NVIDIA Q1 2026 Earnings Report

NVIDIA EPS Results

• Actual EPS: $0.81
• Consensus EPS: $0.87
• Beat/Miss: Missed by -$0.06
• One Year Ago EPS: $0.61

NVIDIA Revenue Results

• Actual Revenue: $44.06 billion
• Expected Revenue: $43.09 billion
• Beat/Miss: Beat by +$972.83 million
• YoY Revenue Growth: +69.20%

NVIDIA Announcement Details

• Quarter: Q1 2026
• Date: 5/28/2025
• Time: After Market Closes
• Conference Call Date: Wednesday, May 28, 2025
• Conference Call Time: 5:00PM ET

NVIDIA (NASDAQ:NVDA) is a leading technology company specializing in the design and development of graphics processing units (GPUs) and system-on-a-chip (SoC) products. Its offerings power a wide range of applications, from high-performance gaming and professional graphics to artificial intelligence (AI) and data center compute. The company’s expertise in parallel computing and GPU architecture has positioned it at the forefront of accelerating workloads across industries such as automotive, healthcare, finance, and scientific research.

The company’s flagship GeForce GPUs serve the gaming market, delivering advanced real-time ray tracing and AI-enhanced graphics. In the professional segment, NVIDIA’s RTX and Quadro series provide visualization and simulation capabilities for designers, engineers, and content creators. For data centers, its A100 and H100 GPUs, along with the CUDA software platform and DGX systems, enable AI model training, inference, and high-performance computing workloads. NVIDIA’s Tegra SoCs and DRIVE platforms are widely adopted in automotive applications, supporting infotainment, advanced driver-assistance systems, and autonomous vehicle development.

Founded in 1993 by Jensen Huang, Chris Malachowsky, and Curtis Priem, NVIDIA introduced the world’s first GPU in 1999 and has since driven industry innovation through key milestones such as the launch of the CUDA parallel computing architecture in 2006. The company expanded its reach through strategic acquisitions, including Mellanox Technologies in 2020, bolstering its networking capabilities and complementing its data center offerings with high-speed interconnect solutions.

Headquartered in Santa Clara, California, NVIDIA operates globally with research, development, and sales offices across North America, Europe, Asia-Pacific, and Latin America. Under the leadership of co-founder and CEO Jensen Huang, along with a senior management team that includes CFO Colette Kress, the company continues to advance GPU technology and software platforms to meet the evolving demands of graphics, compute, and AI-driven markets.

NVIDIA Q1 2026 Earnings Call Transcript

Key Takeaways

• Strong Q1 results: revenue of $44 billion up 69% year-over-year, with Data Center revenue reaching $39 billion (up 73%) and topping guidance in a challenging environment.
• U.S. export controls on the H20 GPU triggered a $4.5 billion inventory and purchase-obligation charge, prevented $2.5 billion in Q1 shipments, and will impose an ~$8 billion headwind in Q2, threatening a ~$50 billion China AI accelerator market.
• The new Blackwell architecture, including GB200 and NVL 72 racks, had the fastest ramp in company history, contributing nearly 70% of Data Center compute revenue, with hyperscalers deploying about 1,000 racks per week.
• Networking revenue surged 64% sequentially to $5 billion, led by over $1 billion in NVLink shipments and strong adoption of Spectrum X Ethernet, including new wins with Google Cloud and Meta.
• For Q2, NVIDIA expects $45 billion revenue ±2%, modest growth across platforms, non-GAAP gross margins of ~72%, and assumes the continued H20 export headwind while pursuing mid-70s margin targets.

Presentation

[Operator]

Good afternoon. My name is Sarah, and I will be your conference operator today. At this time, I would like to welcome everyone to NVIDIA's First Quarter Fiscal twenty twenty six Financial Results Conference Call.

[Operator]

All lines have been placed on mute to prevent any background noise. After the speakers' remarks, there will be a question and answer session. There you. Toshiya Hari, you may begin your conference.

[Toshiya Hari, VP of Investor Relations & Strategic Finance at NVIDIA]

Thank you. Good afternoon, everyone, and welcome to NVIDIA's conference call for the first quarter of fiscal twenty twenty six. With me today from NVIDIA are Jensen Huang, president and chief executive officer and Colette Kress, executive vice president and chief financial officer. I'd like to remind you that our call is being webcast live on NVIDIA's investor relations website. The webcast will be available for replay until the conference call to discuss our financial results the second quarter of fiscal twenty twenty six.

[Toshiya Hari, VP of Investor Relations & Strategic Finance at NVIDIA]

The content of today's call is NVIDIA's property. It can't be reproduced or transcribed without our prior written consent. During this call, we may make forward looking statements based on current expectations. These are subject to a number of significant risks and uncertainties, and our actual results may differ materially. For a discussion of factors that could affect our future financial results and business, please refer to the disclosure in today's earnings release, our most recent forms 10 k and 10 Q, and the reports that we may file on Form eight k with the Securities and Exchange Commission.

[Toshiya Hari, VP of Investor Relations & Strategic Finance at NVIDIA]

All our statements are made as of today, 05/28/2025, based on information currently available to us. Except as required by law, we assume no obligation to update any such statements. During this call, we will discuss non GAAP financial measures. You can find a reconciliation of these non GAAP financial measures to GAAP financial measures in our CFO commentary, which is posted on our website. With that, let me turn the call over to Colette.

[Colette Kress, EVP & CFO at NVIDIA]

Thank you, Toshiya. We delivered another strong quarter with revenue of 44,000,000,000, up 69% year over year, exceeding our outlook in what proved to be a challenging operating environment. Data center revenue of 39,000,000,000 grew 73% year on year. AR workloads have transitioned strongly to inference, and AI factory build outs are driving significant revenue. Our customers' commitments are firm.

