#1NVIDIA Investor Presentation October 2023#2Except for the historical information contained herein, certain matters in this presentation including, but not limited to, statements as to: our financial position; our markets, market opportunity, demand and growth drivers; the benefits, impact, performance, features and availability of our products and technologies; the benefits, impact, features and timing of our collaborations or partnerships; NVIDIA accelerated computing being broadly recognized as the way to advance computing as Moore's law ends; data centers making a platform shift from general purpose to accelerated computing; trillion dollars of installed global data center infrastructure transitioning to accelerated computing; Al driving a platform shift in computing and enabling new, never-before-possible applications; broader enterprises driving the next wave of computing, followed by autonomous machines and industrial digitalization; accelerated computing being needed to tackle the most impactful opportunities of our time; NVIDIA's value to every stakeholder in the ecosystem; the ROI of high compute performance; enterprise as the next big generative Al opportunity; NVIDIA's expanding accelerated computing ecosystem; Al as the greatest technology force of our time; data centers becoming Al factories; generative Al unlocking new opportunities; the next wave of Al being robotics and industrial digitalization; NVIDIA's acceleration stacks and ecosystems helping to bring Al to the world's largest industries; NVIDIA's Al expertise and scale helping to revolutionize businesses; generative Al being the most important computing platform of our generation; full-stack and data center scale acceleration driving significant cost savings and workload scaling; our dividend program plan; and our Automotive design win pipeline and ramp expectations are forward-looking statements. These forward-looking statements and any other forward-looking statements that go beyond historical facts that are made in this presentation are subject to risks and uncertainties that may cause actual results to differ materially. Important factors that could cause actual results to differ materially include: global economic conditions; our reliance on third parties to manufacture, assemble, package and test our products; the impact of technological development and competition; development of new products and technologies or enhancements to our existing product and technologies; market acceptance of our products or our partners' products; design, manufacturing or software defects; changes in consumer preferences and demands; changes in industry standards and interfaces; unexpected loss of performance of our products or technologies when integrated into systems and other factors. NVIDIA has based these forward-looking statements largely on its current expectations and projections about future events and trends that it believes may affect its financial condition, results of operations, business strategy, short-term and long-term business operations and objectives, and financial needs. These forward-looking statements are subject to a number of risks and uncertainties, and you should not rely upon the forward-looking statements as predictions of future events. The future events and trends discussed in this presentation may not occur and actual results could differ materially and adversely from those anticipated or implied in the forward-looking statements. Although NVIDIA believes that the expectations reflected in the forward-looking statements are reasonable, the company cannot guarantee that future results, levels of activity, performance, achievements or events and circumstances reflected in the forward-looking statements will occur. Except as required by law, NVIDIA disclaims any obligation to update these forward-looking statements to reflect future events