NVIDIA Corporation

Good afternoon. My name is Tiffany and I will be your conference operator today. At this time, I would like to welcome everyone to NVIDIA's second quarter earnings call. All lines have been placed on mute to prevent any background noise. After the speaker's remarks, there will be a question and answer session. If you would like to ask a question during this time, simply press star followed by the number one on your telephone keypad. If you would like to withdraw your question, press star 1 again. Thank you. Toshiya Hari, you may begin your conference.

Thank you. Good afternoon and welcome to NVIDIA's conference call for the second quarter of fiscal 2027. With me today from NVIDIA are Jen-Hsun Huang, President and Chief Executive Officer, and Colette Kress, Executive Vice President and Chief Financial Officer. 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 third quarter of fiscal 2027. 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 and Exchange Commission. All our statements are made as of today, August 26, 2026, 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.

Thanks, Toshiya. We delivered another outstanding quarter with record revenue, operating income, and EPS. Total revenue of $96 billion, more than doubled year over year as growth accelerated for the fourth consecutive quarter. The surge in AI demand is driving a global infrastructure build-out, supported by an expanding and diverse set of growth opportunities. spanning hyperscalers, AI labs, AI natives, enterprises, and sovereign customers. We expect to grow revenue by approximately 70% in fiscal 2028. This is a supply-constrained outlook. Q2 data center revenue increased 18% quarter over quarter to $89 billion with strong contributions from both sub-segments, hyperscale and ACINE, which includes our neocloud, industrial, and enterprise customers. Hyperscale revenue of $49 billion grew 13% sequentially, driven by sustained strength in Blackwell. Reinforcing that more compute drives more revenue as new GPU capacity comes online, our hyperscale customers delivered strong financial results in the quarter with accelerating revenue growth and expanding margins. With cloud industry backlog now greater than 2 trillion, CapEx by the top five hyperscalers is expected to reach nearly 800 billion in 2026 and 1.3 trillion in 2027. Today we are delighted to announce an expansion of our partnership with AWS. Building on its already vast installed base of NVIDIA compute, AWS is deploying an additional 2 million GPUs starting this quarter through the second quarter of fiscal 29. Along with Vera CPUs, some integrated with Ruben, others standalone. AWS will serve NVIDIA Nematron family of open models on Amazon Bedrock and SageMaker. Amazon will also adopt our full physical AI stack, Omniverse, Cosmos, Isaac, and Jetson to power its fleet of warehouse robots. ACI and E revenue of 40 billion increased 25% sequentially and 138% year over year. Growth was driven by neocloud capacity additions to meet the rising demand from enterprises, AI startups, and sovereigns, as well as hyperscalers purchasing capacity to supplement their own build-outs. Using NVIDIA DSX reference designs, our NEO cloud partners are bringing capacity online faster and at lower token cost. They are expected to exit the year with eight gigawatts in total installed capacity, up from approximately three gigawatts at the end of 2025. Incredibly, we are seeing demand acceleration even at our scale. Customers' forecasts point to our growth doubling next year. However, as I mentioned earlier, we expect to grow approximately 70% as we are supply constrained. NVIDIA Compute is fully utilized across every cloud we serve. The economic value it generates for our hyperscale, neocloud, and AI lab partners keeps rising. Besides building the best AI computing technologies and the most capable supply chain, NVIDIA has three unique capabilities that are engines powering our growth. First, NVIDIA's architecture runs every model, and we're growing share as closed and open model adoption grow. Closed and open models alike, adoption is skyrocketing. NVIDIA runs the leading closed models, OpenAI, Anthropic, Grok, Meta, Gemini, and the leading open models, TML, Mistral, Quinn, Kimi, GLM, DeepSeq, Minimax, and Nematron. We're great at small models and giant ones, large or video, auto, regressive, or diffusion, in the cloud or in the edge. NVIDIA is great at training, great at inference, great at agentic workloads. One platform, fungible for every model and workload, durable for the entire lifecycle of AI. That combination of performance, fungibility, and durability is what makes NVIDIA the productive and financeable compute infrastructure. Our second unique capability is our full-stack AI factory platform that is