently mentioned. The issue remains present; during the latest earnings call, the company acknowledged it is “not forecasting any revenue from China data center compute in our outlook.” The crisis has been addressed by effectively writing off this market. The clamor has subsided, yielding to a serene acceptance of a new reality.
The New $200 Billion Growth Driver Taking Its PlaceThis calm was facilitated by the vast scope of what NVIDIA is currently emphasizing: CPUs. The company has shifted dramatically, reorienting its future with a significant new initiative. Management is now promoting its Vera CPU, stating it “opens up a completely new $200 billion TAM for NVIDIA, a market we have yet to penetrate.” More specifically, they have announced “visibility to almost $20 billion in total CPU revenue this year.” The focal point has shifted. The narrative has transitioned from defending a struggling GPU market to aggressively pursuing an entirely new one, with the company now aiming to establish itself as the “world’s leading CPU supplier.”
The Silence Has Dual ImplicationsThe evaluation here is mixed but leans towards a reassuring outlook. It is troubling that a substantial growth market was effectively lost, a reality reflected in the company's overall revenue growth slowing from its three-year average. Losing a market like China comes with consequences. However, the company’s response demonstrates remarkable strategic flexibility. Instead of fixating on the loss, management has introduced a new growth avenue in CPUs that, according to their figures, vastly exceeds the revenue setback. The pivot is bold and ambitious. The critical point to monitor now is the implementation: anticipate the solid figure on CPU revenue next quarter to determine if this new narrative fulfills its multi-billion-dollar potential.
This Is Not The NVIDIA You Thought You OwnedThis realization is striking. The NVIDIA you believe you possess, the reigning GPU champion, has subtly transformed into a different investment. It is now a comprehensive systems company whose future growth heavily relies on dominating the CPU market, a transition necessitated by a geopolitical barrier it could no longer surmount. Recognizing that transformation required paying attention to the silence.
And for those interested in the semiconductor sector, rather than being influenced by what one company might not disclose, a semiconductor ETF like SMH provides coverage of that specific industry.
NVDA Has Experienced A 66% Decline From Its Peak BeforeWhen management leaves inquiries unanswered, the uncertainty weighs most heavily on those holding significant amounts of the stock. NVDA has seen a decline of 66% from its peak in the past five years, and a drop of this magnitude feels very different when one position constitutes a large portion of your wealth.
Understanding the implications of a repeat decline on your net worth is precisely what the Trefis Wealth team analyzes, utilizing the same rules-based systematic discipline found in our High Quality Portfolio. Request a free vulnerability audit of your major positions.
SummaryTSMC and ASML both raised guidance, confirming AI infrastructure remains supply constrained, while Rubin's N3 node is fully booked and CoWoS capacity expands nearly 50%.Nvidia's Kyber delay concerns appear limited to Rubin Ultra, leaving mainstream Rubin NVL72 deployments and near-term revenue expectations largely unchanged.Qualification of Samsung, SK hynix and Micron for HBM4 reduces supply-chain risk as the industry shifts toward higher-capacity 16-Hi HBM4 memory.Despite 82% projected FY2027 revenue growth, Nvidia's valuation compresses materially, while upstream capacity expansion suggests AI infrastructure investment remains in its early stages. Getty Images
I believe that the market is getting too focused on Nvidia's (NVDA) quarterly results execution and failing to acknowledge the most robust indication of its outlook. The most bullish signals are no longer coming from
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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.
Seeking Alpha's Disclosure: Past performance is no guarantee of future results. No recommendation or advice is being given as to whether any investment is suitable for a particular investor. Any views or opinions expressed above may not reflect those of Seeking Alpha as a whole. Seeking Alpha is not a licensed securities dealer, broker or US investment adviser or investment bank. Our analysts are third party authors that include both professional investors and individual investors who may not be licensed or certified by any institute or regulatory body.
NVIDIA ve 1. čtvrtletí fiskálního roku 2027 zvýšila tržby o 85,2 % na 81,615 miliardy USD a čistý zisk o 210,63 %. Firma zároveň zvýšila dividendu z 0,01 na 0,25 USD na akcii a schválila dalších 80 miliard USD na zpětné odkupy.
I keep buying NVIDIA. Every paycheck, every pullback, every time the headlines swing bearish on AI capex, I click buy again on NVIDIA (NASDAQ:NVDA | NVDA Price Prediction). This is the single position I trust to compound retirement capital through the AI decade, and my conviction has almost nothing to do with the chips themselves.
What pulls me back to the buy button is the CUDA software ecosystem, embedded across two decades into every major AI framework, library, and developer workflow. Enterprise customers who try to leave face migration costs and operational risk they refuse to swallow. Jensen Huang described the platform on the last call as “the only platform that runs in every cloud, powers every frontier and open source model, and scales everywhere AI is produced.” That reads to me as a toll road on global AI development.
The Receipts Behind My Conviction The financials show what a software moat looks like when it meets a demand cycle. Q1 fiscal 2027 revenue landed at $81.615 billion, up 85.2% year over year, with non-GAAP EPS of $1.87 topping the $1.7738 consensus. Data Center revenue hit $75.246 billion, up 92%, with networking alone up 199%. Net income grew 210.63%, outrunning revenue growth. That is operating leverage I can measure.
Margins tell the pricing-power story. Non-GAAP gross margin expanded to 75.0% from 60.8% a year earlier. Return on equity sits at 101.5%, ROIC at 92.2%, and debt/equity at 0.073. Free cash flow in the quarter reached $48.554 billion. Management responded by raising the dividend from $0.01 to $0.25 per share and authorizing an additional $80.0 billion in buybacks with no expiration. In Q1 alone, roughly $20.0 billion was returned to shareholders.
Then there is visibility. Total supply-related commitments stand at $119.0 billion, backed by multi-year deals with Meta Platforms (NASDAQ:META) for millions of Blackwell and Rubin GPUs, OpenAI’s 10-gigawatt deployment commitment, and CoreWeave’s 5-plus gigawatt buildout through 2030. Guidance for Q2 calls for $91.0 billion in revenue at the same 75% gross margin, and that guide excludes China entirely.
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Why Not the Obvious Alternative The name a reader reaches for first is AMD (NASDAQ:AMD). I keep passing. Nothing available to me shows an AMD data-center business growing at NVIDIA’s 92% pace, a networking line expanding 199%, or gross margins near 75.0%. CUDA is the reason. Every framework optimization, every NIM microservice, every Dynamo release lands on NVIDIA silicon first. AMD ships capable chips into a software world that already speaks CUDA. That gap is what my capital is really paying for.
The Risk I Take Seriously The risk I take seriously is customer concentration meeting custom silicon. Hyperscalers are roughly 50% of Data Center revenue, and Amazon (NASDAQ:AMZN), Alphabet (NASDAQ:GOOGL), and Meta are all funding in-house accelerators. China has already been erased from guidance, costing the $4.6 billion that the year-ago quarter carried. What keeps the thesis intact for me is that Blackwell remains, in Huang’s words, “off the charts,” with cloud GPUs sold out. The same customers funding rival silicon are simultaneously signing multi-gigawatt NVIDIA contracts.
Why the Buy Button Stays Active At a forward P/E of 24x against triple-digit net income growth, a fortress balance sheet, and $119 billion in booked supply, I consider that a reasonable price for the operating system of the AI economy (247’s 7 Stocks Powering the AI Boom report frames the broader stack well). As long as CUDA remains the language every serious model is trained and served in, my next buy is already scheduled.
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Nvidia představila nový model Cosmos 3 Edge pro roboty a vision AI agenty a rozšiřuje tak své působení v japonské fyzické AI. Firma zároveň buduje koalici s Fujitsu, Hitachi a Kawasaki Heavy Industries.
Nvidia unveiled a new AI model for robots and vision AI agents on Wednesday, deepening its push into the physical AI market in Japan.
The company's new model, Cosmos 3 Edge, is a so-called world model, designed to help systems perceive and navigate physical environments in real time. Cosmos 3 edge is a World models are systems that can learn from a wider range of inputs compared to large language models (LLMs). The rollout follows the launch of Cosmos 3 in May.
The regional expansion takes center stage during CEO Jensen Huang's two-day visit to Japan, where the Silicon Valley chip giant is expanding its physical AI footprint by forming a coalition that local industrial giants, including Fujitsu, Hitachi, and Kawasaki Heavy Industries, intend to join, according to Nvidia.
"The next frontier of AI is in the physical world, and this is a once-in-a-generation opportunity for Japan," Nvidia CEO Jensen Huang said in a Wednesday statement. "Japan invented modern manufacturing. Now, it has the opportunity to reinvent it for the age of intelligent industries."
The tech giant's partnership with Japanese firms comes just months after Microsoft's $10 billion investment in the country, which aims to build out AI infrastructure and beef up cybersecurity. Japanese investment giant SoftBank has bet heavily on the boom in AI. It's looking to partner with Microsoft and Sakura Internet to develop AI in Japan.
Japan's AI market is expected to reach $27.9 billion by 2029, opening doors for U.S. firms to invest, according to the International Trade Administration. This growth is driven by Tokyo's active push to promote AI adoption across industries, coupled with the eagerness of local firms to forge international partnerships.
Ajay Rajadhyaksha, global chairman of research at Barclays, told CNBC last month that the country holds an advantage in Asia, driven by its diverse AI and clean structural growth stories.
Nvidia's partnership pushNvidia is also aggressively expanding its AI footprint into Japan's healthcare and biotechnology sectors by extending its reach into agentic AI for advanced sciences through new drug discovery and medical robotics initiatives.
When it comes to agentic AI, Nvidia highlighted the ongoing expansion of Tokyo-1, the AI drug discovery consortium operated by Xeureka, a Mitsui subsidiary. The platform, which has steadily grown since its initial announcement in 2023, is powered by the Nvidia BioNeMo Agent Toolkit, a platform for accelerating autonomous AI drug discovery.
Japan's pharmaceutical heavyweights are already scaling their involvement. Major drugmakers, including Astellas Pharma Inc, Daiichi Sankyo, and Ono Pharmaceutical are utilizing Nvidia's specialized biology toolkit to streamline their workflows, the U.S. company said in a blog post.
Beyond biotech, Nvidia said it is making inroads into industrial automation through a partnership with Kawasaki Heavy Industries.
Fujitsu s FANUC, Yaskawa Electric a Kawasaki Heavy Industries zkoumá platformu fyzické AI s technologií Nvidia pro továrny, logistiku a nemocnice. Zatím jde jen o průzkum bez objednávek či závazků ohledně tržeb.
Nvidia’s latest Japanese collaboration may not change earnings forecasts overnight, but it offers a glimpse of where the chipmaker expects artificial intelligence to travel next.
Fujitsu is bringing together FANUC, Yaskawa Electric and Kawasaki Heavy Industries to explore a physical-AI control platform using Nvidia technology, with applications across factories, logistics networks and hospitals.
For investors, the attraction is not a robot order. It is the possibility that Nvidia can extend its dominance from data centres into machines operating throughout the physical economy.
No orders, deployment targets, or revenue commitments were disclosed.
Fujitsu will lead business discussions around a common platform designed to connect enterprise systems with autonomous robots.
Proposed uses include optimising factory production, automating warehouse material handling and deploying robots to transport medicines, specimens or patients inside hospitals.
Nvidia’s role extends beyond supplying processors. Fujitsu plans to use Cosmos world models to understand and predict real environments.
Omniverse, the Isaac robotics platform and the Newton physics engine will support digital twins, robot learning, simulation, verification and the transition from virtual testing to physical deployment.
The partners also bring experience that Nvidia cannot build alone.
Yaskawa said its MOTOMAN NEXT autonomous robot already carries Nvidia GPUs as standard, while FANUC and Kawasaki contribute established expertise in factory automation, control systems, mobility and healthcare robotics.
Still, the announcement remains exploratory. Fujitsu said the companies will begin by discussing business opportunities and formulating a roadmap for technology development and expansion.
Also read: Nvidia’s Jensen Huang hints at Korea’s next trillion-dollar AI opportunity
The investment argument is that Nvidia could capture several layers of future robotics spending.
Customers may train models on their data-centre GPUs, create synthetic environments with Cosmos, test machines through Omniverse and Isaac, and run intelligence at the edge using Nvidia processors.
That would make robotics another full-stack ecosystem opportunity, rather than a narrow chip market.
A shared development environment used by multiple manufacturers could also strengthen switching costs: the more engineers train, simulate and validate robots through Nvidia software, the harder it becomes to replace that stack.
Wedbush analyst Dan Ives told CNBC’s “Squawk Box” that Nvidia remained the foundation of the physical-AI ecosystem and was four to five years ahead of serious competitors.
His comments preceded the Japan announcement, but the collaboration supports his broader argument that Nvidia’s moat increasingly spans hardware, models and development tools.
Nvidia stock NASDAQ:NVDA was recently trading around $212.50. KeyBanc analyst John Vinh this week raised his price target to $330 from $310 and retained an Overweight rating, citing strong demand and competitive barriers created by CUDA.
He viewed a slight delay in the Vera Rubin ramp as posing limited risk because additional Blackwell B300 shipments could offset the timing shift.
Bank of America analyst Vivek Arya has likewise described Nvidia’s relative underperformance as an “enhanced” buying opportunity.
Arya argues that investors are overemphasising higher memory costs and custom-chip competition while underestimating Nvidia’s pricing power, supply-chain execution and share of hyperscaler infrastructure spending.
Neither call depended on Japan robotics revenue. Wall Street’s current bull case still rests overwhelmingly on data centres, CUDA, Blackwell and Rubin.
The Fujitsu-led initiative adds longer-dated optionality rather than near-term earnings visibility.
NVIDIA a Noetra Corp. spouštějí v Japonsku první národní AI infrastrukturu pro fyzickou AI. Projekt podpořený METI má dodat 140 megawattů kapacity datového centra.
NVIDIA to partner with Noetra Corp. to build the NVIDIA Vera Rubin AI factory with 13,750 Vera CPUs and 27,500 Rubin GPUs to deliver 140 megawatts of data center capacity based on the NVIDIA DSX platform.The initiative, supported by Japan’s Ministry of Economy, Trade and Industry (METI), will provide the computing foundation for Japan’s FRONTia Project to strengthen the country’s ecosystem across manufacturing, logistics, healthcare and more.AI factory to create open multimodal foundation models to develop AI agents, digital twins, robotics and physical AI applications. TOKYO, July 16, 2026 (GLOBE NEWSWIRE) -- NVIDIA today announced it is working with Noetra Corp. to launch an NVIDIA Vera Rubin AI factory with 13,750 NVIDIA Vera CPUs and 27,500 NVIDIA Rubin GPUs for national physical AI. Supported by Japan’s AI and industry leaders, the initiative marks the world’s first national AI infrastructure for physical AI, strengthening the country’s AI ecosystem across manufacturing, logistics, healthcare, telecommunications and more.
The new AI factory, established by Noetra, will be architected with NVIDIA Vera Rubin NVL72 racks using the NVIDIA DSX™ platform, connected and scaled with NVIDIA Spectrum-X™ Ethernet networking. It will enable the development of open multimodal foundation models that power AI agents, digital twins, robotics and other physical AI applications.
The NVIDIA Vera Rubin AI factory will provide the computing foundation for Japan’s FRONTia Project, which refers to the project titled, “Development of Multimodal Foundation Models with a View to AI Robotics and Physical AI,” launched by METI. The project brings together the country’s manufacturing expertise, real-world industrial data and global technology leaders to develop highly reliable multimodal foundation models for physical AI.
The pretrained weights of Noetra’s multimodal foundation models will be made broadly available to domestic model developers and enterprises alongside software such as NVIDIA Nemotron™, NVIDIA Cosmos™, NVIDIA Isaac™ GR00T open models, NVIDIA NeMo™ libraries and more. This will accelerate the development of agentic AI and physical AI applications.
“Japan invented modern manufacturing. Now, it is building the AI factories that will power the next industrial revolution,” said Jensen Huang, founder and CEO of NVIDIA. “NVIDIA is honored to partner with Japan and its industrial leaders to build the AI infrastructure that will power the country’s industries, its economy and a new generation of innovation.”
“Japan has launched the FRONTia Project, which will serve as the core of the country’s physical AI ecosystem,” said Ryosei Akazawa, Japan’s Minister of Economy, Trade and Industry. “By fostering collaboration between Japan and leading global innovators — including NVIDIA — and leveraging Japan’s strengths, such as its onsite expertise and manufacturing technology infrastructure, we will build highly reliable multimodal foundation models and contribute to solving global social challenges.”
“Bringing physical AI into the real world requires enormous computing, data and foundational technologies — challenges no single company can solve alone,” said Hironobu Tamba, CEO of Noetra. “Together with partners across Japan and around the world, Noetra will advance Japan-developed multimodal foundation models and accelerate the deployment of physical AI across Japanese industries by broadly sharing the results of our research.”
Built on the NVIDIA Vera Rubin DSX AI factory architecture, the AI factory will deliver 140 megawatts of data center capacity combined with the NVIDIA Spectrum-X Ethernet networking platform, NVIDIA BlueField® DPUs, and tightly codesigned silicon, systems and software to provide breakthrough AI performance, lower token costs and massive scale for frontier AI training.
NVIDIA DSX provides a reference design and platform for AI factories, helping infrastructure builders accelerate time to production, increase token throughput per megawatt and operate with greater reliability and efficiency.
Advancing Japan’s Physical AI Ambitions
Japan’s AI Robotics Strategy, released in March, sets a goal for the country to capture more than 30% of the global AI robotics market by 2040, representing an estimated $133 billion opportunity. To help achieve the goal, METI is advancing a multimodal foundation model program for robotics and physical AI as part of Japan’s broader industrial AI policy.
As the AI factory expands, it will support training trillion-parameter-scale AI models, giving organizations across Japan access to one of the world’s most advanced AI environments and laying the foundation for the next era of intelligent manufacturing and robotics.
About NVIDIA
NVIDIA (NASDAQ: NVDA) is the world leader in AI and accelerated computing.
For further information, contact:
Kristin Uchiyama
Corporate Communications
NVIDIA Corporation [email protected]
Certain statements in this press release including, but not limited to, statements as to: Japan building the AI factories that will power the next industrial revolution; NVIDIA to partner with Japan and its industrial leaders to build the AI infrastructure that will power the country’s industries, its economy and a new generation of innovation; expectations with respect to growth, performance, availability, and benefits of NVIDIA’s products, services and technologies, and related trends and drivers; expectations with respect to NVIDIA’s third party arrangements, including with its collaborators and partners; expectations with respect to technology developments, and related trends and drivers; projected market growth and trends; expectations with respect to AI and related industries; and other statements that are not historical facts are forward-looking statements within the meaning of Section 27A of the Securities Act of 1933, as amended, and Section 21E of the Securities Exchange Act of 1934, as amended, which are subject to the “safe harbor” created by those sections based on management’s beliefs and assumptions and on information currently available to management and are subject to risks and uncertainties that could cause results to be materially different than expectations. Important factors that could cause actual results to differ materially include: global economic and political conditions; NVIDIA’s reliance on third parties to manufacture, assemble, package and test NVIDIA’s products; the impact of technological development and competition; development of new products and technologies or enhancements to NVIDIA’s existing products and technologies; market acceptance of NVIDIA’s products or NVIDIA’s partners’ products; design, manufacturing or software defects; changes in consumer preferences or demands; changes in industry standards and interfaces; unexpected loss of performance of NVIDIA’s products or technologies when integrated into systems; NVIDIA’s ability to realize the potential benefits of business investments or acquisitions; and changes in applicable laws and regulations, as well as other factors detailed from time to time in the most recent reports NVIDIA files with the Securities and Exchange Commission, or SEC, including, but not limited to, its Annual Report on Form 10-K and Quarterly Reports on Form 10-Q. Copies of reports filed with the SEC are posted on the company’s website and are available from NVIDIA without charge. These forward-looking statements are not guarantees of future performance and speak only as of the date hereof, and, except as required by law, NVIDIA disclaims any obligation to update these forward-looking statements to reflect future events or circumstances.
A photo accompanying this announcement is available at https://www.globenewswire.com/NewsRoom/AttachmentNg/322eb6fb-fe24-4ea5-a123-2c076a6fa629
NVIDIA Vera Rubin AI Factory for Japan Physical AI NVIDIA today announced it is working with Noetra Corp. to launch an NVIDIA Vera Rubin AI factory wit...
Nvidia oznámila partnerství s japonskými firmami včetně Fanuc a Yaskawa Electric na vývoji robotiky a AI. Jensen Huang řekl, že s AI budou roboti chytří, snadno přizpůsobitelní a dostupní.
