NVDA NVIDIA Corporation · Q1 2026 Earnings Call

28-May-2025

(NVDA)

Q1 2026 Earnings Call

Total Pages: 15

1-877-FACTSET www.callstreet.com Copyright © 2001-2025 FactSet CallStreet, LLC

(NVDA) Corrected Transcript

Q1 2026 Earnings Call 28-May-2025

Vice President-Investor Relations & Strategic Finance, NVIDIA Corp. Co-Founder, President, Chief Executive Officer & Director, NVIDIA Corp.

Chief Financial Officer & Executive Vice President, NVIDIA Corp.

.....................................................................................................................................................................................................................................................................

.....................................................................................................................................................................................................................................................................

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 2026 Financial Results Conference Call. All lines have

been placed on mute to prevent any background noise. After the speakers' remarks, there will be a question-and-

answer session. [Operator Instructions]

Thank you. Toshiya Hari, you may begin your conference.

.....................................................................................................................................................................................................................................................................

Thank you. Good afternoon, everyone, and welcome to NVIDIA's conference call for the first quarter of fiscal

2026. 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 for the second quarter of fiscal

2026. 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 8-K with the Securities

2

1-877-FACTSET www.callstreet.com Copyright © 2001-2025 FactSet CallStreet, LLC

(NVDA) Corrected Transcript

Q1 2026 Earnings Call 28-May-2025

and Exchange Commission. All our statements are made as of today, May 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.

.....................................................................................................................................................................................................................................................................

Chief Financial Officer & Executive Vice President, NVIDIA Corp.

Thank you, Toshiya. We delivered another strong quarter with revenue of $44 billion, up 69% year-over-year,

exceeding our outlook in what proved to be a challenging operating environment. Data Center revenue of $39

billion 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. On April 9, the US government issued new export controls on H20. Our

data center GPU designed specifically for the China market. We sold H20 with the approval of the previous

administration. Although our H20 has been in the market for over a year and does not have a market outside of

China, the new export controls on H20 did not provide a grace period to allow us to sell through our inventory.

In Q1, we recognized $4.6 billion in H20 revenue, which occurred prior to April 9, but also recognized a $4.5

billion charge, as we wrote down inventory and purchase obligations tied to orders we had received prior to April

9. We were unable to ship $2.5 billion in H20 revenue in the first quarter due to the new export controls. The $4.5

billion 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 billion, 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

The introduction of GB200 NVL was a fundamental architectural change to enable Data Center scale workloads

and to achieve the lowest cost per inference token. 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.

GB200 NVL 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 NVL72 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 GB200s with OpenAI as one

of its key customers.

Key learnings from the GB200 ramp will allow for a smooth transition to the next phase of our product roadmap,

Blackwell Ultra. Sampling of GB300 systems began earlier this month at the major CSPs, and we expect

production shipments to commerce later this quarter. GB300 will leverage the same architecture, same physical

3

1-877-FACTSET www.callstreet.com Copyright © 2001-2025 FactSet CallStreet, LLC

(NVDA) Corrected Transcript

Q1 2026 Earnings Call 28-May-2025

footprint and the same electrical and mechanical specifications as GB200. The GB300 drop-in design will allow

CSPs to seamlessly transition their systems and manufacturing used for GB200, while maintaining high yields.

B300 GPUs with 50% more HBM will deliver another 50% increase in dense FP4 inference compute performance

compared to the B200.

We remain committed to our annual product cadence with our roadmap extending through 2028, tightly aligned

with the multiple year planning cycles of our customers. 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

trillion tokens in Q1, a five-fold 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 B200, tripling their token generation rate and

corresponding revenues for high value reasoning models such as DeepSeek-R1 as reported by artificial analysis.

