Critical battle before IPO! Anthropic is about to disclose revenue data, and its $2 trillion valuation faces a "major test."

Title context: Critical battle before IPO! Anthropic is about to disclose revenue data, and its $2 trillion valuation faces a "major test." Text: According to reports, Anthropic plans to hold a Pre-IPO investor day at its San Francisco headquarters on October 14 and disclose its third-quarter revenue data to a group of potential institutional investors. As Anthropic advances its listing plans, this latest revenue data is expected to give the market insight into its growth and profitability, and to assess whether the up to $2 trillion valuation it is seeking is reasonable. It could also have a huge impact on AI trades, which are dominated by the technology sector. It is worth noting that Anthropic's disclosure comes at a time when investors are increasingly scrutinizing the financial performance of private AI companies to assess the sustainability of growth across the entire industry. Last week, a report disclosing OpenAI's revenue and accounting treatment caused confusion and dragged down the U.S. AI sector as a whole. OpenAI disclosed to investors that, as of the end of September, its annualized revenue scale was about $50 billion, lower than the $70 billion widely reported by the market at the end of last month. Although people familiar with the matter said the updated figure excludes revenue from cloud partners and does not reflect any change in demand, it is currently unclear whether Anthropic will use the same statistical basis, that is, whether it will include partner revenue. IPO enters a critical stage! Explosive revenue growth supports a sky-high valuation Anthropic's listing plan is gradually becoming a market focus. Recently, reports said Anthropic may officially launch its IPO roadshow as early as the week of November 9, potentially beginning trading before Thanksgiving on November 26. It is said that the company is seeking a $2 trillion valuation. If this valuation is achieved, Anthropic will surpass the $1.77 trillion issuance valuation of SpaceX when it listed in June this year, setting a new record for the world's largest IPO. It must be noted that $2 trillion should currently be regarded as a potential valuation under market discussion, rather than a confirmed issuance price or a formal company commitment. Anthropic, an AI upstart founded only five years ago, is racing from private unicorn to public market at a speed that has stunned Wall Street, and the most direct DRIVE comes from the astonishing explosive power of its financial data. As of the end of July 2026, Anthropic's annualized revenue run rate (ARR) had exceeded $65 billion. This figure increased more than sevenfold from about $9 billion at the end of 2025, and rose another 38% from $47 billion in May. In the second quarter of 2026, the company's preliminary revenue exceeded $11.5 billion, while in the same period of 2025 it was only $787 milliona year-over-year increase of more than 14 times. Even more encouraging to the market, Anthropic turned positive on an adjusted operating profit basis in the second quarter, at about $559 million. This growth trajectory is steep: ARR was only about $87 million in early 2024, about $1 billion at the end of 2024, about $9 billion at the end of 2025, surpassed $30 billion in April 2026, reached $47 billion in May, and surged to $65 billion by the end of July. The most aggressive investor forecast is that annualized revenue will reach $100 billion to $120 billion by the end of 2026. Behind the explosive revenue growth is Anthropic's clear commercialization path. Unlike OpenAI, which relies on consumer subscriptions, more than 80% of Anthropic's revenue comes from API usage payments by enterprises and developers. The number of enterprise customers has exceeded 300,000, and about 70% of Fortune 100 companies have achieved deep adoption. The number of customers spending more than $1 million annually has doubled in recent months, exceeding 1,000. The AI coding tool Claude Code is a core DRIVE, with ARR exceeding $2.5 billion in early 2026 and estimated ARR reaching as high as $15.12 billion by August. A significant improvement in inference efficiency further strengthens the positive cycle of the business model. Anthropic adopts an API-centric, usage-based billing model, with blended gross margin rising to the mid-60s%, and inference gross margin rising from 38% a year earlier to 70% to 85%. For a frontier model company still in a phase of large-scale computing investment, this is a key signal that operating leverage is beginning to emerge from scale effects. Bank of America Securities' chief strategist pointed out that a $2 trillion valuation implies expectations for 2028 revenue and requires growth rates to remain at a level close to triple digits. According to reports, Anthropic internally expects revenue of about $190 billion to $200 billion in 2028. If calculated based on $100 billion in revenue at the end of 2026, a $2 trillion valuation corresponds to a forward price-to-sales ratio of about 20 times, lower than the price-to-sales ratios of more than 50 times common among AI hot stocks such as Palantir and Nebius. Some investors have even said: "If Anthropic can maintain an 800% annual growth rate, even with a conservative 30 times revenue multiple, the company's valuation would be close to $3 trillion." It is worth noting that the other side of high growth is massive cost investment. Anthropic's net loss in 2025 was close to $42 billion, five times the previous year's roughly $8.3 billion. However, about $34 billion of that came from fair value changes in convertible financing instrumentsan