Reported by | NUPIAO
For OpenAI, the formidable rival Anthropic is no longer just a “chaser” — it’s now leading the race.
Recently, Anthropic revealed to potential investors that its second-quarter revenue grew at least 14-fold compared to the same period last year. According to related documents, the company’s preliminary revenue for the most recent full quarter exceeded $11.5 billion, compared to $787 million during the same period in 2025 and $4.73 billion in the first quarter of this year — a sequential growth of over 140%.
The documents also showed that Anthropic recorded its first adjusted operating profit of $559 million in Q2, achieving profitability at the operational level. Based on this performance, Anthropic’s latest annualized revenue run rate has surpassed $46 billion.
On August 18, sources familiar with the matter indicated that Anthropic’s annualized revenue based on current business performance could exceed $65 billion — a more than six-fold increase from the end of last year.
By contrast, OpenAI’s Q2 revenue stood at $6.7 billion, up just 18% sequentially from $5.7 billion in Q1. Its growth has clearly decelerated, while operating losses continued to widen without turning profitable. Its annualized revenue in 2026 is expected to surpass $40 billion, roughly doubling its 2025 figures.
On one side, we have quarterly profitability; on the other, heavy losses. These two very different report cards signal a substantive divergence in the business models of these two leading AI companies.
Some institutional analysts believe the widening revenue gap mainly comes down to choices driven by the actual cost of enterprise usage. Although Anthropic’s flagship models carry a hefty price tag per call, their higher task-completion accuracy reduces repeated calls and manual review — meaning the real comprehensive cost for enterprises actually works out in their favor.
Anthropic has long concentrated its resources on enterprise development scenarios. Its Claude Code programming tool has experienced explosive growth, firmly capturing the needs of developers and tech-focused enterprises, with the enterprise segment contributing the vast majority of incremental revenue. OpenAI, meanwhile, has built a massive consumer base on the back of ChatGPT, but consumer subscription growth has hit a ceiling, and its enterprise business expansion hasn’t kept pace with its rival.
Beyond that, Anthropic places a premium on revenue quality and gross margins, prioritizing the refinement of enterprise tools that can be quickly monetized. OpenAI, in contrast, maintains a strategy of full-scale investment across large models and multiple product lines, with enormous spending on computing infrastructure — for every dollar of revenue generated, it bears heavy hardware and inference costs.
In April of this year, multiple media outlets reported that OpenAI had missed its monthly sales targets for several months, and ChatGPT failed to reach its goal of 1 billion weekly active users by the end of 2025. With Google’s Gemini gaining popularity last year, ChatGPT’s subscriber churn rate continues to pose a challenge.
OpenAI’s CFO Sarah Friar has also expressed concerns in conversations with other company executives, worrying that if OpenAI’s sales growth isn’t fast enough, it may struggle to afford future computing needs.
As the performance landscape shifts, both companies are busily preparing for IPOs, hoping to leverage public market capital to fund future computing and R&D investments. Anthropic already submitted a confidential S-1 filing to the U.S. SEC in June, with Morgan Stanley, Goldman Sachs, and JPMorgan jointly serving as underwriters, targeting an IPO window in September-October of this year.
Some investors have floated valuations as high as $2 trillion for Anthropic. If that target materializes, Anthropic would surpass SpaceX’s previous IPO valuation record of $1.77 trillion, becoming the largest IPO in history. Wall Street is looking further into the future than usual to value this AI company, basing its assessment on the revenue it could generate two years from now.
According to two people familiar with the company’s financials, Anthropic projects 2028 revenue of approximately $190 billion to $200 billion — a figure that has not been previously disclosed.
Anthropic also plans to grant CEO Dario Amodei and other co-founders shares with extra voting rights, a move also aimed at preparing the company for its Wall Street debut. This type of share structure is common in the tech industry, designed to ensure founders retain greater say over the company’s strategic direction. Meta CEO Mark Zuckerberg and others also hold super-voting shares.
OpenAI’s IPO timeline, by contrast, remains relatively vague. On June 8, local time, OpenAI CEO Sam Altman told employees that the company expects to go public “within the next year.” Altman said the actual timing could shift earlier or later, but “filing now gives us more flexibility.” That same day, OpenAI announced it had confidentially submitted its S-1 draft for an IPO to the SEC.
However, with OpenAI’s losses continuing to widen, many investors have doubts about the company’s IPO valuation. Fidelity Securities wrote in a recent report that OpenAI’s anchor valuation is “closer to $700-800 billion, rather than $1 trillion.”
Both companies are aggressively vying for position in the enterprise AI space. On May 4, Anthropic and OpenAI announced major enterprise AI joint ventures on virtually the same day. OpenAI launched “The Deployment Company,” partnering with TPG, Bain Capital, SoftBank, and others to build a $10 billion-scale enterprise AI deployment platform offering customized AI implementation services for large conglomerates. Anthropic, meanwhile, joined forces with Blackstone and Goldman Sachs to establish a $1.5 billion enterprise AI services joint venture, focused on deploying Claude models to mid-sized enterprises in bulk to expand its customer base.
Even with its revenue overtake, Anthropic still faces multiple real-world challenges. Its profitability is a single-quarter, stage-specific result — rising computing costs, the impact of open-source large models, and tightening enterprise budgets could all erode profit margins. Its heavy dependence on enterprise clients also means that if downstream companies cut AI budgets, revenue growth would quickly come under pressure. For OpenAI, the biggest puzzle is how to balance growth, losses, and capital market expectations.
Many industry investors believe that quarterly revenue only represents the present moment — the real test comes after going public, whether these companies can continuously prove to the market that frontier AI can be a healthy, long-term, sustainable business.