NVIDIA Dynamo on Blackwell NVL72 turbocharges AI inference throughput by 30x 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 5x with

In the latest MLPerf inference results, we submitted our first results using GB200 NVL72, delivering up to 30x

higher inference throughput compared to our eight GPU H200 submission on the challenging Llama 3.1

benchmark. This feat was achieved through a combination of tripling the performance for GPU as well as 9x more

GPUs, all connected on a single NVLink domain. And while Blackwell is still early in its lifecycle, software

optimizations have already improved its performance by 1.5x 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 Ampere.

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 two-fold increase year-over-year, with the average number of GPUs powering each factory

also doubling in the same period. 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&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 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.

We introduced the Llama Nemotron family of open reasoning models designed to supercharge agentic AI

platforms for enterprises. Built on the Llama architecture, these models are available as NIMs or NVIDIA

inference microservices with multiple sizes to meet diverse deployment needs. Our post training enhancements

have yielded a 20% accuracy boost and a 5x 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 are being leveraged by leading enterprises

to build, optimize and scale AI applications. With NeMo, Cisco increased model accuracy by 40% and improved

response time by 10x in its code assistant. Nasdaq realized a 30% improvement in accuracy and response time in

4

1-877-FACTSET www.callstreet.com Copyright © 2001-2025 FactSet CallStreet, LLC

(NVDA) Corrected Transcript

Q1 2026 Earnings Call 28-May-2025

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. For AI-powered cybersecurity leading companies like

Check Point, CrowdStrike and Palo Alto Networks are using NVIDIA's AI security and software stack to build,

optimize and secure agentic workflows, with CrowdStrike realizing 2x faster detection triage with 50% less

compute cost.

Moving to networking. Sequential growth in networking resumed in Q1 with revenue up 64% quarter-over-quarter

to $5 billion. 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 for scale up, our NVLink compute fabric in its fifth

generation offers 14x the bandwidth of PCIe Gen5. 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 Q1 shipments exceeding $1 billion. 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. We are now enabling key partners, including ASIC providers

such as MediaTek, Marvell, Alchip Technologies and Astera Labs, as well as CPU suppliers such as Fujitsu and

Qualcomm to leverage and relink Fusion to connect our respective ecosystems.

For scale out, our enhanced Ethernet offerings delivered the highest throughput, lowest latency networking for AI.

Spectrum-X posted strong sequential and year-on-year growth and is now annualizing over $8 billion in revenue.

Adoption is widespread across major CSPs and consumer internet companies, including CoreWeave, Microsoft

Azure, Oracle Cloud and xAI. This quarter, we added Google Cloud and Meta to the growing list of Spectrum-X

customers.

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 3.5x and network resiliency by 10x, while accelerating customer time to market

by 1.3x.

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 H20 export licensing controls. For Q2,

we expect a meaningful decrease in China Data Center revenue. As a reminder, while Singapore represented

nearly 20% of our Q1 billed revenue as many of our large customers use Singapore for centralized invoicing, our

products are almost always shipped elsewhere. Note that over 99% of H100, H200, 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 $3.8 billion, increasing 48% sequentially and 42%

year-on-year. Strong adoption by gamers, creatives and AI enthusiasts have made Blackwell our fastest ramp

ever, against a backdrop of robust demand, we greatly improved our supply and availability in Q1 and expect to

continue these efforts in Q2.

AI is transforming PC and creator and gamers. With a 100 million user installed base GeForce represents the

largest footprint for PC developers. This quarter, we added to our AI PC laptop offerings, including models

5

1-877-FACTSET www.callstreet.com Copyright © 2001-2025 FactSet CallStreet, LLC

(NVDA) Corrected Transcript

Q1 2026 Earnings Call 28-May-2025

capable of running Microsoft's CoPilot+. This past quarter, we brought Blackwell architecture to mainstream

gaming with its launch of GeForce RTX 5060 and 5060 Ti, starting at just $299. The RTX 5060 also debuted in

laptop starting at $1,099. These systems that doubled the frame rate/latency. These GeForce RTX 5060 and

5060 Ti desktop, GPUs and laptops are now available.

In console gaming, the recently unveiled Nintendo Switch 2 leverages NVIDIA's neural rendering and AI

technologies, including next-generation custom RTX GPUs with DLSS technology deliver a giant leap in gaming

performance to millions of players worldwide. Nintendo has shipped over 150 million switch consoles to-date,

making it one of the most successful gaming systems in history.

