Original author: Xu Chao

Original source: Wall Street Opinion

The latest analysis from research institution SemiAnalysis reveals that Anthropic is reshaping the AI commercialization landscape with profitability and growth rates that far exceed its competitors. With a high-margin business model centered on APIs, Anthropic has become a leader in the B2B AI market.

According to the in-depth report released by SemiAnalysis, Anthropic is expected to achieve $1 billion in GAAP earnings before interest and taxes (EBIT) in the third quarter of 2026, corresponding to a profit margin of about 6%. Meanwhile, its annual recurring revenue (ARR) has surged from $9 billion at the end of 2025 to currently over $60 billion. The agency predicts that if Anthropic maintains a net new ARR (NNARR) pace of about $15 billion per month, its ARR by the end of 2027 is expected to reach $300 billion, corresponding to a $6 trillion enterprise value, making it the highest valued company globally.

Anthropic secretly submitted its IPO application on June 1. SemiAnalysis believes that going public now has strategic urgency—Alphabet has completed $84.75 billion in equity financing, and Meta is also rumored to have financing plans worth several tens of billions of dollars, while the capital market window is narrowing. The report notes that Anthropic's superior financial data and business model mean it should go public before OpenAI to seize the initiative in capital competition.

Claude Code ignites the B2B market, ARR nearly doubles in a single quarter

The turning point for Anthropic's performance comes from the explosive popularity of Claude Code. Data from SemiAnalysis shows that Claude Code currently accounts for over 7% of all code submissions on GitHub, directly driving the company's ARR from a monthly addition of $3 billion in January to $11 billion in March.

In terms of revenue structure, Anthropic and OpenAI show significant differentiation. About 75% to 85% of Anthropic's ARR comes from usage-based API business, while consumer subscription only accounts for 5% of total ARR. In contrast, OpenAI still derives over 65% of its revenue from subscription models in the first quarter of 2026, with consumer ARR making up about 40% of the total.

SemiAnalysis points out that the core advantage of the API model is that there is no upper limit to single-user revenue— as the same customer adopts more agentic workflows, the amount of tokens consumed and corresponding revenue will continue to grow, allowing for expansion without acquiring new customers. Anthropic's CFO Krishna Rao disclosed in a podcast this May that the company's net revenue retention rate (NRR) is as high as 500%, meaning that of the customers contributing $30 billion in ARR in one quarter, this batch of customers contributed only $2 billion a year ago.

Gross margin advantage creates a compounding flywheel, significant gap with OpenAI

The difference in business models is directly reflected in gross margins. SemiAnalysis estimates that Anthropic's current overall gross margin has risen to the mid-60% range, up from negative 94% in 2024. The gross margin for its API business exceeds 80%.

The primary driver behind the significant improvement in gross margin is the enhanced efficiency of inference. Measured by ARR per megawatt of computing power, Anthropic's figure is expected to reach $60 million later this year, up from only $16 million nine months ago. Since the cost of inference computing power is essentially fixed, when the number of tokens processed per unit of computing power or the pricing of tokens increases, the marginal profit margin approaches 100%.

The report estimates that if both Anthropic and OpenAI achieve $100 billion in ARR, OpenAI will lose about $25 billion in gross profit compared to Anthropic due to the need to support over 900 million free users (SemiAnalysis estimates the monthly service cost at about $0.70 per person). This gap will directly affect both parties' reinvestment capabilities in the training of next-generation models.

SemiAnalysis introduces "earnings before taxes and interest on training" (EBTIT) as the core indicator for measuring the reinvestment capacity of laboratories, with Anthropic's EBTIT profit margin reaching 36% in the second quarter of 2026. The report predicts that by 2028, Anthropic's cumulative EBTIT will be $250 billion higher than that of OpenAI.

Beyond programming, cybersecurity may become the next growth engine

SemiAnalysis estimates that currently over 65% of the laboratory's ARR comes from programming-related use cases, with start-ups like Cursor, Cognition, Loveable, and Replit contributing a total of about $6 billion in ARR. Meta is Anthropic's largest single customer, but its share remains between 3% and 5%.

The report believes that cybersecurity will be the next explosive vertical field following programming, and it is expected that the release of the new Fable model will further enhance token pricing and expand application scenarios, driving monthly NNARR to surpass the current level of $10 billion by the second half of 2026. Medical health, finance, and biotechnology are also listed as potential major directions for TAM expansion.

In terms of distribution channels, the "Token as a Service" (TaaS) model indirectly sold through large-scale cloud platforms like AWS Bedrock and Azure Foundry is rapidly growing, currently accounting for 15% to 20% of Anthropic's ARR, while just a quarter ago, this proportion was only 5% to 10%. SemiAnalysis believes that paying 20% to 30% of revenue to large-scale cloud platforms remains economically reasonable from the perspectives of reaching enterprise clients and compliance convenience.

Computing power bottleneck is the biggest variable, IPO provides a channel for financing

The growth prospects for Anthropic face a core constraint from computing power supply.

SemiAnalysis predicts that by 2030, the combined unconstrained computing power demand of Anthropic and OpenAI will exceed 100 gigawatts (GW), while the net new computing power for 2025 and 2026 is only 2.5 GW and 5 GW, respectively, and currently, both companies combined have available computing power of just over 6 GW.

This supply-demand gap gives the IPO clear strategic significance. The report points out that the funds raised from the public offering will primarily be used to fill the continuously widening computing power demand gap between inference operations and new model training, and to lock in computing resources at more favorable financing costs in advance. The report also mentions that Meta is considering leasing computing power to external parties (according to market rumors from July 1, 2026) and is expected that Anthropic will procure incremental computing power from such trusted suppliers.

SemiAnalysis also lists key risk factors, including: OpenAI's rumored price-cutting plans, competitive pressure from Google DeepMind and Meta in programming models, potential regulatory restrictions from the government on the release of cutting-edge models, and the dilution effect on overall gross margins from the rising proportion of TaaS revenue. The report clearly states that if the regulatory system hinders model releases and narrows the capability gap between open-source models and cutting-edge proprietary models, it will fundamentally weaken Anthropic's business moat.

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