To The Moon

$NVIDIA(NVDA)$

Nvidia Corporation (NASDAQ: NVDA) once again captured the spotlight this week, notching a new all-time high and extending its winning streak to four consecutive sessions. Shares surged to an intraday record of $185.90, fueled by renewed investor enthusiasm following CEO Jensen Huang’s latest public remarks on the future of artificial intelligence. Huang’s message was clear: we are only scratching the surface of AI’s potential — and Nvidia is building the infrastructure for the next industrial revolution.

The market reaction was immediate. Nvidia’s valuation soared past $4.5 trillion, cementing its position among the world’s most valuable companies. Yet despite the astronomical market cap, sentiment remains bullish, with investors and analysts alike asking the same question: Can Nvidia reach $200 next?

Jensen Huang’s AI Vision: The “Three Laws of Scaling”

In a characteristically energetic presentation, Huang laid out his framework for understanding the next phase of AI’s evolution — what he calls the “Three Laws of AI Scaling.”

1. Pre-training: The process of training massive AI models using vast datasets and computing power.

2. Post-training: The refinement and alignment of models for specific tasks and industries.

3. Inference: The real-world deployment of these models at scale, where they interact with users and continuously process data.

Huang emphasized that while the first two stages have dominated headlines, inference will be the true economic engine of AI — the point where value creation multiplies exponentially. Inference demands ongoing computation, which means a steady stream of GPU demand across data centers, cloud platforms, and edge devices.

“Every time an AI model answers a question, interprets an image, or generates a video,” Huang noted, “there’s an inference engine running on Nvidia hardware somewhere in the world.”

That insight reframed the long-term narrative. Investors have been concerned that the initial AI buildout might taper off, but Huang’s remarks reinforced the idea that AI infrastructure demand is not cyclical — it’s structural.

AI Infrastructure Rally: Nvidia’s Partners Ride the Wave

Nvidia’s strength isn’t just in its chips — it’s in its ecosystem. Following Huang’s comments, a wave of AI infrastructure and GPU-linked stocks rallied across the board.

• CoreWeave, a close Nvidia partner and one of the fastest-growing AI cloud providers, jumped 15% after announcing a $14.2 billion compute deal with Meta Platforms (META). The deal further positions CoreWeave as a cornerstone in the new AI data economy, expanding capacity using Nvidia GPUs to serve hyperscale clients.

• Applied Digital (APLD) and Nebius gained roughly 6% each, reflecting optimism that smaller AI data center operators will benefit from the ongoing GPU supply crunch.

• Even Super Micro Computer (SMCI), a server manufacturer heavily reliant on Nvidia GPUs, saw renewed buying interest.

This synchronized movement highlights how Nvidia’s announcements have market-wide ripple effects. The company’s leadership effectively sets the tone for the broader AI infrastructure trade — similar to how Apple once defined the smartphone hardware cycle or Amazon set the rhythm for e-commerce and cloud computing.

AI Demand Still Outpaces Supply

One recurring theme in Nvidia’s story is scarcity — a problem most companies would love to have. Despite record production and the rollout of the next-generation Blackwell architecture, Nvidia’s GPUs remain chronically oversubscribed, with major customers from Microsoft to Oracle competing for supply.

The company’s H100 chips have been the backbone of AI model training, but attention is now shifting to the Blackwell B200, expected to deliver a 30x performance improvement for large language model workloads. Early production is already underway, and shipments could scale dramatically by mid-2026.

Meanwhile, the inference boom is beginning to reshape global computing infrastructure. Major hyperscalers like Google Cloud, Amazon Web Services, and Microsoft Azure are racing to upgrade their systems with Nvidia’s latest GPUs, while sovereign AI initiatives in Japan, the UAE, and Singapore are also driving incremental demand.

This sustained imbalance between demand and supply continues to underpin Nvidia’s pricing power — a key factor behind its industry-leading 70%+ gross margins.

Financial Highlights: Growth at an Unprecedented Scale

Nvidia’s most recent quarterly report left even bullish analysts impressed.

• Revenue: $30.1 billion, up 154% year-over-year, largely fueled by explosive growth in the data center segment.

• Net Income: $14.8 billion, up more than 200% year-over-year, underscoring operational leverage.

• Free Cash Flow: Over $13 billion in a single quarter — a record for any semiconductor firm.

• Gross Margin: 71.2%, reflecting Nvidia’s near-monopoly position in AI accelerators.

What’s particularly striking is how Nvidia has maintained growth even as competitors try to catch up. AMD’s MI300 and Intel’s Gaudi series have failed to gain meaningful traction. In addition, Nvidia’s CUDA ecosystem and software libraries create a powerful moat that locks in developers and enterprises for years.