Item 1 of 6 Nvidia CEO Jensen Huang, Fujitsu CEO Takahito Tokita, FANUC President and CEO Kenji Yamaguchi, Yaskawa Electric Vice Chairman and Executive Officer Masahiro Ogawa, and Kawasaki Heavy Industries President and CEO Yasuhiko Hashimoto attend a media briefing on the announcement regarding exploring physical AI development and implementation across industries, in Tokyo, Japan, July 16, 2026. REUTERS/Kim Kyung-Hoon
[1/6]Nvidia CEO Jensen Huang, Fujitsu CEO Takahito Tokita, FANUC President and CEO Kenji Yamaguchi, Yaskawa Electric Vice Chairman and Executive Officer Masahiro Ogawa, and Kawasaki Heavy Industries... Purchase Licensing Rights, opens new tab Read more
TOKYO, July 16 (Reuters) - Nvidia (NVDA.O), opens new tab said on Thursday it was partnering with Japanese companies including Fanuc (6954.T), opens new tab and Yaskawa Electric (6506.T), opens new tab to advance the development of robotics and AI.
"With AI, robots will become smart, easily adaptable and accessible," Nvidia CEO Jensen Huang said at a media event in Tokyo.
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On Wednesday Huang attended an event held by gaming firm Sega Sammy (6460.T), opens new tab in the Akihabara electronics district and ate dinner at a Japanese "izakaya" pub.
Huang has achieved rock star status in Taiwan and his appearances have also generated interest from onlookers in Japan, which boasts leading companies in the chipmaking supply chain.
"I think he's the most influential man on Earth," said Chang Hui-Yu, a 57-year-old Taiwanese tourist, speaking outside the Sega event.
"It was my first time seeing Jensen Huang in person and I was so excited," said Brian Yang, 37, who is Taiwanese and lives in Tokyo.
Huang was pictured last night with executives of leading Japanese supply chain firms including the CEOs of chipmaker Kioxia (285A.T), opens new tab and equipment maker Tokyo Electron (8035.T), opens new tab.
Investors are weighing the strength of the AI investment cycle, with chipmaking equipment maker ASML (ASML.AS), opens new tab on Wednesday raising its sales forecast and pledging capacity expansion.
TSMC (2330.TW), opens new tab, the world's leading contract chipmaker, is expected to post a fifth consecutive quarter of record earnings on Thursday due to the AI boom.
Reporting by Sam Nussey, Irene Wang and Anton Bridge; Editing by Sonali Paul
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NVIDIA oznámila Cosmos 3 Edge pro lokální vidění a nasazení robotických politik na platformách NVIDIA Jetson Thor. Japonské firmy včetně FANUC, Fujitsu a Hitachi se chtějí připojit ke koalici Cosmos.
NVIDIA introduces Cosmos 3 Edge for on-device vision reasoning and robot policy deployment on NVIDIA Jetson Thor platforms, and NVIDIA Metropolis libraries built on NVIDIA Cosmos for agentic vision AI development.Japan’s physical AI ecosystem leaders AIRoA, FANUC, Fujitsu, Hitachi, Kawasaki Heavy Industries, Kubota, NEC, SoftBank Corp., Sony Group Corporation and Yaskawa Electric intend to join the NVIDIA Cosmos Coalition to help build open frontier physical AI models.Fujitsu is exploring the development of a collaborative control platform for physical AI, with FANUC, Yaskawa Electric and Kawasaki Heavy Industries integrating NVIDIA technologies, while Japanese manufacturers and physical AI leaders including Enactic, Honda R&D, GROOVE X, Mitsui & Co, OMRON, Shimizu Corporation and Telexistence are building on NVIDIA’s physical AI stack.
TOKYO, July 15, 2026 (GLOBE NEWSWIRE) -- NVIDIA today announced that Japan’s physical AI leaders are building on the NVIDIA Cosmos™, NVIDIA Isaac™, NVIDIA Metropolis and NVIDIA Jetson™ platforms to accelerate the deployment of intelligent machines across manufacturing, mobility, infrastructure and robotics.
NVIDIA also announced Cosmos 3 Edge, a new addition to the NVIDIA Cosmos 3 open world model family, that brings frontier capabilities to NVIDIA Jetson, helping embodied systems see, reason in real time and predict robot actions locally.
Physical AI is bringing intelligence into machines, facilities and infrastructure, helping industries automate complex work and extend human expertise. Japan’s strengths in robotics, manufacturing, automotive, telecommunications and industrial technology give it a powerful foundation for scaling this next wave of AI.
“The next frontier of AI is in the physical world, and this is a once-in-a-generation opportunity for Japan,” said Jensen Huang, founder and CEO of NVIDIA. “Japan invented modern manufacturing. Now, it has the opportunity to reinvent it for the age of intelligent industries. By combining its world-leading heritage in manufacturing, precision engineering and robotics with NVIDIA Cosmos, Isaac, Metropolis and Jetson, Japan’s innovators are building the next generation of intelligent machines. We are honored to partner with them on this journey.”
NVIDIA Cosmos 3 Edge Powers On-Device Vision Reasoning and Robot Policy
NVIDIA Cosmos 3 Edge is a 4-billion-parameter model built on NVIDIA Nemotron™ that helps robots and vision AI agents understand their surroundings, reason in real time and generate robot actions on NVIDIA edge computers.
Using the open NVIDIA Cosmos framework, developers can adapt the model for specific robots, vehicles, sensors and environments in about a day. Lightweight enough to run on edge GPUs and quickly post-train specialized world action models, Cosmos 3 Edge can be deployed across NVIDIA RTX™ GPUs, NVIDIA DGX™ systems and NVIDIA Jetson, including the newly announced T2000 and T3000 modules.
To further accelerate the development of vision AI agents, NVIDIA is also announcing new NVIDIA Metropolis libraries and skills that help developers use coding agents to build, train and operate video intelligence systems with Cosmos at least 6x faster.
Japan’s Physical AI Leaders Intend to Join NVIDIA Cosmos Coalition to Advance Open World Models
NVIDIA is expanding the NVIDIA Cosmos Coalition to Japan, bringing together world model builders, AI developers and physical AI leaders to advance open world models with Cosmos technologies.
Japan’s physical AI ecosystem leaders including AIRoA, classmethod, Enactic, FANUC, Fujitsu, GROOVE X, Hitachi, Honda R&D, Kawasaki Heavy Industries, Kubota, Mitsui & Co., Mitsubishi Corp., Mujin, NEC, Preferred Networks, SoftBank Corp., Sony Group Corporation, Telexistence, TIER IV, TRON K.K., Turing and Yaskawa Electric intend to join the coalition.
Coalition members can contribute to and build on the NVIDIA Cosmos platform, which includes open models, data curation libraries, datasets and frameworks. The resulting world models will help Japanese companies test and optimize physical AI systems before deployment, shortening development cycles across factories, logistics networks, farms, construction sites, hospitals, roads and homes.
NVIDIA Physical AI Powers Momentum Across Japan’s Robotics, Manufacturing and Smart Spaces Ecosystem
Fujitsu is exploring business opportunities in physical AI with FANUC, Yaskawa Electric and Kawasaki Heavy Industries. Led by Fujitsu, the initiative aims to build a collaborative control platform integrating NVIDIA’s physical AI stack to bridge digital and physical operations across all industrial sectors.
Built with Cosmos world foundation models, the open Isaac robotics development platform, NVIDIA Omniverse™ NuRec libraries and the Newton physics engine, the platform will support AI model development, digital twins, robot learning, simulation-to-real workflows and pre-deployment validation.
NEC, Hitachi, OMRON and Preferred Networks are using NVIDIA Cosmos and NVIDIA physical AI technologies to advance world models, industrial AI and physical AI R&D. SoftBank Corp. is developing a physical AI development platform built on NVIDIA Cosmos, NVIDIA Omniverse and NVIDIA Isaac Sim™. The company is also advancing AI-RAN initiatives using NVIDIA AI Aerial with the aim of delivering intelligent connectivity for billions of physical AI devices.
Mujin is exploring NVIDIA Cosmos for autonomous robotics and intelligent industrial automation powered by MujinOS, while TRON K.K. is developing manufacturing data workflows for task-specific physical AI models in assembly, picking, inspection and material handling, as well as factory 3D digitization workflows.
Kawasaki Heavy Industries is applying NVIDIA physical AI technologies across healthcare, shipbuilding, transportation, aerospace and energy; Kubota is exploring Cosmos-based physical AI for autonomous agriculture and smart farming.
Enactic is fine-tuning the NVIDIA Isaac GR00T open model for elder-care semi-humanoid robots; GROOVE X is building Jetson-powered companion robots,
LOVOT; and Telexistence is applying Isaac and exploring Cosmos for retail automation.
Japan’s industry leaders are also using NVIDIA Metropolis to bring Cosmos-powered vision AI agents into physical operations: Hitachi for smart-building operations, OMRON for automated inspection and Shimizu Corporation for construction safety.
About NVIDIA
NVIDIA (NASDAQ: NVDA) is the world leader in AI and accelerated computing.
For further information, contact:
Quentin Nolibois
Corporate Communications
NVIDIA Corporation [email protected]
Certain statements in this press release including, but not limited to, statements as to: by combining its world-leading heritage in manufacturing, precision engineering and robotics with NVIDIA Cosmos, Isaac, Metropolis and Jetson, Japan’s innovators building the next generation of intelligent machines; expectations with respect to growth, performance, availability, and benefits of NVIDIA’s products, services and technologies, and related trends and drivers; expectations with respect to NVIDIA’s third party arrangements, including with its collaborators and partners; expectations with respect to technology developments, and related trends and drivers; projected market growth and trends; expectations with respect to AI and related industries; and other statements that are not historical facts are forward-looking statements within the meaning of Section 27A of the Securities Act of 1933, as amended, and Section 21E of the Securities Exchange Act of 1934, as amended, which are subject to the “safe harbor” created by those sections based on management’s beliefs and assumptions and on information currently available to management and are subject to risks and uncertainties that could cause results to be materially different than expectations. Important factors that could cause actual results to differ materially include: global economic and political conditions; NVIDIA’s reliance on third parties to manufacture, assemble, package and test NVIDIA’s products; the impact of technological development and competition; development of new products and technologies or enhancements to NVIDIA’s existing products and technologies; market acceptance of NVIDIA’s products or NVIDIA’s partners’ products; design, manufacturing or software defects; changes in consumer preferences or demands; changes in industry standards and interfaces; unexpected loss of performance of NVIDIA’s products or technologies when integrated into systems; NVIDIA’s ability to realize the potential benefits of business investments or acquisitions; and changes in applicable laws and regulations, as well as other factors detailed from time to time in the most recent reports NVIDIA files with the Securities and Exchange Commission, or SEC, including, but not limited to, its Annual Report on Form 10-K and Quarterly Reports on Form 10-Q. Copies of reports filed with the SEC are posted on the company’s website and are available from NVIDIA without charge. These forward-looking statements are not guarantees of future performance and speak only as of the date hereof, and, except as required by law, NVIDIA disclaims any obligation to update these forward-looking statements to reflect future events or circumstances.
Many of the products and features described herein remain in various stages and will be offered on a when-and-if-available basis. The statements above are not intended to be, and should not be interpreted as a commitment, promise, or legal obligation, and the development, release, and timing of any features or functionalities described for our products is subject to change and remains at the sole discretion of NVIDIA. NVIDIA will have no liability for failure to deliver or delay in the delivery of any of the products, features or functions set forth herein.
A photo accompanying this announcement is available at https://www.globenewswire.com/NewsRoom/AttachmentNg/1b939b87-c263-455e-bb69-6d0781da11f4
Japan’s Robotics and Manufacturing Leaders Build on NVIDIA Cosmos to Advance Physical AI Frontier NVIDIA today announced that Japan’s physical AI leaders are building on the NVIDIA Cosmos, NVIDIA Is...
NVIDIA uvedla, že japonské firmy a výzkumné instituce staví specializované AI modely a aplikace na otevřených modelech, datech a knihovnách Nemotron. Mezi nimi jsou Institution of Science Tokyo, SoftBank, Hitachi, NTT DATA, ENEOS, Stockmark, avatarin, SB Intuitions a Sakana AI.
Institution of Science Tokyo, SoftBank Corp.’s SB Intuitions and Stockmark are adopting NVIDIA Nemotron to build locally developed AI models designed to serve Japanese users, businesses and institutions amid the country’s demographic and workforce transition.Japanese enterprises avatarin, ENEOS Holdings, Hitachi and NTT DATA are building Japanese-language AI applications with NVIDIA Nemotron, from remote-presence robotics to enterprise agents and specialized medical and contact centers.Sakana AI is integrating NVIDIA Nemotron into its Fugu model-routing platform, expanding the set of AI models Fugu can intelligently orchestrate to dynamically select the best model for each task. TOKYO, July 15, 2026 (GLOBE NEWSWIRE) -- NVIDIA today announced that leading Japanese enterprises, startups and research institutions are building industry-specialized AI models and applications with NVIDIA Nemotron™ open models, data and libraries, accelerating the development of AI tailored to Japan’s language, industries and workforce.
Open models are the foundation of national AI ecosystems, giving organizations the ability to customize, deploy and govern AI they control.
In Japan, these capabilities are increasingly important as the country addresses an aging population and workforce transition, driving demand for AI tailored to local industries that helps strengthen the workforce, sustain productivity and accelerate innovation.
“Every nation and every company should own and control its intelligence infrastructure. Open models make that possible,” said Jensen Huang, founder and CEO of NVIDIA. “They give countries, enterprises and researchers the freedom to inspect, improve, adapt, secure and deploy AI for their own needs. Together with Japan’s AI leaders, we are advancing an open AI ecosystem that accelerates discovery, strengthens national capability and ensures every society can participate in — and benefit from — the AI revolution.”
Building Specialized AI for Japan With NVIDIA Nemotron
Across Japan, developers are building specialized AI with NVIDIA Nemotron open models and datasets, tailoring them to the country’s industries and public-sector needs.
Institute of Science Tokyo developed its Swallow family of open foundation models using NVIDIA Nemotron datasets and the NVIDIA NeMo™ software stack for continual pretraining and post-training. Swallow models enhance Japanese language and reasoning performance while preserving the underlying models’ core English, math and coding capabilities. Enterprises are customizing and deploying Swallow for specialized use cases, including financial-document translation and asset-management report generation.
SB Intuitions Corp., SoftBank Corp.’s generative AI research subsidiary, trained its Sarashina series of homegrown generative AI models using NVIDIA Nemotron, including the NVIDIA NeMo RL and Megatron-LM libraries. Sarashina3 mini has been selected by Japan’s Digital Agency for use in specialized AI use cases. SoftBank Corp. has also developed and deployed a large telco model, using NVIDIA Nemotron, to enable autonomous telecom network operations.
Stockmark’s specialized Japanese-language document-understanding model, released today, is based on the NVIDIA Nemotron 3 Nano Omni model. The company is also developing enterprise knowledge applications using NVIDIA NeMo Retriever™ and the Nemotron-Personas-Japan dataset, serving customers across Japan’s manufacturing, energy and chemical industries through Japan’s Generative AI Accelerator Challenge national project.
Transforming Japan’s Industries With NVIDIA Nemotron
Japanese enterprises are using NVIDIA Nemotron to modernize essential services, improve productivity and support the country’s workforce.
AI and robotics startup avatarin is using NVIDIA Nemotron open models and NVIDIA NeMo to develop Japanese-language speech and reasoning capabilities for enterprise AI agents. NVIDIA HGX™ B300 systems provide the private AI infrastructure that enables those agents to securely analyze customer conversations and access enterprise knowledge for more accurate responses, while NVIDIA Jetson™ powers edge AI capabilities, including digital avatar systems being deployed at airports and other locations across Japan.
ENEOS Holdings is using NVIDIA Nemotron open models with the NVIDIA AI-Q Blueprint and NVIDIA ALCHEMI NIM microservices to advance agentic AI workflows for energy and materials R&D. Researchers are using these technologies to integrate technical document search, vision and language understanding, and simulation-backed molecular screening, helping accelerate materials exploration for applications such as immersion-cooling fluids and advanced catalysts.
NTT DATA, an operating subsidiary of NTT, used NVIDIA Nemotron-Personas-Japan to augment training data for its proprietary tsuzumi 2 model, improving question-answering accuracy and enhancing responses to questions requiring additional knowledge. The company is also looking to deploy a scalable multi-agent framework harnessing NVIDIA Agent Toolkit, including NVIDIA Nemotron, to route tasks to the best models and drive accurate, efficient and autonomous enterprise workflows.
Hitachi is developing physical AI technologies to address real-world operational challenges by using NVIDIA Nemotron and NVIDIA Cosmos™ open models, along with its proprietary information technology (IT) and operational technology (OT) domain knowledge. As part of a multi-agent orchestration platform, these technologies are designed to connect and coordinate IT and OT operations, helping transform enterprise-scale business processes across complex workflows.
Sakana AI is collaborating with NVIDIA to integrate NVIDIA Nemotron into its Fugu model-orchestration platform, expanding the range of AI models Fugu can intelligently orchestrate to dynamically select the best model for each task in agentic AI workflows. By routing each request to the model best suited for the job, Fugu helps developers balance accuracy, performance and cost across multiple open and proprietary AI models. Fugu demonstrates how thoughtful orchestration can unlock capabilities beyond what an individual model achieves on its own. Early performance results on complex, real-world coding tasks reinforce the promise of coordination as a path to more capable AI.
Open and Customizable, Deployable Anywhere
Nemotron models are released with open weights, datasets and recipes, giving organizations the transparency and control to customize models for domain-specific workflows and deploy them where their applications and data reside.
Developers can use NVIDIA NeMo to customize, evaluate and optimize models for their use cases, and deploy them in environments that meet regulatory, sovereignty and data localization requirements.
Nemotron models are available on Hugging Face, ModelScope, OpenRouter and build.nvidia.com as NVIDIA NIM™ microservices, and through NVIDIA Cloud Partners, inference platforms and cloud service providers.
About NVIDIA
NVIDIA (NASDAQ: NVDA) is the world leader in AI and accelerated computing.
For further information, contact:
Natalie Hereth
Corporate Communications
NVIDIA Corporation [email protected]
Certain statements in this press release including, but not limited to, statements as to: Together with Japan’s AI leaders, NVIDIA advancing an open AI ecosystem that accelerates discovery, strengthens national capability and ensures every society can participate in — and benefit from — the AI revolution; expectations with respect to growth, performance, availability, and benefits of NVIDIA’s products, services and technologies, and related trends and drivers; expectations with respect to NVIDIA’s third party arrangements, including with its collaborators and partners; expectations with respect to technology developments, and related trends and drivers; projected market growth and trends; expectations with respect to AI and related industries; and other statements that are not historical facts are forward-looking statements within the meaning of Section 27A of the Securities Act of 1933, as amended, and Section 21E of the Securities Exchange Act of 1934, as amended, which are subject to the “safe harbor” created by those sections based on management’s beliefs and assumptions and on information currently available to management and are subject to risks and uncertainties that could cause results to be materially different than expectations. Important factors that could cause actual results to differ materially include: global economic and political conditions; NVIDIA’s reliance on third parties to manufacture, assemble, package and test NVIDIA’s products; the impact of technological development and competition; development of new products and technologies or enhancements to NVIDIA’s existing products and technologies; market acceptance of NVIDIA’s products or NVIDIA’s partners’ products; design, manufacturing or software defects; changes in consumer preferences or demands; changes in industry standards and interfaces; unexpected loss of performance of NVIDIA’s products or technologies when integrated into systems; NVIDIA’s ability to realize the potential benefits of business investments or acquisitions; and changes in applicable laws and regulations, as well as other factors detailed from time to time in the most recent reports NVIDIA files with the Securities and Exchange Commission, or SEC, including, but not limited to, its Annual Report on Form 10-K and Quarterly Reports on Form 10-Q. Copies of reports filed with the SEC are posted on the company’s website and are available from NVIDIA without charge. These forward-looking statements are not guarantees of future performance and speak only as of the date hereof, and, except as required by law, NVIDIA disclaims any obligation to update these forward-looking statements to reflect future events or circumstances.
A photo accompanying this announcement is available at https://www.globenewswire.com/NewsRoom/AttachmentNg/11dc96e1-0143-4627-8503-c33b1345d070
Japan’s Enterprises and Startups Build Industry-Specialized AI With NVIDIA Nemotron Open Models NVIDIA today announced that leading Japanese enterprises, startups and research institutions are bui...
Jensen Huang uvedl, že Vera Rubin je už ve výrobě a čeká ji „obrovský“ objem produkce, čímž odmítl spekulace o zpoždění. NVIDIA zároveň tvrdí, že má více objednávek a dodavatelský řetězec bude vytížený ještě několik let.
Speaking on the sidelines of a developer event in Tokyo, NVIDIA (NASDAQ:NVDA | NVDA Price Prediction) CEO Jensen Huang pushed back hard on a research report claiming his next flagship product line was slipping. “Vera Rubin is already in production. Giant amounts of production incoming,” Huang told reporters, rejecting delay concerns and dismissing a SemiAnalysis post that suggested a specialized circuit board issue could push the next-generation AI server rack into 2028.
