329 traders prop up Anthropic's 1.2 trillion "valuation" – AI anxiety finally has a price

Original Author: Sleepy

Yesterday, I came across an article with the headline: "A New Global AI King is Born! Anthropic’s Valuation Surges Past $1.2 Trillion, Surpassing OpenAI for the First Time."

This headline perfectly captures the zeitgeist. It has AI, an underdog story, a new king ascending the throne, and a number so large it defies imagination. It’s like a gong. When the gong sounds, it’s hard not to look up.

So, how did this $1.2 trillion valuation come about? It actually originates from the on-chain pre-IPO market.

This so-called on-chain pre-IPO market doesn’t trade common stock visible in your brokerage account. It’s more like a designed "pre-IPO risk exposure." Someone tokenizes, structures an SPV, or uses synthetic structures to slice up the future listing expectations of a private company and facilitates matching trades on-chain. It opens a window for ordinary investors that was previously hard to access, and it provides the market with a real-time price. This is where Anthropic was priced at $1.2 trillion.

Over the past two years, the feeling AI has left on ordinary people isn't often "I'm participating in a new era," but rather "A new era has passed me by." Nvidia surged, cloud providers surged, and large model companies went through round after round of funding. But the truly core equity was mostly locked up in private markets. We could see the ship, but we couldn't touch the ticket. So any ticket that might lead to companies like OpenAI or Anthropic naturally comes with a built-in halo.

But it’s precisely in moments like these that we need to take numbers out of headlines, put them on the table, and see exactly how they came to be. Anthropic is arguably one of the most worthy AI companies to study right now. But the issue is that a good company, a great era, and an aggressive price don't automatically combine into the same thing.

On the crypto exchange Jupiter, Anthropic’s pre-IPO token had a daily trading volume of only $1.39 million, with only 329 traders in the past 24 hours. And it’s precisely this $1.39 million and 329 traders that reflect a trillion-dollar illusion.

But I don’t want to discuss whether Anthropic is worth the money, nor do I want to talk about whether there are issues with trading pre-IPO assets on-chain. First, I want to understand a more fundamental question: what conditions must a price meet to qualify as a "valuation"?

The Birth Certificate of a Price

In February 2026, Anthropic completed its Series G funding round. It raised $300 billion at a $3.8 trillion valuation, led by Singapore’s sovereign wealth fund GIC and hedge fund Coatue Management. A month later, OpenAI also announced the completion of its latest funding round, $1.22 trillion at an $8.52 trillion valuation, with major investors including SoftBank, Microsoft, and other institutional investors.

How were these two sets of numbers generated?

Take Anthropic’s Series G round as an example. GIC is a sovereign wealth fund managing over $700 billion, and Coatue is a global tech hedge fund managing over $600 billion. They each had dozens-strong due diligence teams spending months analyzing Anthropic’s technical architecture, revenue curves, customer retention, and competitive landscape. The final $300 billion investment came with a full set of legal terms, including anti-dilution protections, liquidation preferences, information rights, and board observer seats. If Anthropic underperformed or went downhill, these terms ensured GIC and Coatue could recoup their principal first.

They didn’t just buy a number; they bought a complete, legally enforceable rights structure.

What about the $1.2 trillion on Jupiter? Over three hundred traders, a daily volume of just over a million dollars, and the token carries no promises or obligations from Anthropic. What you buy isn’t a small piece of the company; it’s just an on-chain betting receipt.

Both prices are presented identically in reporting headlines, both called "valuation of XX billion."

In 1985, financial economist Albert Kyle published his seminal paper "Continuous Auctions and Insider Trading," introducing the concept of "market depth," using λ to measure the price impact of a unit capital inflow. In a deep market, a $100 million buy order might only cause a 0.1% price fluctuation. In a shallow market, $50,000 can move the price by 20%. The larger λ is, the greater the price impact of a single trade, and the thinner the consensus information the price itself carries.

In Anthropic’s case on Jupiter, a liquidity pool depth of around one million dollars supports an implied valuation of $1.2 trillion. The ratio of liquidity to valuation is approximately 1:1,200,000. If someone wanted to sell a $10 million position at that $1.2 trillion valuation in this market, the entire liquidity pool would be drained ten times over. This price is unexecutable; it exists only on paper and cannot be realized in the real world.

If it were merely treated as a reference indicator for observation, this would be fine. The problem is it wasn't treated that way. It became the evidence for "formally surpassing OpenAI," the headline for "a new global king is born," and the cognitive input for countless readers.

This practice of packaging a marginal price from a thin market as broad consensus didn't start today. It has been happening for nearly four hundred years.

The Tavern in Haarlem

February 3, 1637, Haarlem, Netherlands.