Moving to Pro Visualization, revenue of $509 million was flat sequentially and up 19% year-on-year. Tariff related

uncertainty temporarily impacted Q1 systems and demand for our AI workstations is strong, and we expect

sequential revenue growth to resume in Q2. NVIDIA DGX Spark and DGX Station revolutionize personal

computing by putting the power of an AI supercomputer in a desktop form factor. DGX Spark delivers up to 1

petaflop of AI compute while DGX Station offers an incredible 20 petaflops and is powered by the GB300

Superchip. DGX Spark will be available in calendar Q3 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 KION Group, Pegatron, Accenture and other leading companies to

enhance industrial operations.

At COMPUTEX, we showcased Omniverse's great traction with technology manufacturing leaders, including

TSMC, Quanta, Foxconn, Pegatron. Using Omniverse, TSMC saves months in work by designing fabs virtually.

Foxconn accelerates thermal simulations by 150x, and Pegatron reduced assembly line defect rates by 67%.

Lastly with our automotive group. Revenue was $567 million, 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 and

demand for NAVs. We are partnering with GM to build the next-gen vehicles, factories and robots using NVIDIA

AI, simulation and accelerated computing. 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 GR00T N1, 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 1X, Agility Robotics, Figure AI, Uber and Waabi. We've begun

integrating Cosmos into their operations for synthetic data generation, while Agility Robotics, Boston Dynamics,

and XPENG Robotics are harnessing Isaac's simulation to advance their humanoid efforts.

GE Healthcare is using the new NVIDIA Isaac platform for healthcare 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.

All right. Moving to the rest of the P&L. GAAP gross margins and non-GAAP gross margins were 60.5% and 61%,

respectively. Excluding the $4.5 billion charge, Q1 non-GAAP gross margins would have been 71.3%, slightly

above our outlook at the beginning of the quarter. Sequentially, GAAP operating expenses were up 7% 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

6

1-877-FACTSET www.callstreet.com Copyright © 2001-2025 FactSet CallStreet, LLC

(NVDA) Corrected Transcript

Q1 2026 Earnings Call 28-May-2025

throughout the fiscal year. In Q1, we returned a record $14.3 billion 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 billion, plus or minus 2%.

We expect modest sequential growth across all of our platforms. 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 billion for the second quarter. GAAP and non-GAAP gross margins are expected to

be 71.8% and 72% 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.

GAAP and non-GAAP operating expenses are expected to be approximately $5.7 billion and $4 billion,

respectively, and we continue to expect full year fiscal year 2026 operating expense growth to be in the mid-30%

range. GAAP and non-GAAP other income and expenses are expected to be an income of approximately $450

million, excluding gains and losses from non-marketable 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. 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 VivaTech 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 2026 is scheduled for August 27.

I'll now let me turn it over to Jensen to make some remarks.

.....................................................................................................................................................................................................................................................................

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.

Today, however, the $50 billion China market is effectively closed to US industry. The H20 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.

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. 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 6G

and quantum, US global infrastructure leadership is at stake. 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

7

1-877-FACTSET www.callstreet.com Copyright © 2001-2025 FactSet CallStreet, LLC

(NVDA) Corrected Transcript

Q1 2026 Earnings Call 28-May-2025

enormous manufacturing capability. In the end, the platform that wins the AI developers wins AI. Export controls

should strengthen US platforms, not drive half of the world's AI talent to rivals.

On DeepSeek, DeepSeek and Qwen 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-R1, 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.

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.

DeepSeek 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. US platforms 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 Qwen runs best on American infrastructure.

