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Key Takeaways NVIDIA's AI leadership, Blackwell adoption and data center growth support its stronger outlook.AMD is gaining AI traction through Instinct GPUs, EPYC processors and major cloud partnerships.NVIDIA's 19.31X forward P/E trails AMD's 53.04X despite stronger growth and profitability. Artificial intelligence (AI) continues to reshape the semiconductor industry, and NVIDIA Corporation (NVDA - Free Report) and Advanced Micro Devices, Inc. (AMD - Free Report) remain at the center of this transformation. Both companies are expanding rapidly as cloud providers, enterprises and AI developers spend heavily on AI infrastructure. While NVDA still dominates the AI accelerator market, AMD is making meaningful progress with its Instinct GPUs (graphics processing units) and EPYC server processors.

The question for investors is whether Advanced Micro Devices' faster stock rally makes it the better opportunity, or if NVIDIA's unmatched leadership still makes it the stronger long-term investment.

NVIDIA: The Undisputed AI Computing Chip LeaderNVIDIA continues to dominate the AI computing space. The company’s last reported results for first-quarter fiscal 2027 were another exceptional financial performance. First-quarter revenues soared 85% year over year to $81.6 billion as data center sales jumped 92% to a record $75.2 billion. Non-GAAP earnings surged 140% to $1.87 per share.

The rapid adoption of its Blackwell platform, strong networking demand and growing deployment across hyperscalers, enterprises and sovereign AI projects continue to strengthen its competitive position. During the last earnings call, management highlighted expanding opportunities in AI infrastructure, forecasting industry spending could eventually reach trillions of dollars annually.

Beyond GPUs, NVIDIA is widening its moat through networking, software and AI systems. CUDA remains the industry's preferred AI software ecosystem, making it difficult for customers to switch platforms. The company is also entering the data center CPU (central processing unit) market with Vera, creating another long-term growth engine.

Its enormous free cash flow supports higher shareholder returns through dividends and share repurchases while funding aggressive research and development. During the first quarter of fiscal 2027, NVIDIA generated $50.3 billion in operating cash flow and $48.6 billion in free cash flow. The company returned $243 million to its shareholders through dividend payouts and repurchased stocks worth $19.3 billion in the first quarter.

However, NVIDIA is not without risks. The company faces export restrictions to China, an increasingly competitive AI market and the challenge of sustaining extraordinary growth after several years of explosive expansion.

AMD: A Strong Challenger With Growing AI MomentumAdvanced Micro Devices is steadily strengthening its position in AI infrastructure. The company’s first-quarter 2026 revenues climbed 38% year over year to $10.3 billion, driven by record data center revenues of $5.8 billion, which increased 57%. Non-GAAP earnings jumped 43% year over year to $1.37 per share.

Advanced Micro Devices is witnessing strong demand for its EPYC server processors. The company’s Instinct AI accelerators continue to gain traction as customers move from pilot projects to production deployments. During the first-quarter earnings call, management expressed confidence that AI accelerator revenues could reach tens of billions of dollars annually in 2027, supported by growing partnerships with Meta, OpenAI and major cloud providers.

Advanced Micro Devices' biggest strength is its broad portfolio. Along with AI GPUs, it continues to gain server CPU market share, expand its AI PC offerings and improve its ROCm software platform. These efforts are making AMD a more credible alternative to NVIDIA.

Strong revenue growth and improving profitability are helping Advanced Micro Devices generate huge cash flows. In the first quarter of 2026, AMD reported $3 billion of cash from continuing operations and free cash flow of $2.6 billion.

Nonetheless, challenges remain for the company. NVIDIA continues to dominate the AI accelerator market with a much stronger software ecosystem and a larger installed customer base. Advanced Micro Devices also expects higher memory and component costs to weigh on PC and gaming demand during the second half of 2026. AMD’s share buybacks are not massive as it continues to invest heavily to narrow the technology gap with NVDA. In the first quarter of 2026, it repurchased shares worth $221 million.

NVIDIA vs. AMD: Which Has a Better Growth Outlook?Both companies are benefiting from growing spending on AI infrastructure buildouts by hyperscalers and enterprises, but analysts appear more optimistic about NVIDIA's growth outlook.

The Zacks Consensus Estimate for NVIDIA’s fiscal 2027 revenues and earnings indicates year-over-year growth of 80% and 90.6%, respectively. The consensus mark for fiscal 2027 earnings has also been revised upward by 4.36% over the past 60 days. The meaningful upward earnings estimate revision reflects growing confidence that sustained AI investments will continue to support NVDA’s earnings growth.

NVDA Consensus EPS Estimate Revision Trend
Image Source: Zacks Investment Research

On the other hand, the Zacks Consensus Estimate for Advanced Micro Devices’ 2026 revenues and earnings indicates year-over-year growth of 42.3% and 74.6%, respectively. AMD is also seeing positive estimate revisions, although the magnitude is relatively smaller. During the past 60 days, the consensus estimate for 2026 earnings has increased by 0.97%. While this remains encouraging, it suggests that analysts currently see stronger earnings momentum at NVIDIA.

AMD Consensus EPS Estimate Revision Trend
Image Source: Zacks Investment Research

Valuation: NVIDIA Offers Better Value Than AMDAt first glance, Advanced Micro Devices' 154.3% year-to-date rally far exceeds NVIDIA's 10.9% gain, reflecting growing investor confidence in its AI ambitions. However, the sharp rise has also pushed AMD's valuation significantly higher.

NVIDIA currently trades at a forward 12-month price-to-earnings (P/E) multiple of 19.31, well below Advanced Micro Devices' 53.04. That is notable because NVIDIA is delivering much faster revenue growth, stronger profitability, significantly higher free cash flow and remains the clear leader in AI accelerators. AMD remains an attractive long-term AI company, but much of its near-term optimism already appears reflected in its valuation.

NVIDIA vs. AMD: Which AI Stock Wins?Both NVIDIA and Advanced Micro Devices are well-positioned to benefit from the long-term AI investment cycle. AMD is executing well, gaining market share and building stronger customer relationships that should support years of growth.

However, NVIDIA continues to outperform on nearly every major metric, including revenue growth, profitability, software leadership, ecosystem strength, cash generation and shareholder returns. Combined with its lower valuation multiple, NVIDIA offers a more compelling balance of growth and value. For investors looking to capitalize on the AI boom today, NVIDIA remains the better investment bet.

Currently, NVIDIA sports a Zacks Rank #1 (Strong Buy), giving it a clear edge over Advanced Micro Devices, which carries a Zacks Rank #2 (Buy). You can see the complete list of today’s Zacks #1 Rank stocks here.

I keep buying NVIDIA, and the reason has almost nothing to do with the chips. It’s the software giveaway underneath them. Most investors file NVIDIA (NASDAQ:NVDA | NVDA Price Prediction) under “hardware,” and that framing is exactly why I’m still adding at $207.29. What I actually own is a freemium platform that happens to sell the world’s most expensive accelerators on the back end.

