Sell NVIDIA Stock Today — Before Wall Street Figures Out What You Already Know

The Thesis in One Sentence#

NVIDIA’s current valuation assumes:

1. Permanent near-monopoly market share in AI accelerators
2. Sustained super-normal gross margins (73%+) for years
3. No meaningful impact from competition, customer insourcing, or architectural shifts
4. The AI spending boom continuing indefinitely without ROI reckoning

All four of these assumptions have to remain true simultaneously for the stock to be fairly valued at current prices.

If any one of them breaks—if AMD gains meaningful share, if hyperscalers shift workloads to custom ASICs, if the AI spending boom hits a wall, if margins compress toward semiconductor industry norms—the downside is brutal.

This isn’t about whether NVIDIA is a “good company.” Of course it is. Jensen Huang executes like a machine. The technology is genuinely impressive. The CUDA ecosystem is a real moat.

But being a great company and being a great stock are two completely different things. And right now, you’re paying a price that requires perfection.

The Smart Money Is Already Moving#

Before we dive into the history and the competition, let’s talk about what the institutional investors are actually doing—not saying, doing.

Peter Thiel’s macro fund—which previously held 40% of its portfolio in NVIDIA—dumped everything and rotated entirely to Microsoft and Apple.⁴ Michael Burry (yes, that Michael Burry) reduced his position during Q3.⁴ According to WhaleWisdom data, 342 hedge funds reduced their NVIDIA stakes in Q3 while 33 closed out entirely.⁵

Thiel explicitly compared the current AI boom to “the irrational exuberance of the late 1990s.”⁴ He’s not some Seeking Alpha permabear. He was one of the earliest investors in Facebook and Palantir. He knows how to identify paradigm shifts.

Is he wrong? Maybe. But I’d rather bet with the guy who made billions timing tech cycles than against him.

From Gaming GPUs to AI Infrastructure#

GPUs weren’t built for AI. They were built for rendering 3D graphics in video games.

The original value proposition was simple: video games require millions of parallel calculations to render pixels on screen. CPUs handle tasks sequentially—one operation at a time. GPUs handle thousands of operations simultaneously. For gaming, this meant smoother framerates and prettier graphics.

Then researchers discovered something interesting: the same parallel processing that renders video game explosions is also perfect for training neural networks. Both workloads involve massive matrix multiplications across huge datasets. What took weeks on CPUs could take hours on GPUs.

NVIDIA saw this opportunity earlier than anyone else. They built CUDA—a software platform that made it relatively easy for developers to harness GPU power for non-graphics workloads. They invested heavily in AI-specific features. They cultivated relationships with researchers and cloud providers.

By the time ChatGPT launched in late 2022 and kicked off the generative AI gold rush, NVIDIA had the only mature, end-to-end stack for training large language models. The hyperscalers—Meta, Microsoft, Amazon, Google—needed to scale model training fast. NVIDIA was the only game in town.

The result? NVIDIA’s data center revenue exploded from $15 billion in fiscal 2023 to over $51 billion in Q3 fiscal 2026 alone.⁶ Market share in AI training chips hovered around 80-90%.⁷ Gross margins expanded to levels that would make a luxury goods company jealous.

Athena Character @ openart.ai

The Part Nobody Wants to Talk About: Crypto Mining#

Here’s where it gets uncomfortable. Because NVIDIA has been through a demand boom before. And it didn’t end well.

Before AI, the big non-gaming use case for high-end GPUs was cryptocurrency mining. Bitcoin, Ethereum, and a zoo of altcoins all required massive parallel computation to “mine” new coins. GPUs were perfect for the job.

During the crypto boom cycles of 2017-2018 and 2020-2021:

• GPU prices spiked 2-3x above MSRP as miners hoarded every card they could find
• NVIDIA couldn’t manufacture chips fast enough to meet demand
• Revenue surged; stock price soared
• Analysts upgraded their targets; everyone declared a new paradigm

Sound familiar?

Then crypto prices crashed. And here’s what happened next:

• Secondhand GPUs flooded the market. Miners dumped their hardware at fire-sale prices.
• Demand for new cards collapsed. Why buy a new GPU when you can get a barely-used mining card for 40% off?
• NVIDIA had to reset expectations. Revenue declined. Margins compressed. The stock cratered.

The crypto bust forced NVIDIA to absorb a painful down-cycle. Gaming revenue dropped 32% year-over-year in Q4 FY2019.⁸ The stock fell from $280 to under $130 (split-adjusted) in less than a year.

The lesson? Demand that looks insatiable can evaporate faster than Wall Street models predict. And when it does, all that capacity you built to meet “unlimited demand” becomes a millstone around your neck.

Why Data Centers Stampeded Into NVIDIA#

The AI gold rush of 2023-2025 makes the crypto boom look quaint.

When ChatGPT demonstrated that large language models could pass the bar exam, write code, and hold conversations that felt genuinely intelligent, every major tech company panicked. The fear wasn’t “this might be useful.” The fear was “if we don’t have this capability, we’re dead.”

So the hyperscalers stampeded into NVIDIA:

• Microsoft needed GPUs to power Azure’s AI services and its partnership with OpenAI
• Google needed GPUs to train Gemini and defend its search monopoly
• Meta needed GPUs to catch up after getting blindsided by the AI wave
• Amazon needed GPUs to keep AWS competitive
• Every enterprise with a CTO suddenly needed “an AI strategy”

NVIDIA was the only vendor with the mature stack to deliver at scale. H100s were backordered for months. Prices held firm despite the premium. Data centers paid whatever NVIDIA asked because the alternative was falling behind in the most important technology race since the internet.