That single word, “giant,” matters. It is the CEO staking his credibility on a product cycle that Wall Street has already begun pricing into forward numbers.
What Rubin Has to Live Up To The bar Blackwell already set is extraordinary. Nvidia’s Q1 FY2027 revenue hit $81.615 billion, up 85.2% year over year, with Data Center alone contributing $75.246 billion and Networking revenue rising 199% YoY. Non-GAAP gross margin came in at 75.0%, and free cash flow reached $48.554 billion in the quarter.
Huang framed the buildout as generational: “The buildout of AI factories, the largest infrastructure expansion in human history, is accelerating at extraordinary speed.” He added that “We have more orders today than we did at the last time I spoke about orders at GTC” and that NVIDIA will “keep our supply chain quite busy for several many more years coming.”
Supply commitments help explain Nvidia’s confidence. The company has $119.0 billion tied to supply-related commitments and is guiding for $91.0 billion in Q2 revenue, a forecast that excludes any China Data Center compute sales. Meanwhile, H200 shipments to China and Hong Kong have reportedly begun after U.S. officials cleared roughly 10 Chinese companies to buy the chips, but deliveries remain minimal so far.
The Rubin Pricing Bombshell The delay narrative that surfaced in early July collided with a more bullish Wall Street read this morning: Morgan Stanley raised its Vera Rubin rack-system price assumption to about $49 billion per gigawatt, implying materially higher customer spending per deployment than Blackwell.
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In NVIDIA’s fiscal Q4 commentary, Huang said “Vera Rubin will extend that leadership even further” on cost per token. The distinction matters: customers may pay more upfront for Rubin systems if the platform lowers the cost of running AI models at scale. If pricing power holds and volumes are truly “giant,” the mix shift lifts NVIDIA’s average selling price base heading into fiscal 2028.
Manufacturing partner Taiwan Semiconductor Manufacturing (NYSE:TSM) is signaling similarly robust demand. June revenue jumped 67.9% YoY to NT$442.68 billion, and TSMC is adding three new advanced packaging facilities in Chiayi Science Park Phase II to relieve CoWoS bottlenecks.
Valuation Math NVDA trades at $211.54, with a trailing P/E of 32x and a forward P/E of 24x. The consensus analyst target sits at $301.62, with 48 Buy and 10 Strong Buy ratings against just 2 Holds.
Prediction markets are more restrained, pricing a 73% probability NVDA hits $216 in July but only 31.5% odds of a $220+ close. If Huang’s “giant” volumes materialize on Rubin at Morgan Stanley’s higher ASPs, current forward estimates likely understate FY2028 earnings power.
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Nvidia i přes nedostatek AI čipů uvnitř firmy rozděluje GPU mezi týmy na týdenní bázi a někdy musí zasáhnout i Jensen Huang. Prioritu má také autonomní řízení.
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Nvidia CEO Jensen Huang. Chung Sung-Jun/Getty Images Even Nvidia isn't immune to the AI chip shortage.
The company's automotive division still has to compete internally for access to the GPUs that have made Nvidia the world's most valuable company, according to Xinzhou Wu, Nvidia's head of automotive.
"Even at Nvidia, basically we do have a limited supply of GPU for compute," Wu said in an episode of The Verge's "Decoder" podcast that aired on Monday.
As demand for Nvidia's chips continues to surge from AI companies building massive data centers, Wu said different teams across the company regularly compete for computing resources needed to train and test their own AI models.
"We have an internal priority, and I'm working with my colleagues basically almost on a weekly basis to decide how to set aside this different compute, sometimes for training, sometimes for test resources for different threads of work in the company," Wu said.
"And sometimes we need Jensen to help," Wu said of the company's CEO, Jensen Huang.
The comments offer a rare glimpse into how Nvidia allocates resources inside a company whose GPUs have become the backbone of the generative AI boom. Demand for its chips has consistently outpaced supply as companies, including OpenAI, Microsoft, Meta, xAI, and Amazon, race to build ever-larger AI models.
Wu said decisions aren't driven solely by near-term revenue.
"It's all of the above," he said when asked how those trade-offs are made. Nvidia balances current business needs with long-term strategic opportunities, including what Huang calls "the zero trillion dollar business" — entirely new markets that could eventually be worth trillions of dollars, Wu said.
One of those bets is autonomous driving.
Wu said Nvidia believes "everything that moves will be autonomous" and is investing heavily in supplying chips, software, AI models, simulation tools, and safety systems for self-driving vehicles. While the automotive business remains much smaller than Nvidia's booming data-center division, Huang continues to prioritize it.
"We are strong believers — Jensen himself as well — of the AV [autonomous vehicle] future," Wu said. "We are keeping investing basically in this technology and in this future, not only from allocating external compute but from fab capacity as well."
Wu also said that even semiconductor manufacturing capacity has become another internal battleground as demand for Nvidia's chips continues to soar.
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Thibault is a business reporter at Business Insider's London office.He covers the intersection of wealth, work, and technology — focusing on the global economy, AI’s impact on the workplace, job and cognitive skills, and how economic changes are affecting careers. Before moving to the trending team, Thibault covered international affairs, including the Russia-Ukraine war, tensions in the South China Sea, and Russia’s economy on the news desk.He has previously worked at the Daily Express and held internships at Agence France-Presse, Politico Europe, and Factal.Il parle français. Se habla español.Email Thibault at [email protected], connect with him on LinkedIn @ThibaultSpirlet, or follow him on X @ThibaultSpirlet and BlueSky @thibaultspirlet.bsky.social.Expertise
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Nvidia může do roku 2026 dál růst díky AI boomu, plánovanému růstu výdajů hyperscalerů a platformě Vera Rubin. Akcie se nyní obchodují za něco přes 23násobek odhadovaného zisku pro rok 2026.
It's been off to the races for Nvidia (NVDA +4.21%) ever since its GPUs became an essential building block for artificial intelligence (AI). The AI data center boom has already made Nvidia one of the world's largest technology companies, and with a massive market cap of $5.1 trillion, it can feel as if there isn't much more upside left.
But investors shouldn't assume that's the case. The company's rampant growth has kept the stock's valuation surprisingly reasonable, and its next-generation Vera Rubin AI chip platform could be yet another catalyst that takes the stock to new heights.
Here are three reasons why Nvidia stock could keep soaring through 2026.
1. Sales could double within the next two years The strongest indicator of Nvidia's future growth is arguably the AI capital expenditures of its customers, the companies racing to build the data centers and other infrastructure to support broad AI adoption. Fortunately for Nvidia, these companies continue to put the pedal to the metal. Hyperscalers, including Meta Platforms, Microsoft, Alphabet, and Amazon, are planning higher capital expenditures in 2026.
Nvidia CEO Jensen Huang. Image source: Nvidia.
These tailwinds should continue to blow at Nvidia's back. Goldman Sachs estimates that AI compute spending will grow from approximately $494 billion this year to $1.13 trillion by 2031. Meanwhile, CEO Jensen Huang has said that he sees at least $1 trillion in revenue from Nvidia's Blackwell and Rubin platforms through the end of 2027.
Wall Street analysts estimate that Nvidia will generate approximately $555 billion in revenue for the company's next fiscal year, ending January 2028. In other words, sales could roughly double within the next two years, based on Nvidia's trailing 12-month revenue of $253 billion. If you were worried about Nvidia's growth, all signs point to big things ahead.
2. Vera Rubin is Nvidia's next big step forward There should be more noise about the shift taking place in the AI industry. Compute is broadening from AI training to inference. Whereas training develops an AI model, inference is the process by which a trained model generates outputs. Inference places greater emphasis on token efficiency. After all, it doesn't matter how powerful an AI model is if it's too slow or expensive for customers to use effectively.
Vera Rubin is not one or two chips but seven, including a GPU, a CPU, Ethernet switches, and other purpose-built chips. It essentially expands Nvidia's footprint in the data center and makes its ecosystem that much stickier.
Nvidia also engineered the platform with inference in mind. The company states that Rubin can reduce inference token costs by up to 10 times those of Blackwell. That gives hyperscalers a strong reason to invest in Vera Rubin, as they will seek efficiency to help monetize their AI investments over the coming years.
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3. The stock's valuation remains compelling relative to Nvidia's growth Growth isn't the only factor in a stock's performance. The price that investors pay for a stock matters a lot, especially in the short term. Therefore, Nvidia's valuation will likely have a big impact on how shares perform through the remainder of 2026. Right now, Nvidia is trading at just over 23 times its 2026 earnings estimates.
It's fair to wonder whether the AI boom has elevated Nvidia's earnings, making the stock seem less expensive than it would in a normal business climate. That would be a legitimate concern, but this isn't an ordinary cycle in size or duration. As noted above, the AI investment cycle still seems to have ample tread left. Analysts estimate that Nvidia could grow its earnings by an average of nearly 52% annually over the next three to five years.
Such strong growth prospects make the stock a strong buy at this valuation, with room for upside. Nvidia could absolutely keep soaring through 2026, assuming the business continues meeting the market's expectations.
Justin Pope has positions in Alphabet, Meta Platforms, and Microsoft. The Motley Fool has positions in and recommends Alphabet, Amazon, Goldman Sachs Group, Meta Platforms, Microsoft, and Nvidia. The Motley Fool has a disclosure policy.
Analytik KeyBanc zvýšil cílovou cenu pro Nvidia na 330 USD z 310 USD a ponechal doporučení Overweight, i přes mírné zpoždění náběhu výroby Vera Rubin. Akcie NVDA byly v úterý výše o 2,65 % na 208,93 USD.
Nvidia remains well-positioned for AI data center growth, according to KeyBanc analyst John Vinh, who raised his price forecast despite some near-term ramp delays.
KeyBanc Raises Nvidia ForecastVinh maintained an Overweight rating on Nvidia and raised his price forecast to $330 from $310. He said his takeaways were mixed but mostly positive, with a slight delay in the Vera Rubin ramp tied to thermal lid issues and SK Hynix qualification delays on HBM4.
The analyst said he sees limited risk to estimates because Nvidia can ship more B300 GPUs in place of R200. He expects Nvidia to ship 5.5 million to 6 million Blackwell GPUs this year, along with 1 million Hopper GPUs.
CoWoS Supply Supports AI DemandVinh said Nvidia’s 2026 CoWoS supply outlook remains unchanged at 650,000 interposers, while 2027 supply has been revised significantly higher to 1.1 million interposers. He said that the increase reflects strong demand and a full-year Rubin ramp.
The analyst expects Nvidia to ship 70,000 to 80,000 total racks this year, including 5,000 to 6,000 Vera Rubin racks. He also expects fewer than 1,000 LPU racks this year due to a delayed ramp, though demand remains strong.
Vinh said Nvidia remains uniquely positioned to benefit from secular growth in data center AI and machine learning. He also pointed to Nvidia’s CUDA software stack as a major barrier to entry and said competitive risks remain limited.
Hedge funds rushed back into U.S. semiconductor stocks last week, buying the sector at the fastest pace in at least three-and-a-half years after two straight weeks of heavy selling.
Hedge Funds Buy The DipGoldman Sachs data shared by The Kobeissi Letter showed semiconductor stocks now make up about 10% of total hedge fund exposure, roughly double last year’s level but below the nearly 14% peak in May.
The renewed buying suggests hedge funds see the recent chip-stock pullback as largely over, while ETF inflows show broader investor demand for AI-related semiconductor names.
Technical AnalysisNvidia is trading above its 20-day SMA ($202.05), 100-day SMA ($198.10), and 200-day SMA ($191.95), which keeps the intermediate-to-long trend constructive even after recent chop. The catch is the stock is still trading slightly below its 50-day SMA ($209.27), and the 20-day SMA remains below the 50-day SMA—an early "cooling" signal that can cap rallies until price reclaims that zone cleanly.
Earnings OutlookLooking further out, the next major catalyst for the stock arrives with the August 26, 2026 (estimated) earnings report.
EPS Estimate: $2.07 (Up from $1.04 YoY) Revenue Estimate: $91.70 Billion (Up from $46.74 Billion YoY) Valuation: P/E of 31.2x (Indicates premium valuation relative to peers) Top ETF ExposureSignificance: Because NVDA carries such a heavy weight in these funds, any significant inflows or outflows will likely trigger automatic buying or selling of the stock.
Price ActionNVDA Stock Price Activity: Nvidia shares were up 2.65% at $208.93 at the time of publication on Tuesday, according to Benzinga Pro data.
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NVIDIA (NASDAQ: NVDA | NVDA Price Prediction) and SanDisk (NASDAQ: SNDK) both delivered blowout AI infrastructure quarters. NVIDIA sells the compute and networking silicon that trains frontier models. SanDisk sells the NAND flash that feeds those models data.
One is the diversified platform king. The other is a freshly independent memory pure play riding a shortage cycle.
Data Center Compute Carries One. NAND Pricing Carries the Other. NVIDIA’s Q1 FY2027 print was a Data Center story. Revenue hit $81.615 billion, up 85.23% YoY, with Data Center alone contributing $75.246 billion (+92% YoY). Networking was the sleeper hit at $14.8 billion (+199% YoY), driven by InfiniBand, Spectrum-X, and NVLink.
Jensen Huang framed the moment bluntly: “The buildout of AI factories, the largest infrastructure expansion in human history, is accelerating at extraordinary speed.” Non-GAAP EPS of $1.87 beat expectations.
SanDisk’s Q3 FY2026 was a different shock. Revenue of $5.95 billion came in 251% higher YoY, and EPS of $23.41 handily beat the $14.66 consensus. Gross margin swung from 22.5% to 78.4% in a year, largely on NAND pricing.
Datacenter revenue rocketed 645% YoY to $1.47 billion. CEO David Goeckeler called it “a fundamental inflection point” for the company’s mix shift toward Datacenter.
Platform Empire vs. Memory Cycle Bet NVIDIA is spending like a company that already won, with $119 billion in supply commitments, an $80 billion buyback authorization, and a dividend hike from $0.01 to $0.25 per share. Its next act (Vera Rubin, Blackwell 300, DRIVE Hyperion with Hyundai, Kia, and Uber) reads like a diversified portfolio.
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Lens NVIDIA SanDisk Core Bet AI compute and networking platform Datacenter NAND mix shift Forward P/E 24 29 Key Vulnerability No H20 shipments to China NAND price cyclicality, Kioxia dependence SanDisk is playing a narrower hand. Goeckeler is anchoring the business to multi-year customer engagements backed by firm financial commitments, with five NBM agreements signed between Q3 and Q4. The zero long-term debt balance sheet after retiring $650 million is impressive, but the model leans on Kioxia manufacturing and structural NAND tightness.
The Next Test Is Whether Storage Keeps Up With Compute NVIDIA guided Q2 to $91 billion in revenue, which assumes zero China Data Center compute. I will watch whether hyperscaler backlog absorbs that gap cleanly.
SanDisk’s Q4 guide of $7.75 to $8.25 billion in revenue and $30 to $33 EPS is aggressive; the question is how many more NBM contracts close before pricing normalizes. Reddit chatter has flagged put option gains and pullback anxiety around SanDisk after its parabolic run.
Why I Lean NVIDIA for Durability, SanDisk for Torque For a three-year holding period, NVIDIA looks like the more durable option. The $5.1 trillion market cap and 63% profit margin feel unusual for a company still compounding revenue at 85%, and the platform lock-in across cloud, sovereign AI, and autonomy is hard to disrupt.
SanDisk is the more interesting risk trade. Shares are up 605.19% year to date, and analysts see a target around $2,035, but the thesis rides on a memory shortage analysts do not expect to ease before 2028. For a turnaround-hungry investor, that torque is the appeal. The platform durability argument favors NVIDIA, while SanDisk’s next two quarters warrant close attention before the thesis firms up.
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ZTE Kangxun Telecom patří mezi dvě čínské firmy, které získaly souhlas Spojených států s nákupem čipů Nvidia H200. Povolení dostala i Maginfra a dceřiná firma Kingsoft, Zhuhai Hengqin Yunxiang Zhisheng Network Technology, na některé čipy AMD.
A sign of ZTE is displayed at the company's booth at the expo of the World Internet Conference in Wuzhen town of Tongxiang city, Zhejiang province, China November 8, 2025. REUTERS/Tingshu... Purchase Licensing Rights, opens new tab Read more
July 14 (Reuters) - A unit of telecoms gear maker ZTE Corp (000063.SZ), opens new tab and two other Chinese firms are among the latest entities to receive U.S. approval to purchase advanced AI chips from Nvidia (NVDA.O), opens new tab and AMD (AMD.O), opens new tab, according to documents and two sources familiar with the matter.
Nvidia's H200 chip, one of its most powerful and used to train and run large AI models, has become a focal point of U.S.-China tech rivalry as Washington seeks to restrict China's access to advanced computing power.
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ZTE Kangxun Telecom and server maker Maginfra have been permitted to purchase Nvidia's H200 chips, while Zhuhai Hengqin Yunxiang Zhisheng Network Technology, a subsidiary of cloud computing company Kingsoft (3888.HK), opens new tab, has been cleared to use some AMD chips that rival the H200, according to the documents and the sources.
The three firms, not previously reported to have received U.S. clearance, expand the known set of companies involved in the licensing process beyond China's largest internet groups and major electronics distributors.
Reuters reported in May that the U.S. had cleared around 10 Chinese firms, including Alibaba (9988.HK), opens new tab, Tencent (0700.HK), opens new tab, ByteDance and JD.com (9618.HK), opens new tab, to buy the Nvidia chips, but that no deliveries had been made at that time as the deals remained caught between approval requirements and scrutiny in both Washington and Beijing.
However, some Chinese cloud firms have recently told partners and clients they may soon be able to obtain H200 chips, the sources said, indicating some progress in import reviews by Chinese authorities.
ZTE, Maginfra, Kingsoft, Nvidia, AMD and China's Ministry of Commerce did not respond to requests for comment. The U.S. Bureau of Industry and Security - the Commerce Department agency overseeing export controls - did not immediately reply to a request for comment.
Washington has steadily tightened restrictions on sending advanced AI chips to China since 2022, arguing the technology could support the PRC's military modernisation.
But the Trump administration has allowed sales of the H200, which first shipped to clients globally in 2024, with some arguing the exports promote U.S. technological dominance, while Nvidia has pushed to preserve access to one of the world's largest technology markets.
China, meanwhile, has encouraged domestic alternatives, creating uncertainty over whether U.S.-approved chip sales can proceed even after Washington grants export licenses.
Reporting by Reuters staff; Editing by Miyoung Kim; Editing by Kirsten Donovan
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NVIDIA dál rozšiřuje AI ekosystém přes partnerství v oblasti cloudu, sítí, aut i telekomunikací, aby si udržela náskok před AMD a Broadcom. Ve 1. čtvrtletí fiskálního roku 2027 tržby meziročně vyskočily o 85 % na rekordních 81,6 miliardy USD.
Key Takeaways NVIDIA is widening its AI moat through partnerships spanning cloud, networking, autos and telecom.NVDA's Q1'27 revenues surged 85% to $81.6 billion, led by 92% data center end-market growth.NVIDIA's Open-source tools and an integrated platform make switching harder as AMD and Broadcom invest in AI. NVIDIA Corporation (NVDA - Free Report) continues to widen its competitive advantage by building strategic partnerships across cloud computing, networking, automotive and telecommunications. Rather than relying only on hardware sales, the company is creating an AI ecosystem that combines chips, networking, software and services. This integrated strategy could help NVIDIA stay ahead as competition in AI infrastructure intensifies.
The strength of these partnerships is reflected in NVIDIA’s financial performance. In the first quarter of fiscal 2027, revenues surged 85% year over year to a record $81.6 billion, while Data Center revenues jumped 92% to $75.2 billion. Management also expects second-quarter revenues of about $91 billion, signaling continued strong demand for its AI platforms.
NVIDIA has expanded its partnership with Google Cloud to deploy Vera Rubin-powered AI instances and support advanced AI models on Blackwell systems. It has also teamed up with Marvell through NVLink Fusion technology to accelerate custom AI infrastructure. Partnerships with Coherent, Corning and Lumentum aim to improve optical networking for next-generation AI data centers, while collaborations with Hyundai, Kia and Uber strengthen NVIDIA’s presence in autonomous driving.
Another advantage is NVIDIA’s growing software ecosystem. Open-source platforms such as Dynamo, Agent Toolkit and Nemotron encourage developers and enterprises to build AI applications on NVIDIA hardware, making it harder for customers to switch to competing platforms.
Although rivals like Advanced Micro Devices, Inc. (AMD - Free Report) and Broadcom Inc. (AVGO - Free Report) are investing aggressively in AI, NVIDIA’s broad partner network and integrated platform create a strong competitive moat. As enterprise AI adoption accelerates, these partnerships should help the company maintain its technology leadership and support long-term revenue growth. The Zacks Consensus Estimate for fiscal 2027 revenues is currently pegged at $385.5 billion, indicating a robust year-over-year increase of 78.5%.