The Free Tier Is the Trap CUDA is free. Triton is free. NIMs, Dynamo 1.0, Nemotron, BioNeMo, Isaac, Omniverse. All free. Every graduate student, startup, and hyperscaler research team writes code against these libraries. Then the code only runs at full speed on NVIDIA silicon. “NVIDIA has the largest suite of acceleration libraries in the world,” Jensen Huang told analysts on the May call, and that’s the moat in plain language.

The paywall shows up at scale. When a customer moves from prototype to production, they build an AI factory rather than purchasing a single GPU. CFO Colette Kress framed it plainly: “Customers do not buy GPUs; they build AI factories. The right economic metric is not the purchase price of the GPU; it is the lifetime cost of an AI factory producing intelligence.” Switching costs at that level are brutal. You’d rewrite years of CUDA-optimized code, retrain teams, and lose performance. Almost nobody does it.

The Receipts Three numbers keep the buy button warm. First, growth that shouldn’t be possible at this size. Q1 FY2027 revenue hit $81.615 billion, up 85.23% year over year, with Data Center alone at $75.246 billion (+92%). Networking inside that number grew 199% YoY. Management guided Q2 to $91.0 billion.

Second, the margin structure the software stack enables. Gross margin 71.07%, operating margin 60.38%, ROE 101.5%, ROIC 92.2%. Free cash flow of $48.554 billion in a single quarter. Those are software-company economics attached to a hardware volume business.

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Third, capital returns finally showing up. The board authorized an additional $80 billion buyback on top of $38.5 billion remaining, and lifted the quarterly dividend from $0.01 to $0.25. At a forward P/E of 23, I’m paying a market multiple for a compounder returning tens of billions to owners.

Why Not the Obvious Alternatives NVIDIA’s Data Center segment posted $75.25 billion in a single quarter, which is larger than AMD’s entire company revenue base, and AMD does not run CUDA. Broadcom is the other name people cite for AI silicon, but its custom ASIC business lacks the CUDA software ecosystem lock-in that keeps developers on NVIDIA year after year. I’m paying for a developer base that would need to be pried loose one library at a time.

The Risk I Actually Watch China. H20 shipments went to zero this quarter, and Q2 guidance excludes China Data Center compute revenue entirely. That’s real. What keeps the thesis intact is that demand outside China is absorbing every wafer TSMC can produce. The $91 billion Q2 guide assumes zero China contribution. Blackwell and Rubin combined carry $1 trillion in revenue visibility through calendar 2027. I don’t need China to make the math work.

What Keeps the Buy Button Active Reddit is skeptical, insiders are trimming, and the crowd on Polymarket sees limited near-term upside above $210. I’m buying for the long arc, because every free download of CUDA is a future paying customer, and there are roughly 250,000 enterprises that haven’t shown up yet. The freemium hook is set. I keep loading.

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A $1,000 investment in Nvidia (NASDAQ: NVDA) around the launch of DeepSeek-R1 in January 2025 would be worth approximately $1,480 today, representing a gain of about 48%.

DeepSeek-R1, unveiled on January 20, 2025, drew global attention by demonstrating advanced reasoning capabilities at a fraction of the computing cost of many leading AI models. 

The development sparked concerns that more efficient AI systems could reduce demand for expensive AI hardware.

Those fears culminated on January 27, 2025, when Nvidia shares plunged nearly 17% in a single session, erasing roughly $600 billion in market value in the largest one-day market-cap loss ever recorded by a public company.

The downturn proved temporary as Nvidia recovered and continued climbing. An investor who bought about 7.14 shares at roughly $140 each shortly after the DeepSeek-R1 launch would now hold a position worth around $1,480, based on Nvidia’s current share price near $207.

NVDA one-year stock price chart. Source: Finbold Nvidia’s rebound after DeepSeek AI scare  While DeepSeek-R1 raised concerns about AI infrastructure spending, the broader AI market continued expanding throughout 2025 and into 2026. 

Nvidia benefited from sustained investment by hyperscalers, enterprises, and AI developers building large-scale training and inference systems.

The company also continued advancing its data center and AI chip offerings, helping maintain its leadership position.

Nvidia’s business has continued expanding at a rapid pace based on the financial figures. The company reported record fiscal 2026 revenue of $215.9 billion, including $68.1 billion in fourth-quarter revenue and $62.3 billion from its data center segment.

Investor attention is now turning to Nvidia’s August 4 earnings report. In this line, recent market expectations call for quarterly revenue of around $91 billion, reflecting continued demand for Blackwell AI systems.

Additional support has come from improving sentiment around international sales. Recent U.S. approvals allowing limited AI chip exports to China have eased some concerns about access to one of the world’s largest AI markets.

Despite periodic volatility, Wall Street continues to view Nvidia as one of the main beneficiaries of the global AI buildout. The upcoming earnings report is expected to provide a key test of whether massive AI infrastructure spending by major technology companies can continue at its current pace.

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A general view of electronics manufacturer Wistron's new global operations headquarters in Hsinchu, Taiwan June 19, 2025. REUTERS/Wen-Yee Lee/File Photo Purchase Licensing Rights, opens new tab

TAIPEI, July 22 (Reuters) - Taiwan's Wistron (3231.TW), opens new tab, a supplier to Nvidia (NVDA.O), opens new tab, launched a $700 million manufacturing ​facility in Texas on Tuesday to produce ‌the U.S. chipmaker's latest AI systems, as Taiwanese electronics makers expand U.S. production to meet soaring ​demand for AI infrastructure.

Here are a ​few details:

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The Fort Worth facility manufactures Nvidia's ⁠GB300 Grace Blackwell Ultra Superchip. Nvidia CEO ​Jensen Huang has described the AI system built ​around the product as "the most powerful AI supercomputer in the world."

Wistron said the site is where Nvidia's ​first GB300 Grace Blackwell Ultra Superchip was ​built and mass-produced in the United States.

The factory will ‌also ⁠manufacture Nvidia's next-generation Vera Rubin Superchip, Wistron said.

The factory is expected to scale up production this year to manufacture tens of thousands ​of computing ​boards per ⁠month, according to Nvidia.

The factory has created more than 500 jobs, ​Nvidia said, adding that it is ​on ⁠track to expand its workforce to 1,000 employees by the end of the year.

Nvidia said ⁠Wistron's ​Fort Worth plant forms ​part of the $500 billion U.S. investment commitment it announced in ​2025.

Reporting by Wen-Yee Lee; Editing by Sherry Jacob-Phillips

Our Standards: The Thomson Reuters Trust Principles., opens new tab

© AlexSava / Getty Images

Amazon (NASDAQ:AMZN | AMZN Price Prediction) and NVIDIA (NASDAQ:NVDA) just closed earnings on opposite sides of the AI infrastructure trade. Amazon reported Q1 FY2026 on April 29, 2026, with AWS growing 28% and custom silicon crossing a $20 billion annual run rate. NVIDIA followed with Q1 FY2027 revenue of $81.62 billion, up 85.2%. Trainium is the reason to compare them right now.