or circumstances. For a complete discussion of factors that could materially affect our financial results and operations, please refer to the reports we file from time to time with the SEC, including our most recent Annual Report on Form 10-K, Quarterly Reports on Form 10-Q, and Current Reports on Form 8-K. Copies of reports we file with the SEC are posted on our website and are available from NVIDIA without charge. Many of the products and features described herein remain in various stages and will be offered on a when-and-if-available basis. The statements within are not intended to be, and should not be interpreted as a commitment, promise, or legal obligation, and the development, release, and timing of any features or functionalities described for our products is subject to change and remains at the sole discretion of NVIDIA. NVIDIA will have no liability for failure to deliver or delay in the delivery of any of the products, features or functions set forth herein. NVIDIA uses certain non-GAAP measures in this presentation including non-GAAP gross profit, non-GAAP gross margin, non-GAAP operating income, non-GAAP operating margin, and free cash flow. NVIDIA believes the presentation of its non-GAAP financial measures enhances investors' overall understanding of the company's historical financial performance. The presentation of the company's non-GAAP financial measures is not meant to be considered isolation or as a substitute for the company's financial results prepared in accordance with GAAP, and the company's non-GAAP measures may be different from non- GAAP measures used by other companies. Further information relevant to the interpretation of non-GAAP financial measures, and reconciliations of these non-GAAP financial measures to the most comparable GAAP measures, may be found in the slide titled "Reconciliation of Non-GAAP to GAAP Financial Measures".#3Headquarters: Santa Clara, CA NVIDIA pioneered accelerated computing to help solve impactful challenges classical computers cannot. A quarter of a century in the making, NVIDIA accelerated computing is broadly recognized as the way to advance computing as Moore's law ends and Al lifts off. NVIDIA's platform is installed in several hundred million computers, is available in every cloud and from every server maker, powers 74% of the TOP500 supercomputers, and boasts over 4 million developers.#4AI APPLICATION FRAMEWORK MODULUS ΜΟΝΑΙ RIVA PLATFORMS ACCELERATION LIBRARIES CLOUD-TO-EDGE DATACENTER-TO- ROBOTIC SYSTEMS 3-CHIPS MAXINE Lot cuNumeric RAPIDS RTX NVIDIA's Accelerated Computing Platform Full-stack innovation across silicon, systems and software NEMO MERLIN NVIDIA HPC DGX CV-CUDA DOCA HGX CUOPT cuQuantum GPU Spark cuDNN cuGraph TensorRT Triton EGX MORPHEUS Mag 10 00 ☐☐ CPU NVIDIA AI Parabricks TOKKIO OVX Aerial Super POD DPU AVATAR Sionna e Deepstream AGX DRIVE Jetpack Flare IGX ISAAC METROPOLIS HOLOSCAN NVIDIA Omniverse With nearly three decades of a singular focus, NVIDIA is expert at accelerating software and scaling compute by a Million-X, going well beyond Moore's law. Accelerated computing requires full-stack innovation - optimizing across every layer of computing - from silicon and systems to software and algorithms, demanding deep understanding of the problem domain. Our full-stack platforms - NVIDIA HPC, NVIDIA AI, and NVIDIA Omniverse - accelerate high performance computing, Al, and industrial digitalization workloads. We accelerate workloads at data center scale, across thousands of compute nodes, treating the network and storage as part of the computing fabric. Our platform extends from the cloud and enterprise data centers to supercomputing centers, edge computing and PCs. NVIDIA#5NVIDIA. Why Accelerated Computing? Advancing computing in the post-Moore's Law era Accelerated computing is needed to tackle the most impactful opportunities of our