NVIDIA’s Rivals Are Also Expanding Their AI EcosystemsWhile NVIDIA has built the industry's broadest AI partner network, Advanced Micro Devices and Broadcom are also deepening collaborations to strengthen their AI businesses.
Advanced Micro Devices is expanding partnerships with major cloud providers, enterprise customers and AI software developers to accelerate adoption of its Instinct GPUs and EPYC processors. In the first quarter of 2026, AMD's Data Center segment revenues surged 57% year over year to $5.78 billion, driven by strong demand for AI accelerators and server CPUs. Advanced Micro Devices has also strengthened its open-source ROCm software platform to attract developers and improve compatibility with leading AI models. These efforts are helping AMD narrow the gap with NVIDIA in enterprise AI deployments.
Broadcom is taking a different approach by partnering closely with hyperscale cloud companies to develop custom AI accelerators and high-speed networking solutions. In its latest reported financial results for the second quarter of fiscal 2026, AI semiconductor revenues climbed 143% year over year to $10.8 billion. Broadcom's Ethernet networking products and custom AI chips are becoming increasingly important as cloud providers build large AI clusters.
Although both companies are making solid progress, NVIDIA still benefits from a broader ecosystem that spans chips, networking, software and AI frameworks. This integrated platform continues to give it a competitive edge as AI adoption expands across industries.
NVIDIA’s Price Performance, Valuation and EstimatesShares of NVIDIA have risen around 9.2% year to date, underperforming the Zacks Computer and Technology sector’s gain of 17%.
NVIDIA YTD Price Return Performance
Image Source: Zacks Investment Research
From a valuation standpoint, NVDA trades at a forward price-to-earnings ratio of 19.32, below the sector’s average of 24.78.
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 91% and 35%, respectively. Estimates for fiscal 2027 have been revised upward over the past seven days, while estimates for fiscal 2028 have been raised over the past 30 days.
Image Source: Zacks Investment Research
NVIDIA currently carries a Zacks Rank #3 (Hold). You can see the complete list of today’s Zacks #1 Rank (Strong Buy) stocks here.
Nvidia logo, computer chips and a 3D-printed representation of a robot hand are seen in this illustration taken August 27, 2025. REUTERS/Dado Ruvic/Illustration Purchase Licensing Rights, opens new tab
WASHINGTON, July 14 (Reuters) - A top U.S. official told Congress on Tuesday that "very few" Nvidia (NVDA.O), opens new tab H200 chips to date have been shipped to China or Hong Kong.
In May, Reuters reported the Commerce Department had cleared around 10 Chinese firms to buy Nvidia's second-most powerful AI chip, the H200, but no deliveries had been made. Jeffrey Kessler, under secretary of commerce for industry and security, told the House Foreign Affairs Committee that H200 chip shipments have begun but the number was "very few."
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Later in the hearing, Kessler said it was a "trivial" amount of chips. He said the Commerce Department has provided a confidential list of applications for H200 chips and their status to Congress but did not elaborate.
The chip shipments are being closely watched because the H200 is one of Nvidia's most advanced AI processors, and sales to China have become a flashpoint in the broader U.S.-China technology rivalry. Washington has sought to limit Beijing's access to cutting-edge chips that could be used for military applications.
U.S. Representative Gregory Meeks, the top Democrat on the committee, on Tuesday criticized the department for not adding any Chinese companies to an export control list since October, which is the longest period in more than a decade.
He said President Donald Trump "has turned (export controls) into a bargaining chip in broader negotiations with China" and "weakened existing safeguards, including by approving licenses for advanced AI chips destined for China."
Kessler defended the department's posture and said it was important to enforce the existing list of Chinese companies facing restrictions.
Reuters reported last month that the Commerce Department has held off on adding China’s AI startup DeepSeek, memory chip maker ChangXin Memory Technologies and more than 100 other companies flagged as national security risks to the "Entity List," according to two people familiar with the matter, as the Trump administration tries to avoid escalating tensions with Beijing.
U.S. companies cannot ship goods, software and technology to companies on the list without a license, which is likely to be denied.
Kessler also defended the decision of the Trump administration on Friday to loosen export controls on the United Arab Emirates, making it easier to export Nvidia AI chips, military equipment, commercial satellites and spacecraft in a boost to relations between the two allies.
Reporting by David Shepardson in Washington and Karen Freifeld in New York; Editing by Matthew Lewis
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Nvidia by podle odhadů mohla do konce dekády výrazně růst, protože její adresovatelný trh v datových centrech může přesáhnout 1 bilion USD. Analytici zároveň čekají 88% nárůst zisku na akcii ve fiskálním roce 2027 (končícím v lednu 2027).
Shares of Nvidia (NVDA +0.42%) have risen by an impressive 380% over the past three years, fueled by the artificial intelligence (AI)-driven demand for its data center chips. However, the stock has been in a rut lately, rising just 12% in 2026, as of this writing.
The surprising thing to note here is that Nvidia stock is struggling to break out despite sustaining impressive revenue and earnings growth, driven by its continued dominance in the lucrative AI accelerator market. However, the world's largest company by market cap can easily step on the gas once again.
In fact, Nvidia could witness a solid increase in its stock price by the end of the decade. Let's see why that may be the case.
Image source: The Motley Fool.
Nvidia's massive addressable market points toward solid long-term growth Nvidia's foundry partner TSMC recently noted that the global semiconductor market's revenue could reach a whopping $1.5 trillion in 2030. The Taiwan-based foundry giant had previously anticipated $1 trillion in semiconductor revenue by the end of the decade. However, AI-fueled demand for chips led to a substantial upgrade to its guidance.
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TSMC points out that AI and high-performance computing (HPC) chips will account for 55% of this lucrative opportunity. That puts Nvidia's addressable opportunity in the AI data center chip market at an impressive $825 billion. For comparison, Nvidia's data center revenue in fiscal 2026 (which ended in January this year) was $193.7 billion.
It is worth noting that $162.3 billion of its fiscal 2026 data center revenue came from sales of compute chips, while the rest was from networking components. So, there is still a lot of room for Nvidia to boost its data center chip revenue over the next five years, especially considering that it is the dominant player in this market with an estimated 80% share.
However, analysts believe that Nvidia's AI data center chip market share may have peaked. That's not surprising, as competitors Advanced Micro Devices and Broadcom have been making solid strides in this space. Additionally, Nvidia's customers, which include both hyperscalers and pure-play AI companies, have been designing in-house chips to lower operating costs.
That's why Nvidia's AI chip market share is anticipated to decline to 75% this year. Let's assume Nvidia continues to lose ground in AI chips for the next four years and ends up at just 50% market share in 2030; it can still generate more than $400 billion in data center chip revenue in 2030 (based on the $825 billion market size estimated above).
That's almost 2.5x the data center compute revenue it generated in fiscal 2026. At the same time, investors shouldn't forget that Nvidia's data center networking revenue is growing at a much faster pace than compute. The company reported a 142% year-over-year increase in networking revenue in fiscal 2026 to $31.4 billion. It has started fiscal 2027 on a stronger note in this segment, with networking revenue tripling year-over-year to $14.8 billion.
Nvidia sells networking hardware, such as Ethernet and InfiniBand switches, and also offers software platforms to help developers program and manage networks. What's worth noting is that demand for these networking switches is increasing rapidly due to AI and HPC. The InfiniBand market, for instance, is expected to clock 36% annual growth over the next five years, according to Mordor Intelligence. It could generate more than $164 billion in revenue in 2031.
Meanwhile, the data center switch market is projected to exceed $100 billion in revenue by 2030, according to Dell'Oro Group. Ethernet switches are expected to dominate this space. The pace at which Nvidia's networking revenue is growing suggests the company is capturing a larger share of this space, which could pave the way for significant growth in this business segment over the next five years.
In all, Nvidia's data center addressable opportunity, including both networking and compute, could surpass $1 trillion by the end of the decade. That's why there has been a significant jump in Nvidia's consensus revenue growth projections through fiscal 2029.
Data by YCharts
The company's earnings growth potential suggests it can become a multibagger Nvidia's impressive top-line growth is all set to filter down to the bottom line. Analysts are projecting an 88% spike in Nvidia's earnings in fiscal 2027 (ending in January 2027) to $8.97 per share. This will be followed by robust double-digit growth over the next two fiscal years.
Data by YCharts
Assuming Nvidia's bottom line grows by even 15% a year in fiscal years 2030 and 2031, its earnings per share could reach $21.24 by the end of the decade (as its fiscal 2031 will end in January 2031). If this AI stock trades at 27 times earnings at that time (in line with the tech-laden Nasdaq-100 index's forward earnings multiple), its stock price could reach $573. That's almost 2.8x Nvidia's current stock price.
As Nvidia trades at just 24 times forward earnings, investors are getting a solid deal on this growth stock, which they should consider grabbing, given the potential upside it could deliver through 2030.
Wall Street čeká, že Nvidia v příštích 12 měsících přidá ještě 40 %. Firma zároveň míří na trh CPU a letos čeká 20 miliard USD výnosů ze samostatných CPU.
Investors are always looking for the next game-changing technology, and in recent years, one emerged: artificial intelligence (AI). This exciting technology is already bearing fruit for many, from developers of infrastructure to companies and organizations that have actually started applying AI to their problems.
These players have reported soaring revenue and have seen their stock performance take off, too. One particular company has been leading the way, as it develops a key element needed for AI to function. I'm talking about Nvidia (NVDA 3.23%), designer of the world's No. 1 AI chip. Nvidia's graphics processing units (GPUs) are used for crucial AI tasks, such as the training of AI models, and customers flock to them because they are the fastest around.
Nvidia's expertise has appealed to investors, and that's helped the stock soar 900% over the past five years. At this point, you might think Nvidia has passed its growth peak, and that share performance moving forward may stagnate. Wall Street begs to differ, predicting that the stock is on track to advance another 40%. Let's check out what may happen next.
Image source: Getty Images.
GPUs designed for AI First, a quick look at the Nvidia story so far. This company has been around for more than 30 years, and in its earlier days, it generated most of its revenue by selling GPUs in the gaming market. But as it became clear that these chips could be valuable for other purposes, Nvidia took steps to make that happen. The company created its parallel computing platform, CUDA, and in more recent years, it designed GPUs specifically for AI.
These moves proved to be wise because today, data center business makes up the lion's share of Nvidia's total revenue. In the recent quarter, data center revenue soared more than 90% to a record $75 billion. That's on a total of $81 billion in revenue. Nvidia's profitability on sales also is high, with gross margin topping 70% quarter after quarter.
Nvidia's first-to-market advantage and its focus on innovation have helped it remain the global GPU leader, and the company also has expanded its products and services to offer customers complete AI systems. This, too, has kept earnings climbing.
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Nvidia stock, as mentioned, has skyrocketed thanks to the company's AI dominance, but in recent times, investors have worried about the massive levels of tech investment in AI -- and whether the revenue opportunity will support that spending. On top of that, they've also worried about Nvidia losing market share as some of its customers -- such as Amazon and Meta Platforms -- develop their own chips. All of this has weighed on Nvidia stock, which only climbed 7% in the first half.
Targeting a new market Still, Wall Street is optimistic and sees a 40% gain from today's level over the coming 12 months. Could that happen? It's very possible. Demand for Nvidia's GPUs remains strong, and now the company is targeting a second key market: the central processing unit (CPU) space. These chips are the main processors in computers, and they are proving to be a key tool in the use of agentic AI. The CPU drives the AI as it takes the steps needed to solve a particular problem.
Since agentic AI is seen as the next big AI growth area, strength in CPUs could be big. Nvidia faces CPU leaders Intel and Advanced Micro Devices in this $200 billion market, and I wouldn't expect Nvidia to strip away their leadership in every part of the CPU space. Intel and AMD are particularly strong in the PC market. But Nvidia, an expert in AI, could dominate in the data center market, and that would be a huge move.
All of this may start later this year with the shipping of the Vera Rubin platform and Nvidia's first stand-alone CPU. Nvidia says it expects to generate $20 billion in stand-alone CPU revenue this year. And this, along with Nvidia's ongoing leadership in GPUs, should keep total revenue climbing.
As investors see this new wave of growth ahead, they may once again turn to Nvidia -- particularly at the current dirt cheap valuation of 23x forward earnings estimates. And that's why Nvidia may be on track for another era of explosive gains.
NVIDIA (NASDAQ:NVDA | NVDA Price Prediction) just reported quarterly net income of $58.32 billion, up 210.63% year over year, for the fiscal first quarter of 2027 ended in the period reported on May 20, 2026. Over the trailing 12 months, Nvidia has now brought in more than $250 billion (a quarter trillion dollars), making its current valuation, at its current run rate, seem more than reasonable.
That said, the number I think more investors may pay attention to is NVIDIA’s operating profit, which more than tripled in twelve months. That tripling comes at a scale that already dwarfs the annual earnings of most companies in the S&P 500.
That figure represents reported GAAP net income for a single three-month period, straight from the filing.
What It Means A tripling of profit at a company already generating tens of billions per quarter tells you the AI infrastructure cycle is still compounding. Revenue for the quarter came in at $81.61 billion, up 85.2% year over year, beating the $79.12 billion consensus by 3.16%. Operating income of $53.54 billion rose 147.42%, and non-GAAP gross margin widened to 75.0% from 60.8% a year earlier.
The engine behind the number is NVIDIA’s data center segment. This business alone brought in more than $75 billion of revenue (up 92% year over year), with data center networking alone at $14.8 billion, up 199%. Free cash flow reached $48.55 billion for the quarter, and that’s what companies are ultimately valued off of.
The bottom line is that NVIDIA’s profitability is now scaling faster than its revenue, which is what margin expansion at hyperscale looks like.
Market Reaction Shares closed at $221.54 on the filing day of May 20, 2026, up from $195.95 at the prior quarter’s filing on February 25, 2026. The stock has since drifted lower, down nearly 12% over the past month and off 2.35% on the current session at $192.94. Year to date, NVDA is still up 6.07%, and one-year return sits at 29.05%. Over five years, the stock has returned 867.71%.
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Bull Case The forward setup is where this gets interesting for long-term holders. Management guided fiscal Q2 2027 revenue to $91.0 billion, plus or minus 2%, with non-GAAP gross margin held at 75.0%. That guidance excludes any China data center compute revenue, meaning the number assumes zero contribution from a market that used to be material. Any thaw is pure upside.
Capital return has finally caught up with the earnings power. The board raised the quarterly dividend from $0.01 to $0.25 per share and authorized an additional $80.0 billion in buybacks, on top of $38.5 billion remaining under the prior authorization. Roughly $20.0 billion was returned to shareholders in the quarter. Supply commitments of $119.0 billion underwrite the Blackwell 300 ramp and the newly announced Vera Rubin platform.
Valuation is the counterweight. The chip giant’s forward P/E stands at 23x, PEG at 0.616, with analyst consensus target at $301.62 and 48 Buy ratings against 1 Sell. CEO Jensen Huang framed the setup bluntly: “The buildout of AI factories, the largest infrastructure expansion in human history, is accelerating at extraordinary speed.”
Bottom Line A 210.63% jump in quarterly net income at a company with a $4.67 trillion market cap is the kind of earnings report that reframes the narrative for retirement-focused holders: the mega-cap earnings base is still compounding.
With forward guidance of $91.0 billion in Q2 revenue, an $80.0 billion buyback authorization, and a 25-fold dividend hike, NVIDIA is signaling that the AI cycle it powers has years of runway left. The stock has cooled off its peak, trading below its 50-day moving average of $209.90 and closer to its 200-day at $190.94. For long-term investors, the profit line is doing the talking. The next test comes when fiscal Q2 2027 results land.
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Jensen Huang na valné hromadě Nvidie označil pašování čipů za 2,5 miliardy dolarů za „slepou uličku“. Uvedl, že čipy z černého trhu bez aktualizací a podpory rychle zastarají.
Nvidia (NVDA 3.52%) has solidified its position as one of the most important companies in the tech world, as the undisputed leader in artificial intelligence (AI)-related hardware. The company started as a graphics card maker for video games, but its graphics processing units (GPUs) and other advanced AI chips have since become the hardware foundation for the current AI boom.
Unfortunately, there has been a $2.5 billion chip-smuggling scheme on the black market, and Nvidia CEO Jensen Huang isn't a fan of what's happening. During Nvidia's shareholder meeting, Huang took a strong stance on the scheme, calling it a "dead end."
This scheme involves smuggling Nvidia chips into markets like China -- where Nvidia has strict import restrictions and controls -- using methods that circumvent audits intended to verify legitimacy. Despite the issue, there are larger implications that should be encouraging to Nvidia investors.
Image source: Nvidia Corporation.
Going nowhere fast A major point Huang made is that Nvidia's AI chips aren't like a typical video game graphics card, where you buy it once and it works indefinitely. These chips are part of an ecosystem that requires constant updates (both software and hardware maintenance) that aren't available to chips acquired on the black market.
In other words, they may work now, but without software updates, security patches, and Nvidia's engineering support, their lifespans are short and will inevitably become unusable or a liability to the companies using them. That's the basis for his "dead end" comments.
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Nvidia wants to stay in Washington's good graces As it stands, Nvidia has a monopoly on the advanced GPUs needed to train and deploy AI. Companies like Amazon and Alphabet are beginning to make their own in-house chips, but for the most part, Nvidia comfortably dominates the market. It won't last forever, but other companies have lots of ground to make up before catching up to Nvidia.
Arguably its biggest obstacle right now, though, is government restrictions and compliance requirements. The U.S. has already implemented strict export bans on certain chips to China, so Huang's taking this stance is a way to stay in the good graces of the U.S. government and avoid further crackdowns or potential fines. The fewer geopolitical and regulatory worries, the better.
Nvidia is still rolling strong The black-market chips haven't had much of a negative effect on Nvidia's business. In its most recent quarter (ended April 26), it made $81.6 billion in revenue (up 85% year over year) and $58.3 billion in net income (up 211% year over year).
Nvidia is a well-oiled machine, and this shows just how wide its technological and competitive moat is. That should be encouraging news for investors seeking sustainable growth and who may have had "AI bubble" worries. There's a reason the company was comfortable authorizing an $80 billion share buyback program and increasing its dividend from $0.01 to $0.25.
Nvidia v pondělí klesla o 3,2 %, ale nové oznámení Meta o vyšších výdajích na AI infrastrukturu dál podporuje očekávání silné poptávky po čipech. Wall Street zůstává vůči NVDA převážně optimistická.
Nvidia NVDA stock declined on Monday, even as fresh announcements on artificial intelligence infrastructure spending reinforced expectations of continued demand for the chipmaker's products.
Shares of Nvidia were down 3.2% at $204.12 in trading.
The decline broadly tracked weakness in the wider market, with the Nasdaq Composite falling 1.4%. However, Nvidia outperformed the broader semiconductor sector, as the PHLX Semiconductor Index fell 4.8%.
Despite Monday's move, Nvidia has significantly lagged the broader chip sector this year.
Through Friday's close, the PHLX Semiconductor Index had gained 75%, while Nvidia shares were up just 12%.
The latest AI infrastructure announcement came from Meta Platforms, which said on Monday it would increase spending on its Louisiana data center to more than $50 billion.
Meta, alongside SpaceX, is one of Nvidia's major customers and uses the company's hardware to train its latest artificial intelligence models.
John Belton, portfolio manager at Gabelli Funds, said in a Barron's report continued competition among AI model developers could benefit Nvidia.
“Fragmentation in the LLM [large language model] space is a good thing for Nvidia. While they still have an opportunity to grow share with [Claude developer] Anthropic, it isn’t necessarily a great thing for Nvidia longer term if the model-as-a-service space starts to look like a winner take all market.”
Wall Street also remains broadly optimistic on Nvidia despite the stock's relative underperformance.
According to FactSet, the company now trades at a forward price-to-earnings ratio of less than 20 times, while the average analyst price target stands at $313.39.
Mizuho Securities analyst Vijay Rakesh reiterated an Outperform rating and a $300 price target on Saturday, arguing that Nvidia would benefit from an expected $1.2 trillion in data center capital expenditures next year.
Tech strategist Dan Ives also expressed confidence in Nvidia during an interview with CNBC, dismissing the recent weakness in the stock.
According to Ives, investors have recently shifted their attention toward memory stocks, creating what he described as the "shiny new toy" effect.
“You’ve seen so many of these names, when the ones that are actually at the center, whether it’s the hyperscalers or Nvidia… those are actually the ones, to some extent, almost in the penalty box.”
Valuation, earnings and supply remain key focusIves argued that there is a disconnect between market performance and the companies driving AI development.
“The reality is, there’s one chip in the world fueling the AI revolution, that’s by the godfather of AI the revolution, Jensen of Nvidia.”
According to Koyfin data, Nvidia's forward price-to-earnings ratio has recovered to around 21.2 after falling to 19.6 last week, levels last seen in January 2019.
Ives also pointed to the importance of the upcoming earnings season in assessing AI monetization.
