AI startup Anthropic is in early talks with investors, aiming to raise at least $30.00B in new funding at a valuation exceeding $900.00B. Sources familiar with the matter revealed that this round of financing is expected to be completed as early as the end of May 2026, but the deal has not been finalized and no term sheets have been signed. If the financing is successful, Anthropic will not only leave OpenAI (valued at $852.00B in March) behind, but also challenge the market capitalization of tech giants such as Apple and Microsoft. It should be noted that early investors in the company have basically chosen to sit on the sidelines in this round.
Why can a company’s valuation skyrocket 15 times in 14 months? The answer seems obvious: growth rate. According to publicly reported data, Anthropic’s annualized revenue soared from $1.00B in December 2024 to $30.00B at the end of March 2026. This means that it has maintained a growth rate of more than 10 times for several consecutive years. Such a growth curve may not find any precedent in the history of enterprise software. Eight of the top ten companies on the Fortune Global 500 list are already Anthropic customers. More than 1000 enterprise accounts spend more than $1.00M annually on Claude. In particular, its developer-oriented coding product, Claude Code, has achieved an annualized revenue of $2.50B from its launch in May 2025 to February 2026, and enterprise subscriptions have quadrupled in the first six weeks of the year.
Based on a valuation of $900.00B and an annualized revenue of $30.00B, the price-to-sales ratio is approximately 30 times. This multiple sounds extreme, but supporters are betting on the future when calculating it. They believe that a company with a 10-fold annual growth rate cannot be valued in the conventional way. Regarding Anthropic’s revenue, OpenAI, as a competitor, has raised its own questions, arguing that the $30.00B annualized revenue reported by Anthropic uses gross revenue accounting. OpenAI estimates that after deducting these transit fees, Anthropic’s true annual revenue is closer to $22.00B. This $8.00B difference is purely a methodological choice, but it will become the focus of market and regulatory scrutiny during the IPO.
What is more noteworthy than the revenue caliber is the cost. According to the data, Anthropic plans to spend approximately $19.00B on training and inference computing in 2026, which is almost equivalent to its full-year revenue. More troublesome is that due to the inference cost exceeding expectations by 23%, the gross profit margin of its business has been compressed to approximately 40%, which is far lower than most mature enterprise software companies. Anthropic is currently not profitable and is expected to break even by 2028. For a company with a valuation approaching $1.00T, these financial indicators combined are indeed unusual.
Why does Anthropic need to raise so much money? Nominally, it is for development and expansion, but in essence, most of this $30.00B financing is to pay for the computing infrastructure that it has already committed to but has not yet built. This seems to be a completely different model from traditional technology finance. In the past, startups raised funds to polish products, expand markets, and then gradually match valuations with growth. But in the AI era, startups need to raise funds at extremely high valuations first, use the money to lock in massive computing power in the future, and then hope that this computing power can drive model capabilities to leap, thereby bringing revenue growth, to finally prove that the high valuation is reasonable. Now, valuation drives computing power commitments, and computing power commitments require the next round of higher valuations to pay for it, and this cycle is constantly accelerating.
According to Forbes, some of Anthropic’s early backers—those who entered in 2023 at a valuation of $4.10B or in March 2025 at a valuation of $61.50B—have almost no intention of participating in this round. The reason is simple: bankers privately expect that if Anthropic goes public as early as October 2026, its public market valuation may fall between $400.00B and $500.00B. This means that if someone invests in the last round of private equity at a valuation of $900.00B, then theoretically, before the stock is unblocked and cannot be traded, this investment has already lost money on paper. This kind of inversion where the late-stage private equity valuation is significantly higher than the expected IPO valuation is very rare in the history of technology financing.
Driven by CFO Krishna Rao, Anthropic has signed in-depth agreements with the three cloud computing giants, Amazon, Google, and Microsoft, and has incorporated NVIDIA’s GPUs, Google’s self-developed TPUs, and Amazon’s chips, forming a diversified supply network. Rao led two major deals at the end of 2025: one was spending $30.00B to use Microsoft cloud servers to run NVIDIA chips; the other was contracting up to 1.00M TPUs from Google. In early April 2026, Anthropic went a step further and reached a new agreement with Broadcom and Google to lock in several gigawatts of data center power supply capacity. These actions are no longer simply “purchasing” computing power, but are massively “reserving” future infrastructure.
According to the current pace, if this round of financing is completed as desired, Anthropic is expected to seek an IPO between October 2026 and the first half of 2027. At that time, the core focus of the market will no longer be “whether Anthropic can continue to grow,” but will become a referendum on the valuation logic of the entire AI industry. If the public market is willing to give Anthropic a valuation of $1.00T or even higher, then the entry price of $900.00B valuation looks like a generous early layout. But if the market only gives $500.00B, then the last batch of private equity investors will be in a very awkward situation. Whether for Anthropic itself or for the entire AI industry, the stress test has just begun.
[Bloomberg]
Anthropic’s $900B Valuation: Implications for the Crypto AI Ecosystem
The reported $900 billion valuation target for Anthropic, with its proposed $30 billion funding round, represents a watershed moment for the artificial intelligence sector and carries significant implications for the broader crypto market. This unprecedented valuation—surpassing even established tech giants and creating a “valuation inversion” where private market valuations exceed expected IPO multiples—signals both the extraordinary potential and extreme risks currently embedded in the AI investment landscape.
