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I'll turn it over to Jensen for a business update. Following which we will announce the preliminary results of the meeting if available and then answer stockholder questions. [clears throat] This has been an extraordinary year for NVIDIA and for computing. Every 10 to 15 years the computer industry resets.
Mainframe to PC PC to internet internet to cloud cloud to mobile cloud. This reset is bigger. For 60 years, humans wrote software and computers executed instructions. That paradigm has changed. With AI, computers can understand, reason, plan, use tools, and do useful work. A computer is no longer just a tool.
In the age of AI it is an assistant that uses tools. And by extension, the data center is no longer a tool shed. It is an AI factory of digital assistants. An infrastructure for producing digital intelligence. NVIDIA's building the computing infrastructure for this new era. Two years ago, generative AI captured the world's attention.
ChatGPT could write, draw, summarize, and answer questions. Then reasoning AI learned to think through problems. Agentic AI has now arrived. Agents can use tools, access memory, write code, call other agents, test results, and keep working until the job is done. Software coding is the first major enterprise breakout use case.
This is important. AI is now useful. When AI does useful work, tokens become valuable, and when tokens become profitable, demand for compute accelerates. Look at the evidence. GitHub developers merged 300 million pull requests in 2023, 400 million in 2024, and 500 million in 2025. A clear steady climb.
But in the first few months of 2026, the pace nearly tripled. Clearly, what that means, clearly, clearly, uh 30 million software developers earn roughly $3 trillion in salary each year. And their work underpins $800 trillion of global economic activity. With agents, that same workforce is now generating nearly $9 trillion of output, $6 trillion more.
Coding is only one of the demand drivers. Useful AI has arrived. The ROI question of AI has been answered. And every industry is racing to adopt agentic AI. Nvidia revenue grew 65% to $216 billion. Operating income rose 60% to $130 billion. Diluted EPS increased 67% to $4.90. We generated $103 billion in operating cash flow and returned $41 billion to shareholders.
Data center revenue of $194 billion increased 68%. Blackwell has significantly broadened NVIDIA's infrastructure footprint across a diverse set of hyperscalers, cloud, AI lab, industrial enterprise, and sovereign customers. Model builders and hyperscalers have each cumulatively deployed hundreds of thousands of Blackwell GPUs.
AI factory build-outs continue to rapidly expand across major industries. Companies like Capital [clears throat] One, Hyundai Motor Group, Jane Street, and Lilly are scaling NVIDIA infrastructure to deploy AI. International revenue more than tripled to over $30 billion. Nearly 40 countries representing $50 trillion in GDP are building AI factories powered by NVIDIA infrastructure.
AI infrastructure is no longer experimental. It is in production. AI's more than a model. It's a new industry. You can think of it You can think of it as a five-layer cake. Energy, chips and systems, infrastructure, models and applications. Traditional data centers store and serve files. AI factories manufacture tokens.
Tokens become code, answers, designs, actions, and services. Useful AI is profitable. Every token is a unit of profit. And that is why demand for compute is extraordinary. Customers are not buying computers. They're building revenue-generating AI factories. The architecture of the factory matters. The question is how much revenue the factory can produce and at what cost.
Inference is the process of generating tokens, and NVIDIA Blackwell sets the standard. In semi-analysis inference X benchmark Blackwell is recognized as the inference king. Delivering the lowest cost to lowest cost per token and 30 times higher token throughput than the next best platform. This is why architecture is critical.
NVIDIA systems may not be the cheapest to produce to purchase but NVIDIA generates the lowest cost tokens the highest token throughput and the most revenues. Vera Rubin is the next step. Hopper was built for pre-training. Blackwell brought inference to rack scale. Vera Rubin is built for agents. Agentic AI changes the computing path pattern.
Agents think, use tools access databases, retrieve memory execute code, and call applications repeat- repeatedly until the task is done. Large language models on GPUs drive the thinking and the CPUs must keep up. If the CPU becomes a bottleneck the GPUs sit idle. And in an AI factory idle GPUs are lost revenue.