[Colette Kress, EVP & CFO at NVIDIA]

On April 9, the US government issued new export controls on h 20, our data center GPU designed specifically for the China market. We sold h 20 with the approval of the previous administration. Although our h 20 has been in the market for over a year and does not have a market outside of China, the new export controls on h 20 did not provide a grace period to allow us to sell through our inventory. In Q1, we recognized $4,600,000,000 in H20 revenue, which occurred prior to April 9, but also recognized a 4,500,000,000.0 charge as we wrote down inventory and purchase obligations tied to orders we had received prior to April 9. We were unable to ship $2,500,000,000 in H20 revenue in the first quarter due to the new export controls.

[Colette Kress, EVP & CFO at NVIDIA]

The $4,500,000,000 charge was less than what we initially anticipated as we were able to reuse certain materials. We are still evaluating our limited options to supply data center compute products compliant with the US government's revised export control rules, Losing access to the China AI accelerator market, which we believe will grow to nearly 50,000,000,000, would have a material adverse impact on our business going forward and benefit our foreign competitors in China and worldwide. Our Blackwell ramp, the fastest in our company's history, drove a 73% year on year increase in data center revenue. Blackwell contributed nearly 70% of data center compute revenue in the quarter with a transition from Hopper nearly complete. The introduction of GB 200 NBL was a fundamental architectural change to enable data center scale workloads and to achieve the lowest cost per inference token.

[Colette Kress, EVP & CFO at NVIDIA]

While these systems are complex to build, we have seen a significant improvement in manufacturing yields, and rack shipments are moving to strong rates to end customers. GV 200 and VL racks are now generally available for model builders, enterprises, and sovereign customers to develop and deploy AI. On average, major hyperscalers are each deploying nearly 1,000 NVL 72 racks or 72,000 Blackwell GPUs per week and are on track to further ramp output this quarter. Microsoft, for example, has already deployed tens of thousands of Blackwell GPUs and is expected to ramp to hundreds of thousands of g b two hundreds with OpenAI as one of its key customers. Key learnings from the g b 200 ramp will allow for a smooth transition to the next phase of our product road map, Blackwell Ultra.

[Colette Kress, EVP & CFO at NVIDIA]

Sampling of GB 300 systems began earlier this month at the major CSPs, and we expect production shipments to commerce later this quarter. GB 300 will leverage the same architecture, same physical footprint, and the same electrical and mechanical specifications as GB 200. The GB 300 drop in design will allow CSPs to seamlessly transition their systems and manufacturing used for g b 200 while maintaining high yields. B 300 GPUs with 50% more HBM will deliver another 50% increase in dense f p four inference compute performance compared to the b 200. We remain committed to our annual product cadence with our road map extending through 2028 tightly aligned with the multiple year planning cycles of our customers.

[Colette Kress, EVP & CFO at NVIDIA]

We are witnessing a sharp jump in inference demand. OpenAI, Microsoft, and Google are seeing a step function leap in token generation. Microsoft processed over 100,000,000,000,000 tokens in q one, a fivefold increase on a year over year basis. This exponential growth in Azure OpenAI is representative of strong demand for Azure AI Foundry as well as other AI services across Microsoft's platform. Inference serving startups are now serving models using b 200, tripling their token generation rate and corresponding revenues for high value reasoning models such as DeepSegaR one as reported

[Colette Kress, EVP & CFO at NVIDIA]

NVIDIA. NMO on Blackwell NVL 72 turbo charges AI inference throughput by 30 x for the new reasoning models sweeping the industry. Developer engagements increased with adoption ranging from LLM providers such as Perplexity to financial services institutions such as Capital One who reduced agentic chatbot latency by five x with Dynamo. In the latest MLPerf inference results, we submitted our first results using GB 200 and BL 72, delivering up to 30x higher inference throughput compared to our eight GPU h 200 submission on the challenging LAMA 3.1 benchmark. This feat was achieved through a combination of tripling the performance per GPU as well as nine x more GPUs, all connected on a single NVLink domain.

[Colette Kress, EVP & CFO at NVIDIA]

And while Blackwell is still early in its life cycle, software optimizations have already improved its performance by 1.5 x in the last month alone. We expect to continue improving the performance of Blackwell through its operational life as we have done with Hopper and Amper. For example, we increased the inference performance of Hopper by four times over two years. This is the benefit of NVIDIA's programmable CUDA architecture and rich ecosystem. The pace and scale of AI factory deployments are accelerating with nearly 100 NVIDIA powered AI factories in flight this quarter, a twofold increase year over year with the average number of GPUs powering each factory also doubling in the same period.

[Colette Kress, EVP & CFO at NVIDIA]

And more AI factory projects are starting across industries and geographies. NVIDIA's full stack architecture is underpinning AI factory deployments as industry leaders like AT and T, BYD, Capital One, Foxconn, MediaTek, and Telenor are strategically vital sovereign clouds like those recently announced in Saudi Arabia, Taiwan, and The UAE. We have a line of sight to projects requiring tens of gigawatts of NVIDIA AI infrastructure in the not too distant future. The transition from gen generative to agentic AI, AI capable of perceiving, reasoning, planning, and acting will transform every industry, every company, and country. We envision AI agents as a new digital workforce capable of handling tasks ranging from customer service to complex decision making processes.

[Colette Kress, EVP & CFO at NVIDIA]

We introduced the LAMA Nemotron family of open reasoning models designed to supercharge agentic AI platforms for enterprises. Built on the LAMA architecture, these models are available as NIMS or NVIDIA inference microservices with multiple sizes to meet diverse deployment needs. Our post training enhancements have yield a 20% accuracy boost and a five x increase in inference speed. Leading platform companies, including Accenture, Cadence, Deloitte, and Microsoft, are transforming work with our reasoning models. NVIDIA, NEMO, microservices are generally available across industries or are being leveraged by leading enterprises to build, optimize, and scale AI applications.

[Colette Kress, EVP & CFO at NVIDIA]

With NEMO, Cisco increased model accuracy by 40% and improved response time by 10 x in its code assistant. NASDAQ realized a 30% improvement in accuracy and response time in its AI platform's search capabilities. And Shell's custom LLM achieved a 30% increase in accuracy when trained with NVIDIA NEMO. NEMO's parallelism techniques accelerated model training time by 20% when compared to other frameworks. We also announced a partnership with Yum Brands, the world's largest restaurant company, to bring NVIDIA AI to 500 of its restaurants this year and expanding to 61,000 restaurants over time to streamline order taking, optimize operations, and enhance service across its restaurants.

