September 2018

INVESTOR UPDATE

SAFE HARBOR

Forward-Looking Statements

Except for the historical information contained herein, certain matters in this presentation including, but not limited to, statements as to: the world’s demand for computing power

growing exponentially; NVIDIA’s ability to advance computing, including by optimizing across the entire stack, and the rate of advancing computing; NVIDIA’s growth into multiple

markets, including through the use of its unified architecture; the availability of NVIDIA GPUs and Jetson AGX Xavier DevKit; NVIDIA GPUs accelerating deep learning frameworks and

applications; the benefits, impact, performance and abilities of: NVIDIA’s computing platform, the Turing architecture, RT Core, ray tracing, Tensor Core, GeForce, GeForce RTX,

Quadro RTX, RTX Servers, NVIDIA’s GPUs and accelerated computing platform, DGX, inference performance, TensorRT, DGX-2, HGX-2, Xavier, AGX, DRIVE AGX, Jetson AGX, Jetson

AGX Xavier, Clara AGX, DRIVE, DRIVE AGX, DRIVE AGX DevKit, NVIDIA Isaac, Clara AGX Xavier, GPU Servers, and our products, technologies, services, platforms and programs; our

market and industry opportunities and TAM; DGX being the world’s most advanced AI platform; shorter training time equaling faster progress in advancing AI; NVIDIA’s ability to

master inference; every industry tapping into the power of AI; DGX-2 being the world’s most powerful AI system for data center deployments; the value of accelerated datacenter

performance; Xavier enabling automation in many large industries; NVIDIA’s full stack enabling market leaders to take advantage of our platform; the entities developing on DRIVE

and creating the future of transportation; the next chapter of AI being autonomous machines; NVIDIA tackling big opportunities in some of the largest markets; accelerated

computing being the way forward as Moore’s Law has ended; NVIDIA’s unified architecture driving growth and margin expansion across markets; our growth and growth drivers; our

strategies; market trends; future financial results, estimates and forecasts; how NVIDIA innovates; our production roadmap and schedules; and other predictions and estimates are

forward-looking statements within the meaning of the Private Securities Litigation Reform Act of 1995. 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 products 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. 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 annual report on Form 10-K and quarterly

reports on Form 10-Q. Copies of reports we file with the SEC are posted on our website and are available from NVIDIA without charge. These forward-looking statements are not

guarantees of future performance and speak only as of the date hereof, based on information currently available to us. Except as required by law, NVIDIA disclaims any obligation to

update these forward-looking statements to reflect future events or circumstances.

Financial Measures

This presentation contains historical revenue amounts for certain of our market platforms and businesses which provides investors with additional information to supplement the

segment reporting information contained in our Form 10-K for the fiscal year ended January 28, 2018. In addition to U.S. GAAP financials, this presentation includes certain non-

GAAP financial measures. These non-GAAP financial measures are in addition to, and not a substitute for or superior to, measures of financial performance prepared in accordance

with U.S. GAAP. See our website for a reconciliation between each non-GAAP measure and the most comparable GAAP measure. Where we present non-GAAP financial measures,

including non-GAAP gross margin, non-GAAP operating margin, and free cash flow we generally exclude stock-based compensation, product warranty charge, restructuring costs, and

other charges, where applicable. Free cash flow is calculated as GAAP net cash provided by operating activities less purchases of property and equipment and intangible assets.

The world’s demand for computing power continues to grow exponentially, yet CPUs are no longer keeping up as Moore’s Law has ended.

NVIDIA pioneered accelerated computing to solve this challenge.

Optimizing across the entire stack —from silicon to software — allows NVIDIA to advance computing in the post-Moore’s Law era for large and important markets:

Gaming, Pro Viz, High Performance Computing (HPC), AI, Cloud, Transportation, Healthcare, Robotics, AI IOT

ACCELERATED COMPUTING 1000X EVERY 10 YEARS

1980 1990 2000 2010 2020

103

105

107

GPU PERFORMANCECPU PERFORMANCE

+

GROWING INTO MULTIPLE LARGE MARKETS

Revenue in millions. 1H FY18 and 1H FY19 represents the first six months of each fiscal year.

