NVIDIA’s meteoric rise continues as Melius Research projects the chipmaker’s stock could climb another 26% to $185 per share, driven by the upcoming Blackwell GPU launch. Managing Director Ben Reitzes draws a compelling parallel between NVIDIA’s current position and Apple’s revolutionary iPhone moment from 15 years ago, suggesting that selling NVIDIA stock now would be as shortsighted as abandoning Apple after the first iPhone release.
Since OpenAI launched ChatGPT in November 2022, NVIDIA has skyrocketed nearly 800%, becoming the world’s largest company with a market capitalization exceeding $3.5 trillion. The company’s dominance in AI chip technology, particularly its Hopper GPU and the forthcoming Blackwell chip, has positioned it as the foundational infrastructure powering the artificial intelligence revolution—from chatbots like ChatGPT to text-to-video generation and autonomous vehicles.
Reitzes emphasizes that major cloud providers, sovereign nations, and large enterprises view AI investment as a “once-in-a-lifetime opportunity,” ensuring continued demand for NVIDIA’s cutting-edge hardware. The analyst’s bullish outlook extends beyond Blackwell, anticipating that the subsequent Rubin chip in 2026 will drive further growth.
Financial projections paint an impressive picture: Melius Research expects NVIDIA’s gross margins to rebound firmly into the mid-70s by mid-fiscal year 2026, with earnings potentially exceeding $5 per share by 2027—a figure Reitzes considers “conservative.” The firm has raised its revenue and profit estimates for 2025-2027, citing higher gross margins and sustained investments from cloud hyperscalers.
From a valuation perspective, NVIDIA appears attractive despite its massive gains. The company’s CY2025 PEG ratio stands at approximately 0.8x, which is 33% lower than Broadcom’s and represents the lowest valuation among the “Magnificent 7” tech giants. This suggests the stock remains reasonably priced even as growth rates decelerate from extraordinary levels.
Year-to-date, NVIDIA stock has surged 197%, currently trading just 2% below its record high of $149.77 per share, demonstrating remarkable momentum in the AI-driven market rally.
Key Quotes
It’s similar to the feeling around product cycles with Apple’s iPhone some 15 years ago, just on a different scale. So, while it sounds strange, giving up on Nvidia here after its hit — Hopper — is like giving up on Apple at iPhone 1 or 2
Ben Reitzes, managing director at Melius Research, draws a powerful historical parallel to emphasize that NVIDIA’s current success with the Hopper chip is just the beginning, not the peak, of its AI-driven growth trajectory.
Big clouds, sovereigns and large enterprises are still more likely to invest more in this ‘once-in-a-lifetime opportunity’
Reitzes highlights the sustained demand drivers for NVIDIA’s chips, indicating that major institutional players view AI infrastructure as a transformational investment rather than a speculative trend.
We are not only excited about Blackwell driving upside to the street in 2025 — and Rubin in 2026 — but we are also increasingly optimistic that gross margins can snap back firmly into the mid-70s by mid-FY26
This quote reveals Melius Research’s confidence in NVIDIA’s multi-year product roadmap and its ability to maintain premium profitability, suggesting the company’s competitive moat remains intact despite growing competition.
Even with a decelerating growth rate on huge numbers, Nvidia’s CY2025 PEG ratio stands at about 0.8x on our estimates. This ratio is 33% less than Broadcom’s and the lowest in the Mag 7 by a wide margin
Reitzes makes the valuation case that despite NVIDIA’s massive gains, the stock remains attractively priced relative to growth prospects and peer companies, countering concerns about overvaluation.
Our Take
The iPhone analogy is more than marketing rhetoric—it captures a fundamental truth about platform shifts. Apple didn’t just create a better phone; it established the infrastructure for mobile computing that generated trillions in downstream value. NVIDIA is achieving something similar for AI computing, providing the essential hardware that enables an entire ecosystem of innovation. The key insight here is the multi-generation product roadmap (Hopper, Blackwell, Rubin) that creates predictable upgrade cycles and sustained demand. However, investors should remain mindful of emerging competition from custom AI chips developed by hyperscalers like Google, Amazon, and Microsoft, which could eventually pressure NVIDIA’s margins. The “once-in-a-lifetime opportunity” framing also raises questions about sustainability—while AI adoption is clearly accelerating, the law of large numbers suggests NVIDIA’s growth rates must eventually normalize. The real test will be whether Blackwell delivers the transformational performance improvements that justify continued premium pricing and market dominance.
Why This Matters
This analysis underscores NVIDIA’s pivotal role as the infrastructure backbone of the AI revolution, with implications extending far beyond a single company’s stock performance. The comparison to Apple’s iPhone moment is particularly significant—it suggests we’re still in the early innings of AI adoption, not approaching market saturation as some skeptics fear.
The continued investment from cloud hyperscalers, governments, and enterprises signals that AI infrastructure spending remains robust, contradicting concerns about an AI bubble. NVIDIA’s ability to maintain premium gross margins while scaling production demonstrates sustainable competitive advantages in chip design and manufacturing.
For businesses, this reinforces the imperative to integrate AI capabilities or risk competitive obsolescence. The transition from Hopper to Blackwell to Rubin chips represents a predictable innovation cycle that enterprises can plan around, similar to smartphone upgrade cycles. For workers and society, NVIDIA’s success reflects the broader transformation of computing infrastructure, suggesting that AI capabilities will become increasingly accessible and powerful, fundamentally reshaping how we work, create, and solve problems across industries.
Recommended Reading
For those interested in learning more about artificial intelligence, machine learning, and effective AI communication, here are some excellent resources: