Key Takeaways
- NVDA shares gained 15% in the last month, though AMD rose 38% and Intel climbed 56% during the same timeframe.
- Rick Schafer from Oppenheimer maintains an Outperform rating on Nvidia with a $265 target, naming it his preferred semiconductor selection.
- The company’s Blackwell Ultra (GB300) NVL systems reportedly lead rivals by two product generations in AI processing.
- NVDA currently trades at 17x forward 2027 earnings projections, compared to the semiconductor sector’s 20x average multiple.
- Company revenues expanded from $27 billion in fiscal 2023 to approximately $216 billion in fiscal 2026, with analysts projecting $480 billion by fiscal 2028.
Nvidia has delivered solid gains among chip manufacturers recently — though not the strongest. NVDA posted a 15% advance over the past month, while AMD rallied 38% and Intel soared 56%. This performance disparity has sparked investor questions, yet one Wall Street analyst suggests the gap shouldn’t cause concern.
Rick Schafer at Oppenheimer maintains an Outperform rating on Nvidia with a $265 price objective. In contrast, he assigns Perform ratings to both AMD and Intel. Schafer identifies Nvidia as his preferred semiconductor investment entering the current earnings cycle.
The stronger recent performance from AMD and Intel reflects growing attention to CPUs in AI server configurations — a segment distinct from Nvidia’s GPU-centric operations. Intel also benefited from a recent Barron’s recommendation.
Meanwhile, Nvidia’s investment narrative continues to develop. NVDA was changing hands around $198.60 during premarket activity on Friday, April 17, showing a 0.2% intraday increase.
Trading Multiple Sits Below Industry Norm
Schafer’s research highlights Nvidia’s Blackwell Ultra (GB300) NVL rack systems as holding a two-generation technological advantage over competitors. He notes that Nvidia currently commands approximately 17x his fiscal 2027 earnings projection — beneath the semiconductor sector’s 20x average — presenting what he views as an appealing entry point for a market leader with such commanding positioning.
The shares have appreciated roughly 75% over the trailing twelve months. The stock carries a trailing price-to-earnings ratio near 41x, which has drawn scrutiny from some market participants. Trefis analysts contend this valuation isn’t unreasonable considering the expansion potential ahead.
Revenue growth illustrates the trajectory. Nvidia expanded from $27 billion in fiscal 2023 to nearly $216 billion in fiscal 2026 — representing approximately 8x multiplication. Wall Street consensus now anticipates $480 billion in sales by fiscal 2028.
Two primary catalysts support this projection. The first involves the transition from AI model training to inference deployment. Training occurs periodically; inference runs continuously. As agentic AI applications proliferate, computational requirements escalate. Organizations already invested in Nvidia’s CUDA platform encounter substantial switching costs, creating customer retention.
National AI Infrastructure and Profitability Dynamics
The second expansion catalyst is Sovereign AI initiatives. Nations globally are establishing domestic AI infrastructure, and Nvidia’s CUDA-based technology stack positions it favorably. During fiscal 2026, Nvidia’s sovereign AI segment revenues tripled, exceeding $30 billion.
Regarding profitability, Nvidia delivered 54% net margins in fiscal 2026, up from 31% in fiscal 2023. AMD, comparatively, operates around 20% margins. Trefis analysts project margins sustaining approximately 52% despite evolving product composition.
If revenues achieve $575 billion with margins maintaining 52% levels, that suggests net income approaching $300 billion — roughly 2.5x the $117 billion recorded in fiscal 2026.
Applying a trailing P/E multiple of 25x to that earnings figure, Trefis calculates a potential market capitalization of $7.5 trillion, which would drive the stock price toward $300.
For perspective, Cisco currently trades around 22x trailing earnings. Microsoft commands above 27x.
Nvidia’s upcoming architecture, Vera Rubin, will succeed Blackwell and aims to enhance inference performance while reducing per-token processing costs.
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