[Colette Kress, EVP & CFO at NVIDIA]

For AI powered cybersecurity, leading companies like Checkpoint, Cloudstrike, and Palo Alto Networks are using NVIDIA's AI security and software stack to build, optimize, and secure agentic workflows with Cloudstrike realizing two x faster detection triage with 50% less compute cost. Moving to networking. Sequential growth in networking resumed in q one with revenue up 64% quarter over quarter to 5,000,000,000. Our customers continue to leverage our platform to efficiently scale up and scale out AI factory workloads. We created the world's fastest switch, NVLink.

[Colette Kress, EVP & CFO at NVIDIA]

For scale up, our NVLink compute fabric in its fifth generation offers 14 x the bandwidth of PCIe Gen five. NVLink 72 carries 130 terabytes per second of bandwidth in a single rack, equivalent to the entirety of the world's peak Internet traffic. NVLink is a new growth vector and is off to a great start with q one shipments exceeding a billion dollars. At Computex, we announced NVLink Fusion. Hyperscale customers can now build semi custom CCUs and accelerators that connect directly to the NVIDIA platform with NVLink.

[Colette Kress, EVP & CFO at NVIDIA]

We are now enabling key partners, including ASIC providers such as MediaTek, Marvell, Alchip Technologies, and Astero Labs, as well as CPU suppliers such as Fuzitsu and Qualcomm to leverage NVLink Fusion to connect our respective ecosystems. For scale out, our enhanced Ethernet offerings deliver the highest throughput, low latency networking for AI. Spectrum X posted strong sequential and year on year growth and is now annualizing over 8,000,000,000 in revenue. Adoption is widespread across major CSPs and consumer Internet companies, including CoreWi, Microsoft Azure, Oracle Cloud, and xAI. This quarter, we added Google Cloud and Meta to the growing list of Spectrum X customers.

[Colette Kress, EVP & CFO at NVIDIA]

We introduced Spectrum X and Quantum X silicon photonics switches featuring the world's most advanced co package optics. These platforms will enable next level AI factory scaling to millions of GPUs through the increasingly power efficiency by 3.5 x and network resiliency by 10 x while accelerating customer time to market by 1.3 x. Transitioning to a quick summary of our revenue by geography. China as a percentage of our data center revenue was slightly below our expectations and down sequentially due to h '20 export licensing controls. For q two, we expect a meaningful decrease in China data center revenue.

[Colette Kress, EVP & CFO at NVIDIA]

As a reminder, while Singapore represented nearly 20 of our q one build revenue as many of our large customers use Singapore for centralized invoicing, our products are almost always shipped elsewhere. Note that over 99% of h one hundred, h two hundred, and Blackwell data center compute revenue billed to Singapore was for orders from US based customers. Moving to gaming and AI PCs. Gaming revenue was a record 3,800,000,000.0, increasing 48% sequentially and 42% year on year. Strong adoption by gamers, creatives, and AI enthusiasts have made Blackwell our fastest ramp ever.

[Colette Kress, EVP & CFO at NVIDIA]

Against a backdrop of robust demand, we greatly improved our supply and availability in q one and expect to continue these efforts in q two. AI is transforming PC and creator and gamers. With a 100,000,000 user installed base, GeForce represents the largest footprint for PC developers. This quarter, we added to our AI PC laptop offerings, including models capable of running Microsoft's Copilot Plus. This past quarter, we brought Blackwell Architecture to mainstream gaming with its launch of GeForce RTX fifty sixty and fifty sixty Ti starting at just $299.

[Colette Kress, EVP & CFO at NVIDIA]

The RTX fifty sixty also debuted in laptops starting at $1,099. These systems that double the frame rate and slash latency. These GeForce RTX fifty sixty and fifty sixty Ti desktop GPUs and laptops are now available. In console gaming, the recently unveiled Nintendo Switch two leverages NVIDIA's neural rendering and AI technologies, including next generation custom RTX GPUs with DLSS technology to deliver a giant leap in gaming performance to millions of players worldwide. Nintendo has shipped over 150,000,000 Switch consoles to date, making it one of the most successful gaming systems in history.

[Colette Kress, EVP & CFO at NVIDIA]

Moving to Pro Visualization. Revenue of $5.00 $9,000,000 was flat sequentially and up 19% year on year. Tariff related uncertainty temporarily impacted q one systems. And demand for our AI workstations is strong, and we expect sequential revenue growth to resume in q two. NVIDIA DGX Spark and Station revolutionize personal computing by putting the power of an AI supercomputer in a desktop form factor.

[Colette Kress, EVP & CFO at NVIDIA]

DGX Spark delivers up to one petaflop of AI compute while DGX Station offers an incredible 20 pair of petaflops and is powered by the GB 300 superchip. DGX Spark will be available in calendar q three and DGX Station later this year. We have deepened Omniverse's integration and adoption into some of the world's leading software platforms, including Databricks, SAP, and Schneider Electric. New Omniverse blueprints such as MEGA for at scale robotic fleet management are being leveraged in Keon Group, Pegatron, Accenture, and other leading companies to enhance industrial operations. At ConfuTech, we showcased Omniverse's great traction with technology manufacturing leaders, including TSMC, Quanta, Foxconn, Pegatron.

[Colette Kress, EVP & CFO at NVIDIA]

Using Omniverse, TSMC saves months in work by designing fabs virtually. Foxconn accelerates thermal simulations by 150 x, and PEGATROM reduced assembly line defects rates by 67%. Lastly, with our automotive group, revenue was 567,000,000, down 1% sequentially, but up 72% year on year. Year on year growth was driven by the ramp of self driving across a number of customers and robust end demand for NEVs. We are partnering with GM to build the next gen vehicles, factories, and robots using NVIDIA AI, simulation, and accelerated computing.