Analysts estimate that for every dollar spent on Nvidia hardware, an additional two to three dollars are spent on software, services, and ecosystem integration — creating a flywheel of recurring revenue that few rivals can replicate.

Market Sentiment: Bullish, but Cautiously So

Wall Street’s stance on Nvidia remains overwhelmingly positive. Out of 58 analysts covering the stock, 50 rate it as “Buy” or “Strong Buy”, with a median price target of $200 and several now pushing their forecasts as high as $220.

However, some voices are calling for caution. Valuation remains the biggest sticking point — Nvidia trades at roughly 50x forward earnings and 25x price-to-sales, metrics that would be considered extreme for any traditional hardware manufacturer. But Nvidia is not a traditional hardware company — it’s effectively the infrastructure layer for AI itself.

Many institutional investors are therefore treating Nvidia more like a platform company than a semiconductor firm, comparable to the way the market values Apple or Microsoft. This re-rating could sustain higher multiples for longer, particularly if Nvidia continues to deliver consistent execution and margin expansion.

Technicals and Market Psychology: $200 as the Next Milestone

From a technical standpoint, Nvidia’s momentum is undeniable. The stock has rallied more than 50% year-to-date, and each dip has been met with aggressive institutional buying. Short interest remains minimal, and options activity suggests traders are betting on a continued breakout.

The $200 level represents both a psychological milestone and a potential short-term resistance zone. Breaking that level decisively would likely trigger additional algorithmic buying and portfolio rebalancing among passive funds.

However, the stock’s RSI above 70 indicates overbought conditions, suggesting that short-term volatility or consolidation could occur before the next leg higher. Even so, as investors have seen repeatedly this year, Nvidia corrections tend to be shallow and short-lived — often lasting just days before momentum returns.

The Global Race for AI Compute: Nvidia at the Center

Perhaps the most telling sign of Nvidia’s dominance is its role in global geopolitics. Nations are increasingly treating AI compute capacity as a strategic resource, on par with oil or rare earth minerals. Governments from the Middle East to East Asia are forming AI alliances, building data centers powered primarily by Nvidia GPUs to secure access to computing power for the next decade.

In the U.S., Nvidia’s chips are at the core of national AI initiatives, including the Department of Energy’s supercomputing projects. Abroad, countries like Saudi Arabia, UAE, and Singapore have become key Nvidia clients, ordering entire clusters of GPUs to fuel their AI strategies.

This global expansion ensures that Nvidia’s growth is not solely dependent on Silicon Valley or Western tech giants, but increasingly diversified across new regions and industries — from financial services and healthcare to robotics and digital infrastructure.

Risks to Watch: Valuation, Competition, and Policy Headwinds

While Nvidia’s story remains overwhelmingly positive, investors should stay aware of potential risks:

1. Valuation risk: At 50x forward earnings, any deceleration in revenue growth could trigger a short-term derating.

2. Competition: AMD, Intel, and emerging players like Cerebras and Tenstorrent continue to invest aggressively in AI accelerators, though Nvidia’s lead remains wide.

3. Geopolitical headwinds: U.S. export restrictions on high-end chips to China could limit some near-term sales, though Nvidia is reportedly developing localized variants to comply with regulations.

4. Supply chain constraints: Ongoing capacity shortages at TSMC could bottleneck production if demand continues to accelerate.

Still, the company’s track record of navigating challenges — from crypto crashes to chip bans — suggests it’s well-positioned to manage volatility.

Verdict: Can Nvidia Hit $200?

Given current momentum, strong earnings, and sector-wide enthusiasm, Nvidia’s path toward $200 per share seems increasingly likely. Whether it happens in weeks or months may depend on market sentiment and macro factors, but the underlying fundamentals remain intact and powerful.

For long-term investors, Nvidia remains the clearest, purest bet on the AI revolution. The company sits at the intersection of every major trend driving technological transformation — data, compute, software, and automation.

For short-term traders, the stock may experience intermittent pullbacks, but each dip continues to represent a buying opportunity for those confident in the long-term trajectory of AI adoption.

Key Takeaways

1. Nvidia hit a new record high near $185.9 after Jensen Huang’s bullish AI commentary.

2. Huang’s “three laws of AI scaling” — pre-training, post-training, and inference — underscore that inference will drive sustained long-term GPU demand.

3. Ecosystem partners like CoreWeave, APLD, and Nebius also rallied, reflecting optimism across the AI infrastructure landscape.

4. Despite its $4.5T valuation, Nvidia’s fundamentals remain unmatched, with 150%+ annual growth in its data center business.

5. Wall Street’s consensus price target now centers around $200, with some expecting even higher.

6. Risks include lofty valuation and policy constraints, but Nvidia’s technological and ecosystem moat remains formidable.

7. Nvidia’s dominance in global AI compute cements it as a generational growth story — not a passing trend.