expanding our share of the data center TAM. Since Hopper, our revenue opportunity has grown from roughly $18 billion per gigawatt to $25 billion with Blackwell to $40 billion with Vera Rubin, which now spans Vera CPU, Rubin GPU, NVLink, InfiniBanner Ethernet, and Grok LPU announced earlier this week. Our ability to extreme code design across GPU, CPU, NB-Link scale-up networking, scale-out networking systems, algorithms, and software enables us to deliver X-factor performance gain every generation. Vera Rubin exemplifies this, delivering 30X higher throughput per megawatt and 35X lower token costs relative to Grace Blackwell Ultra. We commenced production shipments of Vera Rubin earlier this month. Having already received purchase orders from every major hyperscaler, AI cloud, and system OEM, we expect Vera Rubin to mark the fastest product ramp in NVIDIA's history. Our networking business had another record quarter with revenue growing 18% on a sequential basis. SpectrumX Ethernet, which grew 2.6x on a year-over-year basis, is already helping us become the largest and fastest growing network company in the world. Rising adoption of agentic AI is driving an acceleration in demand for data center CPUs. Our great CPU, introduced in 2021, has been a great success, with revenue on a trailing 12-month basis exceeding $5 billion. Today, we are in full production of our next-generation Vera CPU. As a standalone product, Vera expands our TAM even further. Vera completes a genetic task 1.8x faster on the spec benchmark and provides five times the bandwidth per watt than any other data center CPU. We expect Vera to be deployed by every major hyperscaler, neocloud, AI lab, and system OEM with shipments already underway to our lead partners including OCI, SpaceX AI, and starting this quarter, AWS. We continue to see demand for approximately 20 billion in total server CPUs. And based on our customer demand and improving supply outlook, our preliminary expectation is for CPU revenue to more than double in fiscal 28, positioning us as one of the world's leading server CPU suppliers. Since the announcement of our Grok partnership last year, we've been working to unite NVIDIA's high throughput and Grok's high interactivity architectures. At Hot Chips earlier this week, we announced that Grok 3 LPX, our first rack scale LPU system, is in full production and already setting records. demonstrating nearly 4x the number of tokens per second against the next best alternative on our artificial analysis benchmark. We expect to ship Grok 3 LPX in volume later this quarter to early adopters. Nebius will be the first. Today, we're not just selling the best chips. We're selling a full-stack AI factory platform, offering superior economics for customers and capturing a bigger share of the data center TAM. Our third unique capability is the combination of our full-stack AI factory and rich CUDA ecosystem, allowing us to extend AI into markets a single chip alone can never reach. Beyond the hyperscalers lies a massive market, anxious to adopt AI, customers with no interest in designing their own custom silicon. NVIDIA's fully proven full stack platform is uniquely suited to help sovereigns, neoclouds, and enterprises build their AI infrastructure, bring it to full operation, continuously optimize it through CUDA software, and connect it to offtake demand from our vast developer ecosystem. Hyperscalers will remain a major growth driver, but non-hyperscaler growth, our AIC&E segment spanning Sovereign, Regional Neoclouds, Enterprise Edge, and AirGap data centers will represent roughly half of our data center business. Our AI native startup ecosystem, developed and running primarily on the NVIDIA Compute Platform, is scaling at a rapid pace. Global VC funding in AI, roughly 70% of which is spent on compute, exceeded $400 billion in the first half of 2026, surpassing the $265 billion raised in all of 2025. Nearly 20 companies, including Cursor, owned by SpaceX, Figma, and Together AI, now exceed $1 billion in annualized run rate revenue, up from 13 companies in Q4 of last year, with vertical enterprise software logging the fastest growth. In enterprise, on a trailing 12-month basis, on-prem revenue in the automotive vertical reached $8 billion, while financial services, manufacturing, and healthcare combined contributed $7 billion in revenue. Hudson River Trading and Jane Street are leveraging NVIDIA's powered AI factories to accelerate quantitative trading. Samsung Electronics is using NVIDIA Kulitho to achieve up to 20X greater performance in computational lithography, while Bristol-Myers Squibb is investing in Vera Rubin AI Factory, a fast follow to the Roche and Lilly build-outs, as drug R&D timelines compress from years to months. In Sovereign AI, our business primarily