In a small tavern, about thirty people sat around a long table. Following the custom of Amsterdam and Haarlem at the time, these informal tulip bidding gatherings were held several times a week, usually in the back room of a tavern. Participants were local merchants and flower brokers, well acquainted with each other.

The item for auction that day was a Semper Augustus bulb. Its red and white petals were considered a masterpiece of creation. Only about a dozen were known to exist in all of the Netherlands. The bidding lasted the entire evening, finally fetching a price of 10,000 guilders.

In Amsterdam in 1637, a canal-side townhouse sold for about 5,000 guilders, and a skilled craftsman's annual income was about 300 guilders. One bulb was worth two mansions, or 33 years of a craftsman's wages.

This price was born from just thirty people, in a closed space, fueled by alcohol. There were no external constraints, no market maker obligations, no information disclosure requirements. Bidders drove up each other's emotions and were not obligated for anything beyond payment.

The next day, the transaction price was recorded in a pamphlet printed in Haarlem. The pamphlets, carried by postal couriers, spread to Leiden, Rotterdam, Utrecht, and other cities. Peasants and small merchants who read them had no way of knowing how that number was generated. To them, the printed price equaled the market price. Some began hoarding common variety bulbs based on this, believing the entire market would rise as a result.

On February 6th, at a tulip auction in Alkmaar, suddenly no one raised the bid. Then in Haarlem, Amsterdam... within a single day, buy orders vanished across the Netherlands. Those who had hoarded bulbs according to the "market price" found no takers. Prices crashed, falling over 90% within a week.

In hindsight, the "10,000 guilder" price for that Semper Augustus wasn't the judgment of a market; it was the judgment of a single room. But amplified by the printing press, the room's judgment became the nation's perception.

Eighty-three years later, 1720, London.

The South Sea Company's stock rose from £128 at the start of the year to £1,050 in June. This trading company, founded in 1711, held a monopoly on British trade with South America, but actual trading profits were extremely thin. The real driver of the stock price surge was a complex debt-to-equity swap scheme. The company proposed taking over government debt and converting it into company stock, then sustaining the cycle by continuously pushing the stock price higher.

Newton sold his South Sea Company shares when they hit £300, making a profit of £7,000. But the price continued to surge. In July, Newton bought back in, this time at the top. When the crash came that autumn, his total losses reached £20,000, roughly equivalent to ten years of his salary as Master of the Royal Mint.

Newton likely never thought deeply about how that "£1,050" he was referencing came about.

1720 had no electronic trading systems, no central counterparty clearing. Buying and selling South Sea Company shares required going to the company's office in London to process the transfer, or finding a broker in one of the coffee houses of Exchange Alley. Daily actual trades might have numbered in the dozens or low hundreds, involving perhaps a hundred direct counterparties.

These prices were recorded in price lists at Jonathan's Coffee House. When newspapers reprinted these lists, they didn't append a note saying "12 trades today, total volume approximately £8,000." All readers across England saw was the single number: "South Sea Company: £1,050."

When panic selling started in late July, the price generated by a limited game involving a hundred people was shattered instantly. No market maker was obligated to buy. There was no circuit breaker, no central bank intervention. By December, the stock price had fallen back to £124, almost back to its starting point for the year.

Now leap forward another two hundred and sixty years. Tokyo, late 1980s.

"The land value of the Imperial Palace in Tokyo is worth more than the entire state of California." This statement was widely cited by global media in 1989. Based on estimations at the time, the total value of the 2.3 square kilometer Imperial Palace land, extrapolated from surrounding land prices, was about $850 billion. The total assessed value of all land in California was about $500 billion. But this estimate was based solely on the unit price of a few actual transactions in Ginza and Marunouchi.

Japan's land market had a unique structural characteristic: extremely low turnover. Japanese landowners viewed real estate as family assets to be passed down through generations, not for trading and arbitrage. At the peak of the bubble in 1989, the total number of annual land transactions in Tokyo's core business districts was extremely limited. Land that occasionally came to market was usually due to owner bankruptcy or family inheritance disputes, creating a situation where a large number of cash-rich, eager buyers competed for a very small supply.

Prices generated under this extreme supply-demand imbalance were then extrapolated by real estate appraisal agencies as the "fair market value" for all similar land in the area. Their logic was: if this small piece of land is worth 20 million yen per square meter, then every adjacent piece of land must be worth the same.

In 1990, the Bank of Japan raised interest rates consecutively, and banks tightened lending standards. When companies were forced to sell real estate to repay loans, the true liquidity test began. Sell orders flooded in, and buy orders were thin. Actual liquidation prices were 50% to 80% lower than the so-called market valuations.

Japan's nationwide land price index then fell continuously for 26 years, not seeing its first modest recovery until 2016.