time-like Al, climate simulation, drug discovery, ray tracing, and robotics. NVIDIA is uniquely dedicated to accelerated computing -working top-to-bottom-refactoring applications and creating new algorithms, and bottom-to-top-inventing new specialized processors, like RT Core and Tensor Core. "It's the end of Moore's Law as we know it." - John Hennessy, Oct 2018 "Moore's Law is dead." - Jensen Huang, GTC 2013 Trillions of Operations per Second (TOPS) 10⁹ 108 107 106 105 104 10³ 10² 1980 Single-threaded CPU perf 1990 GPU-Computing perf 2X per year 1.5X perf per year 2000 2010 1.1X per year 2020 1000X In 10 years 2030#6ff Waves of Adoption of Accelerated Computing A generational computing platform shift Enterprise Cloud Service Providers & Consumer Internet Industrial Digitalization Autonomous Vehicles & Robotics A new computing era has begun. Accelerated computing enabled the rise of Al, which is driving a platform shift from general purpose to accelerated computing, and enabling new, never-before-possible applications. The trillion dollars of installed global data center infrastructure will transition to accelerated computing to achieve an order of magnitude better performance, energy-efficiency and cost. Hyperscale cloud service providers and consumer internet companies have been the early adopters of Al and accelerated computing, with broader enterprise adoption now under way. Al and accelerated computing will also make possible the next big waves - autonomous machines and industrial digitalization. NVIDIA#7ff NVIDIA Accelerated Computing for Every Wave Enterprise Cloud Service Providers & Consumer Internet Industrial Digitalization Autonomous Vehicles & Robotics NVIDIA Omniverse is a software platform for designing, building, and operating 3D and virtual world simulations. It harnesses the power of NVIDIA graphics and Al technologies and runs on NVIDIA-powered data centers and workstations. NVIDIA DRIVE is a full-stack platform for autonomous vehicles (AV) that includes hardware for in-car compute, such as the Orin system-on-chip, and the full AV and Al cockpit software stack. NVIDIA DGX Cloud is a cloud service that allows enterprises immediate access to the infrastructure and software needed to train advanced models for generative Al and other groundbreaking applications. NVIDIA AI Enterprise is the operating system of Al, with enterprise-grade security, stability, manageability and support. It is available on all major CSPs and server OEMs and supports enterprise deployment of Al in production. NVIDIA HGX is an Al supercomputing platform purpose-built for Al. It includes 8 NVIDIA GPUs, as well as interconnect and networking technologies, delivering order-of-magnitude performance speed-ups for Al over CPU servers. It is broadly available from all major server OEMs/ODMs. NVIDIA DGX, an Al server based on the same architecture, along with NVIDIA Al software and support, is also available. NVIDIA#8NVIDIA's Accelerated Computing Ecosystem The NVIDIA accelerated computing platform has attracted the largest ecosystem of developers, supporting a rapidly growing universe of applications and industry innovation. Developers can engage with NVIDIA through CUDA - our parallel computing programming model introduced in 2006 - or at higher layers of the stack, including libraries, pre-trained Al models, SDKs and other development tools. 