Regarding onshore manufacturing, President Trump has outlined a bold vision to reshore advanced

manufacturing, create jobs and strengthen national security. Future plants will be highly computerized in robotics.

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. SPIL and Amkor 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.

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 GB200 NVLink72 racks contains 1.2

million components and weighs nearly 2 tons. No one has produced supercomputers on this scale. 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 5 gigawatt AI campus in the UAE. President Trump wants US tech to

lead. 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.

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.

.....................................................................................................................................................................................................................................................................

8

1-877-FACTSET www.callstreet.com Copyright © 2001-2025 FactSet CallStreet, LLC

(NVDA) Corrected Transcript

Q1 2026 Earnings Call 28-May-2025

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

.....................................................................................................................................................................................................................................................................

.....................................................................................................................................................................................................................................................................

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.

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 NVL72 rack scale solutions for reasoning

inference going forward?

.....................................................................................................................................................................................................................................................................

Well, we would like to serve all of it, and I think we're on track to serve most of it. Grace Blackwell NVLink72 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

1,000 times more than a one-shot chatbot. It's essentially thinking to itself, breaking down a problem step-by-step.

It might be planning multiple paths to an answer. It could be using tools, reading PDFs, reading web pages,

watching videos and then producing a result, an answer. 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. And so this is going to be a

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 the fundamental reason. That was the core driving reason for Grace Blackwell NVLink72.

Of course, in order to do that, we had to reinvent, literally redesign, the entire way that these supercomputers are

built. But now we're in full production. It's going to be exciting. It's going to be incredibly exciting.

.....................................................................................................................................................................................................................................................................

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

.....................................................................................................................................................................................................................................................................

Thanks for the question. Just a clarification for Colette first. So on the China impact, I think previously it was

mentioned at about $15 billion, so you had the $8 billion in Q2. So is there still some left as a headwind for the

remaining quarters just, Colette, how to model that? And then question, Jensen, for you. Back at GTC, you had

outlined a path towards almost $1 trillion 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 [ph] CSP (00:36:51),

9

1-877-FACTSET www.callstreet.com Copyright © 2001-2025 FactSet CallStreet, LLC

(NVDA) Corrected Transcript

Q1 2026 Earnings Call 28-May-2025

sovereigns, enterprises or build-out, should we expect some periods of digestion in between? Just what are your

customer discussions telling you about how to model growth for next year?

.....................................................................................................................................................................................................................................................................

Chief Financial Officer & Executive Vice President, NVIDIA Corp.

Yes, Vivek. Thanks so much for the question regarding H20. Yes, we recognized $4.6 billion H20 in Q1. We were

unable to ship $2.5 billion, so the total for Q1 should have been $7 billion. When we look at our Q2, our Q2 is

going to 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 H20 in Q2, and that was $8 billion. 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 $4.5 billion. 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. We assess that

TAM to be close to about $50 billion in the future as we don't have a product to enable for the China.

.....................................................................................................................................................................................................................................................................

Vivek, the – probably the best way to think through it is that AI is several things. Of course, we know that AI is this

incredible technology that's going to transform every industry from, of course, the way we do software to

healthcare and financial services to retail to, I guess, every industry, transportation, manufacturing, and we're at

the beginning of that. But maybe another way to think about that is where do we need intelligence, where do we

need digital intelligence? And it's in every country, it's in every industry. And we know because of that, we

recognize that AI is also an infrastructure. It's a way of developing a technology – delivering a technology that

requires factories and these factories produce tokens. And they – as I mentioned are important to every single

industry and 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 or thinking, what people call inference

time scaling. Of course, it created a whole new – we've entered an era where inference is going to be a significant

part of the compute workload. But anyhow, it's going to be a new infrastructure, and we're building it out in the

cloud. The United States is really the early starter and available in US clouds. And this is our largest market, our

largest installed base and we continue to see that happening. But beyond that, we're going to have to – we're

going to 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 move all of every company's data into the cloud. And so we're going to move

AI into the enterprise. And 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 DGX Spark and DGX Station, which is designed

for developers who want to work on-prem. And so enterprise AI is just taking off.