accounting loss generated as the valuation soared, not a cash expenditure. After excluding that, the actual operating loss was about $8.06 billion, widening by 170% from $2.98 billion in 2024. The reason for the widening loss is the expansion of upfront computing spending. In 2025, computing and infrastructure spending reached $7.33 billion, equivalent to 1.6 times that year's revenue. But the loss ratio is narrowingthe operating loss ratio fell from about 750% in 2024 to 176% in 2025. The $2 trillion valuation reflects investors' high expectations for the long-term growth space of the AI industry. Compared with traditional software companies, Anthropic not only hopes to generate revenue through model subscriptions, enterprise services, and API interfaces, but also bets that AI can gradually enter core enterprise scenarios such as programming, customer service, knowledge management, and business process automation. As enterprises move from experimental applications to production environment deployment, AI services have the opportunity to upgrade from auxiliary tools to part of enterprise infrastructure. In particular, the expansion of the Claude series models in enterprise applications and programming has enabled Anthropic to pursue more sustainable commercial demand. Once enterprise customers embed AI models into software development, internal knowledge retrieval, or daily operating processes, they often need to continuously pay model invocation and service fees. This type of demand is expected to form high revenue stickiness and also support the company's future revenue growth. However, a high valuation also means higher requirements for delivery. Investors are not only buying Anthropic's current business scale, but also paying for its growth expectations over the next several years. If revenue growth slows after listing, profit improvement falls short of expectations, or the overall valuation of the AI industry contracts, the company's stock price could face significant pressure. Therefore, whether the $2 trillion valuation can hold ultimately depends on whether the market believes Anthropic has the ability to convert its current technological leadership and demand growth into long-term cash flow generation capability. $518 billion infrastructure commitment! The growth engine is also a source of financial pressure If revenue growth is the core of Anthropic's valuation story, then massive computing and infrastructure demand is one of the cost factors in this business model that most needs scrutiny. According to reports, based on Anthropic IPO prospectus documents seen by the media, the company plans to incur about $518 billion in cloud computing and infrastructure-related expenditures or commitments over the next several years. This scale shows that the company's judgment of future AI demand is very aggressive, and also means that its business expansion will be deeply tied to cloud computing services, data center construction, and advanced chip supply. It should be noted that this figure represents related expenditures and infrastructure commitments over many future years. It does not mean the company needs to pay the entire amount at once in a single fiscal year, nor can it simply be equated with capital expenditure or cash outflows that have already occurred. But even considering differences in performance timing and contract structure, such long-term commitments will still have an important impact on the company's future financial flexibility. The cost structure of AI companies differs significantly from that of traditional software companies. For traditional software, after product development is completed, the marginal delivery cost of adding one more user is usually relatively limited; large model services, however, require continuous inference computing. The more frequently users invoke the service and the more complex the tasks the model handles, the higher the related computing costs. For products such as coding agents that can execute complex tasks over long periods, an increase in user usage may bring more revenue, but may also drive up computing resource consumption. Therefore, whether Anthropic can establish attractive profit margins in the future depends on whether multiple factors can improve simultaneously: whether model inference efficiency can increase, whether unit computing costs can decline, whether enterprise customers are willing to accept higher prices, and whether the company can reduce computing procurement costs through long-term contracts and resource scheduling. If the commercial value of AI models continues to increase and enterprise customers are willing to pay for higher productivity, then massive infrastructure investment may become a necessary condition for building competitive barriers. Conversely, if model capabilities gradually converge, service prices continue to fall, or enterprise customers begin to cut AI budgets, long-term computing commitments may become a heavy cost burden. This also means the market cannot simply view the $518 billion infrastructure commitment as a bullish signal for the chip and data center industries. For upstream suppliers, it may represent future demand; for Anthropic itself, it simultaneously represents performance obligations, resource dependence, and future profitability pressure. With its listing valuation already highly dependent on future growth, Anthropic needs to prove to investors that these expenditures are not simply investments in chasing model scale, but long-term investments capable of generating sufficient commercial returns. Customer concentration and cloud platform dependence may limit revenue quality Another important risk for Anthropic comes from