300 Libraries 400 Al Models 100 Updated in the Last Year 1.8M 2020 6K Developers 2020 4M 2023 Al Startups 15K 2023 CUDA Downloads* 20M 2020 *Cumulative 700 45M GPU-Accelerated Applications 2020 2023 3,200 2023 NVIDIA#9Installed Base Developers NVIDIA's Multi-Sided Platform and Flywheel Scale R&D $ ↓ Speed-Up End-Users NVIDIA Accelerated Computing Virtuous Cycle Cloud & OEMs The virtuous cycle of NVIDIA's accelerated computing starts with an installed base of several hundred million GPUs, all compatible with the CUDA programming model. ● ● ● For developers - NVIDIA's one architecture and large installed base give developer's software the best performance and greatest reach For end users - NVIDIA is offered by virtually every computing provider and accelerates the most impactful applications from cloud to edge For cloud providers and OEMs - NVIDIA's rich suite of Acceleration Platforms lets partners build one offering to address large markets including media & entertainment, healthcare, transportation, energy, financial services, manufacturing, retail, and more For NVIDIA - Deep engagement with developers, computing providers, and customers in diverse industries enables unmatched expertise, scale, and speed of innovation across the entire accelerated computing stack - propelling the flywheel NVIDIA#10Huge ROI from Al Driving a Powerful New Investment Cycle Al can augment creativity and productivity by orders of magnitude across industries Knowledge workers will use copilots based on large language models to generate documents, answer questions, or summarize missed meetings, emails and chats - adding hours of productivity per week. Copilots specialized for fields such as software development, legal services or education can boost productivity by as much as 50%. Social media, search and e-commerce apps are using deep recommenders to offer more relevant content and ads to their customers, increasing engagement and monetization. Creators can generate stunning, photorealistic images with a single text prompt - compressing workflows that take days or weeks into minutes in industries from advertising to game development. Call center agents augmented with Al chatbots can dramatically increase productivity and customer satisfaction. Drug discovery, financial services, agriculture and food services and climate forecasting are seeing order-of-magnitude workflow acceleration from Al. Media Player Microsoft Edge Microsoft Endpoint Manager Microsoft Intune Management Ext...v Microsoft Office Tools 89 Database Compare Office Language Preferences Spreadsheet Compare Telemetry Log for Office Microsoft Edge Weather Play and explore Xbox Console. Movies & TV Office Al Copilots Over 1B knowledge workers Legal Services, Education ... 1M legal professionals in the US 9M educators in the US Customer Service with Al 15M call center agents globally Search & Social Media $700B in digital advertising annually 2/11 Al Software Development 30M software developers globally off do &0 . Al Content Creation 50M creators globally 61.75 61.50 130.000 pe Volume 315,900 62.75 Offers 73.00 73.29 73.50 Drug Discovery 1018 molecules in chemical space 40 exabytes of genome data Source: Goldman Sachs, Cowen, Statista, Capital One, Wall Street Journal, Resource Watch, NVIDIA internal analysis 242.400 142,600 72.75 Volume 423.400 563,000 Financial Services 678B annual credit card transactions Agri-Food | Climate 1B people in agri-food worldwide Earth-2 for km-scale simulation NVIDIA#11TEXT AUDIO IMAGE 3D VIDEO DNA PROTEIN MOLECULE ANIMATION Quantum co mechanics to B hall Generative Al The most important computing platform of our generation HHILI $ le AN Quantum co mechanics to ANIMATION MOLECULE PROTEIN DNA VIDEO 3D IMAGE AUDIO TEXT The era of generative Al has arrived, unlocking new opportunities for Al across many different applications. Generative Al is trained on large amounts of data to find patterns and relationships, learning the representation of almost anything with structure. It can then be prompted to generate text, images, video, code, or even proteins. For the very first time, computers can augment the human ability to generate information and create. 