[Colette Kress, EVP & CFO at NVIDIA]

And we are now in production with our full stack solution for Mercedes Benz, starting with the new CLA, hitting roads in the next few months. We announced Isaac, Groot, and One, the world's first open, fully customizable foundation model for humanoid robots, enabling generalized reasoning and skill development. We also launched new open NVIDIA Cosmo World Foundation models. Leading companies include OneX, Agility Robots, Robotics, Figure AI, Uber, and Wabi. We've begun integrating Cosmos into their operations for synthetic data generation, while Agility Robotics, Boston Dynamics, and Xpenn Robotics are harnessing Isaac simulation to advance their humanoid efforts.

[Colette Kress, EVP & CFO at NVIDIA]

GE Healthcare is using the new NVIDIA ISSIC platform for health care simulation built on NVIDIA Omniverse and using NVIDIA Cosmos. The platform speeds development of robotic imaging and surgery systems. The era of robotics is here. Billions of robots, hundreds of millions of autonomous vehicles, and hundreds of thousands of robotic factories and warehouses will be developed. Alright.

[Colette Kress, EVP & CFO at NVIDIA]

Moving to the rest of the p and l. GAAP gross margins and non GAAP gross margins were 60.561%, respectively. Excluding the 4,500,000,000.0 charge, Q1 non GAAP gross margins would have been 71.3%, slightly below above our outlook at the beginning of the quarter. Sequentially, GAAP operating expenses were up seven percent and non GAAP operating expenses were up 6%, reflecting higher compensation and employee growth. Our investments include expanding our infrastructure capabilities and AI solutions, and we plan to grow these investments throughout the fiscal year.

[Colette Kress, EVP & CFO at NVIDIA]

In Q1, we returned a record $14,300,000,000 to shareholders in the form of share repurchases and cash dividends. Our capital return program continues to be a key element of our capital allocation strategy. Let me turn to the outlook for the second quarter. Total revenue is expected to be $45,000,000,000 plus or minus 2%. We expect modest sequential growth across all of our platforms.

[Colette Kress, EVP & CFO at NVIDIA]

In data center, we anticipate the continued ramp of Blackwell to be partially offset by a decline in China revenue. Note, our outlook reflects a loss in H20 revenue of approximately $8,000,000,000 for the second quarter. GAAP and non GAAP gross margins are expected to be 71.872%, respectively, plus or minus 50 basis points. We expect better Blackwell profitability to drive modest sequential improvement in gross margins. We are continuing to work towards achieving gross margins in the mid-70s range late this year.

[Colette Kress, EVP & CFO at NVIDIA]

GAAP and non GAAP operating expenses are expected to be approximately $5,700,000,000 and $4,000,000,000 respectively, and we continue to expect full year fiscal year 'twenty six operating expense growth to be in the mid-thirty percent range. GAAP and non GAAP other income and expenses are expected to be an income of approximately $450,000,000 excluding gains and losses from nonmarketable and publicly held equity securities. GAAP and non GAAP tax rates are expected to be 16.5%, plus or minus 1%, excluding any discrete items. Further financial details are included in the CFO commentary and other information available on our IR website, including a new financially information AI agent. Let me highlight upcoming events for the financial community.

[Colette Kress, EVP & CFO at NVIDIA]

We will be at the BofA Global Technology Conference in San Francisco on June 4, the Rosenblatt Virtual AI Summit and Nasdaq Investor Conference in London on June 10, and GTC Paris at Viva Tech on June 11 in Paris. We look forward to seeing you at these events. Our earnings call to discuss the results of our second quarter of fiscal twenty twenty six is scheduled for August 27. Well, now let me turn it over to Jensen to make some remarks.

[Jensen Huang, Founder, President and CEO at NVIDIA]

Thanks, Colette. We've had a busy and productive year. Let me share my perspective on some topics we're frequently asked. On export control, China is one of the world's largest AI markets and a springboard to global success. With half of the world's AI researchers based there, the platform that wins China is positioned to lead globally.

[Jensen Huang, Founder, President and CEO at NVIDIA]

Today, however, the $50,000,000,000 China market is effectively closed to US industry. The h twenty export ban ended our Hopper data center business in China. We cannot reduce Hopper further to comply. As a result, we are taking a multibillion dollar write off on inventory that cannot be sold or repurposed. We are exploring limited ways to compete, but Hopper is no longer an option.

[Jensen Huang, Founder, President and CEO at NVIDIA]

China's AI moves on with or without US chips. It has to compute to train and deploy advanced models. The question is not whether China will have AI. It already does. The question is whether one of the world's largest AI markets will run on American platforms.

[Jensen Huang, Founder, President and CEO at NVIDIA]

Shielding Chinese chipmakers from US competition only strengthens them abroad and weakens America's position. Export restrictions have spurred China's innovation and scale. The AI race is not just about chips. It's about which stack the world runs on. As that stack grows to include six g and quantum, US global infrastructure leadership is at stake.

[Jensen Huang, Founder, President and CEO at NVIDIA]

The US has based its policy on the assumption that China cannot make AI chips. That assumption was always questionable, and now it's clearly wrong. China has enormous manufacturing capability. In the end, the platform that wins the AI developers win AI wins AI. Export controls should strengthen US platforms, not drive half of the world's AI talent to rivals.

[Jensen Huang, Founder, President and CEO at NVIDIA]

On DeepSeek. DeepSeek and QN from China are among the most among the best open source AI models. Released freely, they've gained traction across The US, Europe, and beyond. DeepSeek r one, like ChatGPT, introduced reasoning AI that produces better answers the longer it thinks. Reasoning AI enables step by step problem solving, planning, and tool use, turning models into intelligent agents.

[Jensen Huang, Founder, President and CEO at NVIDIA]

Reasoning is compute intensive, requires hundreds to thousands more thousands of times more tokens per task than previous one shot inference. Reasoning models are driving a step function surge in inference demand. AI scaling laws remain firmly intact, not only for training, but now inference too requires massive scale compute. DeepSeq also underscores the strategic value of open source AI. When popular models are trained and optimized on US platforms, it drives usage, feedback, and continuous improvement, reinforcing American leadership across the stack.