Telcos. Today, a lot of the telco infrastructure will be in the future software defined and built on AI, and so 6G is

going to 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 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.

.....................................................................................................................................................................................................................................................................

Operator: The next question comes from C. J. Muse with Cantor Fitzgerald. Your line is open.

10

1-877-FACTSET www.callstreet.com Copyright © 2001-2025 FactSet CallStreet, LLC

(NVDA) Corrected Transcript

Q1 2026 Earnings Call 28-May-2025

Yeah, 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, the UAE. And then also we

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 almost halfway through 2025?

.....................................................................................................................................................................................................................................................................

While we have more orders today than we did 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 the United States. But we're going to keep our supply chain quite busy for several – many more years

coming. And with respect to further announcements, I'm going to be on the road next week through Europe. And

it's – just about every country needs to build out AI infrastructure and their umpteenth AI factories being planned. I

think in the remarks, Colette mentioned there's some 100 AI factories being built. There's a whole bunch that

haven't been announced. And I think the important concept here which makes it easier to understand is that like

other technologies that impact literally every single industry, of course, electricity was one and it became

infrastructure. Of course, the information infrastructure, which we now know as the internet affects every single

industry, every country, every society. Intelligence is surely one of those things. I don't know any company,

industry, country who thinks that intelligence is optional. It's essential infrastructure.

And so we've now digitalized intelligence. And so I think we're clearly in the beginning of the build-out of this

infrastructure. And every country will have it, 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. It's a little bit like the energy infrastructure,

electricity. 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 now there are agents that reason and there are 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 really need to be and are. So I think we're in the

beginning of the build-out, and there should be many, many more announcements in the future.

.....................................................................................................................................................................................................................................................................

Operator: Your next question comes from Ben Reitzes with Melius. Your line is open.

.....................................................................................................................................................................................................................................................................

Yeah. 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 billion for H20 just seems like it's roughly $3 billion more than most

people thought with regard to what you'd be foregoing in the second quarter. So that would mean that with regard

to your guidance, the rest of the business in order to hit $45 billion is doing $2 billion to $3 billion 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 this second part of my question, Jensen, I know you guide one quarter at a time, but with regard to the

AI diffusion rule being lifted and this momentum with sovereign, there's been times in your history where you guys

11

1-877-FACTSET www.callstreet.com Copyright © 2001-2025 FactSet CallStreet, LLC

(NVDA) Corrected Transcript

Q1 2026 Earnings Call 28-May-2025

have said on calls like this, where you have more conviction in sequential growth throughout the year, et cetera.

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.

.....................................................................................................................................................................................................................................................................

Chief Financial Officer & Executive Vice President, NVIDIA Corp.

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 billion for H20, that's correct. That was a

possibility for what we would have had in our outlook for this quarter in Q2. 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 supply that we need for our customers. So putting those together, that's where

we came through with the guidance that we provided. I'm going to turn the rest over to Jensen to see how he

wants to [indiscernible] (00:49:05)...

.....................................................................................................................................................................................................................................................................

Yeah, thanks. Thanks, Ben. I would say compared to the beginning of the year, compared to GTC timeframe,

there are four positive surprises. The first positive surprise is the step function demand increase of reasoning AI. I

think it is fairly clear now that AI is going through an exponential growth, and reasoning AI really busted through.

Concerns about hallucination or its ability to really solve problems, and I think a lot of people are crossing that

barrier and realizing how incredibly effective agentic AI is and reasoning AI is. So number one is inference

reasoning and the exponential growth there, demand growth.

The second one, you mentioned AI diffusion. It's really terrific to see that the AI diffusion rule was rescinded.