1,600+ Generative Al companies are building on NVIDIA. NVIDIA#12Training Compute (petaFLOPS) 101⁰ 109 108 107 106 105 104 103 10² Modern Al is a Data Center Scale Computing Workload Data centers are becoming Al factories: Data as input, intelligence as output All Al Models Excluding Transformers: 8X / 2yrs Transformer Al Models: 275X / 2yrs AlexNet Seq2Seq InceptionV3 Resnet ● VGG-19 Xception ● ResNeXt Microsoft T-NLG ● GPT-2 · Megatron XLNet. ● GPT-1 Transformer ELMO DenseNet201 BERT Large Megatron-Turing NLG 530B GPT-3 ● Wav2Vec 2.0 MOCO ResNet50 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 Al Training Computational Requirements 2022 Large Language Models, based on the Transformer architecture, are one of today's most important advanced Al technologies, involving up to trillions of parameters that learn from text. Developing them is an expensive, time-consuming process that demands deep technical expertise, distributed data center-scale infrastructure, and a full-stack accelerated computing approach. Fueling Giant-Scale Al Infrastructure NVIDIA compute & networking GPU | DPU | CPU NVIDIA#13Classical Computing - 960 CPU-only servers ‒‒‒ - Full-Stack & Data Center Scale Acceleration Drive significant cost savings and workload scaling - Application CPU server racks - LLM Workload: Bert-Large Training and Inference | CPU Server: Dual-EYPC 7763 | GPU Server: Dual-EPYC 7763 +8X H100 PCIe GPUs Accelerated Computing - 2 GPU servers Application Re-Engineered for Acceleration CUDA-X Acceleration Libraries Magnum 10 25X lower cost 84X better energy-efficiency NVIDIA#14The High ROI of High Compute Performance 4-Year Cost of Al Infrastructure ~$1B 16K GPU DC Facility Build & Operate GPU Compute Networking 15% Utilization Increase Worth $350M+ 4-Year Rental Opportunity @$4 per GPU-HR ~$2.5B 25% Performance Increase Worth $600M+ NVIDIA#15NVIDIA. PARTNERS NVIDIA Go-to-Market Across Cloud and On-Premises Reaching customers everywhere aws CLOUD DGX Cloud Google Cloud HGX NVIDIA AI Foundations Google Cloud Microsoft ORACLE Azure Infrastructure Microsoft Azure INFERENCE ORACLE CLOUD Infrastructure ON-PREM DELL Technologies MGX DGX Hewlett Packard Enterprise AGX Lenovo IGX NVIDIA#16TRAINING Training & Inference One Architecture Cloud On-Prem | Edge NVIDIA DGX | HGX H100 NVIDIA L40S 400000 |-|-|- IN THE DATA CENTER NVIDIA L40 Image Generation NVIDIA L4 Al Video NVIDIA H100 | L40S Universal GPUs INFERENCE NVIDIA Grace Hopper RecSys, Gen Al AT THE EDGE IGX Industrial-Grade System for Healthcare, Logistics, Manufacturing AGX Functionally-Safe System for Autonomous Vehicles NVIDIA#17NVIDIA AI Playground NVIDIA Al Foundations DGX Cloud Microsoft Google Cloud CLOUD Infrastructure ■ Azure NVIDIA AI Enterprise Enterprise is the Next Big Generative Al Opportunity NVIDIA Al Enterprise LLM Model Container DGX Cloud Microsoft Google Cloud Enterprise On-Prem DELL Lenovo Hewlett Packard Enterprise vmware Enterprise SaaS & Al Platforms A Adobe gettyimages servicenow. databricks Hugging Face snowflake WPP 8 Al Chatbot "RAG" Vector DB Enterprise Al Chatbots are built as Retrieval Augmented Generation (RAG) workflows, which augment the knowledge in the LLM with vectorized Enterprise data. These Chatbots serve as apprentices, improving the productivity of every employee in every Enterprise company. NVIDIA delivers this capability to Enterprises by packaging LLMs with NVIDIA AI Enterprise, the runtime for hosting the LLMs, into containers that can be deployed anywhere - on any cloud, on premises, or within Enterprise SaaS applications. Cloud Al APIs NVIDIA#18NVIDIA DGX Cloud Al-training-as-a-service platform for the era of generative Al NVIDIA AI FOUNDATIONS NeMo | Picasso Microsoft Azure DGX CLOUD Google Cloud ORACLE CLOUD Infrastructure NVIDIA DGX Cloud is a cloud service that allows enterprises immediate access to the infrastructure and software needed to train advanced models for generative Al and other groundbreaking applications. DGX Cloud provides dedicated clusters of NVIDIA DGX AI supercomputing, paired with NVIDIA Al software. Enterprise customers