through the regional neoclouds grew 35% sequentially and more than tripled year over year in Q2. A country or region can allocate land and power directly to a regional cloud partner in ways it never would to a foreign hyperscaler. We don't own a cloud ourselves. We are a neutral partner to every sovereign and neocloud. and because NVIDIA Compute is productive, fungible, rentable and durable, regional cloud interest is surging around the world. We helped Quarweave, Nebius and Nscale build entire infrastructure businesses and NeoClouds are emerging everywhere. Firebird in Armenia, Casaba Technologies across Africa, GMI Cloud in Taiwan, Yoda and Naysa in India, Hermes in Australia, YTL-AI Cloud in Malaysia, pairing local land, power and operating expertise with our platform. Last month, we announced a partnership with NOATRA, Japan's national AI company, to build an NVIDIA DSX AI factory that will create open models to power AI agents, digital twins, robotics, and physical AI applications. South Korea's LG and Hyundai Motor Group are partnering with NVIDIA to build and scale AI. and in Europe, a record 35 new NVIDIA powered AI supercomputers were unveiled to advance industry and scientific breakthroughs. Neoclouds are seeing strong demand pipelines for many diverse off-takers. Rather than allocating their entire capacity to a single long-term off-take guarantee that lenders typically require to finance a data center independently, we have introduced a revenue sharing structure. NVIDIA provides a take or pay commitment on a portion of the facility's capacity, a minimum revenue guarantee that gives lenders the confidence to underwrite the project, and in exchange, we share in a portion of the Neocloud's revenue earned above that floor. Independent Capital still underwrites every deal on its own merits. We're not making loans. In this model, we get paid twice, once on the hardware sale and again through the share of rental revenue, a highly reoccurring stream layered on top of a one-time equipment purchase. Over time, this model can expand our addressable market and create reoccurring usage-linked revenue stream alongside our core platform revenue with the potential to drive billions in revenue over the medium to long term. Together, NVIDIA's three unique capabilities, a platform that runs every model, a full-stack AI factory platform capturing more of the data center TAM, and a CUDA ecosystem that extends AI into markets no single chip could reach alone, reinforce one another and are the engines of our growth. Let me update you on our progress with our Frontier AI Labs. The Frontier AI Labs have extraordinary demand for training and inference compute, but they are growing faster than what their balance sheets and credit profiles can support. They have rapidly growing customer demand, yet still lack the decades long infrastructure contracts and investment grade financing capacity needed to secure the AI factory infrastructure independently. In other words, their growth isn't limited by their technology or customer demand. It's limited by compute. For these companies, more compute means more and more intelligence, more users, and more revenue. NVIDIA is needed to help power this flywheel. First, we've invested nearly 50 billion in the Frontier AI Labs. This was a meaningful commitment, but it represented a small fraction of our expected free cash flow over the same period. Further, to support the Frontier Labs infrastructure build-outs, we recently announced partnerships with six of the world's leading infrastructure capital providers, Apollo, BlackRock, Blackstone, Brookfield, Goldman Sachs, and KKR, to establish financing platforms that will raise over $500 billion of third-party capital. With these partnerships, building on our unique, fungible, and durable computing platform, the AI labs will be able to build and assess AI infrastructure funded by long-term institutional capital at relatively attractive rates. Last week, we announced that we secured land power shell capacity through our partnership with SoftBank Energy to exclusively host NVIDIA Compute at their Portsmouth campus. The initial deployment expected to support 4.25 gigawatts of AI factory capacity will be utilized by OpenAI. Each generation of NVIDIA AI factory systems deployed at Portspike could represent approximately 1.5 million NVIDIA GPUs. In over 20 years, the site could support multiple upgrade cycles. Here's the essential economic point. The LPS commitment secures a long-lived AI factory site while the NVIDIA compute within the data center can be upgraded repeatedly. This project deepens our longstanding partnership with OpenAI. OpenAI has committed to substantially deployments of NVIDIA AI infrastructure through 2030. OpenAI's existing and planned commitments represent