President Trump wants America to win, and he also realizes that we're not the only country in the race. And he

wants the 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 happened, the rescinding of

it happened at almost precisely the time that 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 start-ups and society. Just as they had to build out infrastructure for electricity and internet, you got

to build out an infrastructure for AI. 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. Agents can understand ambiguous and rather implicit

instructions and able to problem solve and use tools and have memory and so on. And so I think this is a –

enterprise AI is ready to take off. And it's taken us a few years to build a computing system that is able to

integrate and 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, super excited about that. And so computing is one stack, one part of it. But remember, enterprise IT is

really three pillars, it's compute, storage and networking. And we've now put all three of them together finally, and

we're going to market with that.

And then lastly, industrial AI. Remember, one of the implications of the world reordering, if you will, is a regions

on-shoring manufacturing and building plants everywhere. In addition to AI factories, of course, 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 Omniverse and AI and all the work that we're doing with

robotics is emerging. And so this fourth pillar is quite important. Every factory will have an AI factory associated

12

1-877-FACTSET www.callstreet.com Copyright © 2001-2025 FactSet CallStreet, LLC

(NVDA) Corrected Transcript

Q1 2026 Earnings Call 28-May-2025

with it. And in order to create these physical AI systems, you really have to train a vast amount of data. So back to

more data, more training, more AIs to be created, more computers. And so these four drivers are really kicking

into turbocharge.

.....................................................................................................................................................................................................................................................................

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

.....................................................................................................................................................................................................................................................................

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 US 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 billion to $8 billion a quarter into China. 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 whatever you can say there would be great. Thanks.

.....................................................................................................................................................................................................................................................................

The President has a plan. He has a vision and I trust him. With respect to our export controls, it's a set of limits.

And the new set of limits pretty much make it impossible for us to reduce Hopper any further for any productive

use. And so the new limits, it's kind of the end the road for Hopper. We have limited options. And so we just – the

key is to understand the limits. The key is to understand the limits and see if we can come up with interesting

products that could continue to serve the Chinese market. We don't have anything at the moment, but we're

considering it. We're thinking about it. Obviously, the limits are quite stringent at the moment. And we have

nothing to announce today. And when the time comes, 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.

.....................................................................................................................................................................................................................................................................

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?

.....................................................................................................................................................................................................................................................................

Yeah, thank you for that. We now have three networking platforms, maybe four. The first one is the scale-up

platform to turn a computer into a much larger computer. Scaling up is incredibly hard to do. Scaling out is easier

to do but scaling up is hard to do. And that platform is called NVLink. And NVLink is – comes with it chips and

switches and NVLink spines and it's really complicated. But anyways, that's our new platform, scale-up platform.

In addition to InfiniBand, we also have Spectrum-X. We've been 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

traffic of AI is insanely bursty. Latency matters a lot, because 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.

13

1-877-FACTSET www.callstreet.com Copyright © 2001-2025 FactSet CallStreet, LLC

(NVDA) Corrected Transcript

Q1 2026 Earnings Call 28-May-2025

And so 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. 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%, 90%.

And so the difference is if you had a cluster that's $10 billion and you improved its effectiveness by 40%, that's

worth $4 billion. It's incredible. And so Spectrum-X has been really, quite frankly a home run. And this last quarter,

as we said in the prepared remarks, we added two very significant CSPs to the Spectrum-X adoption.

And then the last one is BlueField, which is our control plane and so in those four – those – the control plane and

network, which is used for storage. It's used for security and for many of these clusters that want to achieve

isolation among its users, multi-tenant clusters and still be able to use and have extremely high-performance bare

metal performance, BlueField is ideal for that and it is used in a lot of these cases. And so we these have four

networking platforms that are all growing and we're doing really well. I'm very proud of the team.

.....................................................................................................................................................................................................................................................................

Operator: That is all the time we have for questions.

.....................................................................................................................................................................................................................................................................

.....................................................................................................................................................................................................................................................................

Operator: Jensen, I will turn the call back to you.

.....................................................................................................................................................................................................................................................................