Gaming+59%

Auto+9%

$0

$1,000

$2,000

$3,000

$4,000

1H FY18 1H FY19

$0

$100

$200

$300

$400

1H FY18 1H FY19

$3.5B

Pro Viz+21%

$0

$150

$300

$450

$600

1H FY18 1H FY19

$532M

Datacenter(HPC, Cloud, AI)

+77%

$0

$400

$800

$1,200

$1,600

1H FY18 1H FY19

$1.5B $306M

$0

$2

$4

$6

$8

$10

$12

$14

FY16 Annualized FY19

$5.0B

3 YEARS OF GROWTH AND MARGIN EXPANSION

Gross margin, operating margin, and FCF are non-GAAP measures. 1H FY19 represents first six months of the fiscal year.Annualized FY19 revenue and FCF is calculated based on Q2 FY19 results multiplied by four.

50%

55%

60%

65%

70%

FY16 1H FY19

0%

10%

20%

30%

40%

50%

FY16 1H FY19

$0

$1

$2

$3

$4

FY16 Annualized FY19

$1.1B

Gross MarginUp ~700 bps

Operating MarginUp ~2000 bps

Free Cash FlowUp 2.9X

22%57%

RevenueUp 2.5X

$12.5B 43%

64%

$3.1B

Three types of chips — GPU, SOC, and NVSwitch.

Three types of systems — GTX/RTX for graphics cards, DGX for AI/HPC, AGX for AI machines.

Accelerated computing requires an end-to-end stack, vertical market expertise, and ecosystem partners.

One architecture leverages scale and investment to address large, growing markets.

ONE ARCHITECTURE, EIGHT LARGE MARKETS

ACCELERATION STACKS

GAMING HPC TRANSPORTATION HEALTHCARE

PRO VIZ AI ROBOTICS AI IOT

DEVELOPERS

USERS

Best platform > more developers > more apps > more customers.

NVIDIA GPUs are available in every cloud, from every systems maker.

Accelerate every deep learning framework; 600 applications, including top 15 HPC apps.

1M DEVELOPERS ON NVIDIA COMPUTING PLATFORM

20182013

25K

20182013

8M

CUDA Downloads — 5X in 5 YrsGTC Attendees — 7X in 5 Yrs

TENSOR CORE RT CORE

SHADER | COMPUTE

NVIDIA invents RTX hybrid rendering model that combines rasterization, ray tracing, and AI.

Two new processors make it possible —RT Core and Tensor Core.

New RT Core achieves holy grail of computer graphics — real-time ray tracing.

New multi-precision Tensor Core is a giant leap for AI inference — up to 12X Pascal.

Advanced shaders deliver up to 2X speed-up for traditional rasterized games.

TURING — A GIANT LEAP FOR GRAPHICS AND AI

0

20

40

60

80

100

120

TURING 9X PEAK FLOPS

PASCALTITAN Xp

TURING2080 Ti

114

14.214.212.9

FP32 INT32 TC FP32 INT32 TC

MAXWELL PASCAL TURING

GTX 980 Ti

GTX 980

GTX 1080 Ti

GTX 1080

RTX 2080 Ti

RTX 2080

4K 60FPS

DEEP LEARNINGIMAGING

MAXWELL PASCAL TURING

GTX 980 Ti

GTX 980

GTX 1080 Ti

GTX 1080

4K 60FPSRTX 2080

RTX 2080 Ti

GeForce RTX is the biggest GPU leap in 10 years — first real-time ray tracing GPU, first 100+ TFLOPS GPU, first neural graphics processing.

First to enable 60Hz gaming on 4K monitors.

GeForce RTX delivers 2X performance boost with Deep Learning Super Sampling (DLSS, a new AI-enabled anti-aliasing technique), and up to 6X for ray-traced graphics.

Over 30 games support RTX including Battlefield V, Shadow of the Tomb Raider, and Metro Exodus.

RTX and rising GPU requirements help outgrow gaming market.

GEFORCE RTX RESETS $100B GAMING MARKET

FASTEST GAMING GPUPLAYS AT 4K 60FPS

DEEP LEARNING IMAGING WITH 114 TFLOPS TENSOR CORE

Quadro RTX delivers photoreal graphics that creators didn’t expect for another 5-10 years.

GPUs can now accelerate photoreal rendering for large industries that previously only used CPU server farms — 1.5M CPU servers worldwide.

RTX Server with 8 GPUs can replace 60 dual-CPU servers — reducing cost, space, and power.

Millions of servers, workstations, and PCs — estimated $50B of computing —are in use today for photoreal rendering.