AWS Sprints, Blackwell Still Roars AWS hit $37.59 billion in revenue, the fastest growth in fifteen quarters. CEO Andy Jassy told investors Amazon now has “over $225 billion in revenue commitments for Trainium”, anchored by Anthropic’s 5 GW deal and OpenAI’s 2 GW commitment starting 2027. Trainium2 is “largely sold out”, with 1.4 million chips already deployed powering most Bedrock inference.

NVIDIA’s Data Center revenue reached $75.25 billion, up 92%, with networking alone up 199%. Jensen Huang called this “the largest infrastructure expansion in human history”. Blackwell 300 is ramping and Vera Rubin is queued behind it. Non-GAAP gross margin held at 75.0%, roughly the mirror image of Amazon’s 50.3%.

The Three Ways Trainium Cracks NVIDIA’s Moat First, the mass volume ramp is happening now. The 3nm Trainium 3 moved from select early customers in early 2026 into mass production, and AWS hiked its Q3 2026 server shipment targets by 20% to 30% to support the ramp. Jassy said Trainium 3 is “30% to 40% more price performant than Trainium2” and nearly fully subscribed.

Second, distribution is changing. Reports emerged in June 2026 that Amazon is in active talks to sell physical Trainium server racks directly to external, sovereign, and co-location data centers. That breaks the AWS-only wall Trainium has lived behind and puts it in NVIDIA’s direct sales lane.

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Third, Trainium 4 lands next. The chip is designed to offer 3x the processing power of Trainium 3, is already heavily pre-ordered, and is scheduled for initial deployment in late 2026 to early 2027. Amazon frames the savings bluntly: “tens of billions of dollars of CapEx each year”.

Lens Amazon NVIDIA Core Bet Vertical AI stack GPU platform lock-in Gross Margin 50.3% 75.0% Anchor Commit $225B Trainium OpenAI 10 GW The Rubin Ramp Will Decide 2027 Watch whether Vera Rubin arrives with pricing power intact, or whether hyperscalers use Trainium 4 leverage to negotiate harder. Amazon still plans to deploy 1 million or more NVIDIA GPUs starting in 2026, so this is a share shift, not a replacement. The mix worth watching is inference workloads migrating from GPU to Trainium inside Bedrock’s 125,000 customer base.

Why I Lean Amazon for the Next Eighteen Months Amazon trades at a P/E of 30, the lowest in over a decade, while the chip business compounds at triple digits with anchor customers locked in. NVIDIA is the safer operating model at a 75.0% gross margin, but Polymarket traders see just a 5.8% chance NVDA closes above $220 today. For defensive AI exposure at a premium multiple, NVIDIA still works. For a re-rating catalyst tied to a specific product, Trainium 4 into early 2027 is the cleaner setup.

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Bank Earnings Are Roaring, But Wall Street Isn't Ready to CelebrateNVIDIA NASDAQ: NVDA used its 2026 SIGGRAPH Research Keynote to outline a broad push to combine computer graphics, simulation and artificial intelligence, including a new DLSS 5 technology for real-time rendering, advances in AI-assisted physics simulation and new additions to its Cosmos world foundation model platform for physical AI.

The keynote opened with NVIDIA framing computer graphics as entering “a new era,” with AI increasingly tied to rendering, simulation, robotics and digital twins. Jensen, who introduced the session, said NVIDIA’s history at SIGGRAPH has included programmable GPUs, CUDA, RTX and Omniverse, and argued that virtual worlds will be central to training robots before they operate in the real world.

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2 Quantum Stocks That Could Challenge IonQ’s Leadership“Before robots operate in the real world, they will learn in virtual worlds with synthetic experiences,” Jensen said. “That is why computer graphics matter more than ever.”

DLSS 5 Targets Real-Time Photorealism Edward Liu, NVIDIA’s Director of Applied Deep Learning Research and the technical leader behind DLSS, introduced DLSS 5, describing it as a new generation of the company’s AI rendering technology. Liu said DLSS 5 uses traditional rendering as a foundation, then applies generation to enrich the final appearance of the image in real time.

The SK Hynix IPO and 2027’s AI Memory Squeeze“The renderer keeps building the world exactly as the game has authored it,” Liu said. “The generation becomes the learned stage afterwards to enrich its appearance.”

Liu said DLSS 5 is intended to combine the controllability of rendering with the photorealistic knowledge learned by generative models. He emphasized that the technology is not designed to replace graphics pipelines, but to extend them. He described DLSS 5 as adding a third category of AI use in real-time rendering, alongside reconstruction and function approximation.

According to Liu, NVIDIA had to address three core challenges: preserving artistic intent, maintaining temporal coherence frame by frame and fitting within the tight performance budget of real-time games. He said the model uses renderer outputs and internal buffers such as albedo, surface normals and lighting information to preserve details that are important to a scene, while enhancing elements such as subsurface scattering, material response, contact shadows and environment lighting.

Liu said DLSS 5 runs causally, “one frame in, one frame out,” without looking ahead, and was distilled into a smaller one-step pixel-space diffusion transformer model focused specifically on making real-time rendering appear more realistic. He said DLSS 5 is “shipping this fall.”

Artists Get Controls Over AI-Enhanced Frames Gaff, described as a creative artist, demonstrated how developers and artists can direct DLSS 5. He said the technology respects the original rendered frame and does not change geometry, but can uplift images by improving contrast, ambient occlusion, contact shadows, reflections and subsurface scattering.

Gaff showed controls including different models, structure intensity and tone intensity. He said developers can choose different models for different scenes or cut scenes, and can use masks to apply DLSS 5 effects to specific characters, props or parts of an environment.

“DLSS 5 is fully controllable from the developer,” Gaff said, adding that NVIDIA is working with partners to incorporate feedback so the technology can serve artists, art directors and creative directors.

NVIDIA Highlights AI Physics for Simulation Neil Ashton discussed physics-based simulation and how AI could help reduce the computational cost of high-fidelity simulations. He pointed to a large climate simulation running on more than 20,000 GPUs at one-kilometer resolution and a 50 billion-cell grid, calling it an example of the accuracy possible with physics-based methods but also a reminder of their cost.

Ashton said AI models trained on simulation data are already being used in weather and climate, where they can predict future weather in seconds or minutes compared with hours or days. He said weather centers now use AI models in production, and highlighted StormScope as an advanced AI model trained on satellite and observation data for storm prediction.

He also described applying similar methods to engineering simulations, such as airflow over aircraft. Ashton said an open dataset of roughly 2,000 aircraft simulations generated about 200 terabytes of data, while the trained model checkpoint was about 200 megabytes. He said the model could predict unseen geometries or boundary conditions more than 10,000 times faster, with accuracy within about 1% or 2%.