That is why Vera matters. Vera is the CPU for agents. Rubin is the GPU for thinking. NVLink Spectrum-X storage and security on BlueField and software brings the systems together. NVIDIA in fact is the only company with three networking businesses. NVLink scale up connects the GPUs in a rack into one giant computer.
Spectrum-X is the Ethernet built for AI. It scales out and across AI factories. And it is now larger than all other Ethernet networking peers combined. InfiniBand provides the lowest latency network for the world's largest AI and scientific systems. Together, they enable optimization of the AI factory from the GPU to the rack, across the data center, and across data centers.
Vera Rubin is not a chip. It is an AI factory platform. And the ecosystem is already moving. Vera Rubin is in full production and every major model builder, public cloud, AI cloud, and hyperscaler is preparing to build on it. Vera opens an entire new market. Until now, every CPU was built for people.
We live in a world measured in seconds. Agents live in a world measured in nanoseconds. Every moment a CPU keeps an agent waiting is a moment the most expensive thing in the building, the GPUs, sits idle. So, we built a brand new CPU from the ground up for agents. This is a new market. CPUs for humans were sliced and rented per core.
Agents don't rent cores, but demand ultra-fast responses. There will be billions of agents and they will need a CPU built for them. We believe Vera will be one of the most significant product launches in our company's history. And the orders are already coming in. CUDA is one of the most important investments we have ever made.
For 20 years, we've been dedicated to one architecture for accelerated computing. The installed base attracts developers. Developers create breakthrough applications. Applications create new markets. New markets expand the installed base. That flywheel is accelerating. CUDA X is the library stack built on top of CUDA.
These libraries are the crown jewels of NVIDIA. They solve some of the hardest problems in science and industry. Computational lithography, optimization, genomics, physics, data processing, robotics, AI, radio radio networks, and more. Now, these libraries are becoming tools for agents. This week, we announced BioNeMo, a suite of digital biology and drug discovery tools for agents.
NVIDIA's vertically integrated and horizontally horizontally open. We build the full stack so that we can optimize the system end to end. Then we open it so the whole industry can build on it. Our business is broad and becoming more diverse. To make it easier to understand our business, we now describe NVIDIA through two market platforms.
Data center and edge computing. In data center, we serve two markets. Hyperscale and what we call AC or AI cloud, industrial and enterprise. Two markets. Our customer base is diverse and growing. Edge computing includes PCs, workstations, gaming, AI base stations, robotics and automotive. The reason we can serve all these markets is because we have one architecture, one software stack, and a rich ecosystem.
Physical AI is the next wave of growth for NVIDIA. Physical AI is agentic AI in the real world. Robots, cars, and factories will perceive, reason, plan, and operate in dynamic environments. NVIDIA pioneers this field and builds the full loop. AI factories train models. Omniverse simulates them in virtual worlds.
NVIDIA chips and computers operate in the robot. And Cosmos is the world foundation model that powers it all. Robots and robotic systems are being built across industries from transportation, manufacturing, surgery surgical surgical robotics, to hospitality service. The last several months have seen tremendous acceleration in AI.
Let me leave you with this. Useful AI has arrived and it is profitable. And so, compute is revenue. Vera Rubin is in full production. Vera is opening a brand new CPU market built for agents. And every enterprise is becoming an agent company. And they run on NVIDIA. The age of AI is moving at full steam.
And NVIDIA is building the infrastructure to power it. As we grow, we will continue to scale R&D, invest in our ecosystem, and return capital to shareholders. We recently announced a significant increase in our dividend and stock buyback program. We plan to return 50% or more of our free cash flow to shareholders this year, next year, and beyond.
Thank you. Thanks, Jensen. The time is 9:33 a.m. Pacific time, and the polls are now closed. Based on preliminary voting results, the inspector of elections has confirmed that all 10 nominees have received the requisite number of votes to be reelected as directors of the company, and proposals two and three have been approved.
Proposal four, to replace supermajority voting provisions in our charter and bylaws with a simple majority standard, has been approved. Proposals five, six, and seven have not been approved. The final vote results are not yet available to us, but will be published in a form 8-K, which we expect to file with the SEC within four business days.