[Jensen Huang, Founder, President and CEO at NVIDIA]

US platforms must must remain the preferred platform for open source AI. That means supporting collaboration with top developers globally, including in China. America wins when models like DeepSeek and QN runs best on American infrastructure. Regarding onshore manufacturing, president Trump has outlined a bold vision to reshor advanced manufacturing, create jobs, and strengthen national security. Future plants will be highly computerized in robotics.

[Jensen Huang, Founder, President and CEO at NVIDIA]

We share this vision. TSMC is building six fabs and two advanced packaging plants in Arizona to make chips for NVIDIA. Process qualification is underway with volume production expected by year end. Spill and Amcor are also investing in Arizona, constructing packaging, assembly, and test facilities. In Houston, we're partnering with Foxconn to construct a million square foot factory to build AI supercomputers.

[Jensen Huang, Founder, President and CEO at NVIDIA]

Wistron is building a similar plant in Fort Worth, Texas. To encourage and support these investments, we've made substantial long term purchase commitments, a deep investment in America's AI manufacturing future. Our goal from chip to supercomputer built in America within a year. Each g b 200 MB LINK 72 racks contains 1,200,000 components and weighs nearly two tons. No one has produced supercomputers on this scale.

[Jensen Huang, Founder, President and CEO at NVIDIA]

Our partners are doing an extraordinary job. On AI diffusion rule, president Trump rescinded the AI diffusion rule, calling it counterproductive, and proposed a new policy to promote US AI tech with trusted partners. On his Middle East tour, he announced historic investments. I was honored to join him in announcing a 500 megawatt AI infrastructure project in Saudi Arabia and a five gigawatt AI campus in The UAE. President Trump wants US tech to lead.

[Jensen Huang, Founder, President and CEO at NVIDIA]

The deals he announced are wins for America, creating jobs, advancing infrastructure, generating tax revenue, and reducing The US trade deficit. The US will always be NVIDIA's largest market and home to the largest installed base of our infrastructure. Every nation now sees AI as core to the next industrial revolution, a new industry that produces intelligence and essential infrastructure for every economy. Countries are racing to build national AI platforms to elevate their digital capabilities. At Computex, we announced Taiwan's First AI factory in partnership with Foxconn and the Taiwan government.

[Jensen Huang, Founder, President and CEO at NVIDIA]

Last week, I was in Sweden to launch its first national AI infrastructure. Japan, Korea, India, Canada, France, The UK, Germany, Italy, Spain, and more are now building national AI factories to empower startups, industries, and societies. Sovereign AI is a new growth engine for NVIDIA. Toshiya, back to you. Thank you.

[Toshiya Hari, VP of Investor Relations & Strategic Finance at NVIDIA]

Operator, we will now open the call for questions. Would you please poll for questions?

[Operator]

Thank you. At this time, I would like to remind everyone, in order to ask a question, press star Your first question comes from the line of Joe Moore with Morgan Stanley. Your line is open.

[Joseph Moore, Managing Director at Morgan Stanley]

Great. Thank you. You guys have talked about this scaling up of inference around reasoning models for at least a year now. And we've really seen that come to fruition as you talked about. We've heard it from your customers.

[Joseph Moore, Managing Director at Morgan Stanley]

Can you give us a sense for how much of that demand you're able to serve? And give us a sense for maybe how big the inference business is for you guys? And do we need full on NBL 72 rack scale solutions for reasoning inference going forward?

[Jensen Huang, Founder, President and CEO at NVIDIA]

Well, we would like to serve all of it, and and I think we're on track to serve most of it. Grace Blackwell NVLink 72 is the ideal engine today, the ideal computer thinking machine, if you will, for reasoning AI. There's a couple of reasons for that. The first reason is that the token generation amount, the number of tokens reasoning goes through, is a hundred, a thousand times more than a one shot chatbot. You know, it's essentially thinking to itself, breaking down a problem step by step.

[Jensen Huang, Founder, President and CEO at NVIDIA]

It might be planning multiple paths to an answer. It's could be using tools, reading PDFs, reading web pages, watching videos, and and then producing a a result, an answer. The the longer it thinks, the better the answer, the smarter the answer is. And so what we would like to do, and the reason why Grace Blackwell was designed to give such a giant step up in inference performance is so that you could do all this and still get a response as quickly as possible. Compared to Hopper, Grace Blackwell is some 40 times higher speed and throughput compared.

[Jensen Huang, Founder, President and CEO at NVIDIA]

And so, this is gonna be a huge, huge benefit in driving down the cost while improving the quality of response with excellent quality of service at the same time. So that's that's the fundamental reason. That was the core driving reason for Grace Blackwell and VLink seventy two. Of course of course, in order to do that, we had to reinvent, literally redesign the entire way that these supercomputers are built. And and, but now we're in full production.

[Jensen Huang, Founder, President and CEO at NVIDIA]

It is it's, it's going to be exciting. It's gonna be incredibly exciting.

[Operator]

The next question comes from Vivek Arya with Bank of America Securities. Your line is open.

[Vivek Arya, Managing Director at Bank of America]

Thanks for the question. Just a clarification for Colette first. So on the China impact, I think previously, it was mentioned that at about $15,000,000,000 So you had the 8,000,000,000 in Q2. So is there still some, left as a headwind for the remaining quarters? Just call it, how to model, that?

[Vivek Arya, Managing Director at Bank of America]

And then question, Jensen, for you. Back at GTC, you had outlined a path towards almost $1,000,000,000,000 of AI spending over the next few years. Where are we in that build out? And do you think it's going to be uniform that you will see every spender, whether it's CSP, sovereigns, enterprises or or build out? Should we expect some periods of digestion in between?

[Vivek Arya, Managing Director at Bank of America]

Just what are your customer discussions telling you about how to model growth for next year?

[Colette Kress, EVP & CFO at NVIDIA]

Yes, Vivek. Thanks so much for the question regarding h twenty. Yes. We recognized 4.6 h 20 in q one. We were unable to ship 2,500,000,000.0, so the total for q one should have been 7,000,000,000.