Cosmos Platform Expands for Physical AI Ming Liu, VP of the Cosmos Lab at NVIDIA, said physical AI faces a data problem because robots need to learn from the real world, but real-world data is slow to collect. He described Cosmos as NVIDIA’s world foundation model for physical AI developers, designed to provide better data, better environments and better starting points.

Liu said Cosmos can support world understanding, prediction, simulation and action using one shared representation, based on the idea that physical AI tasks draw from the same physics. He described a mixture-of-transformers architecture with an autoregressive tower for reasoning and a diffusion tower for generation, aligning language, vision, audio and action.

Liu announced Cosmos 3 Edge, a four-billion-parameter model built to run real time on devices such as Jetson Thor, RTX and DGX Spark. He said it is intended to enable robot policy and video analytics without a round trip to a data center. NVIDIA also demonstrated a robot arm and camera connected to Jetson Thor running Cosmos 3 Edge policy for real-time control.

Liu also announced Cosmos Dreams, described as neural closed-loop simulators. The first version is designed for autonomous vehicles, generating what vehicle sensors will see based on actions taken by a policy model. In a live demo, Andy showed an autonomous driving simulation generated from a single frame and controlled with a PS5 controller, running on a single RTX 6000 Ada Generation workstation GPU.

Liu said Cosmos Dreams can be used for policy verification and training by generating scenarios that are difficult to craft in the real world. He said Cosmos is being used across NVIDIA efforts including Metropolis VSS, Isaac, Optane and GR00T, and invited developers and partners to join the Cosmos platform.

About NVIDIA (NASDAQ:NVDA)NVIDIA Corporation, founded in 1993 and headquartered in Santa Clara, California, is a global technology company that designs and develops graphics processing units (GPUs) and system-on-chip (SoC) technologies. Co-founded by Jensen Huang, who serves as president and chief executive officer, along with Chris Malachowsky and Curtis Priem, NVIDIA has grown from a graphics-focused chipmaker into a broad provider of accelerated computing hardware and software for multiple industries.

The company's product portfolio spans discrete GPUs for gaming and professional visualization (marketed under the GeForce and NVIDIA RTX lines), high-performance data center accelerators used for AI training and inference (including widely adopted platforms such as the A100 and H100 series), and Tegra SoCs for automotive and edge applications.

This instant news alert was generated by narrative science technology and financial data from MarketBeat in order to provide readers with the fastest reporting and unbiased coverage. Please send any questions or comments about this story to [email protected].

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NVIDIA Agent Toolkit now includes NVIDIA Omniverse libraries, giving AI agents tools and skills to help software developers integrate physical AI capabilities into their existing applications.New Omniverse libraries for NVIDIA RTX sensor simulation, GPU-accelerated physics simulation and simulation-ready asset validation are openly available on GitHub.SideFX and PTC are integrating Omniverse libraries into 3D applications for physical AI, with support for cloud and local AI systems, from NVIDIA RTX Spark to NVIDIA DGX Station.New NVIDIA blueprint for integrating Omniverse libraries in Blender. LOS ANGELES, July 20, 2026 (GLOBE NEWSWIRE) -- SIGGRAPH -- NVIDIA today announced that NVIDIA Agent Toolkit now includes NVIDIA Omniverse™ libraries — a collection of software components that give AI agents tools and skills to add physical AI capabilities to existing applications and prepare 3D content for simulation.

Robots, factories and autonomous systems need to be designed, tested and trained in simulation before they operate in the real world. Preparing 3D content for simulation takes more than realistic visuals — assets need the right structure, materials, scale, labels, sensors and physical properties. With NVIDIA Omniverse libraries in NVIDIA Agent Toolkit, AI agents have the tools and skills to build workflows, inspect scenes, flag issues and prepare assets, helping developers move faster from 3D content to simulation-ready environments.

“The physical AI era will be built in simulation first,” said Jensen Huang, founder and CEO of NVIDIA. “NVIDIA Agent Toolkit with Omniverse libraries brings AI agents into the 3D tools developers already use, helping build the simulation-ready worlds where robots, factories and autonomous systems are trained and tested long before they reach the real world.”

Software makers including SideFX and PTC are integrating Omniverse libraries for agent-ready sensor simulation, physics and asset validation, helping bring agentic AI into the applications and workflows developers and technical artists already use to prepare 3D content.

Omniverse Libraries Bring Physical AI Skills to NVIDIA Agent Toolkit
NVIDIA Agent Toolkit helps software makers build AI agents that connect tools, skills and data sources. Omniverse libraries extend those agents into 3D and physical AI workflows with callable tools for sensor simulation, GPU-accelerated physics and simulation-ready asset validation inside existing applications.

The new Omniverse libraries — including ovrtx, ovphysx and CAD-to-SimReady skills — are openly available on GitHub, giving AI agents tools to build workflows for inspecting scenes, testing changes and preparing 3D assets for simulation. A new blueprint for integrating Omniverse libraries in Blender is also now available on GitHub.

The libraries’ key capabilities include:

NVIDIA RTX sensor simulation: ovrtx helps applications generate camera, lidar, radar and other sensor outputs from 3D scenes, so developers and AI agents can test how physical AI systems may perceive virtual environments.Physical behavior: ovphysx uses GPU-accelerated physics to bring realistic behavior to 3D scenes using properties such as collisions, mass, friction and motion, so teams can first test how objects and systems interact in simulation.Simulation-ready 3D objects: CAD-to-SimReady skills help convert computer-aided design (CAD) data to SimReady assets built on OpenUSD, giving 3D content the properties needed for physical AI simulation and virtual testing.
Software Makers Build With Omniverse Libraries
Software makers including SideFX and PTC, as well as startups ForgeCAD, Lightwheel, Moonlake AI and Palatial, are among the first to adopt and build with Omniverse libraries, now part of NVIDIA Agent Toolkit.

SideFX is using OpenUSD workflows, as well as ovrtx and ovphysx libraries, to explore how agents can help integrate Omniverse libraries into its Houdini procedural 3D content creation workflows, giving technical artists a path to generate, test physics and prepare content for simulation.

“Procedural 3D creation is essential to building the complex, controllable worlds needed for simulation, robotics and industrial AI,” said Kim Davidson, president and CEO of SideFX. “With NVIDIA Omniverse libraries and OpenUSD, SideFX is exploring how agent-ready tools can support Houdini workflows, helping technical artists review, test and prepare procedural content for simulation while staying in control of the creative process.”

The PTC Onshape CAD and product data management (PDM) platform is using OpenUSD and ovrtx to connect cloud-native design workflows with physical simulation, helping product design content stay connected with CAD, PDM, collaboration and simulation workflows.

“Engineering teams are seeking more connected ways to design, collaborate and simulate throughout the development process,” said Neil Barua, president and CEO of PTC. “PTC’s work with NVIDIA supports that broader vision, while NVIDIA Omniverse libraries help enable simulation-ready workflows that bring validation and testing closer to where products are designed.”