“When you look at memory, where is memory with Nvidia? Where's memory without hyperscalers? This all plays into what's going to be a crucial earnings season in Q2 for monetization.”
He added that demand for AI chips continues to exceed available supply.
“I continue to see chip demand far outstripping supply,” estimating the demand-to-supply ratio at “15-to-1.”
Nvidia odmítla zprávy o zpoždění architektury Kyber a uvedla, že plán zůstává beze změny, s uvedením na trh ve druhé polovině roku 2027. Akcie otevřely 6. července na 194,42 USD a 10. července uzavřely na 210,96 USD.
On July 5, the semiconductor and artificial intelligence (AI) analysis company SemiAnalysis issued a statement suggesting that Nvidia (NVDA 2.39%) could be facing a more than one-year delay in an important product launch.
The chipmaker was quick to respond, and the stock price has climbed since CEO Jensen Huang's company issued a statement that pushed back against those claims.
Image source: Getty Images.
Nvidia's response to the Kyber delay claim The reporting suggested Nvidia's Kyber rack architecture, which is designed to pack 144 of the company's GPUs into a single server so that they can work as one powerful system, was experiencing delays that would push its launch out to 2028.
Nvidia responded, telling Yahoo! Finance that the roadmap for Kyber was still "intact," which would put its launch window in the second half of 2027. The market appeared to absorb the initial news without any major fallout for the stock price. Shares of Nvidia opened at $194.42 on July 6 and closed at $210.96 on July 10. The chipmaker maintains its position as the world's most valuable publicly traded company by market cap.
During the period when the talk of a potential Kyber delay was circulating, however, another surprise was unfolding.
The challenges of being successful Nvidia has been the face of the AI trade; as of this writing, the stock price is up more than 900% over the past five years. But even as the chipmaker keeps beating expectations in its quarterly earnings reports, the bar has been set so high from its previous successes that it's becoming increasingly difficult for it to impress the markets.
Nvidia recently traded at a forward price-to-earnings (P/E) ratio of 22.2; the last time its forward P/E was around that level was in June 2019.
At first glance, that seems like a disconnect. Unlike in 2019, there is now an active race to win AI, with companies spending hundreds of billions of dollars each year on AI infrastructure.
Nvidia is generating more revenue than it ever has before, and demand for its wares is not slowing down. Yet its future earnings are still being valued at roughly the same level on a medium-term basis as they were in 2019. There is, however, a valid reason why the markets are becoming less bullish on Nvidia.
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What the market is saying Nvidia is clearly a dominant player in the AI hardware space, but what the market is asking now is, how much future growth is there left for it to capture? The forward P/E isn't so much a knock on Nvidia's operations, but rather a question of how much bigger the world's largest company can get.
As all AI roads still mostly run through Nvidia, it's a company that can still reward long-term shareholders. The caveat, however, is that investors should keep their expectations reasonable. As of the start of this month, the entire value of the U.S. stock market was about $75 trillion.
Nvidia's market cap is now about $5 trillion. If it were to climb by another 900% (as it did over the last five years), it would be worth $50 trillion. That would be an unreasonable share of the economy for any company to hold, showing why maintaining rapid growth from here will be far more of a challenge than it previously was.
Nvidia stock's NASDAQ:NVDA latest movement has little evidence that the AI infrastructure boom is losing momentum.
NVDA jumped 4% on Friday to close at $210.96, extending their weekly gain to about 8.3% as investors returned to the AI-chip leader following a period of relative underperformance.
The advance left the stock roughly 13% higher in 2026, based on its adjusted year-end close of $186.27.
Yet a warning from Taiwan has drawn attention to the financial conditions supporting that growth.
Central bank governor Yang Chin-long told lawmakers on July 9 that AI was driving genuine economic expansion, but excessive borrowing could encourage speculative investment and overbuilding.
Taiwan matters because TSMC sits at the centre of the supply chain, serving Nvidia and other global technology companies.
Yang did not declare that AI demand was about to collapse, nor did he single out Nvidia’s valuation.
His concern was that technology companies could borrow too aggressively and expand before the financial returns from their investments were fully established.
“AI is driven by real growth potential,” Yang said at the parliamentary hearing, while warning about over-expansion caused by excessive leverage.
That distinction goes directly to Nvidia’s business model. The company supplies the processors, networking equipment and complete systems used to build AI data centres.
Large cloud operators must spend heavily on chips, buildings, electricity and cooling before those assets produce meaningful revenue.
For Nvidia, greater hyperscaler spending supports near-term sales.
But if that expenditure creates weaker cash flow, rising debt or disappointing returns, customers could eventually delay data-centre projects, keep existing hardware running for longer or increase their use of cheaper custom processors.
Taiwan has therefore highlighted a financial-cycle risk rather than a product weakness.
Nvidia could remain the dominant AI-chip supplier and still suffer if the overall infrastructure budget grows more slowly.
Bank of America remains firmly bullish. Analyst Vivek Arya reiterated a Buy rating and $350 price target, arguing that investors are undervaluing Nvidia’s pricing power.
Nvidia can “sustain” roughly 65% to 70% of AI capital spending over the long term, Arya said in a research note.
He expects the Rubin platform to command higher prices than Blackwell, helping Nvidia maintain gross margins in the mid-70% range despite rising memory costs.
Goldman Sachs analyst James Schneider has also maintained a Buy rating, with a $285 target.
Schneider noted that Nvidia traded at less than 14 times his forecast for 2027 earnings, a valuation he considers compelling given the company’s growth.
Even after allowing for market-share gains by custom AI chips and rival processors, Goldman expects Nvidia’s revenue to climb about 55% to $635 billion next year.
The message from both banks is that competition is real, but Nvidia’s valuation already reflects a considerable amount of anxiety about it.
Nvidia podle článku stále míří na čtvrtletní tržby 91 miliard USD a její tržby z AI Cloud, Industrial a Enterprise vzrostly mezičtvrtletně o 31 %. Tržby z AI Cloud se meziročně ztrojnásobily.
SummaryKyber delay concerns remain unconfirmed, while Nvidia maintains its roadmap and $91 billion quarterly revenue outlook.Nvidia's second AI wave expands beyond hyperscalers into enterprise, sovereign AI, and agentic applications globally.AI Cloud, Industrial, and Enterprise revenue grew 31% sequentially, while AI Cloud revenue tripled year-over-year.Nvidia's ecosystem, software moat, and AI factory strategy support growth beyond traditional GPU demand cycles. PonyWang/iStock via Getty Images
Introduction The industry is still thinking about Nvidia (NVDA) in the context of the first wave of AI, where demand was largely limited to a select group of hyperscalers looking to train ever-more complex foundation
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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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Nvidia v pátek vzrostla asi o 2,3 % poté, co investoři přešli přes zprávu, že Meta vyvíjí vlastní AI čip. Morgan Stanley přesto zopakovala doporučení Overweight a cílovou cenu 288 USD.
Nvidia stock NVDA traded higher on Friday as investors looked past reports that one of the company's largest customers is stepping up development of its own artificial intelligence processors.
The stock was up about 2.3% at around $207 at the time of writing after trading lower in premarket activity.
The latest development came after Reuters reported that Meta Platforms plans to begin manufacturing a new in-house artificial intelligence chip from September, citing an internal company memo.
The processor, code-named "Iris," forms part of Meta's multi-generation Meta Training and Inference Accelerators (MTIA) program and is intended to support the artificial intelligence systems powering Facebook and Instagram.
According to Reuters, testing of the chip took six weeks and uncovered no major issues, marking progress for an initiative that has faced challenges since it began more than five years ago.
The report said Meta is working with Broadcom on the chip's design, while Taiwan Semiconductor Manufacturing Co. will manufacture the processors.
Meta's goal is to lower its computing costs and reduce dependence on third-party chip suppliers by using silicon tailored to its own workloads.
However, Reuters reported that the new chip is intended to augment, rather than replace, the large volumes of graphics processing units Meta continues to purchase from Nvidia and Advanced Micro Devices.
Meta has previously introduced several generations of MTIA chips and has said they could eventually replace GPUs in some servers while expanding into AI training workloads.
To date, custom chips have primarily been used for inference, the process of generating responses from trained AI models.
The report represents another example of a broader trend across the artificial intelligence industry, where major technology companies are increasingly investing in custom silicon to optimize performance and reduce infrastructure costs.
While those efforts have raised concerns about Nvidia's long-term market share, custom processors have so far complemented rather than displaced the company's graphics processors in many large-scale AI deployments.
Nvidia continues to dominate the market for AI accelerators, particularly for training frontier models, even as hyperscalers pursue greater control over portions of their computing infrastructure.
Wall Street remains constructiveMorgan Stanley reiterated its Overweight rating and $288 price target on Nvidia following the company's recent non-deal roadshow with senior executives.
The investment bank said Nvidia conveyed confidence in an accelerating and increasingly diversified growth story that could appeal to both growth- and value-oriented investors.
Morgan Stanley also maintained Nvidia as its top pick within the semiconductor sector.
Earlier this week, TD Cowen reaffirmed its Buy rating and $275 price target after meeting with Chief Executive Officer Jensen Huang, Chief Financial Officer Colette Kress, and Head of Investor Relations Toshiya Hari.
According to the brokerage, Nvidia executives said demand for AI computing infrastructure remains strong, pointing to constrained compute availability, rising rental prices for legacy GPUs, expanding enterprise AI adoption, and cloud agreements signed at premium pricing.
NVIDIA uvedla výhled tržeb na druhé čtvrtletí fiskálního roku 2027 na 91,0 miliardy USD, plus minus 2 %, bez příjmů z datacenter v Číně. V 1. čtvrtletí fiskálního roku 2027 tržby vzrostly o 85,2 % na 81,61 miliardy USD.
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NVIDIA (NASDAQ:NVDA | NVDA Price Prediction) told investors to expect $91.0 billion in revenue for the second quarter of fiscal 2027, plus or minus 2%. That figure is guidance, not a reported result, and it excludes any Data Center compute revenue from China.
Now, this figure is significantly higher than the $81.61 billion the company just delivered in Q1 FY27, which itself was up 85.2% year over year and topped consensus expectations. For a company already generating roughly a quarter-trillion dollars of trailing revenue, the guide implies sequential acceleration on a base that most industries could not reach in a decade.
What It Means Break the Q1 result apart and the story sharpens. Data Center revenue landed at $75.25 billion, up 92% year over year. Inside that, Data Center Networking pulled in $14.8 billion, up 199%, as InfiniBand, NVLink, and Spectrum-X demand tripled. Non-GAAP gross margin printed at 75.0%, and net income reached $58.32 billion, up 210.63%. Perhaps most importantly, free cash flow (what the market is growing increasingly concerned with) came in at $48.55 billion. The company has now beaten consensus EPS four quarters in a row, most recently with $1.87 versus a $1.77 estimate.
This $91 billion guide carries additional weight because it is stated to exclude Chinese Data Center compute revenue. NVIDIA shipped no H20 units to China in the quarter, versus $4.6 billion in the year-ago period. Whatever comes back from that market is upside optionality on top of the guide, not baked in. Supporting that outlook is a stated $119.0 billion in total supply-related commitments and $30.0 billion in multi-year cloud service commitments.
Market Reaction NVDA stock closed at $194.83 on July 2, 2026. Over the past week, shares are down 0.46%, and over the past month down 12.46%, moving from $222.57 on June 2 to the current level. Year to date, the stock is up 4.59%, and one-year performance stands at up 24.06%. On the day the Q1 FY27 report hit, May 20, 2026, shares were at $221.54.
Bull Case The bull case for Nvidia starts with acceleration on a base that was already very large. The AI giant grew its revenue in Q1 by 85.2%, and the Q2 guide points higher in absolute dollars. Networking growth of 199% shows the buildout extending beyond GPUs into the interconnect fabric that ties them together. These numbers were driven by an absolutely incredible gross margin of 75% with Q2 guidance holding at 75% plus or minus 50 basis points, given strong pricing power as Blackwell ramps.
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Capital return has changed investors’ perspective on NVDA stock, in my view. The company’s board approved a new $80.0 billion share repurchase authorization in May 2026 on top of $38.5 billion remaining under the prior program, with roughly $20.0 billion was returned in Q1 alone. Nvidia’s quarterly dividend was raised from $0.01 to $0.25 per share, declared May 18, 2026 and paid June 26, 2026. Analyst consensus target price sits at $301.62, with 10 Strong Buy and 48 Buy ratings against 2 Hold and 1 Sell. Forward P/E is 23, which is 30 on a trailing basis.
CEO Jensen Huang framed the setup on the earnings call: “The buildout of AI factories, the largest infrastructure expansion in human history, is accelerating at extraordinary speed.” He added that “Agentic AI has arrived, doing productive work, generating real value and scaling rapidly across companies and industries.” Partnerships announced or expanded in the quarter include Google Cloud on Vera Rubin A5X instances, Marvell on NVLink Fusion, Coherent, Corning, and Lumentum on optics, plus automotive tie-ins with Hyundai, Kia, Uber, BYD, Geely, and Nissan, and telecom collaboration with T-Mobile and Nokia on AI-RAN and 6G.
Risks aren’t to be ignored, however. Nvidia’s Q2 guide already excludes China Data Center compute, a substantial Q2 cash tax increase is expected, consumer PC demand is softer, and third-party manufacturing reliance concentrates supply chain risk. None of those items alter the anchor, that the company is guiding to $91.0 billion in a single quarter, with China stripped out.
Bottom Line For long-term holders, the $91 billion guide is the number that keeps the AI infrastructure thesis intact on hard math rather than narrative. Data Center growth of 92%, Networking growth of 199%, gross margin at 75.0%, and a new $80.0 billion buyback authorization together describe a business compounding at scale while returning cash.
The next reported result will test whether that guide holds. Until then, the number on the page is the story.
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Dukeova studie varuje, že lidar lze snadno zfalšovat malwarem i fyzicky, což může ohrozit samořídicí vozy v USA. Nvidia přesto zvolila Hesai jako možnost pro DRIVE Hyperion 10 na CES v lednu 2026.
Duke University professor Miroslav Pajic recently demonstrated how brittle the sensors underneath America’s self-driving fleet are. In one attack, malware embedded in a lidar unit conjured a person in the sensor’s point cloud who was not physically present. In a second, a real physical obstacle was made to vanish entirely from the sensor output. Pajic told CNBC it is “easy to physically spoof lidar,” warning that malware inserted at the factory or via firmware updates can stay dormant until triggered, and that automakers usually cannot audit a lidar maker’s proprietary source code.
The company at the center of that risk is Hesai Group (NASDAQ:HSAI), a Shanghai-based lidar maker that commands roughly one-third of worldwide automotive lidar sales. The Pentagon blacklisted Hesai as a Chinese military entity in 2024, a designation that prohibits Pentagon contracts but does not ban commercial sales to US autonomous platforms. Hesai sensors are already inside Amazon’s Zoox robotaxis, trucking firms Waabi and Kodiak, AV company Nuro, and Agtonomy, and they monitor passenger and traffic flow at New York’s JFK Airport security checkpoints.
NVIDIA Doubles Down NVIDIA (NASDAQ:NVDA | NVDA Price Prediction) selected Hesai as a lidar option for DRIVE Hyperion 10, its reference architecture for Level 4 autonomy, at CES in January 2026. In March, Hesai joined the Nvidia Halos AI Systems Inspection Lab, the first ANSI-accredited inspection lab for AI-driven physical systems. Jensen Huang framed the ambition simply: “Our vision is that some day, every single car, every single truck will be autonomous.” NVIDIA’s automotive revenue for fiscal year 2026 was up 39% year over year. Asked about security concerns, NVIDIA described Hyperion as an “open architecture” operating “in compliance with applicable regulations,” and did not address the exploit risk directly.
The National Security Case Craig Singleton of the Foundation for Defense of Democracies told CNBC that Chinese law gives Beijing authority to demand companies like Hesai hand over whatever data they possess, making the sensors both an attack vector and a data-collection risk. At a Senate Commerce Committee hearing on February 4, 2026, Sen. Bernie Moreno pressed Waymo’s chief safety officer, who acknowledged Chinese-made components are present in the vehicles.
Hesai’s Defense CEO David Li rejected the framing: “In the DOD case, I don’t feel there is sufficient evidence, and it’s not logical.” Li argues Hesai’s sensors have no onboard storage, that any data belongs to the partner, and that Hesai’s firmware is publicly available for outside scrutiny. Hesai reported Q1 2026 revenue of $98.66 million and holds a 55% market share in China’s long-range automotive lidar market.
Investor Exposure HSAI carries the most direct risk: shares are down 27.9% year to date to $16.15, and forced removal from US AV platforms would be existential. NVDA faces near-term supply-chain and reputational risk if regulators close the commercial-sales gap. Non-Chinese alternatives Luminar Technologies (NASDAQ:LAZR) and Innoviz Technologies (NASDAQ:INVZ), the latter trading at $0.69, would benefit from any mandated fleet-wide swap, though both are financially fragile today.
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Nvidia zrychlila výrobu architektury Vera Rubin, která má umožnit trénovat AI modely s o 75 % méně GPU a snížit náklady na tokeny inference až o 90 % ve srovnání s Blackwellem.
Elon Musk's space transportation, satellite internet connectivity, and artificial intelligence (AI) company, Space Exploration Technologies (SPCX +2.60%), went public on June 12, and opened that trading session at $150 per share. In the days that followed, the stock soared to an all-time high of $225.64, but it has since plunged back to about $150 as investors grapple with its sky-high valuation.
SpaceX has a market capitalization of $2 trillion as I write this, and with just $19.3 billion in trailing-12-month revenue, that gives it a price-to-sales (P/S) ratio of 103. That's 16 times more expensive than the average for the tech-heavy Nasdaq-100 index. As a result, I won't be surprised if SpaceX declines from here.
If I had $10,000 to invest in one stock for my diversified portfolio, I'd definitely consider an alternative. Here's why Nvidia (NVDA 0.62%) might be a much better buy than SpaceX for the long term.
Image source: Nvidia.
Vera Rubin is in full production Nvidia supplies the world's best graphics processing units (GPUs) for data centers, and its chips are still the main providers of parallel processing power for AI training and inference workloads. The company's dominance in that niche started in 2022 with the H100 GPU, which was built on the Hopper architecture. But in the years since, Nvidia has launched its Blackwell and Blackwell Ultra GPU architectures, the latter of which can deliver up to 50 times better performance than Hopper-based chips in certain configurations.
And the chipmaker just upped the ante again. It has ramped its newest architecture, Vera Rubin, up to full production and will begin shipping them in commercial quantities in the coming months. That new platform includes the Rubin GPU, the Vera central processing unit (CPU), copious memory, and a series of upgraded networking components, which combine to provide another big leap in AI computing performance. In fact, Nvidia says this new architecture will allow developers to train AI models with 75% fewer GPUs, while reducing inference token costs by up to 90% compared to its Blackwell processors.
Inference tokens represent the text, symbols, and images produced by an AI model in response to a query. So to simplify what the company is saying, Vera Rubin will dramatically reduce the cost of using AI software, which could fuel a surge in its adoption. It will also make AI providers like OpenAI and Anthropic more profitable, which could lead to even more demand for Nvidia's chips.
Vera Rubin is almost certain to be Nvidia's most successful product platform ever. According to CEO Jensen Huang, every frontier model company plans to adopt it at launch. That was not the case for Blackwell when it debuted.
Nvidia is on track for another record year Nvidia generated $81.6 billion in revenue during its fiscal 2027 first quarter (which ended April 26), representing year-over-year growth of 85%. Its data center business accounted for $75.2 billion of that total, and it grew at an even faster rate of 92%.
Analysts estimate that Nvidia could generate $392 billion in total revenue during its fiscal 2027, and a whopping $554 billion in its fiscal 2028. If the company continues to grow at this pace, it could be bringing in as much money as Walmart -- the world's biggest retailer -- within a few years.
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However, there are risks ahead. Concerns are mounting about the sustainability of the AI infrastructure boom, as shortages of GPUs and high-bandwidth memory have significantly driven up the cost of building data centers. AI software providers like Anthropic and Microsoft have implemented passive price increases this year in an effort to pass some of those additional costs to their customers -- who have not responded well to the moves.
The chief operating officer at Uber Technologies recently said it's becoming harder to justify AI spending, after his company burned through its entire 2026 AI budget in just four months. It appears he isn't alone, because a recent survey by UBS Group suggests 60% of businesses are now opting for cheaper AI models that use less computing power. That might be bad news for semiconductor demand going forward.
Buyers today are getting a great price for Nvidia stock While there are certainly risks ahead, I would argue that Nvidia's attractive valuation makes those risks worth accepting. The stock is trading at a price-to-earnings (P/E) ratio of 30.2, which is half its 10-year average of 61.6.
It's also cheaper than the Nasdaq-100 index, which has a P/E ratio of 35.2, suggesting the chipmaker is undervalued compared to its big-tech peers.