Market Impact: The AI Halo Effect on Crypto
Anthropic’s meteoric rise, with revenue purportedly growing from $1 billion to $30 billion in just 14 months, has created a powerful “halo effect” that is already reverberating through the crypto sector. AI-related tokens are experiencing renewed speculative interest as investors seek exposure to what appears to be the next major technological paradigm shift. However, this enthusiasm must be tempered with critical analysis of the underlying fundamentals.
The most immediate impact is visible in the AI token sector, where projects like SingularityNET (AGIX), Fetch.ai (FET), Ocean Protocol (OCEAN), and Render Token (RNDR) have seen correlated price movements. This correlation, while potentially beneficial in the short term, poses significant risks as these tokens become increasingly tied to the valuation narratives of traditional AI companies rather than their own utility and adoption metrics.
Token Price Implications: Short-Term Hype, Long-Term Fundamentals
The extreme valuations in traditional AI are creating a dangerous feedback loop in crypto markets. We’re witnessing what can only be described as “valuation spillover,” where the astronomical multiples assigned to centralized AI companies are being extrapolated to their crypto counterparts. This has resulted in AI tokens trading at price-to-sales ratios that exceed even those of their traditional counterparts, creating significant valuation disconnects from fundamental metrics.
The case of RNDR is particularly instructive. As a token representing decentralized GPU resources, it should theoretically benefit from the massive computing demands of companies like Anthropic. However, the current pricing already incorporates years of future growth assumptions, leaving little room for error if Anthropic’s growth trajectory falters or if decentralized computing fails to capture meaningful market share.
Risks: The Fragile Foundation of AI Valuations
Several significant risks emerge from Anthropic’s valuation narrative that crypto investors must carefully consider:
-
The Profitability Gap: Anthropic’s 40% gross margin—significantly below typical software industry standards—highlights the fundamental challenge of monetizing AI at scale. The company’s plan to spend nearly $19 billion on computing infrastructure in 2026, nearly equal to its projected revenue, creates a precarious financial model that depends on perpetual growth and cost reduction. This “growth at all costs” approach has historically proven unsustainable in technology sectors.
-
Valuation Inversion: The expectation that Anthropic’s IPO valuation could be $400-500 billion—substantially below the current $900 billion private valuation—creates a dangerous precedent. This inversion, where late-stage private investors face immediate paper losses upon listing, could trigger a cascade of deleveraging across both traditional and crypto AI investments.
-
Infrastructure Bottlenecks: Anthropic’s aggressive commitments to computing resources, including 1 million Google TPUs and multi-gigawatt power supplies, highlight the physical constraints of the AI revolution. These bottlenecks could limit growth projections and create unexpected cost overruns, with implications for the entire AI ecosystem.
-
Regulatory Scrutiny: The accounting discrepancies highlighted between Anthropic’s $30 billion revenue claim and OpenAI’s estimate of $22 billion (after transit fees) suggests that regulatory scrutiny will intensify as these companies approach public markets. This could extend to crypto projects that make similar bold claims about AI capabilities and revenue potential.
Opportunities: Decentralization as a Differentiation Strategy
Despite the risks, several compelling opportunities emerge for the crypto AI ecosystem:
-
Cost Efficiency through Decentralization: The massive computing costs faced by Anthropic represent a fundamental weakness in centralized AI models. Crypto-native projects offering decentralized computing solutions—particularly those with innovative tokenomics that can share the cost burden across a network—have the potential to capture significant market share if they can demonstrate comparable performance at a fraction of the cost.
-
Data Sovereignty and Privacy: Anthropic’s reliance on centralized data collection and processing creates inherent vulnerabilities. Blockchain-based AI solutions that emphasize data privacy, user control, and verifiable computation can carve out valuable niches in enterprise and consumer markets.
-
AI-Enabled Smart Contracts: The convergence of AI and blockchain represents a largely untapped opportunity. Projects that successfully integrate AI capabilities into smart contracts—creating systems that can learn, adapt, and optimize automatically—could unlock entirely new categories of decentralized applications.
-
Tokenized AI Services: The high valuations of AI companies suggest significant interest in gaining exposure to AI capabilities. Crypto projects that facilitate fractional ownership of AI services or create marketplaces for AI models could tap into this demand while avoiding the infrastructure cost burdens faced by centralized players.
Strategic Considerations for Crypto Investors
For experienced crypto investors, the Anthropic valuation narrative serves as both a cautionary tale and an opportunity map. The key is to distinguish between:
-
Speculative Hype: Tokens rising purely on association with AI themes without fundamental utility or clear path to revenue.
-
Fundamental Value: Projects solving real problems in the AI space, particularly those addressing cost, efficiency, or decentralization challenges.
-
Technological Convergence: Projects successfully integrating blockchain and AI in ways that create new capabilities or business models.
The current environment demands extreme discernment. While the AI revolution is real, the valuation excesses in traditional markets are creating dangerous speculative conditions that could spill over into crypto. The most prudent approach may be to focus on projects with strong fundamentals, clear revenue models, and the ability to thrive regardless of the broader AI market’s valuation fluctuations.
The coming 12-18 months will be critical as we see whether Anthropic and other AI giants can deliver on their extraordinary promises. For crypto investors, this period offers both significant risks and compelling opportunities—the challenge lies in distinguishing between the two.