NVIDIA Corporation (NVDA)

Company Snapshot

• Founded: 1993 by Jensen Huang, Chris Malachowsky and Curtis Priem.
• Headquarters: Santa Clara, California, USA.
• Industry: Technology – Semiconductors, AI-Infrastructure, Graphics Processing Units (GPUs) and Data Center Compute.
• CEO: Jensen Huang.
• Employees: 36,000 (as of Oct 2025)
• Market Cap: $5.03 trillion
• Ticker Symbol: NVDA (NASDAQ)
• Exchange: NASDAQ

Business Segments

NVIDIA operates across several major segments:

• Data Center & AI Infrastructure: Includes GPUs for AI training/inference (such as Blackwell platform), networking, and large-scale compute systems.
• Gaming & Graphics: High-end graphics cards (GeForce), gaming platforms, ray-tracing hardware, and related software.
• Automotive & Autonomous Machines: Includes NVIDIA DRIVE platform for autonomous vehicles, robotics, and edge AI.
• Professional Visualization & Other: Graphics for design, simulation, data science, HPC (high-performance computing).

Financial Highlights (Q2 2025)

• Revenue: $46.7 billion (+56% YoY and +6% quarter-on-quarter)
• Data Center Revenue: $41.1 billion (+56% YoY)
• Gross Margin (GAAP): 72.4%; Non-GAAP 72.7%.
• Operating Income: $29.2 billion (+64% YoY)
• Net Income: $26.3 billion (+67% YoY)
• Free Cash Flow: $28.2 billion (record high)
• Earnings Per Share (Non-GAAP diluted): $1.05 for the quarter.
• Key Highlight: Strong AI/accelerator demand, particularly Blackwell-architecture GPUs.
• Strategic Note: Reinforced share repurchase authorisation expansion (additional US$ 60 billion) during the quarter.

Global Presence

• NVIDIA is a leader in the global GPU and AI-accelerator market, supplying major hyperscalers and data centers worldwide.
• Strong exposure in high-growth markets: AI, cloud computing, autonomous vehicles, and edge computing.
• Faces regulatory / export risks in major markets (notably China) which impact certain product lines (e.g., H20 chips).

Strategic Initiatives

• AI Platform Leadership: The Blackwell generation of GPUs tailored for the reasoning AI era; ramping production aggressively.
• Automotive & Edge AI: Expansion of NVIDIA DRIVE and automotive AI stack moving toward mass deployment.
• Shareholder Returns & Capital Efficiency: Large‐scale buybacks and disciplined capital allocation reflect management’s confidence.
• Software Ecosystem & Platform Integration: Beyond hardware, focus on software stack, AI deployments, and ecosystem lock-in.

Challenges & Considerations

• Regulatory & Geopolitical Risk: Export restrictions (e.g., H20 chips to China) and geopolitical tensions add uncertainty.
• Valuation & Expectations: Much of the growth is already priced in; high expectations mean execution missteps are more exposed.
• Concentration of Revenue: A large portion of revenues stem from data center/AI segments—any slowdown or capital-spend shift can impact.
• Supply Chain & Manufacturing Risk: Advanced node manufacturing dependencies, chip supply constraints, and high fixed costs.