can also use the NVIDIA AI Foundations model making service, which includes NVIDIA NeMo for training custom LLMs and NVIDIA Picasso for custom generative Al models for visual design. The service is equipped with models, tools, and accelerated computing for training, customizing, optimizing, and deploying Al. NVIDIA#19NVIDIA AI Enterprise NVIDIA AI Enterprise is software for deploying and running Al with enterprise-grade security, API stability, manageability and support. Cloud-native and available in every major cloud marketplace - AWS, Microsoft Azure, Google Cloud Platform and Oracle Cloud. Certified to run on servers and workstations from all major OEMs. ↓ Hello LLM OO Medical Imaging Al Use Cases and Workflows bok Speech Al NVIDIA AI Enterprise The operating system for enterprise Al Video Analytics Recommenders. Route Optimization Cybersecurity More Cloud Run Anywhere Azure | GCP | OCI | AWS Consumption pricing per GPU-hour NVIDIA AI Enterprise NVIDIA Certified Server Dell | HPE | Lenovo Subscription pricing per GPU/year (included with H100 PCIe/DGX) NVIDIA#20GSI & Service Delivery accenture Booz | Allen | Hamilton Capgemini Deloitte. Infosys tcs TATA CONSULTANCY SERVICES wipro NVIDIA AI Enterprise Broad and deep ecosystem and distribution to reach every enterprise + Al Platforms databricks Hugging Face aws Public Cloud Marketplaces **** ORACLE Cloud Infrastructure snowflake Google Cloud Microsoft Azure ()) Software Platforms gettyimages servicenow Private Cloud Server OEMs shutterstock vmware® BOXX HPE GreenLake CISCO hp A Adobe DELL Technologies Lenovo. SUPERMICR= NVIDIA#21$11,716 FY19 $10,918 FY20 Revenue ($M) $16,675 Driving Strong & Profitable Growth FY21 $26,914 FY22 $26,974 FY23 $20,699 1H FY24 $15,000 $12,000 $9,000 $6,000 $3,000 $0 $4,407 38% FY19 Operating Income (Non-GAAP, $M) 42 1H FY21 $3,735 44 34% FY20 $6,803 43 41% FY21 -Operating Margin (Non-GAAP) $12,690 47% FY22 $9,040 1H FY24 34% FY23 $10,828 331 23 O 70 52% 1H FY24 Fiscal year ends in January. Refer to Appendix for reconciliation of Non-GAAP measures. Operating margins rounded to the nearest percent. 70% 60% 50% 40% 30% Gaming Data Center ProViz ■Auto ■ OEM & Other FY23 financial metrics reflect a $2.2B charge for inventory and related reserves primarily related to Data Center and Gaming. NVIDIA#22NVIDIA Gross Margins Reflect Value of Acceleration Accelerated computing requires full-stack and data center-scale innovation across silicon, systems, algorithms and applications. Significant expertise and effort are required, but application speed-ups can be incredible, resulting in dramatic cost and time-to-solution savings. For example, 2 NVIDIA HGX nodes with 16 NVIDIA H100 GPUs that cost $400K can replace 960 nodes of CPU servers that cost $10M for the same LLM workload. NVIDIA chips carry the value of the full-stack, not just the chip. Cost comparison example based on latest available NVIDIA A 100 GPU and Intel CPU inference results in the commercially available category of the MLPerf industry benchmark; includes related infrastructure costs such as networking. $7,233 62% FY19 Gross Profit (Non-GAAP, $M) -Gross Margin (Non-GAAP) $6,821 63% FY20 $10,947 66% FY21 $17,969 67% FY22 $15,965 59% FY23 $14,417 70% 1H FY24 FY23 financial metrics reflect a $2.2B charge for inventory and related reserves primarily related to Data Center and Gaming. Fiscal year ends in January. Refer to Appendix for reconciliation of Non-GAAP measures. Gross margins are rounded to the nearest percent. NVIDIA#23$3.1B FY19 Free Cash Flow (Non-GAAP) $4.3B FY20 $4.7B FY21 $8.0B Strong Cash Flow Generation FY22 $3.8B FY23 Fiscal year ends in January. Refer to Appendix for reconciliation of Non-GAAP measures. ¹ Subject to continuing determination by our Board of Directors. $8.7B 1H FY24 Capital Allocation Share Repurchase $10B repurchased in FY23 Additional $25B in stock repurchases