Despite widespread skepticism, five common bear cases against Nvidia fail to account for the company’s entrenched position in AI infrastructure, sustained revenue momentum, and long-term growth drivers. The analysis reveals that each concern is either empirically unsupported or misinterprets market dynamics.
- Nvidia’s Q3 2025 revenue hit $39.3 billion, up 230% YoY
- Data center segment accounted for 87% of total revenue
- TSMC’s advanced node capacity supports 85% of latest GPU production
- Forward P/E of 43x is below 5-year average of 51x
- Free cash flow reached $18.6 billion in FY2025, up 185% YoY
- Microsoft’s Azure AI infrastructure relies on 70%+ Nvidia-based workloads
Nvidia’s stock has surged over 200% year-to-date, prompting a wave of cautionary narratives. Among the most cited concerns: fears of AI market saturation, rising competition from AMD and Intel, reliance on a single customer base, supply chain bottlenecks, and valuation disconnects. Yet each argument lacks substantive evidence when examined against current financial and industry data. Nvidia’s Q3 2025 revenue reached $39.3 billion, a 230% year-over-year increase, driven by data center demand. The company’s AI chip shipments to cloud providers and enterprise clients accounted for 87% of total revenue, underscoring continued demand strength. Meanwhile, AMD’s market share in high-performance GPUs remains below 20%, with no meaningful shift observed in server-grade AI chip adoption despite recent product launches. The narrative around supply constraints is outdated. TSMC, Nvidia’s primary foundry partner, has expanded capacity for 5nm and 3nm nodes, with 85% of Nvidia’s latest H200 and B200 chips produced on advanced nodes. Sourcing stability has not hindered delivery timelines, with fulfillment rates exceeding 94% in Q3. Valuation concerns also fall short. Nvidia’s forward price-to-earnings ratio stands at 43x, still below its 5-year average of 51x, and the company’s free cash flow generation reached $18.6 billion in FY2025—up 185% from the prior year. Investors are paying for future growth, but that growth is demonstrably materializing across AI training, inference, and edge computing. The broader ecosystem remains dependent on Nvidia. Microsoft’s Azure AI services, for instance, are built on Nvidia’s GPUs, with over 70% of its AI workloads running on NVIDIA infrastructure. This entrenched integration reduces the likelihood of rapid displacement.