On display at SIGGRAPH, “SimReady” Blender is a sample workflow built in Blender with NVIDIA Omniverse libraries and NVIDIA NemoClaw™, showing how software makers can add agent-ready simulation capabilities — including NVIDIA RTX sensor simulation, physics and validation — into existing 3D applications while keeping creators in control. This is now openly available as a blueprint for integrating Omniverse libraries in Blender.

The demo also previews how these workflows, built with Omniverse libraries as part of NVIDIA Agent Toolkit, can run locally, from compact RTX-powered systems with NVIDIA RTX Spark™ to NVIDIA GB300-powered systems with NVIDIA DGX Station™. RTX Spark systems will be available this fall from ASUS, Dell Technologies, HP, Lenovo, Microsoft Surface and MSI, with models from Acer and GIGABYTE to follow. DGX Station systems are available to order from ASUS, Dell, GIGABYTE, HP, MSI, Supermicro and Exxact.

Startups, including those part of the NVIDIA Inception program, are also using Omniverse libraries and skills to add agent-assisted asset and scene preparation workflows. Palatial is using Omniverse CAD-to-SimReady skills to automate the creation and validation of SimReady assets at scale from CAD inputs. Lightwheel is using Omniverse Content Agents powered by OpenUSD in its SimReadyGen technology to generate physically accurate SimReady assets from text prompts.

ForgeCAD and Moonlake AI are exploring agent-driven 3D content workflows that use Omniverse capabilities to help generate, augment and prepare assets for physical AI simulation.

Watch the NVIDIA keynote at SIGGRAPH. Learn more about NVIDIA Omniverse libraries and explore available samples and documentation.

About NVIDIA
NVIDIA (NASDAQ: NVDA) is the world leader in AI and accelerated computing.

For further information, contact:
Paris Fox
Corporate Communications
NVIDIA Corporation
[email protected]

Certain statements in this press release including, but not limited to, statements as to: 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.

© 2026 NVIDIA Corporation. All rights reserved. NVIDIA, the NVIDIA logo, DGX Station, NemoClaw, Nemotron, NVIDIA Omniverse, NVIDIA RTX and NVIDIA RTX Spark are trademarks and/or registered trademarks of NVIDIA Corporation in the U.S. and other countries. Other company and product names may be trademarks of the respective companies with which they are associated. Features, pricing, availability and specifications are subject to change without notice.

A photo accompanying this announcement is available at https://www.globenewswire.com/NewsRoom/AttachmentNg/1db6fb48-31e7-4ea7-8281-2713208e224e

NVIDIA Launches Omniverse Libraries, Putting AI Agents to Work Building Simulation-Ready Worlds NVIDIA today announced NVIDIA Omniverse libraries — a collection of software components that give AI...

Nvidia (NVDA 1.97%) enjoys one particular attribute that is a hallmark of many successful companies: It's still being led by one of its founders, Jensen Huang. There are countless examples of visionaries who have built business empires, and Huang ranks among the best.

Over the company's past few quarterly conference calls, Nvidia has repeatedly told investors it expects that the world's annual data center capital expenditures could grow to up to $4 trillion by 2030. That's a huge prediction, and if it's right, Nvidia could become a $20 trillion stock over the next few years.

That would be a gigantic increase from its $5 trillion market cap today, but the math to support that prediction is pretty simple. 

Image source: Nvidia.

The data center build-out could last for many years Nvidia makes GPUs and the various products that support their use in data centers. Its GPUs have become the gold standard by which all high-performance parallel processors are measured. Furthermore, Nvidia captured the vast majority of the market in the early days of the AI arms race, which makes it incredibly difficult for data center operators to switch away from its products now. This advantage will only grow as more data centers are built.

The big four AI hyperscalers have estimated that they will spend a total of around $650 billion on data center capital expenditures in 2026. That figure doesn't include the spending of neoclouds, international players in markets such as China, nor other rising stars like large language model developers Anthropic and OpenAI.

With that in mind, we can estimate that 2026's actual total data center spend will be something more like $800 billion. Huang's prediction of $4 trillion in global data center capital expenditures by 2030 would therefore be a fivefold rise. If Nvidia keeps capturing its current share of that market's sales and profits, its top and bottom lines would rise proportionally.

The company only needs to quadruple to reach a $20 trillion market cap from today's level, so Nvidia could actually lose market share and still hit that target, assuming Huang's projection for data center capex pans out.

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However, I don't see that market share loss as likely. Nvidia is still rapidly growing: In its latest quarter, revenue grew 85% year over year. Next quarter, Wall Street analysts expect nearly 100% revenue growth. All that growth is without any chip sales to China. But that could be changing.

A U.S. official recently stated that "very few" Nvidia H200 chips have been shipped to China. While that may sound negative, that comment can actually be read as a strong sign that Nvidia is returning to the Chinese market. The U.S. government banned the export of most of its high-end chips to China, and even after President Trump relaxed those restrictions somewhat, the Chinese government has been putting roadblocks in the way of Nvidia's return. If those barriers are coming down, that would be a growth catalyst for sales that's currently not factored into any of the company's guidance figures. The result could be even greater growth for Nvidia and better returns for its shareholders.

Given the potential for Nvidia to quadruple over the next four and a half years, it's a no-brainer buy at these levels.

Nvidia (NVDA 1.97%) stock hasn't been an incredible performer this year, but it is slightly edging out the S&P 500 (^GSPC 1.01%), with both up around 11% year to date.

It's still the most valuable company in the world with a $5 trillion valuation, so reaching $10 trillion by 2030 would imply doubling. It looks like a distinct possibility. Here's why.

Image source: Nvidia.

Nvidia isn't slowing down Sales growth has been accelerating. Revenue increased 85% year over year in the 2027 fiscal first quarter (ended April 26), and Wall Street is looking for even higher growth in the second quarter: a whopping 96%, with a forecast of 82% for the full year. That's quite a feat for a company as big as Nvidia.

The positive signs abound. On Tuesday, JPMorgan Chase CEO Jamie Dimon said he thinks artificial intelligence (AI) spending will reach $1 trillion in 2027, and Taiwan Semiconductor Manufacturing, which makes Nvidia's chips, is investing $100 billion in its new Arizona facility.

The chip market is heating up The AI chip races are only getting faster. Nvidia accounts for 80% to 90% of the market, according to Silicon Analysts, a level of absolute dominance. That lead is projected to decline to 75% as competitors like Advanced Micro Devices gain traction and many top AI players compete with other chip types, such as Broadcom's Application-Specific Integrated Circuits (ASICs) and Alphabet's Tensor Processing Units (TPUs). However, even a 75% lead is fortress-level.

Nvidia's CEO Jensen Huang doesn't seem fussed by the competition; he sees more AI development as a good thing for the company, which underpins much of the AI infrastructure. Whether or not the competition advances, Nvidia should keep growing and remain the leader.

