NextFin News - The arithmetic of the artificial intelligence boom is being rewritten as New Street Research elevates NVIDIA to its "best ideas list for 2026," arguing that the market has fundamentally miscalculated the scale of upcoming chip orders. The upgrade, issued by lead analyst Pierre Ferragu on March 19, follows a week of intense scrutiny over U.S. President Trump’s trade policies and their potential impact on the semiconductor supply chain. Yet, for New Street, the noise of geopolitics is secondary to a staggering new data point: NVIDIA has effectively added $500 billion to its order book in just five months.
The catalyst for this renewed bullishness stems from Jensen Huang’s keynote at NVIDIA GTC 2026 in San Jose. During the event, Huang projected that the company has visibility into "at least $1 trillion" in cumulative revenue through 2027. While some corners of Wall Street greeted the figure with a shrug—viewing it as a mere confirmation of existing high expectations—Ferragu contends that the market’s reaction was "misplaced." By comparing this $1 trillion figure to Huang’s October 2025 statement in Washington, where visibility stood at $500 billion, New Street calculates a run rate that suggests NVIDIA is now operating at a scale previously thought impossible for a hardware manufacturer.
This massive leap in demand is being driven by the transition from the Blackwell architecture to the next-generation Vera Rubin chips. The technical shift is more than a simple speed upgrade; it represents a move toward what Huang calls "agentic AI as a service." By integrating Groq 3 LPX compute with Vera Rubin systems, NVIDIA is targeting a 10x revenue jump in the AI inference market alone. This "five-layer cake" strategy—spanning power delivery, networking, and software—is designed to capture the entire data center stack, turning NVIDIA from a component supplier into the primary architect of global sovereign AI infrastructure.
However, the path to $1 trillion is not without friction. Skeptics, including analysts at D.A. Davidson, have questioned whether hyperscalers like Amazon and Google can continue to expand capital expenditure at this breakneck pace. There is a growing "belief gap" between NVIDIA’s internal order visibility and the market's fear of a cyclical peak. If the broader economy cools or if the Trump administration’s tariffs on high-end components tighten further, the logistical challenge of building out these massive data centers could become the primary bottleneck, regardless of how many chips are ordered.
Despite these macro headwinds, the structural shift toward agentic AI—where software engineers use tools like Anthropic’s Claude Code and OpenAI’s Codex to automate entire workflows—suggests that the demand for compute is becoming less discretionary and more foundational. New Street’s conviction lies in the belief that NVIDIA will not just meet but "materially beat" 2027 expectations. As the company moves toward a run rate of $1 trillion per year, the distinction between a "chip company" and a "platform company" has effectively vanished, leaving competitors to fight for the remnants of a market that NVIDIA now largely defines.
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