RTX OPENS $250B VISUAL EFFECTS INDUSTRY

DESIGN AEC

VISUALIZATION FILM & TELEVISION

RTX-ACCELERATED RENDERERSPHOTOREAL VFX

RTX-ACCELERATED RENDER FARM: 1/4 THE COST, 1/10 THE SPACE, 1/11 THE POWER

11%

25%

56%

2015Tesla K80

2017Tesla P100

2018Tesla V100

DELIVERED 56% OF NEW TOP500 PERFORMANCE IN 2018

17 OF TOP 20 MOST ENERGY-EFFICIENT

5 OF WORLD’S TOP 7 MOST POWERFUL

#1 Summit: 122 PF#3 Sierra: 72 PF#5 ABCI: 20 PF#6 Piz Daint: 20 PF #7 Titan: 18 PF

NVIDIA powers five of top seven supercomputers, 17 of top 20 most energy-efficient.

Five of the six 2018 Gordon Bell prize finalists did their work on the new NVIDIA GPU-accelerated Summit and Sierra systems.

Delivered 56% of new performance on the latest Top500 list.

Accelerate ~100 of the Top500 —4X expansion opportunity.

NVIDIA GPUS POWER NEW SUPERCOMPUTERS IN $10B HPC MARKET

FASTESTSINGLE NODE

FASTESTSINGLE CHIP

FASTESTSINGLE NODE

FASTESTAT SCALE

FASTESTAT SCALE

108minutes

24hours

5hours

32minutes

6.6minutes

IMAGES TRANSLATION

DGX-2 WORLD’S LARGEST GPU: 2 PFLOPS, 512GB HBM2

Images: Single Chip: Resnet-50 V1 Training on Tesla V100 with NVIDIA NGC MXNet Container 18.09 Pre-release by NVIDIA. Single Node: Resnet-50 V1 Training on NVIDIA DGX-2 with NVIDIA NGC MXNet Container 18.09 by NVIDIA. At scale: Resnet-50 Training with 2048 P40 GPUs by Tencent. Translation: Single Node Strong NMT (Transformer) Training on WMT ‘14 English-German Translation with DGX-1 by Facebook Research. At Scale Strong NMT (Transformer) Training on WMT ‘14 English-German Translation with 16 DGX-1 Systems by Facebook Research.

AI training is the ultimate HPC challenge.

NVIDIA DGX is a reference full-stack-optimized system designed for AI, HPC, and big data analytics.

Shorter time to train equals faster progress in advancing better and more accurate AI.

WORLD’S MOST ADVANCED AI PLATFORM

12,000+ NVIDIA TENSORRT DOWNLOADS FROM 4,000 COMPANIES

CAMBRIAN EXPLOSION OF NETWORKS

Speech

NLP

ImageMaps

Video

Search

Programmability: Increasing diversity of neural networks

Latency: The right answer, right now

Accuracy: If the answer isn’t right, speed doesn’t matter

Size of network: Exploding neural network complexity

Throughput: Concurrently run many AI models

Efficiency: Deliver performance within power budget

Rate of learning: Constant retraining and deployment, sometimes multiple times per day

MASTERING THE COMPLEX CHALLENGE OF INFERENCE

Images: Fastest Inference: Resnet-50 Inference on Tesla V100 with TensorRT, Batch size: 1, Int8 optimized. Inference Throughput: Resnet-50 Inference on Tesla V100 with TensorRT, Batch size: 128, Int8 Optimized. Inference Efficiency: Resnet-50 Inference on Tesla T4, Int8 optimized, batch size = 32. Translation: GMNT Inference on Newstest2015 test dataset on Tesla V100.

13,160words/second

IMAGES TRANSLATION

6,250images/second

1millisecond

56images/second/watt

HIGHEST INFERENCE EFFICIENCY

HIGHEST INFERENCE THROUGHPUT

FASTEST INFERENCE

HIGHEST INFERENCE THROUGHPUT

Convolutional Networks Recurrent Networks

Generative Adversarial Networks Reinforcement Learning

GIANT LEAPS IN INFERENCE PERF.TENSORRT HYPERSCALE

21XASR

Deep Speech 2

36XNLPGNMT

20XRECOM

NCF

8XTTS

WaveNet

27XVIDEO/IMAGE

ResNet-50

DNN Models

NV DL SDK

Kubernetes

NV Docker

TensorRT

Inference Server

TENSORRT HYPERSCALE PLATFORM BOOSTS SERVER UTILIZATION

Tesla T4 is a universal inference accelerator designed for hyperscale datacenters.

TensorRT Hyperscale is a fully optimized Kubernetes stack and an inference server that enables multiple types of models from different frameworks to run concurrently on one GPU node.