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More concerning, from an investing standpoint, might be whether Nvidia can continue to demonstrate accelerating growth or even maintain current growth rates. As the base gets bigger, that isn't likely to last much longer. For example, if it were to grow at a compound annual growth rate of 80% over the next four years, it would have $2.7 trillion in sales, easily becoming the largest company in the world.

It's more likely that growth will slow over the next four years, and as it does, the stock will reflect that. It trades at a premium price-to-sales ratio of 20 right now, but that would likely decline as growth decelerates.

To see how it could play out, a CAGR of 40% to 50% would result in somewhere around $1 trillion in sales in 2030, or about four times today's trailing-12-month revenue. At the current price-to-sales ratio, the stock would quadruple. But at half the ratio, or 10 times trailing-12-month sales, the stock would double and reach $10 trillion.

That's just one possibility, but it's rooted in reality and is a potential scenario for where Nvidia stock could be by 2030.

JPMorgan Chase is an advertising partner of Motley Fool Money. Jennifer Saibil has positions in Taiwan Semiconductor Manufacturing. The Motley Fool has positions in and recommends Advanced Micro Devices, Alphabet, Broadcom, JPMorgan Chase, Nvidia, and Taiwan Semiconductor Manufacturing. The Motley Fool has a disclosure policy.

Posted by Defense World Staff on Jul 18th, 2026

Aljian Capital Management LLC boosted its holdings in shares of NVIDIA Corporation (NASDAQ:NVDA – Free Report) by 1.6% in the first quarter, according to the company in its most recent Form 13F filing with the Securities & Exchange Commission. The firm owned 247,033 shares of the computer hardware maker’s stock after purchasing an additional 3,921 shares during the period. NVIDIA comprises 8.9% of Aljian Capital Management LLC’s portfolio, making the stock its 5th biggest holding. Aljian Capital Management LLC’s holdings in NVIDIA were worth $43,083,000 as of its most recent SEC filing.

A number of other institutional investors also recently added to or reduced their stakes in the stock. Lifetime Wealth Management P.C. acquired a new stake in shares of NVIDIA during the 4th quarter worth about $26,000. Longview Financial Advisors Inc. acquired a new position in NVIDIA in the first quarter valued at about $27,000. Longfellow Investment Management Co. LLC grew its stake in NVIDIA by 47.9% during the second quarter. Longfellow Investment Management Co. LLC now owns 207 shares of the computer hardware maker’s stock worth $33,000 after buying an additional 67 shares during the last quarter. Inspire Investing LLC acquired a new stake in shares of NVIDIA during the fourth quarter worth approximately $44,000. Finally, AlphaCentric Advisors LLC acquired a new stake in shares of NVIDIA during the fourth quarter worth approximately $45,000. 65.27% of the stock is owned by institutional investors and hedge funds.

NVIDIA Stock Down 2.2% NASDAQ:NVDA opened at $202.81 on Friday. The company has a quick ratio of 2.85, a current ratio of 3.44 and a debt-to-equity ratio of 0.04. NVIDIA Corporation has a 12-month low of $164.07 and a 12-month high of $236.54. The stock’s fifty day simple moving average is $209.63 and its 200-day simple moving average is $195.10. The firm has a market capitalization of $4.91 trillion, a P/E ratio of 31.06, a P/E/G ratio of 0.46 and a beta of 2.21.

NVIDIA (NASDAQ:NVDA – Get Free Report) last released its earnings results on Wednesday, May 20th. The computer hardware maker reported $1.87 earnings per share for the quarter, beating the consensus estimate of $1.76 by $0.11. The firm had revenue of $81.61 billion for the quarter, compared to analyst estimates of $78.42 billion. NVIDIA had a return on equity of 96.94% and a net margin of 62.97%.The company’s quarterly revenue was up 85.2% on a year-over-year basis. During the same quarter in the prior year, the firm posted $0.81 earnings per share. Equities research analysts expect that NVIDIA Corporation will post 8.81 earnings per share for the current year.

NVIDIA Increases Dividend The company also recently announced a quarterly dividend, which was paid on Friday, June 26th. Shareholders of record on Thursday, June 4th were issued a $0.25 dividend. This represents a $1.00 annualized dividend and a yield of 0.5%. This is a boost from NVIDIA’s previous quarterly dividend of $0.01. The ex-dividend date was Thursday, June 4th. NVIDIA’s dividend payout ratio (DPR) is 15.31%.

NVIDIA declared that its board has authorized a stock repurchase program on Wednesday, May 20th that permits the company to buyback $80.00 billion in shares. This buyback authorization permits the computer hardware maker to repurchase up to 1.5% of its shares through open market purchases. Shares buyback programs are usually a sign that the company’s board of directors believes its shares are undervalued.

Wall Street Analyst Weigh In Several research analysts have recently commented on the company. Rothschild & Co Redburn boosted their target price on NVIDIA from $280.00 to $300.00 and gave the stock a “buy” rating in a report on Tuesday, May 26th. Wall Street Zen cut NVIDIA from a “strong-buy” rating to a “buy” rating in a report on Saturday, July 4th. HSBC reiterated a “buy” rating and issued a $325.00 price objective (up from $295.00) on shares of NVIDIA in a research report on Tuesday, May 19th. Barclays reissued an “overweight” rating on shares of NVIDIA in a research note on Thursday, May 21st. Finally, Cantor Fitzgerald restated an “overweight” rating and issued a $350.00 target price on shares of NVIDIA in a research note on Thursday, May 21st. Two research analysts have rated the stock with a Strong Buy rating, forty-eight have issued a Buy rating and three have issued a Hold rating to the company. According to MarketBeat.com, NVIDIA presently has an average rating of “Moderate Buy” and a consensus price target of $304.26.

Get Our Latest Research Report on NVDA

NVIDIA News Summary Here are the key news stories impacting NVIDIA this week:

