Article | Su Yang

Editor | Xu Qingyang

Bloomberg reported that informed sources disclosed that the AI startup Anthropic is engaged in early-stage talks with investors to raise at least $30 billion in new funding, with a valuation exceeding $900 billion.

Informed sources revealed that this round of financing is expected to be completed by the end of May 2026 at the earliest, although the deal has not yet been finalized, and no terms have been signed.

If the financing is successful, Anthropic will not only surpass OpenAI (valued at $852 billion in March) but also challenge the market values of tech giants like Apple and Microsoft. It is noteworthy that early investors in this company have largely chosen to sit on the sidelines in this round.

Anthropic CEO Dario Amodei. This image was generated by AI

01 $30 Billion Annual Revenue with 40% Gross Margin

Why can a company see its valuation surge 15-fold in 14 months? The answer seems obvious: growth rate.

According to publicly reported data, Anthropic’s annualized revenue skyrocketed from $1 billion in December 2024 to $30 billion by the end of March 2026. This means that over several consecutive years, it has maintained a growth rate exceeding tenfold.

Such a growth curve may have no precedent in the history of enterprise software.

Among the top ten companies in the Fortune Global 500 list, eight are clients of Anthropic. More than 1,000 enterprise accounts spend over $1 million annually on Claude. Particularly, its developer-focused coding product, Claude Code, after launching in May 2025, achieved an annualized revenue of $2.5 billion by February 2026, with enterprise subscriptions quadrupling within the first six weeks of the year.

Based on a valuation of $900 billion and an annualized revenue of $30 billion, the price-to-sales ratio is approximately 30 times. This multiple sounds extreme, but supporters are betting on the future when they calculate it. They believe that a company growing tenfold annually cannot be valued in a conventional way. Its pricing logic assumes it can maintain a similar compound growth rate until 2028, making the current valuation reasonable in hindsight.

Regarding Anthropic's revenue, competitor OpenAI has raised its own questions, arguing that Anthropic’s reported $30 billion annualized revenue employs a total revenue accounting method, where it counts all end-user consumption as revenue when customers use its models via Amazon Cloud, Google Cloud, etc., while listing the fees paid to cloud platforms as expenses.

OpenAI estimates that after deducting these intermediary costs, Anthropic's true annual revenue is closer to $22 billion. This $8 billion discrepancy is purely a methodological choice, but it will be a focal point for markets and regulators during the IPO.

More noteworthy than revenue metrics is the cost.

According to reports, Anthropic plans to spend approximately $19 billion in 2026 on training and inference computing, a number nearly equivalent to its annual revenue. More troubling is that due to inference costs surpassing expectations by 23%, the company's gross margin has shrunk to about 40%, a level far lower than most mature enterprise software companies.

Anthropic has yet to achieve profitability, with expectations to break even by 2028. These financial indicators are indeed unusual for a company with a valuation nearing a trillion dollars.

02 Valuation-Driven Arms Race in Computing Power

Why does Anthropic need to raise so much money?

Nominally for development and expansion, but in reality, the majority of this $30 billion financing is aimed at paying for the computational infrastructure it has already committed to but has not yet built. This seems to represent a model that is entirely different from traditional tech finance.

In the past, startups sought financing to refine products and expand markets, gradually matching valuations through growth. But in the AI era, startups need to first secure financing at extremely high valuations to lock in massive amounts of future computing power, hoping that this computing capability will drive model performance leaps, leading to revenue growth, ultimately demonstrating that high valuation is reasonable.

It resembles a debate over whether the chicken or the egg came first.

Currently, the cycle of valuation driving commitments of computing power, and those commitments requiring the next round of even higher valuations, is accelerating. Anthropic exemplifies this model to the utmost.

Once this cycle begins, it is difficult to stop. It can elevate a company to great heights, but it can also plummet it into the abyss.

By early 2026, Anthropic's valuation soared to $380 billion.

Dario Amodei, CEO of Anthropic, stated in an interview with Fortune magazine shortly after the company completed its previous $30 billion financing round, that if AI progress were delayed by 12 months, Anthropic would go bankrupt.

For a company valued at $900 billion, the distance between “extraordinary success” and “operational bankruptcy” may only be a few bad quarters.