TensorRT Hyperscale enables higher utilization, scalability, and resilience for large-scale deep learning operations.

TENSOR CORE OPS16X PASCAL FP INFERENCE

5.52265

130

260

0

50

100

150

200

250

300

FLOAT INT8 INT4 FLOAT INT8 INT4

P4 T4

65

130

260

5.522

FLOAT INT8 INT4 FLOAT INT8 INT4

0

5,000

10,000

15,000

20,000

2013 2014 2015 2016 2017 2018 2019

Maxwell FP32

Kepler FP32

Pascal FP32

Volta FP16

TuringINT8

TuringINT4

ResN

et-

50 I

nfe

rence (

i/s)

$20B TAM IN 2023 INDUSTRY LEADER ADOPTION

HGX FOR CLOUDDGX FOR DATACENTERS

Transportation

Healthcare

Public Sector

Manufacturing

Oil & Gas

Cloud/Other

Every industry is tapping into the power of AI; our full-system expertise enables enterprise adoption.

DGX-2: World’s most powerful AI system for datacenter deployments; $399K system can replace $3M of CPU servers.

HGX-2: Cloud server platform for OEM and ODM partners; Single HGX-2 can replace 300 dual-CPU server nodes.

AI IS REVOLUTIONIZING THE ENTERPRISE

WORKLOAD BASELINECPU-Only

HPC (Amber, LAMMPS, NAMD, VASP)

VISUALIZATION(Rendering, Ray Tracing)

AI TRAINING(Caffe2, TensorFlow, MXNet)

AI INFERENCE (Image, Speech, Translation)

Speed Up 1X 20X 60X >100X 200X

Servers 5,000 250 84 <50 25

Capex $45M $11M $10.5M $7.5M $1.5M

3-Year Opex

(Power + Cooling)$19.5M $2.5M $2M $1M $0.5M

TCO Savings N/A 79% 81% 86% 97%

“THE MORE YOU BUY, THE MORE YOU SAVE”

ACCELERATED DATACENTER VALUE

Note(s): CPU Baselined to 5000 Servers for each workload | Capex Costs: CPU node with 2x Skylake CPU’s ~$9K; | Opex Costs: Power & cooling is $180/kW/month | Power: CPU server + n/w = 0.6 KW; GPU server + n/w = 1.6 KW; DGX-1V/HGX-1 Server = 3.2KW | Visualization: GPU node with 8x RTX 8000 GPU’s compared to 12 core CPU server | HPC: GPU node with 4xV100 compared to 2xCPU Server | DL Training: DGX-1V compared to a 2xCPU server | DL Inference: GPU Node with 16 xT4 Compared to 2x CPU Server |numbers rounded to nearest $0.5M

Trajectory planning

Vehicle dynamics

LQR

F/I kinematics

Visualization

Compression

3D-2D transform

Image registration

Classification

Route/lane/path planning

Env prediction

A*/D*

Collision testing

Language translation

Tree search

Beam-forming

Iterative recon

Odometry

Tracking

SLAM

Deep Learning (CNN, RNN, GAN, U-Net, MLP, etc.)

EXAMPLE AI COMPUTATION PIPELINE

INPUT DATA PROCESSING

PERCEPTION &INFERENCE

REASONING ACTION

Tensor Core

CUDA

CPU

Tensor Core

CUDA

CPU

CUDA

GPU

Video Processor

CPU

“Where can I go for ramen?”

“Let me suggest Jankara Ramen”

ISP

Video Processor

Vision Process

CUDA

CPU

Calibrate sensor

Decompression

Tone mapping

De-warping

ICP

FFT/IFFT

De-noise

Optical flow

Motion comp

Feature point

Xavier, the first chip ever designed for autonomous AI systems, will enable automation in many large industries.

AGX is our line of systems that addresses this opportunity.

DRIVE AGX for autonomous cars, trucks, and robotaxis.

Jetson AGX for robots and drones, as well as AI IOT systems for safe and smart cities.

Clara AGX for next-generation imaging in medical instruments.

For each, we’ve created a full stack to enable market leaders to take advantage of our platform.

AGX FOR AUTONOMOUS MACHINES AND AI IOT

NVIDIA AGX

DRIVE CLARAJETSON

SIMULATINGTRAINING

DRIVING

DRIVE is a full-stack open platform for the transportation industry.

More than a driving computer and software stack, DRIVE is an HPC infrastructure for training, simulation, and testing.

DRIVE AGX car computer delivers the performance needed to run a wide array of deep learning models and algorithms concurrently.