Looking ahead, the consensus among Wall Street analysts is that Nvidia's earnings will grow to $12.76 in its fiscal 2028, giving its stock a forward P/E ratio of just 15.4.
NVDA PE Ratio data by YCharts.
I'm not suggesting this will happen, but if Wall Street's fiscal 2028 estimate proves to be accurate, Nvidia stock would have to double over the next 18 months just to maintain its current P/E ratio, and quadruple to trade in line with its 10-year average P/E.
Of course, the picture will look very different if the AI industry starts buying fewer GPUs. However, I think Nvidia's valuation leaves quite a bit of room for error -- especially if we're comparing it to SpaceX, which is objectively extremely overvalued right now.
Akcie Nvidia od květnového maxima klesly o 15 %, i když očekávané tržby dál rostou. Investoři se mezitím přesouvají do paměťových firem, zejména Micron, protože cena DRAM roste.
Long the leading light of the industry, Nvidia has had a bad couple of months. Bloomberg has the ugly details, but the upshot is that the company’s stock price has fallen 15% since its peak in May, even as projected revenue continues to grow. Compared with expected earnings, the company is now cheaper than the S&P average; investors are paying less per dollar of Nvidia’s projected profit than they do for the typical large American company.
Money is still flooding into AI infrastructure stocks, but it’s mostly going into memory companies. Over the same period, Micron — one of the world’s largest makers of DRAM, the standard type of memory chip found in computers and servers — has nearly tripled in value, establishing memory as the new bottleneck for data centers and the hot new AI trade. The basic reason is simple: The GPU shortage that looked so alarming last year has eased off a bit. At the same time, data centers need all the memory money can buy.
For anyone who appreciates Nvidia’s technological accomplishments, this can feel a bit deflating. There’s a lot of genuinely impressive technology behind Nvidia’s rise, both in developing CUDA, its widely adopted programming platform that made Nvidia GPUs the default engine for AI research, and in pushing the pace of GPU development to a speed few thought possible. Nvidia’s success is the kind of thing you can write whole books about, and the GPUs themselves are among the most complex devices ever produced, right at the bleeding edge of human capability.
For memory companies like Micron, the story is much simpler. They build high-bandwidth memory chips — specialized components designed to move data in and out of processors as fast as possible — which have been getting incrementally better for 20 years. Without the chips or the companies changing too much, the service they provide suddenly became very valuable — and since demand is growing faster than anyone can scale up supply, they have been able to increase prices tenfold over the past year.
This, via Datatrack, is what the spot price for DRAM — the price buyers pay for chips on the open market, as opposed to long-term contract rates — looks like since 2023:
Image Credits:Datatrack (screenshot) You might think there was some amazing technical breakthrough in the summer of 2025, but no, the industry as a whole just vastly underestimated how much memory it would need for the data center buildout.
In comparison, this (via the compute marketplace Ornn) is how the spot price for an hour of time on an Nvidia H100 GPU has changed over the last year:
Image Credits:Ornn (screenshot) Just like Nvidia’s stock price, there’s a peak in May (around $3.20 an hour) and then a steady drop-off. For better or worse, Nvidia’s value as a company is tied to the price of compute and that price is falling. Micron and its cohort are tied to the price of DRAM, and that price keeps rising.
When I talked to Ornn co-founder and CTO Wayne Nelms about the forces driving that disparity, he framed it as a simple issue of supply and demand. Google, Amazon, Microsoft, and even OpenAI have launched their own custom processors to lessen their dependence on Nvidia; even if those chips aren’t as good as the latest model from Nvidia, they’re good enough to drive down the price of compute.
“More GPU and accelerator players are entering the market. Everyone wants to make their own silicon, but no one is making their own DRAM,” Nelms told me. “Until there’s a major technological breakthrough on HBM [high-bandwidth memory], a shift in supply and demand, or someone new [enters the market in memory], I think things will more or less persist as we see today.”
It’s a frustrating state of affairs for Nvidia, and largely a product of its own success. Having proven how valuable compute can be, the company finds itself at the center of a market everyone wants to be in — while simpler technologies and less interesting companies get rich on the sidelines.
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Russell Brandom has been covering the tech industry since 2012, with a focus on platform policy and emerging technologies. He previously worked at The Verge and Rest of World, and has written for Wired, The Awl and MIT’s Technology Review. He can be reached at [email protected] or on Signal at 412-401-5489.
SemiAnalysis odhaduje, že NVIDIA v druhé polovině fiskálního roku 2027 dosáhne v datových centrech tržeb zhruba 203 miliard USD, asi o 20 % více, než čeká Wall Street. To by mohlo zvednout EPS a snížit valuaci akcie.
The Number SemiAnalysis, the semiconductor research firm that AI hardware investors track obsessively, pegs NVIDIA’s (NASDAQ:NVDA | NVDA Price Prediction) Data Center compute revenue at roughly $203 billion for the back half of Fiscal 2027, about 20% above Wall Street consensus of about $169 billion.
That gap is the anchor of this story. If SemiAnalysis is right, the sell-side model that currently underwrites Nvidia valuation math is materially low on the company’s largest business unit.
What It Means Data Center is the engine. Last quarter, Data Center revenue hit $75.246 billion, up 92% year over year, split between Data Center Compute at $60.4 billion (up 77% YoY) and Data Center Networking at $14.8 billion (up 199% YoY). Roughly 50% of Data Center revenue comes from hyperscale customers, and NVIDIA has already locked in $119 billion of total supply-related commitments and $30 billion of multi-year cloud service commitments.
SemiAnalysis carries weight because its estimates are stitched together from the full supply chain: wafer starts, HBM availability, server integrator shipments, hyperscaler build plans. That is grittier input than the sell-side models that lean on company guidance. The firm attributes the upside to a large Rubin ramp after earlier HBM4 issues that are now resolved and front-end wafer supply that has been built up.
There is a wrinkle. SemiAnalysis also flagged that NVIDIA’s Kyber NVL144 rack-scale system may slip from 2027 to 2028 due to a PCB midplane manufacturing challenge, a claim NVIDIA disputed by saying its roadmap is intact. That debate concerns a 2028 product. The bullish revenue call is about the 2H FY2027 ramp already in flight, so the two threads do not collide.
Market Reaction Shares closed at $204.12 on July 8, 2026, up 3.65% on the day. Year to date the stock is up 9.58%, and it is up 27.74% over the past year. Prediction markets on Polymarket assign an 83% probability NVDA closes July above $208, with the crowd showing a 75.5% historical accuracy on NVDA markets.
Bull Case The valuation math is the point. NVDA trades near $204, with a forward P/E around 35. If the largest business unit earns 20% more than consensus expects in the back half of FY2027, forward EPS moves higher and the multiple compresses on its own. The stock becomes cheaper without doing anything.
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The trailing evidence supports the direction. Q1 FY2027 delivered non-GAAP diluted EPS of $1.87 versus a $1.77 estimate, a 5.42% beat, on revenue of $81.615 billion, up 85.23% YoY and 3.16% ahead of consensus.
That was the twelfth consecutive quarterly EPS beat. Margins told the same story: non-GAAP gross margin expanded to 75% from 60.8% a year ago, while net income rose 210.63% and operating income rose 147.42% year over year.
Cash generation is doing the work in the background. Free cash flow reached $48.554 billion in Q1, up 85.41% YoY. Management responded by raising the quarterly dividend from $0.01 to $0.25 and authorizing an additional $80 billion share repurchase with no expiration. Wall Street’s read is aligned: an analyst target price of $301.62 with 10 strong buy, 48 buy, 2 hold, and 1 sell ratings.
Q2 guidance from the company itself calls for $91 billion in revenue plus or minus 2%, gross margin of 75.0% plus or minus 50 bps, and excludes any China Data Center compute revenue. SemiAnalysis is layering a higher ramp on top of an already high bar.
Bottom Line For a retirement-focused investor, the real question is whether the denominator in that P/E is right, not the sticker multiple. SemiAnalysis says it is too low by roughly 20% in the biggest revenue line, driven by a Rubin ramp that is already staged.
The risks are real: the estimate is a research firm’s, not company guidance, consensus expectations are already elevated, and any execution or demand hiccup pressures a mega-cap at scale. The next hard data point is the Q3 FY2027 earnings report on August 26, 2026, after the close. Until then, the anchor number is $203 billion.
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Nvidia je po poklesu o 14 % od květnového maxima podle článku nejlevnější za roky, když se obchoduje za 16násobek očekávaného zisku v příštím roce. Tržby přitom ve fiskálním prvním čtvrtletí vzrostly o 85 %.
The artificial intelligence (AI) bellwether has had its bell rung lately. Is the ding a dinner bell for opportunistic investors? Nvidia (NVDA 0.88%) may have kicked off the AI revolution a couple of years ago, but the market has been rotating out of the global leader lately.
Nvidia stock has fallen 14% since hitting an all-time high in May. Despite inching higher through the first three trading days of this week, the shares are lower over the past month. It's a stunning contrast to the overall market, which is clawing toward fresh highs.
Image source: Getty Images.
Rotation out of the leading AI chipmaker while business is still booming is surprising, but it's not without precedent. More importantly, it's not likely to be permanent. Bullish market sentiment turning its buy order attention to the next step of AI beneficiaries, including memory and data storage manufacturers, earlier this year, isn't outlandish, even if that segment has come under selling pressure in recent weeks.
You can go up and down the pick-and-shovel ecosystem in the near term. It just seems as if you can't ignore the lead horse over the long run.
Nvidia stock is facing plenty of challenges right now, but they seem small compared to the opportunity. Let's take a closer look at the company that continues to be the largest player by market cap, but one that is now the cheapest that it's been in years, according to one popular valuation metric.
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You can buy Nvidia for just 16 times next year's earnings You read that subhead correctly. Nvidia is now trading for 23 times this fiscal year's earnings, but an even more jaw-dropping 16 times next year's analyst profit target. There are some potential headwinds out there, and I don't want to dismiss them.
China's DeepSeek is making waves again. Its latest DSpark inference module reportedly improves AI rendering speed by up to 85% without requiring new hardware. If you can do more with existing hardware, there is no need to upgrade to Nvidia's shiniest new chips. That's not something you just sweep under the rug, but do you remember when Nvidia tumbled in early 2025, when DeepSeek made headlines? Nvidia's growing client base needs reliability more than it craves the gamble of cutting corners.
Nvidia's revenue has accelerated for three consecutive quarters. The 85% top-line jump it posted in its fiscal first quarter is the strongest increase in a year and a half. The growth rate isn't sustainable, but it shows that the initial DeepSeek headlines didn't slow Nvidia's skyrocketing trajectory.
Bears can point to growing competition in AI chips and Chinese trade restrictions. Nvidia just had its first major debt offering in five years. Demand is outpacing the uptick in competitors and trade restrictions. Betting against Nvidia could be a mistake here, especially with Nvidia shares at their cheapest level in years.
It all adds up The chart is interesting. The purple line is Nvidia's stock, which has had a stellar run as a market leader, more than tripling over the past three years. The blue line is Nvidia's earnings multiple for the current fiscal year. You see it drop come late January, when the baton is passed to the next fiscal year, but notice how hype exceeded reality in 2024 (Nvidia's fiscal 2025) before normalizing a year later and outright reversing this year. The orange line -- looking out to bottom-line forecasts for the following fiscal year -- is understandably a year ahead of that swing in valuation momentum.
Saying that Nvidia is trading for just 16 times next year's Wall Street profit target means that it's cheaper than the S&P 500 itself. Should Nvidia really be trading at a discount to the market when it's growing considerably faster? Nvidia's growth will decelerate at this point, and margins may contract as rivals improve their hardware alternatives.
The problem -- and your opportunity -- is that this is the same bear case that has been debunked in recent quarters. Nvidia keeps getting stronger, and analyst profit estimates keep rising. In short, by the end of the next fiscal year, there's a fair chance that Nvidia stock's snapshot today was trading for a lot less than 16 times next year's earnings.
Nvidia klesla od květnového maxima o 16 % a její ocenění spadlo na nejnižší úroveň od začátku roku 2019. Akcie se nyní obchodují asi za 18násobek očekávaného zisku na příštích 12 měsíců, pod S&P 500.
Despite rising earnings forecasts, investors rotate into other semiconductor stocks while Nvidia's valuation falls below the S&P 500. Summary
Analysts still see over 50% upside despite the valuation reset.
Nvidia NVDA, a major chipmaker whose graphics processing units dominate artificial intelligence data centers, has seen its stock valuation fall to its cheapest level since early 2019 after losing roughly $1 trillion in market value in less than two months. Nvidia shares have declined 16% since reaching an all-time high on May 14, even as the company's GPUs continue to hold a leading position in the AI data center market. The stock is now trading at about 18 times projected earnings over the next 12 months, below the S&P 500 Index at more than 20 times and the Nasdaq 100 Index at almost 23 times, suggesting investors may be reassessing one of the market's most crowded AI trades.
The decline appears less connected to weakening fundamentals and more tied to a rotation within the semiconductor sector. Wall Street analysts have continued raising Nvidia's profit estimates, while investors have shifted attention toward Micron Technology MU, a memory-chip maker benefiting from stronger high-bandwidth memory pricing, as well as Advanced Micro Devices AMD and Intel INTC, competing chipmakers whose shares have doubled or even tripled this year. Nvidia is still expected to deliver the fourth-fastest revenue growth in the S&P 500 SPY this year, but its shares are up only 5.6% in 2026, trailing the S&P 500's 9.6% gain, the Nasdaq 100's 16% rise, and the Philadelphia Stock Exchange Semiconductor Index's 74% jump.
Nvidia's market position still appears strong, with the company holding 97% of the server GPU market at the end of 2025, up from 95% at the end of 2024, according to Bloomberg Intelligence data cited in the source. The company is projected to generate $228 billion in profit on $393 billion in sales in fiscal 2027, which ends Jan. 31, representing expected growth of 90% and 82%, respectively, while its profit estimate has risen 13% over the past three months. Of the 82 analysts tracked by Bloomberg, only three rate the stock a hold and one recommends selling, while the average price target of $302 implies more than 50% potential upside over the next 12 months, leaving investors to weigh whether Nvidia's valuation reset could mark a temporary pause or a deeper shift in AI market leadership.
Disclosures I/we have no positions in any stocks mentioned, and have no plans to buy any new positions in the stocks mentioned within the next 72 hours.
Čína zvažuje povolit vybraným AI firmám, včetně Alibaba, ByteDance a DeepSeek, nákup omezeného množství čipů Nvidia H200. Podle The Information by mohlo jít o méně než 200 000 kusů.
An NVIDIA logo and a computer motherboard appear in this illustration taken August 25, 2025. REUTERS/Dado Ruvic/Illustration/File Photo Purchase Licensing Rights, opens new tab
July 8 (Reuters) - China is planning to allow the country's top AI companies to buy a limited number of Nvidia's (NVDA.O), opens new tab H200 chips, the Information reported on Wednesday, citing two people with direct knowledge of the matter.
Chinese officials have told Alibaba (9988.HK), opens new tab, ByteDance and DeepSeek in recent weeks that they may soon receive permission to buy some H200 chips, the report said.
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Shares of Nvidia rose 1% after the report.
The chip giant did not immediately respond to a Reuters request for comment, nor did the U.S. commerce department, which oversees exports of advanced AI chips overseas.
China's commerce ministry also did not immediately respond to a request for comment, while Alibaba, ByteDance and DeepSeek did not respond outside of regular business hours.
The U.S. government has allowed Nvidia to sell its advanced H200 chips to China, and licensed about 10 Chinese firms to buy the chips. However, Chinese officials, keen to nurture domestic suppliers, have withheld approval so far.
Reuters reported in March that Nvidia had won Beijing's approval to sell the chips to China, citing sources, and around the same time, Nvidia CEO Jensen Huang also told CNBC that the company had clearance from China.
Beijing is still determining the exact number of Nvidia chips to approve, and it could amount to fewer than 200,000 in total, the Information said, adding that was less than half of what the companies requested earlier this year.
Last month, Reuters exclusively reported that Nvidia told Chinese clients its new "Vera" central processors for AI data centres could be available as soon as August and that they can begin placing orders.
Nvidia's market share in China has effectively fallen to zero, Huang said in October, hurt by U.S. export controls and Beijing's push for self-reliance in key technologies.
The potential shift in China's stance underscores the growing computing capacity crunch that the country's tech companies are facing.
Reporting by Deborah Sophia in Bengaluru; Editing by Shinjini Ganguli
Our Standards: The Thomson Reuters Trust Principles., opens new tab
Nvidia klesla na 189 USD, tedy 18 % pod letošní maximum, ale technicky se drží na klíčové podpoře a vytváří býčí pattern. Forward P/E spadl na 20, nejníže za roky.
Nvidia stock remains under pressure this week as the recent sell-off continues. It dropped to $189, down by 18% from its highest point this year, with its valuation falling by nearly $1 trillion. Still, the stock has formed a highly bullish pattern and has landed at a core support, suggesting a rebound is possible.
Technicals suggest that the NVDA stock price may bounce back in the near future. For one, it has landed at the 200-day Exponential Moving Average (EMA), which has provided it with substantial support over time. It has barely remained solidly below this MA in years.
At the same time, the stock has slowly formed a falling wedge pattern, which is made up of two descending and converging trendlines. These two lines are now nearing their confluence, which may lead to a bullish reversal.
Technically, a key risk is that the Relative Strength Index (RSI) is falling and is yet to hit the oversold level. As such, the stock may continue to drift lower for a while before it eventually bounces back.
NVDA stock chart | Source: TradingView
Nvidia is being valued like a value stock despite being one of the fastest-growing companies in the United States. Its latest earnings showed that first-quarter revenue surged to $81.6 billion, representing an 85% year-over-year increase.
Most notably, analysts believe that the growth path remains intact. Its second-quarter revenue is expected to be $91.7 billion, up by 96% YoY. This growth is being driven by soaring data center spending, with the top hyperscalers planning to spend over $700 billion in capital expenditure this year.
Yahoo Finance data shows that its annual revenue is expected to grow by 81% to $392 billion. Unless things change, Nvidia has a long history of beating analyst estimates, meaning that its revenue may hit $400 billion for the first time ever. It is then expected to hit $554 billion next year.
Despite these developments, the company’s valuation has plunged. SeekingAlpha data shows that the company has a forward price-to-earnings ratio of 20, much lower than the five-year average of 53. It has dropped to the lowest level in years.
This valuation multiple makes it cheaper than other slow-growing and lower-margin companies. For example, Walmart has a forward PE ratio of 38, while Tesla’s multiple is 189.
Other valuation multiples suggest that the company is a bargain considering that its growth is accelerating. For example, the company has a rule of 40 metric of 132%, based on its forward revenue growth of 70% and a profit margin of 62%.
Nvidia has some notable catalysts that may help to supercharge its growth. The US has allowed it to sell its H200 chips to some Chinese companies, and most recently, it launched a new line of CPUs.
The undervaluation is likely because investors are concerned about the AI industry and whether companies will continue spending. Also, there are concerns about competition, with its biggest customers like Microsoft, OpenAI, Amazon, and Google are launching their GPUs. More competition is coming from smaller companies like Cerebras and SambaNova.
Analysts remain upbeat about Nvidia, with the consensus target being $309, representing a 60% gain from the current level.
Nvidia čelí rostoucí konkurenci v AI čipech, protože startupy i velcí zákazníci jako Google, Amazon a OpenAI vyvíjejí vlastní procesory pro inference. Přesto její datacentrová divize vykázala rekordní tržby 75,2 miliardy USD, meziročně o 92 % více.
The race to challenge Nvidia's dominance in artificial intelligence chips is entering a new chapter, with startups attracting billions of dollars in funding, Big Tech accelerating in-house chip development, and investors betting that the next phase of AI computing may not belong exclusively to graphics processing units.
While Nvidia continues to dominate the market for AI hardware, attention is increasingly shifting from training massive AI models to running them efficiently in real-world applications, known as AI inference.
That transition has opened the door for a new generation of chipmakers promising faster performance, lower power consumption, and significantly lower operating costs.
The latest reminder came on Wednesday when AI chip startup SambaNova raised $1 billion in fresh financing, highlighting investors' willingness to back companies seeking to carve out a share of one of the world's fastest-growing technology markets.
The funding round values SambaNova at $11 billion and was led by General Atlantic, with participation from Seligman Ventures, T. Rowe Price, and Capital Group.
The latest investment follows a separate funding round earlier this year in which the company raised more than $350 million from investors including Intel, alongside a strategic partnership.
According to a CNBC report published in April, AI chip startups raised $8.3 billion globally in 2026.
Unless funding markets experience a sharp downturn, investment in the sector is expected to reach record levels this year.
Source: CNBC
Nvidia built its dominance on graphics processing units originally designed for gaming but later adapted for AI model training.
Those chips remain the industry standard for building large language models.
However, as enterprises increasingly deploy AI applications rather than train new foundation models, the industry is paying greater attention to inference, the process through which trained AI models respond to user queries.