This precarious balance might explain why sensitive early investors have largely refrained from participating in this round.

03 Early Investors Hold Back

According to Forbes, some early supporters of Anthropic—those who entered at a valuation of $4.1 billion in 2023 or $61.5 billion in March 2025—have virtually no intention of participating in this round.

The reason is simple: bankers privately estimate that if Anthropic goes public as early as October 2026, its valuation in the public market could fall between $400 billion to $500 billion. This means that anyone investing at a valuation of $900 billion in the last private round would theoretically be at a loss on paper before the stocks can be traded.

This discrepancy between late-stage private equity valuation being significantly higher than expected IPO valuation is very rare in tech financing history.

It serves as a signal that either suggests the company is severely overvalued in the private market or indicates that the public market will provide a vastly different pricing. Either possibility is fraught with uncertainty.

And the upcoming decisive event is the IPO itself.

We've previously mentioned a key figure behind Anthropic's IPO and financing—the company's financial head, Krishna Rao.

The Information reported that, at that time, Anthropic's lifeline for computing power was essentially reliant on Google alone. Rao felt this was not acceptable and proposed a new strategy to diversify power suppliers among investors and internally within the company.

According to The Information, citing informed sources, Rao had in-depth discussions with one of the investors, Byron Deeter of Bessemer Venture Partners, about this strategy. Deeter later commented that it was Rao who made the company realize that finding more partners would enable faster growth.

Looking back now, Anthropic moved faster than OpenAI. They have signed deep agreements with three cloud computing giants: Amazon, Google, and Microsoft. At the chip level, they have incorporated NVIDIA’s GPUs, Google’s proprietary TPUs, and Amazon’s chips, forming a diversified supply network.

However, merely signing agreements is not enough; the core is to ensure that suppliers can truly deliver the computing resources. Rao led two major contracts at the end of 2025: one worth $30 billion to use Microsoft’s cloud servers to operate NVIDIA chips, and another to reserve up to 1 million TPUs from Google.

By early April 2026, Anthropic took another step forward and reached a new agreement with Broadcom and Google to secure several gigawatt-level data centers' power capacity. These actions go beyond merely “purchasing” computing power and move towards large-scale “reserving” future infrastructure.

Since Rao's joining, the total financing he has helped the company complete has reached $60 billion. By January of this year, the company’s valuation had risen to $380 billion.

It can be said that under Rao's strong push, Anthropic's computing infrastructure and financial ammunition have reached an unprecedented scale.

04 Is There a Bubble? Only Time Will Tell in Six Months

At the current pace, if this round of financing is successfully completed, Anthropic is expected to seek an IPO between October 2026 and the first half of 2027, with Goldman Sachs, JPMorgan Chase, and Morgan Stanley reportedly in discussions regarding this matter.

At that time, the core concern of the market will no longer be whether “Anthropic can sustain growth,” but rather a referendum on the valuation logic in the entire AI industry: Over the past three years, has the private market’s pricing of AI been correct?

The commitments for capital expenditures by massive enterprises, multi-year power reservation contracts, a 40% gross margin, disputes between total revenue and net income accounting methods, and the accelerating cycle of “valuation-computing power-reevaluation”—all these complex issues, which can be obscured in the private market, will be placed under the microscope of the public market during the IPO.

If the public market is willing to assign Anthropic a valuation of $1 trillion or even higher, then the price of entry at a valuation of $900 billion looks like a generous advance placement. However, if the market only assigns $500 billion, the final group of private investors will find themselves in a very awkward position.

A third possibility, perhaps more far-reaching, is that Anthropic's IPO will serve as a key data point to validate or invalidate the entire structural hypothesis of AI finance.

Remember Michael Burry, the protagonist of The Big Short? He has recently been calling out bubbles in “internet stocks” and “chip stocks” in his subscription column. If Anthropic's IPO disproves the assumptions of AI finance, it will be the moment the bubble bursts.

Therefore, whether for Anthropic itself or for the entire AI industry that has become accustomed to skyrocketing valuations over the past three years, the stress test is just beginning and will soon be presented with the most authentic and ruthless pricing reflected in a stock movement curve.

Contributed by special translator Jin Lu

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