Companies can build their own AV applications with the new DRIVE AGX DevKit.

NVIDIA DRIVE FOR AV REVOLUTION

Pedestrians LightsSignsPathLanesCars

Hundreds of automakers, mobility services, truck makers, tier ones, mapping, and sensor companies are developing on DRIVE to create the future of transportation.

Toyota is using DRIVE AGX Xavier as the AI brain in production cars beginning 2020.

Daimler and Bosch are developing robotaxi fleets with DRIVE.

VW is developing AI-infused cockpit experiences on DRIVE.

$25B TAM opportunity by 2025.

NVIDIA DRIVE ADOPTION ACROSS $10T TRANSPORTATION INDUSTRY

The next chapter of AI is autonomous machines.

Jetson AGX Xavier delivers the energy-efficient computational power needed for embedded systems like robots, drones, and smart cities.

NVIDIA Isaac is a simulation environment and SDK that accelerates the development and deployment of robots of all kinds.

Jetson AGX Xavier DevKit is available for order now.

$5B TAM opportunity by 2022.

JETSON AGX AND ISAAC DELIVER AI TO $250B ROBOTICS AND IOT INDUSTRY

NVIDIA ISAACJETSON AGX XAVIER DEV KIT

Scale Up to 200 TOPS DL Processing

8 GIGA Rays | 200W

AI-ENHANCED ULTRASOUNDCLARA AGX

3D SegmentedVisualization

2DVisualization

Ultrasound, CT, MR, Endoscopy, Sequencing, and Pathology allow us to see the invisible in the human body.

Instruments are large sensors that require supercomputing level of processing for high-speed sensor processing, reconstruction, AI, and visualization.

Traditionally build with FPGA, CPU, and GPU.

Clara AGX Xavier replaces all three into one programmable architecture.

$2B TAM opportunity by 2022.

JETSON AGX TRANSFORMS $100B MEDICAL IMAGING INDUSTRY

Large markets — Gaming, Pro Viz, HPC, AI, Transportation, Healthcare, Robotics, and AI IOT — adopt NVIDIA Accelerated Computing as Moore’s law ends.

1M+ developers

56% of new FLOPS in Top500

12,000+ TensorRT downloads from 4,000 companies

New Turing is a giant leap for GPU — extending leadership in gaming and opening new growth for rendering and hyperscale AI.

New AGX line fuses HPC and AI — opening new growth opportunities in AV, medical instruments, robotics, and AI IOT.

Leveraging one architecture across multiple large markets allows us to drive growth and margin expansion.

INCREASING NVIDIA ADOPTION

NEW PRODUCTS

NEW MARKETS

ANOTHER GIANT LEAP

RECONCILIATION OF NON-GAAP TO GAAP FINANCIAL MEASURES

GROSS MARGIN ($ in millions & margin percentage)

NON-GAAPSTOCK-BASED

COMPENSATION (A)

PRODUCT WARRANTY

(B)GAAP

FY16

$2,846 (15) (20) $2,811

56.8% (0.3) (0.4) 56.1%

1H FY19

$4,059 (16) — $4,043

64.1% (0.2) — 63.9%

RECONCILIATION OF NON-GAAP TO GAAP FINANCIAL MEASURES

A. Stock-based compensation charge was allocated to cost of goods sold

B. Consists of the release of warranty reserve balance and warranty charge associated with a product recall

OPERATING MARGIN ($ in millions & margin percentage)

NON-GAAPSTOCK-BASED

COMPENSATION (A)

RESTRUCTURING

COSTS

OTHER

(B)GAAP

FY16

$1,125 (205) (131) (42) $747

22.5% (4.1) (2.6) (0.9) 14.9%

1H FY19

$2,718 (262) — (4) $2,452

42.9% (4.2) — — 38.7%

RECONCILIATION OF NON-GAAP TO GAAP FINANCIAL MEASURES (CONTD.)

A. Stock-based compensation charge was allocated to cost of goods sold, research and development expense, and sales, general and administrative expense.

B. Consists of the release of warranty reserve balance and warranty charge associated with a product recall, amortization of acquisition-related intangible assets, transaction costs, compensation charges, and other credits related to acquisitions.

($ IN MILLIONS) FY16 Q2 FY19

GAAP net cash flow provided by operating activities $1,175 $913

Purchase of property and equipment

and intangible assets(86) (128)

Free cash flow $1,089 $785

RECONCILIATION OF NON-GAAP TO GAAP FINANCIAL MEASURES (CONTD.)