Many startups argue that GPUs, while exceptionally powerful, were never purpose-built for AI workloads.
Instead, they believe specialized processors designed specifically for inference can dramatically reduce costs while consuming less electricity.
SambaNova is far from the only company trying to loosen Nvidia's grip on AI infrastructure.
Cerebras, which recently debuted on public markets after raising $5.5 billion, has long positioned itself as one of Nvidia's strongest competitors.
Morgan Stanley has argued that the company enjoys a first-mover advantage in certain AI computing segments.
Another closely watched player is Groq, whose inference-focused architecture attracted so much attention that Nvidia agreed to license some of its chip technology and hired away its chief executive last December.
CNBC later reported that Nvidia had agreed to acquire Groq for $20 billion in cash, although neither company confirmed the report.
Groq has said it would continue operating independently under chief executive Simon Edwards.
Interestingly, Nvidia later introduced its own language processing unit at its annual GTC conference in March, suggesting that it is incorporating ideas emerging from newer competitors rather than ignoring them.
Another startup attracting attention is D-Matrix, founded in 2019.
The company says its processors can execute inference workloads up to 10 times faster while consuming five times less energy than standalone Nvidia GPUs, provided workloads remain relatively small.
D-Matrix has raised around $500 million to date, reaching an estimated valuation of roughly $2 billion.
Microsoft participated in its funding through its venture arm M12.
The competitive pressure is not coming solely from startups.
Many of Nvidia's largest customers are simultaneously becoming rivals as they invest heavily in designing proprietary AI chips.
The rationale is straightforward. Developing custom silicon reduces dependence on Nvidia, lowers long-term infrastructure costs, and enables tighter integration between hardware and software.
Reuters reported this week that Chinese AI startup DeepSeek is developing its own AI chip in an effort to reduce reliance on Nvidia and Huawei processors used to train and deploy its models.
Earlier this month, The Information reported that Anthropic had held discussions with Samsung about collaborating on a future chip, although key decisions regarding its specifications and intended use remain unresolved.
OpenAI, last month, unveiled its first custom AI processor, named Jalapeño, developed alongside Broadcom.
Broadcom chief executive Hock Tan told Reuters that the processor performs on par with Nvidia's Blackwell chips and Google's tensor processing units.
Google itself is moving aggressively to reduce its reliance on Nvidia.
Rather than using the same processors for both AI training and inference, the company is separating those workloads into dedicated chips under the eighth generation of its tensor processing unit family.
Its TPU 8t and TPU 8i processors are expected to become available later this year.
Amazon is following a similar strategy.
Its AI chief, Peter DeSantis, recently told Bloomberg that Amazon Web Services is discussing the possibility of selling its Trainium AI chips to external customers, potentially creating one of the strongest alternatives to Nvidia in data centre infrastructure.
Such discussions remain at an early stage, but they follow Amazon chief executive Andy Jassy's comments that demand for the company's internally developed AI chips has been so strong that commercializing them is now under consideration.
Meta is also investing aggressively in custom AI hardware through an expanded partnership with Broadcom.
The company's Meta Training and Inference Accelerator (MTIA) programme has already produced its first chip, the MTIA 300, which powers ranking and recommendation systems across Meta's platforms.
Three additional generations are expected through 2027, with the later versions designed specifically for inference workloads that power AI assistants and respond to user queries.
Like Google and Amazon, Meta's objective is to reduce dependence on Nvidia while tailoring chips to its own software stack and AI infrastructure.
The shift illustrates a broader trend across hyperscalers.
Rather than relying entirely on off-the-shelf GPUs, technology giants are increasingly building application-specific integrated circuits (ASICs) optimized for their own workloads.
Unlike many startups, AMD and Broadcom have already established themselves as meaningful competitors in AI infrastructure.
AMD's transformation has mirrored Nvidia's in several ways.
Originally known for gaming graphics cards and PC processors, the company shifted its focus toward data centre accelerators and AI chips, allowing it to emerge as the second-largest public player in the AI accelerator market.
The strategy has paid off handsomely for investors.
AMD shares have surged more than 460% over the past five years, giving the company a market value exceeding $840 billion.
Broadcom, meanwhile, has become one of the most strategically important companies in custom AI silicon.
Rather than competing directly with Nvidia through merchant chips, Broadcom designs custom processors for some of the world's biggest AI developers.
Melius Research analysts recently said Broadcom has visibility into about 10 gigawatts of AI demand by 2027 from customers including Anthropic and Meta Platforms.
The company's influence expanded further on Wednesday after it signed a semiconductor agreement worth more than $30 billion with Apple.
Under the deal, Broadcom will design and manufacture "custom silicon components and cutting-edge wireless connectivity technologies" for Apple's products.
Despite the growing number of competitors, most analysts believe Nvidia's leadership remains overwhelming.
"Nvidia is definitely going to see more competition compared to a year ago," said KinNgai Chan, a managing director at Summit Insights Group, in comments to Reuters in March.
"Nvidia still has over 90% market share in both training and inference markets today."
However, Chan expects that dominance to gradually erode over the coming years.
"We think Nvidia will begin to see share loss starting in 2027, once in-house ASIC programs gain some scale, especially in the inference market," he said, referring to application-specific integrated circuits that are designed for dedicated workloads and offer higher efficiency than general-purpose GPUs.
Morningstar shares a similar long-term outlook.
"In the long term, we think it's inevitable that Google and AWS will push to bring more chips and AI gear in-house, to Nvidia's detriment," Morningstar analyst Brian Colello wrote.
"We expect Nvidia to lose market share to Google's TPUs and Amazon's Trainium (especially if Anthropic and/or Google Gemini emerge as dominant frontier models), but we think Nvidia's share should level out at 68% in 2030 (versus 80% today) within a much larger pie of AI spending," he added.
However, all said and done, Nvidia is not standing still.
The company spent more than $18 billion on research and development during the financial year ended January 2026 as it accelerated work on next-generation AI processors, networking products and photonics technology.
During the latest conference call in May, Huang said Nvidia's new "Vera" central processors give it access to a new $200 billion market.
Nvidia expects its Vera chips to generate $20 billion in revenue by the end of the current fiscal year.
Huang said those sales were not included in the company's earlier projection of $1 trillion in revenue from its Blackwell and Rubin AI chip platforms between 2025 and 2027.
Perhaps more significantly, Nvidia is increasingly choosing collaboration over confrontation.
Instead of competing head-on with every emerging AI chip startup, Nvidia is increasingly choosing to collaborate with companies developing specialized inference processors.
Acquiring assets from AI inference startup Groq in December for $20 billion and announcing investments worth $4 billion in two photonics companies earlier this year were part of this strategy.
Also, by integrating some rival chips alongside its own GPUs in AI server racks, Nvidia is broadening its ecosystem while ensuring it continues to benefit from AI infrastructure spending regardless of which inference technologies gain the most traction.
That strategy allows Nvidia to participate in multiple AI hardware ecosystems while continuing to generate revenue even if customers adopt specialized inference chips alongside its GPUs.
On Wednesday, inference cloud provider Parasail announced it would deploy D-Matrix's Corsair inference accelerators alongside Nvidia Hopper and Blackwell systems to deliver "up to 10x faster, more cost-efficient inference services" for customers.
Further, SambaNova's products are designed to complement Nvidia hardware rather than replace it outright.
Rodrigo Liang, SambaNova's chief executive officer, said its SN40 and SN50 chips can run the so-called decode portion of inference, unpacking the query from the model five to 10 times faster, which helps free up the same number of Nvidia chips for other tasks such as training.
Nvidia's latest financial results suggest competition has yet to meaningfully dent its business.
Its data centre division, which remains the company's primary growth engine, reported revenue of a record $75.2 billion, up 92% year over year.
Chief executive Jensen Huang sought to reassure investors that demand remains broad-based and that new products would help the company surpass the $1 trillion revenue opportunity it has projected for its flagship AI platforms.
Even so, NVDA shares fell 1.6% following the earnings release despite stronger-than-expected revenue guidance and the announcement of an $80 billion share repurchase programme.
The market reaction suggested investors are increasingly looking beyond current earnings and focusing on whether Nvidia can defend its dominant position as competitors multiply.
The stock has gained a relatively modest 4% this year and just over 23% over the past 12 months, a sharp moderation compared with its extraordinary gains during the early stages of the AI boom.
Nvidia by mohla vyplatit další dividendu za 2. čtvrtletí fiskálního roku 2027 už 1. října 2026, přičemž oznámení se čeká 26. srpna 2026. Firma po výplatě 0,25 USD na akcii 26. června 2026 může tuto úroveň zopakovat.
After paying a $6.1 billion dividend on June 26 for the first quarter of fiscal 2027, as Finbold reported, Nvidia Corp. (NASDAQ: NVDA) is likely to repeat a similar move during the next payout for the second quarter, potentially in early October 2026.
The Q2 fiscal 2027 Nvidia dividend could be paid on October 1, 2026, based on Nvidia dividend history, as analyzed by Finbold on July 8. Officially, the date for the company’s dividend payout for the second quarter of fiscal year 2027 is expected to be announced on August 26, 2026, when the company releases its earnings report.
As such, as per Nvidia dividend history, the ex-dividend date, the cutoff day on which investors must already own a stock to receive the next dividend payment, could be on September 10, 2026, as per forecast from dividendmax.
What is the expected amount to be paid in the next Nvidia dividend? For the first time in Nvidia’s dividend history, the company paid $0.25 per share last month. The company increased its dividend payout by 25-fold from the prior quarter, fueled by the ongoing AI (Artificial Intelligence) boom.
With Nvidia forecasting $91 billion in revenue for the second quarter, following a record $81.6 billion in the first quarter of fiscal 2027, the company is well positioned to pay at least $0.25 again on October 1, 2026.
Is NVDA stock a good buy? NVDA stock is worth considering, as it has maintained a parabolic bull rally over the past few years and has significantly increased its dividend. Furthermore, the Nvidia stock dividend makes the company more competitive.
NVDA stock price performance. Source: Finbold Year-to-date (YTD), NVDA stock has gained over 5% and is trading at about $196.93 at press time. Nonetheless, Wall Street analysts, including Vivek Arya of Bank of America Corp. (NYSE: BAC), anticipate further upside for NVDA shares over the coming 12 months.
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Perplexity potvrdila, že plánuje používat nový procesor Vera od Nvidia. Nvidia chce z těchto čipů do konce fiskálního roku získat tržby ve výši 20 miliard USD.
An Nvidia Vera CPU compute tray on display at the sidelines of the Computex trade show in Taipei, Taiwan, June 3, 2026. REUTERS/Ann Wang/File Photo Purchase Licensing Rights, opens new tab
SAN FRANCISCO, July 7 (Reuters) - AI startup Perplexity on Tuesday confirmed it plans to use Nvidia's (NVDA.O), opens new tab new central processing units, as the chip giant works to broaden its market and take on entrenched players such as Intel (INTC.O), opens new tab and Advanced Micro Devices (AMD.O), opens new tab.
Nvidia has said it expects to generate $20 billion in sales from its "Vera" CPU, a more generic computing chip than its AI-specific offerings, by the end of this fiscal year. The Vera chips are part of Nvidia's efforts to diversify sales as artificial intelligence companies such as OpenAI and DeepSeek make their own AI chips.
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Nvidia is entering a crowded market for CPUs long dominated by Intel and AMD, who supply CPUs for everything from laptops to web servers. But many of those chips were designed before the rise of what are known as AI "agents" that can carry out complex tasks on their own after receiving instructions from their human users.
Unlike human users of CPUs, who take breaks between tasks, AI agents do not. Perplexity Vice President for Computer Enterprise and Infrastructure Nate Kupp said Nvidia's CPU carried out AI agent coding tasks about 1.5 times faster than traditional CPUs.
"Vera really stood out to us as just like a dead-on fit for a lot of the core workloads that we have," Kupp said in an interview.
Perplexity declined to disclose how many Nvidia CPUs it plans to buy. Nvidia has previously disclosed that OpenAI, Anthropic and Oracle plan to use its CPUs.
Reporting by Stephen Nellis in San Francisco Editing by Bill Berkrot
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Nvidia je jen necelých 6 % pod hranicí 5 bilionů USD, když po pondělním uzavření měla tržní hodnotu asi 4,74 bilionu USD. V prvním fiskálním čtvrtletí jí tržby meziročně vzrostly o 85 % na rekordních 81,6 miliardy USD.
Only one company in history has ever been worth $5 trillion: Nvidia (NVDA +0.55%) itself. The chipmaker first crossed the mark last October, then slipped back below it. After closing Monday at about $195.55 per share, the chipmaker carried a market value of roughly $4.74 trillion. That leaves it less than 6% below a milestone no other business has ever touched.
So how close is Nvidia, exactly, and what would it take to get there? The math is simple, and the underlying business is firing on all cylinders.
Image source: Getty Images.
The number that gets it there With about 24.2 billion shares outstanding, Nvidia crosses $5 trillion at a share price of roughly $206. From Monday's close near $195.55, that's a gain of a little more than $10 per share, or about 5.5%. Put another way, Nvidia needs to add about $260 billion in market value. That is a rounding error for a company this size, though it still exceeds the entire market value of most companies in the S&P 500.
With that said, shares are down slightly on Tuesday, so the stock will need to add a bit more than that, but the point remains: it's extremely close.
For a stock that has climbed more than 350% over the past three years on the back of the AI boom, a move that small is nothing. Nvidia has gained that much in a single day more than once. So the $5 trillion mark is less a distant summit than a step the stock could clear on any morning of good news.
What could close the gap, or widen it The case for Nvidia getting there soon rests on the same thing that got it here: extraordinary demand for its chips. In its fiscal first quarter (the period ended April 26, 2026), revenue rose 85% year over year to a record $81.6 billion. Data center revenue climbed 92% to $75.2 billion. Management then guided for about $91 billion in revenue this quarter, another sharp step up.
"The buildout of AI factories -- the largest infrastructure expansion in human history -- is accelerating at extraordinary speed," said Nvidia CEO Jensen Huang in the company's fiscal first-quarter earnings release. As long as that spending holds, the earnings power behind the stock keeps growing.
But the gap can widen just as easily, and it's widening today. Case in point: Tuesday morning's sell-off, part of a broader memory-led chip sell-off after Samsung's preliminary record quarterly profit forecast, which still wasn't enough for Wall Street, stoked fresh worries about how long the AI boom can last. That's the near-term headwind. Sentiment toward the whole sector has turned jumpy, and Nvidia rarely trades apart from it.
Meanwhile, the longer-term risks are familiar ones. Nvidia's biggest customers, including Amazon and Alphabet, are designing their own chips to lean less on it, which could soften Nvidia's pricing power over time. And the semiconductor industry has always moved in cycles, so today's demand surge probably won't run this hot forever.
It's also worth putting the company's sheer size in perspective. At about $4.7 trillion, Nvidia is already worth more than the entire annual output of most of the world's economies, and the last leg to $5 trillion alone would add about the market value of a large-cap company in a single move. That scale is a reminder of how much optimism is already reflected in the price.
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What the milestone actually means At about 30 times trailing earnings and less than 20 times forward earnings, Nvidia isn't priced like a stock that has run out of room. Indeed, that forward multiple is actually significantly cheaper than the broader market -- a reflection of the extraordinary trajectory of the company's underlying earnings. The real question, therefore, isn't the valuation so much as the durability of the demand behind it. If AI spending stays strong, the stock has a clear path well past $5 trillion. If today's sell-off marks the start of a genuine cooling in that spending growth, the milestone could stay out of reach for a while.
Either way, I'd treat the number itself as a curiosity, not a catalyst. What matters for investors is what happens to demand for its chips, not which side of a round number the stock happens to sit on.
Certara integruje Nvidia BioNeMo Agent Toolkit do své platformy AI pro vývoj léčiv. Silo Pharma prostřednictvím své dceřiné společnosti QwikAgents vstoupila do programu Nvidia Developer Program.
Certara is integrating Nvidia’s BioNeMo Agent Toolkit into its AI-driven drug development platform, while Silo Pharma’s subsidiary, QwikAgents, has joined the Nvidia Developer Program to strengthen its AI agent capabilities.
• Nvidia stock is gaining positive traction. Why are NVDA shares climbing?
Certara Integrates Nvidia BioNeMo Into AI Drug Development PlatformCertara said it is partnering with Nvidia to advance its open, integrated AI platform by combining its scientific software, regulatory expertise, and proprietary datasets with AI-first, agentic frameworks.
Under the collaboration, the Nvidia BioNeMo Agent Toolkit will become one of several agentic frameworks available within Certara’s platform.
The toolkit is designed to turn AI agents into autonomous life sciences researchers by providing access to Nvidia’s life sciences technology stack while complementing Certara’s biosimulation models, regulatory expertise and scientific teams.
AI Agents Target Drug Development WorkflowsAccording to Certara, specialized AI agents will analyze scientific models, datasets and domain expertise across multiple stages of drug development.
The company said these agents can support tasks such as optimizing dosing strategies using systems pharmacology models, analyzing clinical datasets, simulating patient and clinical trial scenarios, evaluating ADMET properties, assembling regulatory-ready evidence and assessing early-stage drug discovery hypotheses.
Certara added that the technology is intended to enhance the work of biosimulation experts and scientific teams by accelerating insight generation while keeping scientists at the center of decision-making.
Silo Pharma Subsidiary Joins NVIDIA Developer ProgramSeparately, Silo Pharma announced its wholly owned subsidiary, QwikAgents, has joined the Nvidia Developer Program.
The company said QwikAgents’ platform automates complex workflows using autonomous AI agents capable of reasoning, taking action and interacting with enterprise systems.
The platform also incorporates persistent memory, intelligent routing across multiple large language model providers, browser automation and secure data management to support scalable AI-driven operations.
Silo Pharma said participation in the Nvidia Developer Program will provide QwikAgents with access to Nvidia’s AI software ecosystem, development frameworks, technical training and optimization resources.
The company expects those resources to help accelerate platform enhancements as it expands AI agent capabilities for enterprise customers.
CERT/SILO Stock Price Activity: Certara shares were down 0.63% at $7.09, Silo Pharma shares were down 2.10% at $6.09 at the time of publication on Tuesday, according to Benzinga Pro data.
Image via Shutterstock/ Alexander56891
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NVDY vyplácí mnohem nižší výplaty než v roce 2024: z 2,62 USD na akcii v březnu 2024 klesly na 0,0984 USD na akcii k ex-date 2. července 2026. Fond tak obětuje růst NVIDIA za hotovost.
YieldMax NVDA Option Income Strategy ETF (NYSEARCA:NVDY) monetizes NVIDIA‘s (NASDAQ:NVDA | NVDA Price Prediction) volatility through a synthetic covered-call strategy, converting option premiums into weekly cash distributions. The fund once ranked among the highest-yielding listed ETFs, but the critical question is whether those distributions represent durable income or a slow-motion return of your own capital. The answer, based on the May 2026 fact sheet and recent distribution data, is more nuanced than the headline yield suggests.
How NVDY Manufactures Its Yield NVDY holds a small slice of NVIDIA stock (11.5% of net assets) and uses options to synthetically replicate exposure, then sells short-dated calls at strikes near NVIDIA’s spot price to harvest premium. The rest of the portfolio, over 80% in Treasury Bills and a First American Government Obligations money market position, sits as collateral and earns short-term interest.
The income you receive blends option premium (which scales with implied volatility) and T-Bill yield. When NVIDIA trades around 40 vol, premiums are rich and distributions swell. When volatility compresses or NVIDIA rallies past the short strike, the math turns against holders. NVDY caps upside at the sold strike, meaning if NVIDIA rises 15% in a month, the fund captures 3% to 5% while the call is assigned or rolled at a loss.
The Distribution Trend Tells the Real Story NVDY’s payout history is the single most important safety signal. In March 2024, the fund paid $2.62 per share in a single month. By mid-2024, monthly distributions were still running above $1.00. By the July 2, 2026 ex-date, and the weekly payment was $0.0984, with recent weeks clustering between $0.08 and $0.15. Even annualized across 52 weekly payments, the current run-rate falls well short of the 2024 pace.
That decline reflects two forces. NVIDIA’s realized volatility has moderated as the stock matured into a mega-cap, compressing the premiums NVDY can harvest. Meanwhile, the fund had to fund several distributions during periods when NVIDIA rallied through the short strike, which erodes NAV to make the payment whole. NAV erosion is the covered-call ETF‘s silent tax: the yield looks fine on paper, but the price per share drifts lower over time.
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Total Return, Not Just Yield NVIDIA itself returned roughly 24% over the past year and more than 854% over five years. NVDY, by design, cannot match that because every meaningful upside move is capped. Investors who bought NVDY at inception seeking “Nvidia income” have collected large distributions but watched share price decline while NVIDIA rallied. The tradeoff is real cash today for surrendered compounding tomorrow.