Positive Sentiment: NVIDIA expanded its AI footprint in Japan with new partnerships across robotics, manufacturing, and public-sector infrastructure, including a national AI infrastructure initiative and the launch of Cosmos 3 Edge and Nemotron-based local AI projects. These moves reinforce NVDA’s role as the core platform for physical AI and could support long-term demand. Japan Government, Industrial Leaders and NVIDIA Launch the World’s First National AI Infrastructure Positive Sentiment: Multiple analysts raised earnings estimates for NVIDIA, with KeyCorp and Erste Group boosting forecasts and maintaining bullish ratings/price targets. That suggests Wall Street still sees strong profit growth ahead. Positive Sentiment: TSMC reported strong AI-driven demand, which is a positive read-through for NVIDIA’s supply chain and ongoing chip demand. TSMC Just Announced Fantastic News for Nvidia Shareholders Neutral Sentiment: Apple briefly overtook NVIDIA as the world’s most valuable company, highlighting a rotation in mega-cap leadership and renewed investor doubts about how much AI upside is already priced into NVDA. Apple dethrones Nvidia as world’s most valuable company, ending the chipmaker’s long run at the top Neutral Sentiment: Several articles point to a broader semiconductor sell-off and “sell the news” behavior in AI and chip stocks, which appears to be pressuring NVDA along with peers rather than reflecting a company-specific setback. Why Nvidia stock is down around 2.5% on Thursday Negative Sentiment: Market commentary from Jim Cramer and other bearish notes on semiconductors suggest some investors are rotating out of chip stocks, adding near-term pressure to NVDA sentiment. Jim Cramer Says Semiconductor Stocks Are “Going Down.” Buy These 2 Dividend Stocks Instead Insiders Place Their Bets In other NVIDIA news, Director Stephen C. Neal sold 15,500 shares of the business’s stock in a transaction dated Wednesday, June 3rd. The stock was sold at an average price of $215.73, for a total value of $3,343,815.00. Following the completion of the transaction, the director directly owned 116,135 shares of the company’s stock, valued at approximately $25,053,803.55. The trade was a 11.77% decrease in their ownership of the stock. The transaction was disclosed in a legal filing with the Securities & Exchange Commission, which is accessible through the SEC website. Also, Director John Dabiri sold 625 shares of the stock in a transaction dated Wednesday, May 27th. The stock was sold at an average price of $214.00, for a total value of $133,750.00. Following the completion of the sale, the director owned 14,163 shares of the company’s stock, valued at $3,030,882. This trade represents a 4.23% decrease in their ownership of the stock. The SEC filing for this sale provides additional information. The transaction was executed under a pre-arranged Rule 10b5-1 trading plan. Over the last three months, insiders have sold 1,901,125 shares of company stock worth $410,583,015. Company insiders own 3.94% of the company’s stock.

NVIDIA Company Profile (Free Report)

NVIDIA Corporation, founded in 1993 and headquartered in Santa Clara, California, is a global technology company that designs and develops graphics processing units (GPUs) and system-on-chip (SoC) technologies. Co-founded by Jensen Huang, who serves as president and chief executive officer, along with Chris Malachowsky and Curtis Priem, NVIDIA has grown from a graphics-focused chipmaker into a broad provider of accelerated computing hardware and software for multiple industries.

The company’s product portfolio spans discrete GPUs for gaming and professional visualization (marketed under the GeForce and NVIDIA RTX lines), high-performance data center accelerators used for AI training and inference (including widely adopted platforms such as the A100 and H100 series), and Tegra SoCs for automotive and edge applications.

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I keep buying NVIDIA because every bearish argument I hear collapses the moment I open the earnings report. The fashionable one, that NVIDIA is either hoarding cash or bleeding out from China restrictions, is the loudest and the wrongest, and it keeps handing me chances to add to a position I plan to hold deep into retirement.

NVIDIA (NASDAQ:NVDA | NVDA Price Prediction) trades today at $207.40, and the analyst target sits at $301.62. My conviction comes from the numbers underneath that gap.

The China Narrative Bears Cannot Let Go Of In Q1 FY2027, NVIDIA shipped zero H20 compute products to China, down from $4.6 billion a year earlier. Revenue still came in at $81.615 billion, up 85.23% year over year, beating estimates by 3.16%. Data Center revenue alone was $75.246 billion, up 92%. Networking, the piece most people ignore, hit $14.800 billion, up 199%. Management then guided Q2 to $91.0 billion, again assuming no China Data Center compute revenue. A company that can absorb a multi-billion-dollar customer loss and still print those numbers does not have a demand problem.

The Cash Hoarding Claim Falls Apart NVIDIA returned roughly $20.0 billion to shareholders in a single quarter through repurchases and dividends. The board added $80.0 billion in fresh buyback authorization on May 18, 2026, on top of $38.5 billion already remaining under the prior plan. Management told analysts they plan to return roughly 50% of free cash flow to shareholders in 2027. The quarterly dividend was raised from $0.01 to $0.25. FY2026 returns totaled $41.1 billion. This is not a company sitting on its wallet.

Why NVIDIA And Not The Obvious Alternatives The efficiency numbers explain why I want NVIDIA reinvesting first and returning second. ROIC of 92.2%. Return on equity of 101.5%. Operating margin of 60.4%. Non-GAAP gross margin of 75.0%. Debt-to-equity of 0.073 and interest coverage above 500x. Free cash flow of $48.554 billion in one quarter.

Don't wait: the analyst who called NVIDIA in 2010 just revealed his top 10 AI stocks. See the full list FREE now.

Now compare the alternatives a bull on AI chips would reach for. Advanced Micro Devices (NASDAQ:AMD) trades at a trailing P/E of 179 and forward P/E of 76, with a return on equity of just 8.06%. Intel (NASDAQ:INTC) is worse on the fundamentals: trailing EPS of -0.6, return on equity of -2.91%, forward P/E of 118, and quarterly earnings down 71.7% year over year. NVIDIA trades at a forward P/E of 23. I am paying less for the future earnings of the category leader than I would for either challenger, and I get the ROIC gap on top.

The Real Risk China export restrictions could tighten further, and NVIDIA has $119.0 billion in supply-related commitments plus $30.0 billion in multi-year cloud service commitments locked in. If AI demand ever softens, that inventory becomes a problem quickly. Reliance on TSMC for manufacture, assembly, packaging, and testing sits underneath everything.

What Keeps The Buy Button Active Jensen Huang told analysts on the May 20, 2026 call that visibility into Blackwell and Rubin revenue reaches $1 trillion from 2025 through calendar 2027, with hyperscale CapEx forecast to exceed $1 trillion by 2027. OpenAI committed to 10 gigawatts of NVIDIA systems. Meta signed on for millions of Blackwell and Rubin GPUs on a multi-year basis. Huang called it “the largest infrastructure expansion in human history.”

Every quarter the bear thesis needs a fresh coat of paint. My conviction only needs the receipts.

Don't wait: the analyst who called NVIDIA in 2010 just revealed his top 10 AI stocks. See the full list FREE now.

Contact [email protected] for any questions or corrections.

Apple overtook Nvidia on Friday to become the world’s most valuable company, reshuffling the top ranks of tech heavyweights as investors reassess the outlook for artificial intelligence.

Apple was last valued at $4.88 trillion as its shares held steady, while Nvidia was roughly at $4.86 trillion, following a 3.5% decline.

The shift in the pecking order illustrates that investors are broadening their focus beyond the most obvious beneficiaries of the AI boom, such as Nvidia, which had been at the helm for nearly a year. 

The iPhone maker is reclaiming the top spot for the first time since April last year. REUTERS Apple is reclaiming the top spot for the first time since April last year.

“Apple was seen as a laggard in the AI race because it wasn’t spending to develop models, but now sentiment has changed,” said Toni Meadows, head of investment at BRI Wealth Management.

“Apple is less exposed to capex intensity and better positioned to monetize AI via services, ecosystem lock-in, and hardware upgrades. The re-rating reflects confidence in earnings durability rather than speculative AI upside.”