The tavern in Haarlem. The coffee house in London. The real estate appraiser's office in Tokyo. The Jupiter DEX on Solana. Four scenes spanning nearly four centuries, sharing the same narrative structure:

A tiny number of participants generate an extreme price in a very thin market → Media spreads it as broad consensus → A wider public makes decisions based on it → When liquidity is truly tested, the price reverts.

The media evolved: pamphlets, newspapers, telegraphs, television, WeChat public accounts. But that core flaw was never fixed: when a price is transmitted, its birth conditions are systematically omitted.

Why?

Complex Stories Are Always Compressed into an Easily Spreadable Number

Business reporting has a natural challenge: the real world is too complex, and the dissemination window is too short.

Telling what really happened to a company often involves explaining funding structures, product progress, revenue quality, competitive positioning, equity rights, exit paths, and market sentiment. But a headline has only one line, and a reader's attention span is only a few seconds. So expressions like "valuation breaks a hundred billion," "market cap evaporates by a trillion," "unicorn is born," "super platform rises" become an easily chosen form of compression. It's a narrow gate that complex business information must pass through when entering public discourse.

Writers are certainly stuck in this gate too. We all know that explaining the birth conditions of a valuation is much harder than writing a headline with impact. The former requires patience, space, and time the reader is willing to spend. The latter just needs a bright enough number for people to instantly know "something is happening here." If a headline were written as "Anthropic's on-chain pre-IPO synthetic asset marginal price in a low-volume market, extrapolated to an implied valuation of $1.2 trillion," it might be more accurate, but it might also exhaust its propagation power before reaching the reader.

If it's written as "A New Global AI King is Born," things are different. It has drama, winners and losers, a throne, and the power transfer humans always love to watch. Dissemination isn't just moving facts; it's more like a juicer. You put facts in, and what comes out is emotion.

The second reason is market structure. A crucial role is missing in the Chinese-language business information environment: the short seller.

In the US capital market, a price detached from fundamentals doesn't stay safe for long. The business model of short-selling research firms like Muddy Waters, Citron Research, and Hindenburg Research is to identify targets whose price far exceeds what their liquidity or fundamentals can support, then publicly release reports while shorting the stock for profit.

They have strong economic incentives to show the public the birth conditions of a number. Muddy Waters' 2020 report shorting Luckin Coffee was 89 pages long, using 92 full-time and 1,418 part-time investigators, recording over 11,000 hours of store footage at 981 stores nationwide, and meticulously verifying 25,843 receipts. All this was just to prove one thing: Luckin's reported daily cups sold per store were fake; the real number was about half of what was claimed.

This level of adversarial research requires two prerequisites. First, a short-selling mechanism exists to profit from the "price reversion." Second, legal protections exist so short-selling reports aren't suppressed. Both conditions are present in the US stock market. In China's A-share market and primary market, both are essentially absent.

The result is that no one can make money by questioning a valuation, so no one has the incentive to ask under what conditions the price was generated.

Short sellers are not destroyers. They are a corrective mechanism within the pricing system. The consequence of dismantling this corrective mechanism is that price deviations can continue to expand without resistance until they collapse under their own weight one day. And every day before the collapse, the market looks normal.

The consequences of these two forces combined are not without precedent in Chinese business history.

In June 2015, LeEco's stock hit its peak on the Shenzhen ChiNext board, with a market cap of about 170 billion RMB. Jia Yueting's vision of a LeEco ecosystem spanning phones, TVs, cars, sports, and films, the concept of "chemical reactions" among its seven sub-ecosystems, led investors to believe that the synergies of these businesses shouldn't be valued by sum-of-the-parts, but by the exponential growth of the entire ecosystem.

No one questioned how much capital was actually gaming behind this 170 billion RMB market cap. LeEco's daily trading volume in 2015 was indeed significant. However, over 70% of the shares behind this 170 billion market cap were locked up; the actual tradable float was much smaller than the total market cap implied. Retail investors and small institutions, trading based on this limited float, pushed up the price, and this price was automatically multiplied by the total share count to arrive at "170 billion."

A large number is produced → It enters rankings → It provides certainty → No one has the incentive or ability to question it → An even larger number is produced.

Seen this way, Anthropic's "$1.2 trillion" isn't an anomaly; it's just the output of a functioning system.

Anxiety, Anxiety

Let's read that $1.2 trillion from a different angle.

What kind of person buys a synthetic token with no legal guarantees at an implied valuation three times higher than the latest institutional round, in a market with a liquidity pool of just over a million dollars?

The answer is someone whose FOMO is strong enough to pay an anxiety premium.

When Anthropic's Series G round closed in February 2026, the valuation was $3.8 trillion. Two months later, the implied valuation of the token on Jupiter was already over three times that number.

Is this