its revenue structure. According to reports, Anthropic's prospectus shows that in 2025 the company generated $2.16 billion in revenue through the cloud platforms of Amazon.com, Inc. and Alphabet Inc. Class C, accounting for 47% of full-year revenue. That proportion was only 11% in 2023 and rose to 32% in 2024, indicating that the company's dependence on cloud platform channels is gradually deepening. For Anthropic, selling through cloud platforms can help the company significantly reduce customer acquisition difficulty. Many large customers purchase Claude services directly through cloud marketplaces, which can reduce contract, settlement, and technical deployment steps. Anthropic said in its listing materials that these cloud platforms have sales networks that a single enterprise would find difficult to replicate independently, helping Claude enter the global enterprise market faster. The problem, however, is that Amazon.com, Inc. and Alphabet Inc. Class C are not ordinary channel partners: they both invest in Anthropic and sell it the computing resources needed for training and inference, while also owning their own AI models and cloud computing businesses. This means these competitors can access some of Anthropic's pricing and commercial terms and may influence computing allocation, product promotion, and customer relationships. Anthropic also acknowledged in its prospectus that reliance on a small number of partners and suppliers may give rise to conflicts of interest and adversely affect the company's access to computing resources. High customer concentration does not necessarily mean there is a problem with the business model. For AI companies in a phase of rapid expansion, large technology companies, enterprise customers, and cloud platform partners can often provide considerable procurement scale in the early stages and also help drive products into broader application scenarios. But when a small number of customers contribute a relatively large share of revenue, the company's sensitivity to customer procurement decisions also increases. Once important customers adjust procurement budgets, shift to in-house models, reduce usage, or demand lower prices in contract negotiations, Anthropic's revenue growth CKH HOLDINGS profit margin could be affected. More complicated still, some large partners in the AI industry are both customers and computing suppliers or investors. This relationship helps Anthropic obtain computing resources and commercial channels, but may also leave the company facing a certain degree of dependence. If partners change commercial terms, adjust resource allocation, or devote more resources to promoting their own models, Anthropic will need to cope with potential cost and competitive pressure. Cloud platform channels also involve a difference between revenue recognition and economic returns. Sales revenue obtained through partners can expand a company's customer coverage, but a portion of it must be paid to the cloud service provider. Investors therefore need to focus on revenue after channel commissions, gross margin, customer renewal rates, and customer retention, rather than only looking at unadjusted revenue run rate. After listing, whether Anthropic can continue to expand its direct enterprise customer base, reduce dependence on a small number of customers, and improve the diversity of its revenue sources will become an important indicator for measuring the resilience of its business model. AI competition is accelerating; technological leadership may not excess profit over the long term The competitive environment Anthropic faces also cannot be ignored. Competition in the generative AI market comes not only from direct rivals such as OpenAI, but also from large technology companies' in-house models, open-source models, and a constant stream of vertical solutions. As model capabilities continue to improve, enterprise customers are increasingly likely to consider performance, price, data security, system compatibility, and deployment costs when choosing AI services, rather than relying solely on the brand advantage of a particular model. For Anthropic, the advantages of the Claude series models in enterprise services and programming scenarios are an important foundation for winning customers. But the model industry is characterized by rapid iteration, and today's technological leadership may not necessarily be maintained over the next several years. Even if the company continues to launch new models, it must keep investing in research and development, computing power, and talent to maintain competitiveness. According to reports, prediction markets are currently betting that Alphabet Inc. Class C (GOOGL.US) may overtake Anthropic and lead the 2026 AI model race. In addition, improvements in model capabilities and commercial profits are not always synchronized. Stronger models may help enterprises solve more complex problems and increase customers' willingness to pay; but if competitors offer comparable performance at lower prices, Anthropic may face pricing pressure. If inference costs fall faster than selling prices, profit margins may improve; conversely, price competition may offset the benefits of efficiency gains. The development of AI agents provides Anthropic with new growth opportunities. Compared with chat Siasun Robot&Automation that simply answer questions, agents capable of executing programming, research, and business process tasks may create clearer enterprise productivity gains and also have the opportunity to drive higher usage frequency and deeper workflow integration. But agents may also bring higher computing consumption, reliability requirements, and security responsibilities. Enterprises