[Colette Kress, EVP & CFO at NVIDIA]

When we look at our q two, our q two is gonna be meaningfully down in terms of China data center revenue, and we had highlighted in terms of the amount of orders that we had planned for h twenty in q two, and that was 8,000,000,000. Now going forward, we did have other orders going forward that we will not be able to fulfill. That is what was incorporated, therefore, in the amount that we wrote down of the 4.6 $4,500,000,000. That write down was about inventory and purchase commitments, and our purchase commitments were about what we expected regarding the orders that we had received. Going forward, though, it's a bigger issue regarding the amount of the market that we will not be able to serve.

[Colette Kress, EVP & CFO at NVIDIA]

We assess that TAM to be close to about 50,000,000,000 in the future as we don't have a product to enable for the China.

[Jensen Huang, Founder, President and CEO at NVIDIA]

In fact, the the the probably the best way to think through it is that AI is several things. You know? Of course, we know that AI is this incredible technology that's going to transform, every industry, you know, from, of course, the way we do software to to, health care and financial services to, you know, retail to to, I guess, every industry, transportation, manufacturing. And and we're at the beginning of that. But maybe maybe another way to think about that is is where do we need intelligence?

[Jensen Huang, Founder, President and CEO at NVIDIA]

Where do we need digital intelligence? And and it's in every country. It's in every industry. And we know we know because of that, we recognize that AI is also an infrastructure. It's a it's a way of developing a techno delivering a technology that requires factories.

[Jensen Huang, Founder, President and CEO at NVIDIA]

And these factories produce tokens, and they, as I mentioned, are important to every single industry in every single country. And so on that basis, we're really at the very beginning of it because the adoption of this technology is really kind of in its early early stages. Now we've reached an extraordinary milestone with AIs that are reasoning, are thinking, what people call inference time scaling. You know, of course, it created a a whole new we've entered an era where where inference is going to be a significant part of the compute workload. But any anyhow, you're it's gonna be a new infrastructure, and we're building it out in the cloud.

[Jensen Huang, Founder, President and CEO at NVIDIA]

The United States is is really the the the early starter and, available in US clouds. And this is our largest market, our largest installed base, and we can continue to see that happening. But beyond that, we're gonna have to we're gonna see AI go into enterprise, which is on prem because so much of the data is still on prem. Access control is really important. It's really hard to to move all of every company's data into the cloud, and so we're gonna move AI into the enterprise.

[Jensen Huang, Founder, President and CEO at NVIDIA]

And you you saw that we announced a couple of really exciting new products. Our RTX Pro enterprise AI server that runs everything enterprise and AI, our our DGX Spark and DGX Station, which is designed for developers who wanna work on prem. And so enterprise AI is is just taking off. Telcos. Today, a lot of the telco infrastructure will be in the future software defined and built on AI.

[Jensen Huang, Founder, President and CEO at NVIDIA]

And so six g is gonna be built on AI, and that infrastructure needs to be built out. And as I said, it's very, very early stages. And then, of course, every factory today that makes things will have an AI factory that sits with it. And, the AI factory is going to be drive creating AI and and operating AI for the factory itself, but also to power the products and the things that are made by the factory. So it's very clear that every car company will have AI factories, and, very soon, there'll be robotics companies, robot companies, and those companies will be, also building AIs to, drive the robots.

[Jensen Huang, Founder, President and CEO at NVIDIA]

And so we're at the beginning of all of this build out.

[Operator]

The next question comes from CJ Muse with Cantor Fitzgerald. Your line is open.

[CJ Muse, Senior Managing Director at Cantor Fitzgerald]

Yes, good afternoon. Thank you for taking the question. There have been many large GPU cluster investment announcements in the last month and you alluded to a few of them with Saudi Arabia, UAE and then also we've heard from Oracle and XAI just to name a few. So my question, are there other that have yet to be announced of the same kind of scale and magnitude? And perhaps more importantly, how are these orders impacting your lead times for Blackwell and your current visibility sitting here today, you know, almost halfway through 2025?

[Jensen Huang, Founder, President and CEO at NVIDIA]

Well, we have more orders today than we did at the at the last time I spoke about orders at GTC. However, we're also increasing our supply chain and building out our supply chain. They're doing a fantastic job. We're building it here onshore in United States, but we're gonna keep our supply chain, quite busy for several many more years coming. And, with respect to with respect to further announcements, I'm gonna be on the road next week through Europe.

[Jensen Huang, Founder, President and CEO at NVIDIA]

And, it's it's, just about every country needs to build out AI infrastructure, and their they're, team AI factories, being planned. We're I think I think, in the remarks, Colette mentioned there's some a a hundred AI factories being built. There's a whole bunch that haven't been announced. And I think the important concept here, which makes it makes it, you know, easier to understand, is that like like other technologies that impact literally every single industry, of course, electricity was one, and it became infrastructure. Of course, the information infrastructure, which which we now know as the Internet, affects every single industry, every country, every society.

[Jensen Huang, Founder, President and CEO at NVIDIA]

Intelligence is surely one of those things. I don't know any company, industry, country who who thinks that intelligence is optional. It's essential infrastructure. And so we've now digitalized intelligence. And and so I I think we're we're clearly in the beginning of a of the the build out of this infrastructure, and every every country will have it.

[Jensen Huang, Founder, President and CEO at NVIDIA]

I'm certain of that. Every industry will use it. That, I'm certain of. And what's unique about this infrastructure is that it needs factories. You know, it's a little bit like like the like the energy infrastructure, electricity.

[Jensen Huang, Founder, President and CEO at NVIDIA]

It needs factories. We need factories to produce this intelligence, and the intelligence is getting more sophisticated. We were talking about earlier that we had a huge breakthrough in the last couple of years with reasoning AI, and and now there are agents that reason. And there's super agents that use a whole bunch of tools, and then there's clusters of super agents where agents are working with agents, solving problems. And so you could just imagine compared to one shot chatbots and the agents that are now using AI built on these large language models, how much more compute intensive they they really need to be and are.

[Jensen Huang, Founder, President and CEO at NVIDIA]

And so so I I think we're in the beginning of the build out, and there there should be there should be many, many more announcements in the future.