Thank you. This is the start of a powerful new wave of growth. Grace Blackwell is in full production. We're off to

the races. We now have multiple significant growth engines. 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 lifecycle from training frontier models to

running complex inference and reasoning agents at scale. Training demand 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.

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 billion IT infrastructure on-prem or in the cloud. Every major IT provider is partnering with us.

Industrial AI from training to digital twin simulation to deployment, NVIDIA Omniverse and Isaac GR00T 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, our keynote at VivaTech on June 11, talking about quantum GPU computing, robotic

factories and robots and celebrate our partnerships building AI factories across the region. 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.

14

1-877-FACTSET www.callstreet.com Copyright © 2001-2025 FactSet CallStreet, LLC

(NVDA) Corrected Transcript

Q1 2026 Earnings Call 28-May-2025

The information herein is based on sources we believe to be reliable but is not guaranteed by us and does not purport to be a complete or error-free statement or summary of the available data.

As such, we do not warrant, endorse or guarantee the completeness, accuracy, integrity, or timeliness of the information. You must evaluate, and bear all risks associated with, the use of any

information provided hereunder, including any reliance on the accuracy, completeness, safety or usefulness of such information. This information is not intended to be used as the primary basis

of investment decisions. It should not be construed as advice designed to meet the particular investment needs of any investor. This report is published solely for information purposes, and is

not to be construed as financial or other advice or as an offer to sell or the solicitation of an offer to buy any security in any state where such an offer or solicitation would be illegal. Any

information expressed herein on this date is subject to change without notice. Any opinions or assertions contained in this information do not represent the opinions or beliefs of FactSet

CallStreet, LLC. FactSet CallStreet, LLC, or one or more of its employees, including the writer of this report, may have a position in any of the securities discussed herein.

THE INFORMATION PROVIDED TO YOU HEREUNDER IS PROVIDED "AS IS," AND TO THE MAXIMUM EXTENT PERMITTED BY APPLICABLE LAW, FactSet CallStreet, LLC AND ITS LICENSORS,

BUSINESS ASSOCIATES AND SUPPLIERS DISCLAIM ALL WARRANTIES WITH RESPECT TO THE SAME, EXPRESS, IMPLIED AND STATUTORY, INCLUDING WITHOUT LIMITATION ANY IMPLIED

WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE, ACCURACY, COMPLETENESS, AND NON-INFRINGEMENT. TO THE MAXIMUM EXTENT PERMITTED BY APPLICABLE

LAW, NEITHER FACTSET CALLSTREET, LLC NOR ITS OFFICERS, MEMBERS, DIRECTORS, PARTNERS, AFFILIATES, BUSINESS ASSOCIATES, LICENSORS OR SUPPLIERS WILL BE LIABLE FOR ANY

INDIRECT, INCIDENTAL, SPECIAL, CONSEQUENTIAL OR PUNITIVE DAMAGES, INCLUDING WITHOUT LIMITATION DAMAGES FOR LOST PROFITS OR REVENUES, GOODWILL, WORK STOPPAGE,

SECURITY BREACHES, VIRUSES, COMPUTER FAILURE OR MALFUNCTION, USE, DATA OR OTHER INTANGIBLE LOSSES OR COMMERCIAL DAMAGES, EVEN IF ANY OF SUCH PARTIES IS ADVISED

OF THE POSSIBILITY OF SUCH LOSSES, ARISING UNDER OR IN CONNECTION WITH THE INFORMATION PROVIDED HEREIN OR ANY OTHER SUBJECT MATTER HEREOF.

The contents and appearance of this report are Copyrighted FactSet CallStreet, LLC 2025 CallStreet and FactSet CallStreet, LLC are trademarks and service marks of FactSet CallStreet, LLC. All

other trademarks mentioned are trademarks of their respective companies. All rights reserved.

15

1-877-FACTSET www.callstreet.com Copyright © 2001-2025 FactSet CallStreet, LLC