willing to pay for AI that can complete tasks does not mean they are willing to bear unlimited invocation costs. Anthropic needs to prove that the commercial value of agent products can cover their resource consumption and form a replicable profit model. Therefore, technological leadership is only part of Anthropic's valuation. Longer-term competitive advantages also need to come from multiple aspects, including customer relationships, enterprise workflow integration, product reliability, model efficiency, and cost control. Legal conflict with the U.S. government adds hard-to-quantify policy risk to the IPO In addition to financial and competitive issues, Anthropic also faces a special risk closely related to corporate governance, business expansion, and technology safety: a dispute with the U.S. Department of Defense over restrictions on AI use. According to reports, Anthropic has asked the U.S. Court of Appeals for the D.C. Circuit to rehear a ruling that previously upheld a U.S. Department of Defense decision. Previously, the court ruled 2-1 in support of listing Anthropic as a national security supply chain risk enterprise. The core of the dispute is that Anthropic refuses to allow its AI technology to be used for autonomous weapons or mass surveillance of the American public, while the U.S. Department of Defense believes the relevant restrictions may affect military operations. Anthropic argues that the government's relevant decision exceeds the scope of legal authorization and has a retaliatory nature targeting its AI safety stance. The company previously said this determination has already caused billions of dollars in business losses. At the same time, another related legal dispute saw a different development in August this year: a federal judge in California overturned a parallel determination made under another law. It can thus be seen that the relevant legal issues remain complex and cannot simply be regarded as settled. The impact of this conflict on Anthropic is not limited to potential government contract revenue. A government determination may affect its eligibility to participate in federal projects, cooperation with government contractors, and some customers' judgment of supplier compliance risk. Even if the company has strong demand in the commercial enterprise market, policy risk may still change some customers' procurement decisions. At the same time, Anthropic's stance also involves its brand positioning and long-term strategy. The company has consistently emphasized AI safety and taken a relatively cautious attitude toward the risks and regulatory issues of advanced AI systems. If it loosens relevant restrictions to win government business, it may raise questions about its corporate principles and safety commitments; but if it insists on strict restrictions, it may also lose some government contracts or face adverse policy effects. From a capital market perspective, this is a type of risk that is difficult to measure directly through traditional financial indicators. It may affect not only revenue, but also the company's reputation, regulatory environment, and future business boundaries. Listing documents need to fully disclose relevant litigation, potential losses, and their impact on the business, and investors also need to assess whether these disputes are short-term uncertainties or structural factors that may affect the company's growth path over the long term. Anthropic's listing will become an important stress test for AI trades Anthropic's listing process is not only related to one AI company's financing and shareholder exits, but may also become an important window for the market to test the business model of the entire AI industry. If the company can continue to prove rapid revenue growth after disclosing financial data, while improving profit margins, controlling infrastructure costs, expanding its customer base, and reducing policy risk, then its IPO may further strengthen market confidence in the commercialization prospects of enterprise AI and bring new demand expectations for the AI infrastructure and chip industries. But if financial disclosures show that revenue growth is highly dependent on a small number of customers, cloud platform channel costs are high, or long-term computing commitments place significant pressure on cash flow, then investors may re-examine the basis for its valuation. If the legal dispute with the government further affects the business, it may also cause the market to demand a higher risk discount for its long-term growth path. For potential investors, what is most worth watching about Anthropic is not a single valuation number, but the relationship among revenue, costs, profit, cash flow, and risk. Rapid growth can prove market demand, but it cannot automatically prove that the business model has matured; massive infrastructure investment can support future competition, but it may also amplify financial pressure if demand falls short of expectations. Ultimately, Anthropic is facing one of the most core questions in the AI industry: as large models move from technological breakthroughs to large-scale commercial applications, can a company establish sustainable economic returns while continuing to innovate? What the $2 trillion valuation represents is not only investors' expectations for Anthropic, but also a promise that must be fulfilled by future performance. What truly determines the quality of its IPO will not be how high the market's enthusiasm is for the AI vision, but whether the company can prove that revenue growth can ultimately be converted into stable profits, sustainable cash flow, and competitive barriers sufficient to support a long-term valuation.