approximately 12 gigawatts of NVIDIA compute. For another frontier AI lab, we will provide selective credit enhancement for nearly two gigawatts of compute. This complements the substantial NVIDIA compute capacity they've secured independently without NVIDIA's credit support. We recognize the scale of this support, and we know some will call this circular financing. We see it differently. We're going through a major computing platform shift. Thank you for joining us. We believe these investments, measured against the strength of their demand, the business they create for us, the ecosystem they build on NVIDIA's platform, and the equity returns on our invested capital will be excellent. And our risk is limited. The NVIDIA Compute platform is fungible and durable and can be redeployed to support other customers. For context, we expect demand from the AI labs for which we expect to leverage our balance sheet to contribute toward roughly a quarter of our business next year. This remains compute we ship will be consumed by investment grade customers or those that are backed by one. In Q2, we ship less than 1% of our total data center revenue in Hopper 200 products to customers based in China in accordance with the U.S. government licenses. Current Hopper shipments are dilutive to corporate gross margins. And given ongoing geopolitical uncertainty, there is no China data center compute revenue in our forward outlook. Moving to the rest of the P&L, GAAP and non-GAAP gross margins were both 75%, largely unchanged from last quarter due to a similar product mix. GAAP and non-GAAP operating expenses were up 10% and 11% sequentially, primarily due to high compute infrastructure costs and compensation and benefits costs. Our non-GAAP effective tax rate of 16% increased from a year ago, primarily due to higher revenue. On our balance sheet, inventory increased to 32 billion as we prepared for the Vera Rubin launch. Days of sales outstanding increased to 60 days reflecting extended payment terms for large purchases by certain investment grade customers to be shipped over multiple quarters. In Q2, we returned a record $26 billion to shareholders, $20 billion through share repurchases, and $6 billion through our quarterly dividend of $0.25 per share. Relative to our plan to return 50% or more of free cash flow, we have returned 60% on a year-to-date basis. And going forward, we intend to increase and return excess free cash flow net of strategic uses. Let me turn to the outlook for the third quarter. Total revenue is expected to be 108 billion, plus and minus 2%. We expect sequential growth to be driven primarily by ACINE with data center, while growth in hyperseal is expected to reaccelerate in Q4 and into fiscal year 28, as supply of Vera Rubin grows over time. We see Vera Rubin accounting for about 20% of data center revenue in Q3. Looking ahead, our preliminary expectation is for fiscal year 28 revenue to grow approximately 70% year over year. Although we will work to close the supply demand gap, we expect supply to remain a bottleneck at least through the end of fiscal year 28. Many of you have expressed concerns regarding our gross margins as component costs have risen significantly. As you are already aware, we are experiencing extreme pricing conditions in memory. The magnitude of the price increase has exceeded our prior expectations and are headed even higher into next year. As a result, we are resetting expectations today. For Q3, we expect gap and non-gap gross margins to be 74%, plus or minus 50 basis points. We expect margins to bottom in Q4 in the 71% to 72% range. before settling at 72% to 73% in fiscal year 28 as executed price increases take effect in Q1. We want to be direct about this rather than let it linger as an open question. Memory scarcity today is being driven in large part by the AI build-out itself and unlike a component that simply raises our costs with no offset benefit. Tighter memory supply is a symptom of the same demand surge that's driving our own growth. We have a longstanding, deep relationships with all three major memory suppliers, and we're working closely with them to further increase the capacity our roadmap requires. GAAP and non-GAAP operating expenses are expected to be approximately $9.2 billion and $9.0 billion, respectively. For the full year, we now expect OPEX to grow in the low 50s, driven by a broadening of our product portfolio and further increase in the usage of AI tools, which is already and will continue to enhance engineering productivity. For full year, fiscal year 27, we continue to expect GAAP and non-GAAP tax rates to be between 16 and 18%, excluding any discrete items and material changes to our tax environment. With that, we will now transition to Q&A. Operator, please poll for questions.