authorized, adding to $4B which remained as of end of Q2 Dividend $398M in FY 2023 Plan to Maintain¹ Strategic Investments Growing Our Talent Platform Reach & Ecosystem NVIDIA#24Data Center 56% of FY23 revenue FY23 Revenue $15.0B 5-yr CAGR 51% DGX/HGX/MGX/IGX systems GPU | CPU | DPU | Networking NVIDIA Al software Our Market Platforms at a Glance 6600 RETURNAL GACKOOK FORT DYINGLIGHT2 STAY HUMAN PORTAL WITH BTX MINECRAFT Gaming 33% of FY23 revenue FY23 Revenue $9.1B 5-yr CAGR 10% GeForce GPUs for PC gaming GeForce NOW cloud gaming PLAQUETA Professional Visualization 6% of FY23 revenue FY23 Revenue $1.5B 5-yr CAGR 11% NVIDIA RTX GPUs for workstations Omniverse software 0. Automotive 3% of FY23 revenue FY23 Revenue $0.9B 5-yr CAGR 10% DRIVE Hyperion sensor architecture with AGX compute DRIVE AV & IX full stack software for ADAS, AV & Al cockpit NVIDIA#2551% 5-YR CAGR Through FY23 $2,932 FY19 $2,983 FY20 Revenue ($M) $6,696 Data Center The leading computing platform for AI, HPC & graphics FY21 $10,613 FY22 $15,005 FY23 $14,607 1H FY24 Leader in Al & HPC #1 in Al training and inference Used by all hyperscale & major cloud computing providers and 40,000 enterprises Powers 74% of the TOP500 supercomputers Growth Drivers Rapid Al adoption across industries Full-stack Al | Software Three chip strategy - GPU | CPU | DPU Rising computation requirements for modern Al Data-center scale innovation Omniverse NVIDIA#26NVIDIA AI - One Architecture | Train and Deploy Everywhere From Two-Year Rhythm to One-Year Rhythm | Training & Inference | x86 & Arm | Hyperscale & Enterprise 2021 A 100 2023 H100 Quantum Spectrum-X 2024 GH200NVL GH200 H200 L40S 400G 400G GB200NVL GX200NVL GB200 B100 B40 800G 2025 800G GX200 X100 X40 1,600G 1,600G Arm Training & Inference Arm Inference X86 Training & Inference X86 Enterprise & Inference InfiniBand Al Infrastructure Ethernet-X Enterprise & Hyperscale Al Infrastructure NVIDIA#27NVIDIA GH200 72-Core Grace CPU 500 GB LPDDR5X 4 PFLOPS Hopper GPU 141 GB/5 Tbps HBM3e NVIDIA Grace Hopper Superchip 6 6 es 6 6 6 ECHICHURCH 8 8 ē 8 NVIDIA BlueField-3 NVIDIA#28$250B $OB Revenue FY20 Addressing the Entire Data Center $1T+ data center infrastructure installed base FY21 FY22 Source: Mercury Research, Dell'Oro Assumes NVIDIA Fiscal Year aligns to Calendar Year (e.g. FY23 = CY22) FY23 Other Data Center Infrastructure Network Infrastructure Servers NVIDIA Data Center Server CPU Q2 FY24 Annualized NVIDIA#2910% 5-YR CAGR Through FY23 $6,246 FY19 $5,518 FY20 Revenue ($M) $7,759 FY21 Gaming GeForce - the world's largest gaming platform $12,462 FY22 $9,067 FY23 $4,726 1H FY24 Leader in PC Gaming Strong #1 market position 15 of the top 15 most popular GPUs on Steam Leading performance & innovation 200M+ gamers on GeForce Growth Drivers Rising adoption of NVIDIA RTX in games Expanding universe of gamers & creators Gaming laptops & Gen Al on PCs GeForce NOW Cloud gaming NVIDIA#30GeForce Gaming Revenue 20% CAGR GeForce Extends Growth, Large Upgrade Opportunity FY20 FY23 3YR CAGR ASP 10% Units 9% More Gamers, Richer Mix Installed Base 47% RTX 20% RTX3060+ Performance RTX 3060+ Installed Base Needs Upgrade Source: NVIDIA estimates $699+ Cumulative Sell-Through $ 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 Weeks After Launch NVIDIA Ada NVIDIA Ampere NVIDIA Turing Ada: 3X Turing Ramp at $699+ NVIDIA#3111% 5-YR CAGR Through FY23 $1,130 FY19 $1,212 FY20 Revenue ($M) $1,053 FY21 $2,111 FY22 Professional Visualization Workstation graphics $1,544 FY23 $674 1H FY24 Leader in Workstation Graphics 95% + market share in graphics for workstations 45M Designers and Creators Strong software ecosystem with over 100 RTX accelerated and supported applications Growth Drivers Ray Tracing and generative Al revolutionizing design and content creation Expanding universe of designers and creators Collaborative 3D design / Omniverse Hybrid work environments