That concludes the formal portion of today's annual meeting, and I now declare the official portion of the meeting adjourned. I'll turn it over to Colette Chisholm for stockholder questions. Thanks, Tim. We'll now move to Q&A. We grouped together duplicative questions that we received to streamline the discussion.
[clears throat] Question one. How sustainable is the current AI infrastructure buildout? At what point do the principal drivers of your business mature and growth slow? As I mentioned during my presentation, AI is more than a model. It represents a fundamental shift in computing. For the first time in 60 years, computing is being reinvented from largely retrieving, storing, and sending information to generating intelligence with AI.
Tokens are the fundamental unit of intelligence. They're manufactured in a new type of data center called an AI factory and monetized to generate revenue. The more compute, the more tokens, the more revenue. This build-out will be measured in decades, similar to other essential infrastructure initiatives, including the electric grid, transportation systems, and the internet.
We believe this will become the largest infrastructure build-out in human history. Agentic AI is accelerating infrastructure investments as for the first time, AI is doing real work and creating real economic value. As organizations seek to manufacture intelligence at scale, demand for AI factories will extend far beyond today's clouds to enterprises, sovereign nations, and regional AI clouds.
Nvidia is uniquely enabled and uniquely enables AI factory build-outs with our full stack, end-to-end co-designed infrastructure, and a large ecosystem of partners supporting these initiatives. The next major leg of growth is physical AI, which is only beginning. Over time, AI will move beyond the digital world into robotaxis, humanoid robots, and industrial systems, enabling these enabling these machines to perceive, reason, and act with agency in the physical world.
Powering physical AI will require new wave of infrastructure investment. Here, Nvidia provides AI infrastructure, Omniverse simulation and digital twin platforms, open models, Jetson Thor embedded compute, and [clears throat] software stacks to develop and deploy physical AI at scale. We have a long runway of growth ahead of us.
Nvidia's GPUs now power the majority of the world's AI training infrastructure. But as inference workloads overtake training, how confident is Nvidia that the GPU architecture remains the preferred platform for inference at scale? Nvidia is indeed excellent at training. With Blackwell, we also established leadership for inference.
Inference is monetizing AI. Because data centers are power limited, their token throughput and revenue potential are defined by the AI infrastructures performance per watt. In semi-analysis inference X benchmarks, Blackwell was declared the inference king. Delivering the best performance per watt, the lowest cost token, and 30 times higher token throughput.
In the latest round of MLPerf inference benchmarks, we delivered our seventh consecutive win. And for AI agents, Artificial Analysis new agent perf results showed Grace Blackwell 300 NVLink 72 systems run up to 20 times more agents per megawatt compared to Hopper. Its superior performance is the culmination of Nvidia's extreme co-design across chips, systems, algorithms, and software.
Nvidia AI infrastructure delivers the best performance and therefore the best inference economics. But our advantage extends beyond our leading performance. Our large installed base enables developers to reach the greatest number of AI users. Nvidia's programmable GPU architecture runs over 7,000 applications, giving cloud customers the greatest revenue opportunity and potential for financing and off-take.
For enterprises and sovereigns, NVIDIA offer unmatched deployment flexibility. The broadest set of leaderboard open models for custom AI and the industry's deepest IT ecosystem support. Today, the vast majority of NVIDIA's compute footprint is used for inference. And we are favorably positioned to expand our share as we demonstrate with our recent announcements with Anthropic and and Apple.
Is supporting frontier systems worth the national security and reputational risk? NVIDIA has long been a leading American innovator for over three decades and is a core part of the United States AI and semiconductor industrial base. For over a decade, NVIDIA designed, built, and delivered the first AI supercomputer to American AI researchers.
And since that time, has remained dedicated keeping American researchers, academics, startups, and businesses at the frontier of AI. America's safety, security, and prosperity depend on leadership across all five layers of the AI stack. From energy, chips, infrastructure, models to applications. Supporting frontier systems strengthen that leadership, creates high-skilled American jobs, helps reindustrialize our nation, and reinforces both economic and national security.