NOTE

If you want to see how that same AI infrastructure arms race shows up in the real world when AWS face-plants, read our post on why AWS keeps crashing and everyone blames AI.

The result was the fastest revenue ramp in semiconductor history:

These numbers are real. The demand is real. The products are genuinely best-in-class.

But here’s the question: Is this the new normal, or is this the peak of a cycle?

Athena Character @ openart.ai

The Valuation Boom (And What It Assumes)#

The stock market isn’t stupid. Investors saw the revenue explosion and bid up NVIDIA accordingly. The stock went from $15 (split-adjusted) in early 2023 to over $200 at its peak—a 13x move in under three years.

But here’s what that valuation implies:

Current metrics (November 2025):

• Market cap: ~$4.4 trillion⁹
• Forward P/E: ~44x¹⁰
• Price-to-Sales: ~30x¹¹
• Gross margin: 73%+⁶

For comparison, historical semiconductor averages:

• Forward P/E: 15-20x
• Price-to-Sales: 3-5x
• Gross margin: 40-50%

NVIDIA trades at roughly 2-3x the valuation of a typical semiconductor company on every metric. That premium is only justified if NVIDIA can maintain near-monopoly economics indefinitely.

But semiconductors are inherently cyclical. Supply gluts follow periods of over-investment. Pricing power collapses when capacity overshoots demand. And every “unassailable” market leader in chip history has eventually faced margin compression once competition caught up.

Intel dominated CPUs for two decades. Then AMD and ARM ate their lunch. Qualcomm dominated mobile chips. Then Apple built their own silicon and Samsung gained share. Texas Instruments dominated analog. Then they faced pricing pressure from Asian competitors.

We’ve already watched what happens when a mega-cap priced for perfection stumbles—Apple’s iPhone 17 launch wiped out $112 billion in value in two days. If you want that play-by-play, check out Apple Lost $112 Billion in Two Days — Here’s What Went Wrong at the iPhone 17 Event.

The question isn’t whether NVIDIA’s monopoly will erode. The question is when.

Smash that subscribe button at wayfinder.page/subscribe to get notified when new articles drop.

The Crypto Parallel Nobody Wants to Hear#

Let me connect the dots:

Crypto boom (2020-2021):

• Unprecedented demand for GPUs
• Prices held firm despite premium pricing
• Supply couldn’t keep up with demand
• Revenue and margins exploded
• Stock hit all-time highs
• Analysts declared a new paradigm

Crypto bust (2022):

• Demand collapsed faster than supply could adjust
• Secondhand hardware flooded the market
• Pricing power evaporated
• Revenue and margins compressed
• Stock cratered

AI boom (2023-2025):

• Unprecedented demand for AI accelerators ✓
• Prices held firm despite premium pricing ✓
• Supply couldn’t keep up with demand ✓
• Revenue and margins exploded ✓
• Stock hit all-time highs ✓
• Analysts declared a new paradigm ✓

AI bust (2026-?):

• ???

I’m not saying the AI boom is a bubble. The technology is real. The use cases are real. ChatGPT isn’t going away.

But I am saying that the demand dynamics that drove NVIDIA’s revenue from $15 billion to $115 billion in three years are not sustainable forever. At some point:

• Cloud providers will have enough GPU capacity and stop panic-buying
• Custom ASICs from hyperscalers will absorb a growing share of workloads
• AMD and other competitors will offer “good enough” alternatives at lower prices
• Some AI projects will fail to deliver ROI and get cancelled
• The cycle will turn

If you’re trying to figure out which AI use cases actually deliver value instead of just lighting money on fire, start with our guide to ChatGPT tasks that actually work.

When that happens, NVIDIA won’t disappear. It will still be a great company with great products. But the stock that’s priced for permanent monopoly economics will have to reprice for semiconductor industry reality.

And that repricing won’t be gentle.

Q: Isn’t this just fear-mongering? NVIDIA keeps beating earnings.#

A: NVIDIA is beating earnings—spectacularly. Q3 revenue of $57 billion crushed estimates.⁶ But here’s the thing: the stock dropped 3.2% the day after that blowout report. When a company beats on every metric and the stock still falls, the market is telling you the good news is already priced in. Great earnings don’t guarantee great returns if you bought at the wrong price.

Q: What about NVIDIA’s $500 billion in visibility through 2026?#

A: “Visibility” means orders on the books, not delivered revenue. Orders can be delayed, reduced, or cancelled if AI spending slows. And even if NVIDIA delivers every dollar of that $500 billion, it’s largely already reflected in a $4.4 trillion market cap. You’re not buying the backlog—you’re buying what comes after the backlog.

Q: Didn’t the crypto crash end up being a buying opportunity?#

A: Eventually, yes—NVIDIA stock recovered and then some. But it took 17 months to return to pre-crash levels. And during that time, you could have bought at prices 50% cheaper than the October 2018 peak. The question isn’t whether NVIDIA will survive a correction. The question is whether you want to own it through the correction or after it.

Q: What if AI demand is different from crypto demand?#

A: It is different—AI has clearer enterprise use cases and real revenue. But the dynamics are similar: panic buying during scarcity, overcapacity during normalization, margin compression when competition arrives. The technology being “real” doesn’t protect you from paying too much for a stock.

Q: Should I sell everything immediately?#

A: I’m not a financial advisor, and this isn’t financial advice. But if NVIDIA is a significant portion of your portfolio, consider whether you’re comfortable with the asymmetric risk: upside requires near-perfection, while downside only needs one or two assumptions to crack. Trimming to a smaller position is different from selling everything.