NVIDIA Corporation
NVIDIA dominates AI computing with its GPU technology. The company's data center business has exploded due to demand for AI training and inference workloads.
Investment Thesis
NVIDIA has a 10+ year lead in AI computing infrastructure. The AI revolution is in early innings, and NVIDIA's CUDA moat makes it the infrastructure provider of choice.
Published: February 8, 2026
Company Overview
NVIDIA Corporation designs graphics processing units (GPUs) for gaming and professional markets, as well as system on chip units (SoCs) for mobile computing and automotive. The company has emerged as the dominant player in AI computing infrastructure.
Business Segments
- Data Center - AI training & inference, HPC (85% of revenue)
- Gaming - GeForce GPUs for gaming PCs (10% of revenue)
- Professional Visualization - Workstation GPUs (3% of revenue)
- Automotive - Self-driving platforms (2% of revenue)
Financial Performance
NVIDIA has experienced explosive growth driven by AI adoption:
- Revenue (FY2025): $88.0B (+115% YoY)
- Gross Margin: 75.0% (up from 65%)
- Operating Margin: 62.0%
- Free Cash Flow: $55.0B
Key Metrics
- Data Center revenue: $75B (+172% YoY)
- H100/H200 GPU demand: Sold out through 2026
- CUDA developers: 4M+ worldwide
- Installed base: Hundreds of thousands of GPUs
Competitive Advantages
- CUDA Ecosystem: 15+ years of software development creates massive moat
- Performance Leadership: 2-3x performance advantage over competitors
- Full Stack Solution: Hardware + software + networking (Mellanox)
- First Mover Advantage: Early AI infrastructure investment pays off
- Network Effects: More developers → better tools → more developers
Growth Drivers
AI Infrastructure Build-Out
Enterprises and hyperscalers are spending billions on AI infrastructure:
- Microsoft: $50B capex in 2025
- Google: $35B capex in 2025
- Meta: $40B capex in 2025
- Amazon: $45B capex in 2025
Most of this spending flows to NVIDIA GPUs.
Inference Opportunity
While training gets the headlines, inference will drive long-term growth:
- Inference is 90% of lifetime compute for most models
- Every ChatGPT query uses NVIDIA GPUs
- Inference TAM larger than training long-term
Sovereign AI
Countries investing in domestic AI capabilities:
- UAE: $50B AI investment
- Saudi Arabia: $40B AI fund
- Japan: AI supercomputer projects
- Europe: AI independence initiatives
Investment Risks
Despite dominant position, several risks exist:
- Valuation: Trading at 50x P/E on $88B revenue
- Competition: AMD MI300X, Google TPU, Amazon Trainium gaining traction
- Customer Concentration: Top 4 customers are 50%+ of revenue
- Export Controls: China revenue declining due to restrictions
- Cyclical Nature: Semiconductor industry historically cyclical
Competitive Landscape
Direct Competitors
- AMD: MI300X competitive on some workloads, pricing aggressive
- Intel: Gaudi chips for inference, far behind on training
- Custom Silicon: Google TPU, Amazon Trainium for internal use
The CUDA Moat
NVIDIA’s sustainable advantage lies in software:
- 15+ years of CUDA development
- Libraries optimized for AI workloads
- 4M+ developers trained on CUDA
- Switching costs extremely high
Valuation
At current prices (~$700/share), NVIDIA trades at:
- P/E: 50x (based on $88B revenue run-rate)
- Forward P/E: 35x (2026 estimates)
- EV/Sales: 32x
- Price/Free Cash Flow: 50x
Valuation is extremely rich but reflects dominant market position and growth trajectory.
Financial Outlook
Consensus estimates for next 2 years:
- FY2026 Revenue: $125B (+42% growth)
- FY2027 Revenue: $165B (+32% growth)
- Gross margins stabilizing at 70-75%
- Operating margins 55-60%
Conclusion
NVIDIA is the best-positioned company for the AI revolution. The CUDA moat is real and provides durable competitive advantages. However, at 50x P/E, much of the good news is priced in.
For long-term investors, NVIDIA remains a core AI infrastructure holding. Short-term, be prepared for volatility as expectations are extremely high.
Rating: Hold at current prices, Buy on dips below $550
Next Steps
Monitor these key indicators:
- Data center revenue growth trends
- GPU utilization rates at hyperscalers
- Competitive wins/losses vs AMD
- Export control impacts on China business
- Gross margin trajectory
Key Risks
- Customer concentration (hyperscalers account for 50%+ of data center revenue)
- Emerging competition from AMD, custom AI chips, and startups
- Export restrictions to China impact ~20% of data center revenue
- Cyclical semiconductor industry dynamics