NVIDIA#3210% 5-YR CAGR Through FY23 $641 FY19 $700 FY20 Revenue ($M) $536 FY21 $566 FY22 Automotive Autonomous Vehicles (AV) & Al Cockpit $903 FY23 $549 1H FY24 Leader in Autonomous Driving Revenue growth primarily fueled by NVIDIA DRIVE, our AV and Al cockpit platform with full software stack Inflection in FY23 driven by AV as DRIVE Orin SoC began to ramp Next-generation DRIVE Thor SoC to ramp in FY26 Growth Drivers Adoption of centralized car computing and software-defined vehicle architectures $14B Design Win Pipeline Through FY29 AV software and services: Mercedes Benz Jaguar Land Rover NVIDIA#33ff $1 Trillion Long-Term Annual Market Opportunity Enterprise Cloud Service Providers & Consumer Internet Industrial Digitalization Autonomous Vehicles & Robotics Gaming $100B Omniverse Enterprise Autonomous Machines Data Center Systems $300B $150B $300B NVIDIA AI Enterprise & DGX Cloud $150B NVIDIA#34Summary Gen Al is the tipping point for the new computing era Al is the new software and Accelerated Computing the new hardware Huge ROI from Gen Al - from new revenue or dramatically lower costs - is driving a powerful new investment cycle NVIDIA's accelerated computing platform delivers unmatched performance and TCO savings Strong revenue, operating profit, and cash flow growth $1T market opportunity NVIDIA#35Reconciliation GAAP Financial Measures of Non-GAAP to#36Gross Margin ($ in Millions & Margin Percentage) FY 2019 FY 2020 FY 2021 FY 2022 FY 2023 1H FY 2023 1H FY 2024 Reconciliation of Non-GAAP to GAAP Financial Measures Non-GAAP $7,233 61.7% $6,821 62.5% $10,947 65.6% $17,969 66.8% $15,965 59.2% $8,636 57.6% $14,417 69.7% A. Consists of amortization of intangible assets and inventory step-up B. Stock-based compensation charge was allocated to cost of goods sold Acquisition-Related and Other Costs (A) (425) (2.6) (344) (1.4) (455) (1.7) (214) (239) (1.2) Stock-Based Compensation (B) (27) (0.2) (39) (0.4) (88) (0.5) (141) (0.5) (138) (0.5) (76) (0.5) (58) (0.3) IP-Related Costs (35) (0.3) (14) (0.1) (38) (0.2) (9) (16) (0.1) T (10) GAAP $7,171 61.2% $6,768 62.0% $10,396 62.3% $17,475 64.9% $15,356 56.9% $8,346 55.7% $14,110 68.2% NVIDIA#37Reconciliation of Non-GAAP to GAAP Financial Measures (contd.) Operating Income and Margin ($ in Millions & Margin Percentage) FY 2019 FY 2020 FY 2021 FY 2022 FY 2023 1H FY 2023 1H FY 2024 Non-GAAP $4,407 37.6% $3,735 34.2% $6,803 40.8% $12,690 47.2% $9,040 33.5% $5,280 35.2% $10,828 52.3% Acquisition Termination Cost T T (1,353) (5.0) (1,353) (9.0) T Acquisition-Related and Other Costs (A) (2) (31) (0.3) (836) (5.0) (636) (2.5) (674) (2.5) (324) (2.2) (311) (1.5) Stock-Based Compensation (B) (557) (4.7) (844) (7.7) (1,397) (8.4) (2,004) (7.4) (2,710) (10.0) (1,227) (8.2) (1,576) (7.6) A. Consists of amortization of acquisition-related intangible assets, inventory step-up, transaction costs, compensation charges, and other costs B. Stock-based compensation charge was allocated to cost of goods sold, research and development expense, and sales, general and administrative expense C. Comprises of legal settlement costs, contributions, restructuring costs and assets held for sale related adjustments IP-Related Costs (35) (0.3) (14) (0.1) (38) (0.2) (9) (16) (0.1) (10) T Other (C) (9) (0.1) I I I (63) (0.2) (9) 10 GAAP $3,804 32.5% $2,846 26.1% $4,532 27.2% $10,041 37.3% $4,224 15.7% $2,367 15.8% $8,941 43.2% NVIDIA#38($ in Millions) FY 2019 FY 2020 FY 2021 FY 2022 FY 2023 1H FY 2023 1H FY 2024 Reconciliation of Non-GAAP to GAAP Financial Measures Free Cash Flow $3,143 $4,272 $4,677 $8,049 $3,750 $2,171 $8,691 Purchases Related to Property and Equipment and Intangible Assets 600 489 1,128 976 1,833 794 537 Principal Payments on Property and Equipment and Intangible Assets 17 83 58 36 31 Net Cash Provided by Operating Activities $3,743 $4,761 $5,822 $9,108 $5,641 $3,001 $9,259 NVIDIA#39NVIDIA.