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NVIDIA CORP Annual Report, Year Ended Jan 27, 2019

Filing Date
Filed February 21, 2019
Period End
January 27, 2019
Security
NVDA
In the record · 2016–202610-K1110-Q328-K110

NVDA filed 11 annual reports (10-K), 32 quarterly reports (10-Q) and 110 current reports (8-K) between 2016 and 2026.

  1. Leadership change8-K · Mar ’18Mar ’18
  2. Deal closed8-K · Jul ’20Jul ’20
  3. Leadership change8-K · Jun ’22Jun ’22
  4. Material agreement8-K · Aug ’26Aug ’26

Summary

Summary of the 10-K filed February 21, 2019. Cited figures are marked; the original filing is the authoritative source.

NVIDIA Corporation's 2019 10-K filing reveals a company undergoing a significant transformation, leveraging its foundational GPU technology for the burgeoning field of Artificial Intelligence (AI).

The company's strategy centers on a unified architecture that serves diverse markets including Gaming, Professional Visualization, Datacenter, and Automotive. While Gaming remains a core market, driven by products like GeForce, NVIDIA is increasingly emphasizing its Datacenter and AI capabilities, highlighted by the Tesla and DGX product lines, which are crucial for deep learning and high-performance computing. The fiscal year ending January 27, 2019, showed robust revenue growth of 21% year-over-year, reaching $11.7 billiona, with a notable 52% surge in Datacenter revenue.

This growth underscores the strategic shift towards AI and accelerated computing. However, the company also navigated challenges, including volatility in the gaming segment influenced by cryptocurrency mining demand and macroeconomic slowdowns, particularly in China. Despite these headwinds, NVIDIA demonstrated strong financial performance with increased gross margins and net income, signaling its ability to capitalize on emerging technology trends and expand its platform's reach.

Key Highlights

  1. Revenue grew 21% year-over-year to $11.7 billion for the fiscal year ended January 27, 2019.
  2. Datacenter revenue saw significant growth of 52%, indicating strong adoption of NVIDIA's AI and HPC solutions.
  3. The company continues to invest heavily in R&D, crucial for maintaining its technological leadership in GPUs and AI.
  4. NVIDIA is expanding its reach beyond gaming, with significant progress in Professional Visualization, Datacenter, and Automotive markets.
  5. The company experienced volatility in its Gaming segment, partly attributed to the influence of cryptocurrency mining and macroeconomic factors impacting consumer demand.
  6. NVIDIA maintained strong profitability, with gross margins improving to 61.2% and net income rising 36% year-over-year.
  7. A strategic platform approach, combining hardware, system software, and programmable algorithms, is central to NVIDIA's value proposition across all its markets.

Follow one dollar

Of each $1.00 of revenue in FY2019, NVIDIA Corp kept $0.35.

  1. Revenue$11.72B100.0%
  2. Cost of revenue−$4.54B38.8%
  3. Gross profit$7.17B61.2%
  4. Operating costs−$3.37B28.7%
  5. Operating income$3.80B32.5%
  6. Interest, other & tax$337.0M2.9%
  7. Net income$4.14B35.3%
Computed from 10-KFY2019filed February 21, 2019Computed from this filing’s revenue, gross profit, operating income and net income · right columngrey figure: share of revenue

Where FY2019 revenue went

$11.72B
  • Cost of revenue: $4.54B, 39% of revenue
  • Operating income: $3.80B, 32% of revenue
  • R&D: $2.38B, 20% of revenue
  • SG&A: $991.0M, 8.5% of revenue

Kept 32% as operating income

Full revenue history →

Financial Statements

FY2019 against FY2018

Line itemFY2019FY2018Change
Revenue$11.72B$9.71B+20.6%
Cost of Revenue$4.54B$3.89B+16.8%
Gross Profit$7.17B$5.82B+23.2%
R&D Expenses$2.38B$1.80B+32.2%
SG&A Expenses$991.00M$815.00M+21.6%
Operating Expenses$3.37B$2.61B+28.9%
Operating Income$3.80B$3.21B+18.5%
Interest Expense$58.00M$61.00M−4.9%
Net Income$4.14B$3.05B+35.9%
EPS (Basic)$0.17$0.13+33.8%
EPS (Diluted)$0.17$0.12+37.6%
Shares Outstanding (Basic)24.32B23.96B+1.5%
Shares Outstanding (Diluted)25.00B25.28B−1.1%

Frequently Asked Questions

  1. What are NVIDIA's primary business segments and the key markets they serve?

    NVIDIA's business is organized into two primary reportable segments: GPU and Tegra Processor. These segments are based on a single underlying architecture. The GPU segment serves specialized markets including Gaming (GeForce), Professional Visualization (Quadro), Datacenter (Tesla, DGX), and Cloud-based Visual Computing (GRID). The Tegra Processor segment integrates GPUs and CPUs onto a single chip and is used for autonomous robots, drones, cars, game consoles, and mobile entertainment (DRIVE, SHIELD, Jetson). The four large markets NVIDIA addresses are Gaming, Professional Visualization, Datacenter, and Automotive.

  2. What were the key revenue drivers for NVIDIA in fiscal year 2019?

    Revenue in fiscal year 2019 increased by 21% to $11.7 billion. Key drivers included a 25% increase in the GPU business, with notable growth in gaming GPUs (up 18%), datacenter solutions (up 52%), and professional visualization products (up 21%). The Tegra Processor business saw a slight increase, primarily driven by automotive applications (up 15%), though offset by a decline in gaming platform SOC modules.

  3. What challenges or risks did NVIDIA highlight in its 2019 10-K filing?

    NVIDIA highlighted several risks, including the need to meet evolving market demands and identify new technologies, intense competition, potential disruptions from system security breaches, the risk of product defects, reliance on third-party manufacturers, business disruptions from geopolitical events or natural disasters, and the challenge of accurately forecasting customer demand. Specifically in fiscal year 2019, they noted volatility in the gaming segment due to cryptocurrency mining after-effects and macroeconomic factors, as well as a temporary pause in datacenter deal closures due to economic uncertainty.

  4. How is NVIDIA addressing the artificial intelligence (AI) market?

    NVIDIA is heavily focused on AI, leveraging its GPU architecture and CUDA programming model. Its platform strategy includes GPUs designed for AI workloads (like Tesla and DGX), along with software libraries, system software, and services. The company is engaged with thousands of organizations, including major cloud providers and enterprises, to accelerate AI development and deployment, particularly in areas like deep learning and machine learning for training and inference.