[Operator]

Your next question excuse me. Your next question comes from Ben Reitzis with Melius. Your line is open.

[Ben Reitzes, Managing Director – Head of Technology Research at Melius Research LLC]

Yes. Hi. Thanks for the question. I wanted to ask first to Colette, just a little clarification around the guidance and maybe putting it in a different way. The $8,000,000,000 for H20 just seems like it's roughly $3,000,000,000 more than most people thought with regard to what you'd be foregoing in the second quarter.

[Ben Reitzes, Managing Director – Head of Technology Research at Melius Research LLC]

So that would mean that with regard to your guidance, the rest of the business in order to hit $45,000,000,000 is doing 2,000,000,000 to $3,000,000,000 or so better. So I was wondering if that math made sense to you. And then in terms of the guidance that would imply the non China business is doing a bit better than the Street expected. So wondering what the primary driver was there in your view? And then the second part of my question, Jensen, I know you guide one quarter at a time.

[Ben Reitzes, Managing Director – Head of Technology Research at Melius Research LLC]

But with regard to the AI diffusion rule being lifted and this momentum was sovereign, there's been times in your history where you guys have said on calls like this where you have more conviction in sequential growth throughout the year, etcetera. And given the unleashing of demand with AI diffusion being revoked and the supply chain increasing, does the environment give you more conviction in sequential growth as we go throughout the year? So first one for Colette and then next one for Jensen. Thanks so much.

[Colette Kress, EVP & CFO at NVIDIA]

Thanks, Ben, for the question. When we look at our Q2 guidance and our commentary that we provided that had the export controls not occurred, we would have had orders of about 8,000,000,000 for H20. That's correct. That was a possibility for what we would have had in our outlook for this quarter in q two. So what we also have talked about here is the growth that we've seen in Blackwell, Blackwell across many of our customers as well as the growth that we continue to have in terms of supply that we need for our customers.

[Colette Kress, EVP & CFO at NVIDIA]

So putting those together, that's where we came through with the guidance that we provided. I'm gonna turn the rest over to Jensen to see how he wants to do this.

[Jensen Huang, Founder, President and CEO at NVIDIA]

Thanks. Thanks, Ben. I would say compared to the beginning of the year, compared to GTC time frame, there are four positive surprises. The first positive surprise is the step function demand increase of reasoning AI.

[Jensen Huang, Founder, President and CEO at NVIDIA]

I think it is fairly clear now that AI is going through an exponential growth, and reasoning AI really busted through. Concerns about about hallucination or its ability to to really solve problems. And I think I think a lot of people are are crossing that barrier and realizing how incredible incredibly effective agentic AI is and reasoning AI is. So number one is inference reasoning, alright, and, the the exponential growth there, demand growth. The second one, you you mentioned AI diffusion.

[Jensen Huang, Founder, President and CEO at NVIDIA]

It it's really terrific to see, that the AI diffusion rule was rescinded. President Trump wants America to win, and and, he also realizes that that, we're not the only, country in the race, and, he wants he wants, United States to win and recognizes that we have to get the American stack out to the world and have the world build on top of American stacks, instead of alternatives. And so, AI diffusion, hap happened. The res the rescinding of it happened at almost precisely the time that the countries around the world are awakening the importance of AI as an infrastructure, not just as a technology of great curiosity, and great importance, but infrastructure for their industries and startups and society. Just as they had to build out infrastructure for electricity and Internet, you gotta build out infrastructure for AI.

[Jensen Huang, Founder, President and CEO at NVIDIA]

I think that that's an awakening, and that creates a lot of opportunity. The third is enterprise AI. Agents work, and agents are doing these agents are really quite successful. Much more than generative AI, agentic AI is game changing. You they you know, agents can understand ambiguous and rather rather implicit instructions and able to problem solve and use tools and have memory and and so on.

[Jensen Huang, Founder, President and CEO at NVIDIA]

And and so I think this is enterprise AI is ready ready to take off, and and it's taken us a few years to build a computing system that that is able to integrate, run run enterprise AI stacks, run enterprise IT stacks, but add AI to it. And this is the, RTX Pro enterprise server that we announced at Computex, just last week. And just about every major IT company has joined us, and I'm super excited about that. And so computing is one stat one part of it. But remember, enterprise IT is really three three pillars.

[Jensen Huang, Founder, President and CEO at NVIDIA]

It's compute, storage, and networking, and we've now put all three of them together for finally, and we're going to market with that. And then lastly, industrial AI. Remember, one of the implications of of the the the world reordering, if you will, is is, regions onshoring manufacturing and building plants everywhere. In addition to AI factories, of course, there there are new electronics manufacturing, chip manufacturing, being built around the world. And all of these new plants and these new factories are creating exactly the right time when when Omniverse and AI and all the work that we're doing we're doing with robotics is is emerging.

[Jensen Huang, Founder, President and CEO at NVIDIA]

And so so this this fourth pillar is is quite important. Every factory will have an AI factory associated with it. And and in order to create these physical AI systems, you really have to train a a vast amount of data. So so back to more data, more training, more AIs to be created, more computers. And so, these four these four drivers are are really kicking into turbocharge.

[Operator]

Your next question comes from Timothy Arcuri with UBS. Your line is open.

[Timothy Arcuri, Managing Director at UBS Group]

Thanks a lot. Jensen, I wanted to ask about China. It sounds like the July guidance assumes there's no SKU replacement for the H20. But if the President wants The U. S.

[Timothy Arcuri, Managing Director at UBS Group]

To win, it seems like you're going to have to be allowed to ship something into China. So I guess I had two points on that. First of all, have you been approved to ship a new modified version into China? And you're currently building it, but you just can't ship it in fiscal Q2. And then you were sort of run rating 7,000,000,000 to $8,000,000,000 a quarter into China.

[Timothy Arcuri, Managing Director at UBS Group]

Can we get back to those sorts of quarterly run rates once you get something that you're allowed to ship back into China? I think we're all trying to figure out how much to add back to our models and when. So, you know, whatever you can say there would be great. Thanks.