The 1.09% expense ratio compounds that drag. On $1.37 billion in net assets, that is meaningful friction versus simply holding Nvidia and selling covered calls in a personal account.
The Verdict The distribution mechanics work. The Treasury collateral is safe, and premium income will keep flowing as long as NVIDIA trades with reasonable volatility. What is at risk is the size of the check. Distributions have already fallen sharply from 2024 highs, and there is no structural reason to expect a return to those levels absent a fresh volatility regime.
For investors who understand they are trading upside for cash flow and are comfortable with a slowly eroding NAV, NVDY works as an income sleeve. For anyone treating it as a proxy for owning NVIDIA, the past year has been an expensive lesson. A lower-yielding alternative such as a broad dividend growth ETF, or simply holding NVIDIA and selling covered calls selectively, will usually produce better total returns.
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NVIDIA uvedla, že ve 2. čtvrtletí fiskálního roku 2027 čeká tržby 91,0 miliardy USD při hrubé marži 75,0 %, přičemž odhad nezahrnuje žádné příjmy z Číny. Společnost zároveň schválila dalších 80,0 miliardy USD na zpětný odkup akcií.
I keep hitting the buy button on NVIDIA (NASDAQ:NVDA | NVDA Price Prediction), and after the June pullback I hit it again. I bought near $225 in May, I bought near $212 in June, and I added last week close to $194.83. The story that got me into this position keeps getting louder.
Here is what pulls me back every time. NVIDIA sells the picks and shovels for what CEO Jensen Huang calls “the buildout of AI factories, the largest infrastructure expansion in human history.” The checks his customers are writing agree with him, and the numbers behind those checks are why I own more shares this week than I did last month.
The Valuation Has Quietly Compressed Forward earnings sit near 20x, and the trailing multiple prints at 30. For a business that just delivered 85.2% year-over-year revenue growth to $81.61 billion at a 75.0% non-GAAP gross margin, that reads like a mature-industrial multiple on a platform running every frontier AI model. Shares are down 12.46% over the past month and sit 28% below the 52-week high of $236.26, even as Q1 non-GAAP EPS came in at $1.87 against a $1.7738 consensus.
The Cash Machine Behind The Buyback Q1 free cash flow was $48.554 billion, roughly 59.5% of revenue turning directly into cash. Full-year FY2026 free cash flow hit $96.575 billion, up 58.7%. Management returned $41.1 billion to shareholders in FY2026 and another $20.0 billion in Q1, then approved an additional $80.0 billion buyback authorization on top of $38.5 billion still remaining. The dividend jumped from $0.01 to $0.25, a 25x raise declared May 18, 2026. Owners are getting paid while Blackwell 300, Vera Rubin, and BlueField-4 get funded out of the same wallet.
The Demand Book Is Booked The $119.0 billion in supply-related commitments that spooks the bears reads differently when you know the customer list. Meta committed to millions of Blackwell and Rubin GPUs. OpenAI signed for at least 10 GW of NVIDIA systems. Anthropic is scaling on 1 GW of initial capacity. CoreWeave is building 5+ GW of AI factories by 2030. Sovereign deals with the UK, South Korea, and Germany layer on top. Q2 FY27 guidance calls for $91.0 billion in revenue at a 75.0% gross margin, and that number excludes any China Data Center compute.
The Real Risk China exposure is real. H20 Data Center compute revenue from China is zero in the guide, versus $4.6 billion in the year-ago quarter. A cash tax step-up hits in Q2. And $119.0 billion in supply commitments cuts both ways if hyperscaler capex ever cools. I sat with all of it. My answer is that Data Center networking revenue grew 199% year over year, hyperscalers are roughly half of Data Center revenue with sovereign, enterprise, and industrial buyers filling the other half, and multi-year cloud service commitments have grown to $30.0 billion. The book keeps deepening.
Why The Buy Button Stays Warm Analyst consensus sits at a $301.62 price target with 58 buys against one sell. I focus on the free cash flow, the platform, and the runway of a company that just went from a penny dividend to a quarter and told me another $80.0 billion of buybacks is coming. When the market sells the picks-and-shovels vendor of the biggest capex cycle of my lifetime at roughly 20x forward earnings, I keep buying.
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Akcie Nvidia oslabují poté, co se objevily zprávy, že DeepSeek vyvíjí vlastní AI čipy pro inferenci, čímž by snížil závislost na Nvidii. NVDA je při publikaci níže o 1,62 % na 192,39 USD.
Nvidia Corporation (NASDAQ:NVDA) shares are trading lower following reports suggesting China’s DeepSeek is developing AI chips for inference, which reduces its reliance on the company.
DeepSeek’s Quiet Push Into SemiconductorsIf successful, the move would mark a major strategic shift for DeepSeek — widely regarded as China’s AI champion — and could reduce its reliance on both Nvidia and Huawei chips, which it has historically depended on to train and run its globally popular models.
The Broader ContextDeepSeek would be joining a growing list of AI companies seeking to reduce dependence on Nvidia by developing custom silicon. OpenAI last month unveiled Jalapeño, its first custom inference chip developed with Broadcom, while Anthropic has been weighing building its own chips, Reuters reported in April.
Nvidia Shares FallNVDA Price Action: At the time of publication, Nvidia shares are trading 1.62% lower at $192.39, according to data from Benzinga Pro.
Image via Shutterstock
This content was partially produced with the help of AI tools and was reviewed and published by Benzinga editors.
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NVIDIA (NASDAQ:NVDA | NVDA Price Prediction) owns the AI compute market, but every major customer is spending billions to buy less of what it sells.
NVIDIA carries a $4.75 trillion market cap and sits between a 52-week low of $158.18 and a high of $236.26. Q1 FY27 revenue came in at $81.61 billion, up 85.2% year over year, with data center revenue of $75.25 billion.
About 50% of that data center number comes from hyperscalers, the same companies bankrolling Amazon Trainium, Google TPU, Microsoft Maia and Meta MTIA.
The bull case Growth accelerates at NVIDIA’s scale. Management guided Q2 FY27 revenue to $91.0 billion with non-GAAP gross margin holding at 75%. Networking revenue grew 199% year over year to $14.8 billion, evidence the moat extends past GPUs into InfiniBand, Spectrum-X and NVLink.
Blackwell Ultra is ramping, Rubin was announced, and Jensen Huang called the AI factory buildout “the largest infrastructure expansion in human history.” The dividend raised to $0.25 quarterly and an additional $80 billion buyback was authorized.
All of this says NVDA stock is set to keep delivering, as long as the broader market remains bullish.
The bear case The customer list is the threat. Amazon has disclosed Trainium is now a multi-billion-dollar business, and every hyperscaler funding NVIDIA’s data center segment also funds an alternative. Custom silicon “not only gives you a differentiation factor where you can be cheaper than competitors, but it also allows you to have some leverage over NVIDIA in negotiations.”
China data center compute revenue is effectively zero, and Colette Kress (Nvidia’s CFO) said losing that market, which NVIDIA sizes at “close to about $50 billion in the future,” would be material. Supply commitments of $119 billion compound demand risk if hyperscaler orders slow, and insiders have logged 16 recent transactions, net selling.
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What’s actually happening Neither thesis has resolved. Blackwell ramps while Trainium and TPU volumes rise in parallel. NVIDIA’s NVLink Fusion strategy lets hyperscalers bolt custom accelerators onto NVIDIA’s fabric so the interconnect stays sticky even when compute does not.
Watch hyperscaler capex mix, whether networking growth stays vertical, and any China SKU announcement over the next two quarters. Any one breaking hard could tip the call.
The market view NVIDIA trades at $196 against an analyst consensus target of ~$301.62 as of this writing, implying 53% upside. Coverage skews heavily positive with 10 Strong Buy, 48 Buy, 2 Hold, 1 Sell ratings. Forward P/E sits at 22x, trailing P/E at 29x.
Performance is mixed. NVDA is up 4.59% year to date and 24.06% over the trailing year, but down 12.46% over the past month. The S&P 500 delivered a smaller trailing-year gain, so NVDA outperformed with more turbulence.
The verdict At $196, NVIDIA remains a buy.
The numbers do not argue for selling. A company compounding data center revenue at 92% with 75% gross margins and $48.55 billion of quarterly free cash flow is a durable franchise. The numbers also do not argue for aggressively adding. Roughly half of that data center revenue comes from six companies actively engineering their way off NVIDIA’s price list, and management’s NVLink Fusion pivot is an implicit acknowledgment that fighting custom silicon head-on loses.
Buy conviction requires durable evidence that networking and software capture margin even when compute goes custom, plus a China resolution. Sell conviction requires a hyperscaler capex reset or a Trainium/TPU disclosure that reframes NVIDIA as a supplier rather than the platform. Prediction markets show 80.5% conviction NVDA touches $192 in July and only 7% for a week close above $210, a range consistent with the fundamentals.
Owning NVIDIA at this price is defensible. Buying it aggressively requires believing the customer base will keep writing checks it is openly trying to stop writing.
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Amazon rozšiřuje vlastní čipy Trainium, které začal používat ve své cloudové infrastruktuře AWS před čtyřmi lety, a jejich vývoj pokračoval uvedením Trainium2 v roce 2024 a Trainium3 v roce 2025. Dlouhodobě by to mohlo vyvíjet tlak na Nvidii. Krátkodobě ale poptávka po GPU Nvidie stále výrazně převyšuje nabídku.
Four years ago, Amazon (AMZN +1.22%) started using its own Trainium AI chips in its cloud infrastructure platform, Amazon Web Services (AWS). Those first-party chips became even more powerful with the launches of the Trainium2 in 2024 and Trainium3 in 2025. That expansion indicated that Amazon wanted to reduce its dependence on Nvidia (NVDA +0.86%), which still provides the majority of its data center GPUs.
Several of Nvidia's other top customers -- including Microsoft (MSFT 1.13%), Alphabet's (GOOG +2.19%) (GOOGL +1.71%) Google, and Meta -- also produced their own AI chips for the same reason. Google and Microsoft even plan to sell their own chips to third-party customers that want to break free from Nvidia's sticky ecosystem.
Image source: Getty Images.
That's why it wasn't surprising when recent reports suggested that Amazon would hop aboard the bandwagon and start selling its Trainium chips to external customers. Could this seismic shift shake up Nvidia's booming data center business?
Nvidia faces long-term threats Amazon's Trainium3 chips can't compete against Nvidia's top-tier Blackwell GPUs on their own. But by densely stacking 144 Trainium3 chips into its UltraServers, Amazon can actually match the rack-scale performance of Nvidia's Blackwell systems at a much lower cost. Microsoft and Google are utilizing that same "system-level stacking" strategy to challenge Nvidia's chips.
Many privacy-oriented markets, such as Europe, want to expand their cloud infrastructure without storing their data on servers operated by American hyperscalers. To solve that, they'll likely purchase more third-party chips from Amazon, Microsoft, and Google to build their own cloud platforms. Other large companies that don't want to rely on those tech giants or become too dependent on Nvidia's chips will likely follow the same playbook.
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But Nvidia still has a wide moat Amazon's sales of third-party AI chips would certainly represent a long-term challenge for Nvidia, but it probably won't meaningfully impact its near-term sales.
Nvidia still locks in its customers with its proprietary software ecosystem, CUDA, and most AI models, libraries, and frameworks are natively optimized to run on its industry-standard GPUs. Many companies that have already invested in Nvidia's ecosystem won't eagerly sever those ties to buy new chips from Amazon, Microsoft, or Google.
For now, Nvidia's investors shouldn't worry too much because the demand for its data center GPUs is still easily outstripping its supply. However, they should still keep a close eye on how its biggest customers are gradually evolving into formidable competitors.
Leo Sun has positions in Amazon and Meta Platforms. The Motley Fool has positions in and recommends Alphabet, Amazon, Meta Platforms, Microsoft, and Nvidia. The Motley Fool has a disclosure policy.
NVIDIA v 1. čtvrtletí vygenerovala rekordní provozní cash flow 50,3 miliardy USD a na zpětné odkupy a dividendy vrátila akcionářům asi 19,5 miliardy USD. Na zpětné odkupy má nyní zhruba 119 miliard USD.
Key Takeaways NVDA's cash flows surged in the first quarter of 2026, supporting buybacks, dividends and AI investments.NVIDIA returned about $19.5B to shareholders in Q1 and now has roughly $119B available for buybacks.NVIDIA expects Q2 revenues of about $91B, reflecting 95% YoY growth and a 16% sequential increase. NVIDIA Corporation (NVDA - Free Report) is generating enormous cash flows from the global artificial intelligence (AI) infrastructure boom, giving it ample flexibility to reward shareholders while continuing to invest for future growth. The company’s latest financial results suggest its aggressive share repurchase strategy is well supported by its expanding business.
In the first quarter of fiscal 2027, NVIDIA generated a record $50.3 billion in operating cash flow, up from $27.4 billion a year earlier. Free cash flow also climbed sharply to $48.6 billion from $26.1 billion in the prior-year quarter. These gains were driven by record revenues of $81.6 billion, supported by booming demand for Blackwell AI systems and data center products.
Strong cash generation enabled NVIDIA to return approximately $19.5 billion to shareholders during the first quarter through stock buybacks and dividends. The company also raised its quarterly dividend from a penny to 25 cents per share and authorized an additional $80 billion for share repurchases. Combined with roughly $39 billion remaining under its previous authorization, NVIDIA now has approximately $119 billion available for future buybacks.
Importantly, the company continues to invest heavily in long-term growth. Multi-year cloud service commitments reached $30 billion at the end of the first quarter, while inventory and supply-related commitments also rose to support future AI demand. At the end of the first quarter, inventory was $25.8 billion, while total supply-related commitments were $119.0 billion. This shows NVIDIA is balancing shareholder returns with strategic investments.
Management expects second-quarter revenues of about $91 billion, even without assuming data center compute revenues from China. The top-line forecast reflects year-over-year growth of 95% and a sequential increase of 16%. If AI infrastructure spending remains strong, NVIDIA's growing cash flows should comfortably support continued share repurchases while funding product innovation and global expansion.
How Do NVIDIA’s Peers Fare in Shareholder Return Policy?Broadcom Inc. (AVGO - Free Report) and Texas Instruments Incorporated (TXN - Free Report) are leveraging strong AI-driven cash generation to strengthen shareholder returns.
Broadcom has built a solid capital return strategy backed by robust cash flows. In the first half of fiscal 2026, the company generated $18.3 billion in free cash flow, representing roughly 44% of revenues. Broadcom has consistently returned excess cash through dividends and share repurchases while continuing to invest in AI technologies. In the first six months of fiscal 2026, it returned $14.6 billion to shareholders through share buybacks and dividend payments.
Texas Instruments is also benefiting from rising AI demand. The company generated an operating cash flow of approximately $1.52 billion in the first quarter of 2026. During the quarter, it repurchased stocks worth $158 million and paid $1.29 billion in dividends. Supported by growth in industrial, automotive and data center markets, Texas Instruments appears well-positioned to generate higher cash returns for shareholders in the coming years.
NVIDIA’s Price Performance, Valuation and EstimatesShares of NVIDIA have risen around 23.1% over the past year compared with the Zacks Computer and Technology sector’s gain of 34.9%.
NVIDIA One-Year Price Return Performance
Image Source: Zacks Investment Research
From a valuation standpoint, NVDA trades at a forward price-to-earnings ratio of 18.87, below the sector’s average of 22.73.
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 89% and 35%, 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 #3 (Hold). You can see the complete list of today’s Zacks #1 Rank (Strong Buy) stocks here.
SemiAnalysis uvedla, že klíčová racková architektura Kyber od NVIDIA se kvůli výrobním potížím s PCB deskou odkládá z roku 2027 na 2028. Zpoždění může dát prostor konkurenci AMD a Google.
NVIDIA's next marquee product — the Kyber rack-scale architecture designed to house its 2027 Rubin Ultra chips — has been delayed by more than 12 months to 2028, according to research firm SemiAnalysis, the latest in a string of reported setbacks raising questions about the AI giant's product roadmap.
Kyber is a server cabinet that packs 144 of Nvidia's most powerful chips into a single unit so they can work together as one giant computer, providing the horsepower AI companies need to train and run their most advanced models.
The design mounts graphics processing units in compute trays that sit vertically instead of horizontally to boost density and reduce latency, and had been slated to debut with Vera Rubin Ultra, Nvidia's next-generation rack-scale system, in 2027.
The setback stems from difficulties manufacturing a key circuit board at the heart of the system, SemiAnalysis said in a post on Monday.
"Kyber NVL144 rack architecture has been delayed to 2028 as the PCB midplane remains challenging from a manufacturability standpoint," the firm said, referring to a specialized, multi-layer printed circuit board that connects electronic modules within a system.
NVL576 — a larger system linking eight racks via optical connections — is also likely delayed or limited to small volumes, the research firm said.
Nvidia did not respond to CNBC's request for comment.
The reported delay adds to mounting strains across Nvidia's product lines, underscoring concerns that Nvidia's breakneck annual release cadence is colliding with manufacturing limits.
A backup plan — bolting two of Nvidia's current-generation racks together for similar power — has also been scrapped after cloud customers rejected the design as awkward and costly to operate. "It has since been cancelled due to heavy pushback from CSPs [cloud service providers] and hyperscalers over its odd design and heavy operational burden," SemiAnalysis said.
That leaves Nvidia with "no proven solution to expand the scale-up world size for Rubin Ultra," SemiAnalysis said, predicting that could give rivals Advanced Micro Devices and Google, whose in-house chips are already winning business from top AI labs, a rare technical opening at the high end of the market.
Nvidia's current-generation Rubin systems are in full production and begin shipping this fall to eight cloud partners, including Amazon Web Services, Microsoft Azure and Google Cloud. SemiAnalysis also projects Nvidia's data-center compute revenue will run 20% above Wall Street consensus in the second half of fiscal 2027.
Shares of Nvidia fluctuated in premarket trading, last down less than 0.1% at $194.79.
NVIDIA oznámila za Q1 FY2027 tržby ve výši 81,61 mld. USD, meziročně o 85,2 % více, a upravený EPS 1,87 USD překonal odhady. Vedení navíc zvýšilo výhled tržeb pro Q2 na 91 mld. USD.
My cost basis on NVIDIA (NASDAQ:NVDA | NVDA Price Prediction) keeps climbing, and I keep adding anyway. The stock dropped 12.46% over the past month. I bought. It closed the most recent session at $194.83, down 1.39% on the day. I bought again.
This is the position I cannot stop building, because the company running under the ticker is powering what its CEO calls “the largest infrastructure expansion in human history.”
The pull is simple. NVIDIA sells the compute every serious AI project needs, and the buyers show up with sovereign-sized checkbooks. Meta committed to millions of Blackwell and Rubin GPUs.
OpenAI signed for at least 10 gigawatts of NVIDIA systems. Anthropic started with 1 gigawatt of Grace Blackwell and Vera Rubin. CoreWeave is building 5+ gigawatts of AI factories by 2030. That customer list looks like a toll road under the AI economy.
Here is why the buy button stays warm Growth is accelerating. Q1 FY2027 revenue hit $81.61B, up 85.2% year over year, beating the estimate by 3.16%. Non-GAAP EPS of $1.87 beat by 5.42%, the fourth consecutive beat. Data Center alone did $75.25B, up 92%. Networking inside that segment ran $14.8B, up 199%. Management guided Q2 to $91B.
Margins and cash flow are the second reason. Non-GAAP gross margin sits at 75%, up from 60.8% a year ago. Operating income hit $53.54B, up 147.42%. Free cash flow in a single quarter was $48.55B, up 85.41%. Full fiscal 2026 delivered $96.58B in free cash flow on $215.94B of revenue. Shareholders’ equity of $195.47B stands against just $64B of total liabilities.
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Third, management is returning cash to me. The board raised the quarterly dividend from $0.01 to $0.25, a 25x increase, and authorized another $80B in buybacks on top of $38.5B already remaining. Roughly $20B was returned to shareholders in Q1 alone. Supply commitments climbed to $119B, which reads to me as demand already booked.
The Real Risk China. H20 shipments went to zero in the quarter versus $4.6B in the year-ago period, and Q2 guidance excludes any China Data Center compute revenue. Export restrictions are real, and TSMC concentration adds a single point of manufacturing dependency.
I have sat with this. My conviction holds because the rest of the world is buying so aggressively that the company still guided to $91B for next quarter with a zero from China baked in. If restrictions ease, that is upside I am not paying for.
Valuation is the fair pushback. Trailing P/E is 30, forward P/E is 23, PEG is 0.616. For a business compounding revenue at 85% with 75% gross margins and $48B of quarterly free cash flow, those numbers work for me. The consensus analyst target sits at $301.62. Polymarket traders cluster the July outcome at $192 with a 98% probability of closing above $140.
I keep buying because the AI factory buildout is early, the customer commitments are contractual, the cash is real, and the board is sending it back. Every dip is the market handing me a discount on the same thesis I owned last quarter. The buy button stays live.
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