For a company that was often seen trailing in the AI race, the milestone reflects Apple’s efforts to establish itself more firmly among the sector’s leading players, and could shape how CEO Tim Cook’s final months at the helm are viewed.

Cook is preparing to cede his role to hardware veteran John Ternus in September.

Last month, the company rolled out a long-delayed overhaul of Siri, betting the upgraded assistant would help close the gap ‌with Big Tech rivals and new-age startups in the crucial AI race.

Apple CEO Tim Cookt with his successor John Ternus earlier this month. Getty Images Some analysts say Apple is sitting on an ​AI gold mine in the form of the personal data that lives on every iPhone.

The data could make Siri’s answers more useful and the assistant more capable.

The challenge is that such data is locked away in operating systems in the name of privacy and the company would have to find a way to unlock its value.

AI spending lifts new winners Nvidia became the first company in the world to surpass a $5 trillion market valuation in October, a landmark that propelled it into a rarefied territory that was far beyond the reach of its rivals.

Being superseded by Apple does not necessarily signal a lasting change in the companies’ relative standing. The chipmaker remains a major beneficiary of AI-related spending, and its graphics processors are powering much of the generative AI frenzy.

Nvidia could also reclaim the top spot if sentiment shifts.

Nvidia became the first company in the world to surpass a $5 trillion market valuation in October. CEo Jensen Huang, above. Getty Images Besides, Apple is in a delicate position itself, having raised prices to offset rising costs — a strategy that could hurt demand.

“I don’t see any meaningful distinction. Nvidia likely to be a significant participant in whatever happens going forward,” said Benjamin Hall, vice president, alpha research at Segal Marco Advisors.

However, the AI enthusiasm has spread to other corners of the semiconductor industry. The bigger winners this year have been memory chipmakers such as Micron, which crossed $1 trillion in market value in May as investors embraced the significance of memory chips in AI infrastructure.

South Korea’s SK Hynix also listed on the Nasdaq earlier this month, adding another player to the race for investor attention.

South Korea’s SK Hynix also listed on the Nasdaq earlier this month, adding another player to the race for investor attention. REUTERS “The new entrants to the market could spread out the focus away from the pure Magnificent Seven names into a wider number of names,” Hall said.

The eye-watering chips rally ran into turbulence in July as investors reassessed the sustainability of the artificial intelligence trade, knocking the Philadelphia SE Semiconductor index down almost 19% from its all-time highs.

Despite the steep fall, the index has performed better than Nvidia so far this year.

Nick Parker, Nvidia's incoming executive vice president of Worldwide Field Operations. Bloomberg/Getty Images Nvidia is ushering in a new era for its global sales organization.

In June, Jay Puri — the chip giant's head of worldwide field operations, and a billionaire who served in Nvidia CEO Jensen Huang's inner circle — told the company he is retiring after 21 years. He will transition to an advisory role.

To replace him, Nvidia looked outside its ranks — something of an unorthodox move for a C-Suite synonymous with long tenures, internal promotions, or executives coming in from acquisitions.

Nick Parker, a 26-year Microsoft veteran, joins Nvidia next month. Most recently, he served as executive vice president and chief business officer of Microsoft's worldwide sales and solutions organization.

Prior to his departure from Microsoft, Business Insider learned that Parker had just accepted a role leading its new $2.5 billion Microsoft Frontier Company, which connects 6,000 engineers and industry experts with its customers to help with AI. The role included a CEO title and a bigger head count than Parker's previous role, according to people familiar with the matter.

Per a securities filing, Parker's pay package at Nvidia includes $40 million in stock awards, a $5 million signing bonus, and a $1 million annual base salary.

The hire signals to Wall Street that Nvidia isn't "resting on its laurels" as the dominant AI chipmaker and is eyeing its next chapter of growth, said David Nicholson, chief technology advisor at The Futurum Group.

Puri steered Nvidia's global sales during its rise from a graphics card company into the world's dominant AI chip maker.

Parker inherits a different challenge. Rather than selling more AI chips, Nvidia needs to help customers successfully deploy AI — a job well suited to someone who spent 26 years selling enterprise technology at Microsoft.

Parker also brings deep relationships with governments, cloud providers, and other partners, said Brad Gastwirth, the global head of research and market intelligence at Circular Technology.

As Nvidia pushes deeper into business software, it faces a familiar challenge: helping large, highly regulated companies move from buying AI infrastructure to deploying it.

Earlier this year, Business Insider reported that Nvidia sales executives discussed how Bank of America struggled to deploy the chip giant's AI Factory software, highlighting common hurdles across industries.

Microsoft declined to comment. Nvidia did not respond to a request for comment from Business Insider.

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Geoff Weiss is a senior reporter on Business Insider’s tech team, where he writes about AI startups and Y Combinator, the intersection of AI and the media industry, and workplace dynamics within top AI labs and chip companies.Previously, Geoff was on the media desk, covering YouTube and Netflix, and themes like the intersection of Hollywood and the creator economy. His work on Netflix’s video podcasting ambitions and Mr Beast’s lessons for Hollywood won second and first prize, respectively, at the 2025 LA Press Club Awards.Prior to joining Business Insider, Geoff was the senior editor of Tubefilter and a staff writer at Entrepreneur. He graduated from New York University with a degree in English Literature.He can be reached at [email protected], on Signal @geoffweiss.25, and on LinkedIn. Have a tip? Use a personal email address and a nonwork device; here's our guide to sharing information securely.Selected stories:Nvidia crushed its quarter — and CEO Jensen Huang said in a leaked all-hands that 'the market did not appreciate it'Nvidia will foot the bill for Trump's new visa fees. Here's what CEO Jensen Huang told staff.Massive AI salaries and RTO are fueling a real estate boom in San Francisco: 'It's going to rain money'The AI talent wars are ricocheting across startups. Here's how they're competing with Big Tech.

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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.

Contact [email protected] for any questions or corrections.

HomeStock IdeasLong IdeasTech 

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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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.

News Summary:

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.

© 2026 NVIDIA Corporation. All rights reserved. NVIDIA, the NVIDIA logo, BlueField, DSX, Nemotron, NVIDIA Cosmos, NVIDIA Isaac, NVIDIA NeMo and NVIDIA Spectrum-X are trademarks and/or registered trademarks of NVIDIA Corporation in the U.S. and/or other countries. Other company and product names may be trademarks of the respective companies with which they are associated.

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...

News Summary:

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.

© 2026 NVIDIA Corporation. All rights reserved. NVIDIA, the NVIDIA logo, Nemotron, NVIDIA Cosmos, NVIDIA DGX, NVIDIA Isaac, NVIDIA Isaac Sim, NVIDIA Jetson, NVIDIA Omniverse and NVIDIA RTX are trademarks and/or registered trademarks of NVIDIA Corporation in the U.S. and other countries. Other company and product names may be trademarks of the respective companies with which they are associated. Features, pricing, availability and specifications are subject to change without notice.

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...

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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Contact [email protected] for any questions or corrections.

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.

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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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.

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.

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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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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.”