[Jensen Huang, Founder, President and CEO at NVIDIA]

The the president has a plan. He has a vision, and I trust him. With respect to with respect to our export controls, it's a it's a set of limits, and the new set of limits pretty pretty much make it impossible for us to to reduce Hopper any further, you know, for for any productive use. And and so the new limits the new limits, you know, it's kind of the end of the road for Hopper. We have some we have limited options, and and and so we just the the key is to to understand the limits.

[Jensen Huang, Founder, President and CEO at NVIDIA]

The key is to understand the limits and see if we can come up with with, with interesting products that could that could continue to serve the Chinese market. We we don't have anything at the moment, and, but we're we're considering it. We're thinking about it. Obviously, the limits are are quite stringent at the moment, and, we we have nothing to announce today. And and when the time comes, you know, we'll we'll, we'll, engage the administration and discuss that.

[Operator]

Your final question comes from the line of Aaron Rakers with Wells Fargo. Your line is open.

[Jake Wilhelm, Vice President at Wells Fargo]

Hi. This is Jake on for Aaron. Thanks for taking the question, and congrats on a great quarter. I was wondering if you could give some additional color around the strength you saw within the networking business, particularly around the adoption of your Ethernet solutions at CSPs as well as any change you're seeing in network attach rates.

[Jensen Huang, Founder, President and CEO at NVIDIA]

Yeah. Thank you for that. We now have three networking platforms, maybe maybe four. The the first one the first one is the scale up platform to turn a computer into a much larger computer. Scaling up is incredibly hard to do.

[Jensen Huang, Founder, President and CEO at NVIDIA]

Scaling out is easier to do, but scaling up is hard to do. And that platform is called NVLink. And NVLink is is comes with it chips and switches and, you know, NVLink spines, and it's really complicated. But, anyways, that's our new platform, scale up platform. In addition to InfiniBand, we also have SpectrumX.

[Jensen Huang, Founder, President and CEO at NVIDIA]

We've been fairly fairly consistent that Ethernet was designed for a lot of traffic that are independent. But in the case of AI, you have a lot of computers working together, and the the traffic of AI is insanely bursty. Latency matters a lot because the the AI is thinking, and it wants to get work done as quickly as possible. And you got a whole bunch of nodes working together. And so we enhanced a we enhanced Ethernet, added capabilities like extremely low latency, congestion control, adaptive routing, the type of technologies that were available only in InfiniBand to Ethernet.

[Jensen Huang, Founder, President and CEO at NVIDIA]

And as a result, we improved the utilization of Ethernet in these clusters. These clusters are gigantic from as low as 50% to as high as 85%, ninety %. And and so the difference is if you had a cluster that's $10,000,000,000 and you improved its effectiveness by 40%, that's worth $4,000,000,000. It's incredible. And so Spectrum X has been really, quite frankly, a home run.

[Jensen Huang, Founder, President and CEO at NVIDIA]

And and this this last quarter, as as we said in the in the prepared remarks, we added two very significant CSPs to the Spectrum x adoption. And and then the last one the last one is BlueField, which is our control plane. And so in those four those the control plane of network, which is used for storage, is used for security, and for many of these clusters that want to achieve isolation among its users, multitenant clusters, and and still be able to use and and have extremely high performance bare metal performance, BlueField is ideal for that and is used in a lot of the a lot of these cases. And so we have these four four networking platforms. They're all growing, and and we're we're we're we're doing really well. I'm very proud of the team.

[Toshiya Hari, VP of Investor Relations & Strategic Finance at NVIDIA]

Jensen, over to you.

[Operator]

That is all the time we have for questions. Jensen, I will turn the call back to you.

[Jensen Huang, Founder, President and CEO at NVIDIA]

Thank you. This is the start of a powerful new wave of of growth. Grace Blackwell is in full production. We're off to the races. We now have multiple significant growth engines.

[Jensen Huang, Founder, President and CEO at NVIDIA]

Inference, once the lighter workload is surging with revenue generating AI services. AI is growing faster and will be larger than any platform shifts before, including the Internet, mobile, and cloud. Blackwell is built to power the full AI life cycle from training frontier models to running complex inference and reasoning agents at scale. Training demands continues to rise with breakthroughs in post training and like reinforcement learning and synthetic data generation, but inference is exploding. Reasoning AI agents require orders of magnitude more compute.

[Jensen Huang, Founder, President and CEO at NVIDIA]

The foundations of our next growth platforms are in place and ready to scale. Sovereign AI, nations are investing in AI infrastructure like they once did for electricity and Internet. Enterprise AI AI must be deployable on prem and integrated with existing IT. Our RTX Pro, DGX Spark, and DGX Station enterprise AI systems are ready to modernize the $500,000,000,000 IT infrastructure on prem or in the cloud. Every major IT provider is partnering with us.

[Jensen Huang, Founder, President and CEO at NVIDIA]

Industrial AI from training to digital twin simulation to deployment, NVIDIA Omniverse and Isaac Groot are powering next generation factories and humanoid robotic systems worldwide. The age of AI is here from AI infrastructures, inference at scale, sovereign AI, enterprise AI, and industrial AI. NVIDIA is ready. Join us at GTC Paris. I'll keynote at Viva Tech on June 11 talking about quantum GPU computing, robotic factories and robots, and celebrate our partnerships building AI factories across the region.

[Jensen Huang, Founder, President and CEO at NVIDIA]

The NVIDIA band will tour France, The UK, Germany, and Belgium. Thank you for joining us, at the earnings call today. See you in Paris.

[Operator]

This concludes today's conference call. You may now disconnect.

Participants

Executives

• Toshiya Hari, VP of Investor Relations & Strategic Finance
• Colette Kress, EVP & CFO
• Jensen Huang, Founder, President and CEO

Analysts

• Joseph Moore, Managing Director at Morgan Stanley
• Vivek Arya, Managing Director at Bank of America
• CJ Muse, Senior Managing Director at Cantor Fitzgerald
• Ben Reitzes, Managing Director – Head of Technology Research at Melius Research LLC
• Timothy Arcuri, Managing Director at UBS Group
• Jake Wilhelm, Vice President at Wells Fargo