America's technology leadership is one of our national treasures. NVIDIA's proud to be one of its core pillars. We are an American company building American technology, investing in American workers, and supporting a broader industrial base that helps ensure that the United States, not strategic competitors, shapes the future of AI.
AI is a once-in-a-generation opportunity to re-industrialize America with chips and systems [clears throat] manufacturing, bring back advanced manufacturing jobs, upgrade our aging power grid, and invest in sustainable energy. Because of AI, we have the profits and scale to invest in partners such as Intel, Micron, TSMC, Wistron, Foxconn, Ampere, Marvell, Corning, Coherent, and Lumentum, all of which are hiring and building factories in the United States to support Nvidia's business and the broader AI ecosystem.
This deep US-anchored ecosystem enhances supply chain resilience and supports long-term value creation for our shareholders. In the energy sector, companies such as Caterpillar, GE Vernova, and Vertiv, along with partners in nuclear and renewable energy, we're working with them we're working with them to enhance America's power generation and grid capabilities.
This buildout of resilient modern infrastructure is essential to enable America to lead this next industrial revolution and to ensure that our AI infrastructure is secure, reliable, and domestically anchored. Is Nvidia concerned that its products reach restricted or adversary end users through diversion?
National security is first and foremost. Where commercial opportunities conflict with US national security, national security comes first. Nvidia complies with US export controls and is prepared to accept commercial restrictions where required by law or policy. We are committed to compliance with all US laws and work in collaboration with the entire AI ecosystem and the US government.
The company sells data GPUs to well-known large-scale customers such as original equipment manufacturers, hyperscalers, and cloud service providers. We work with our partners' legal and compliance teams and coordinate with law enforcement to ensure compliance with all regulations. Our compliance efforts have repeatedly stopped would-be smugglers who risk prosecution on both sides of the globe.
Moreover, advanced AI data centers are massive, integrated systems that require trusted hardware, software, networking, and continuing support. Trying to cobble together data centers with smuggled products is a dead end. Building them out of contraband would be extremely difficult and we do not provide any support or repairs for restricted products.
Why has Nvidia offered opinions to US government regarding export controls? Is there a formal plan in place for selling data center compute to the China market? As an American company, Nvidia has an obligation to help our government promote national security, economic security, and sustain leadership of America's technology industry.
We believe these goals can be achieved together through strong, balanced policies that both protect sensitive information and technologies and preserve US leadership. National security is foremost. Our government counts on America's innovators and private corporations to deliver prosperity, create high-paying jobs, and provide tax revenue that supports the national defense and supports essential government government services.
The United States will only maintain its edge in AI if government, industry, and researchers work together. Our role is to contribute our expertise so that policymakers can design strong, effective rules that keep the US ahead of strategic competitors. Real-time information regarding advanced technologies, the AI ecosystem, and emerging competition is essential to policy makers.
As a leading provider of AI platforms, we assist the US government wherever we can. For shareholders, constructive engagement with policy makers is a way to reduce regulatory uncertainty, support stable long-term investments in AI infrastructure, and position NVIDIA as a trusted long-term partner to the US government.
While the US government has approved licenses of H200s to be shipped to China-based customers, we have yet to generate any revenue, and we are uncertain whether any imports will be allowed into the country. Can you provide an update on your capital return policy? What should we expect in terms of dividends and share repurchases?
NVIDIA offers investors a unique combination of exceptional growth, strong margin and free cash flow execution, and rising capital returns. On our recent earnings call, we announced a 25x increase in our quarterly dividend and authorized an additional $80 billion in share repurchases. Supported by our conviction in sustainable market growth and free cash [clears throat] flow generation, we plan to return 50% or more of our free cash flow this year, next year, and beyond, growing both our share repurchases and dividend over time.
Our program has now concluded. A copy of this webcast will be available online on our website through June 24th, 2027. We look forward to another great year at NVIDIA. Thank you for attending and for your continued support. Our 2026 annual meeting is now closed. The meeting has now concluded. Thank you for joining and have a pleasant day. All right, good job, everyone.
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