📰 Key Takeaways

Anthropic’s annualized revenue run rate keeps accelerating. Bloomberg reported Monday that as of the end of July, the AI model developer’s annualized revenue run rate (an estimate of full-year revenue based on a recent shorter period) topped $65 billion, up sharply from $47 billion in May and far above the roughly $9 billion it posted at the end of last year. Anthropic hasn’t responded to a request for comment. According to the Financial Times, investors expect the company to maintain a similar growth pace in the second half of the year, with full-year revenue projected to land between $100 billion and $120 billion. By comparison, rival OpenAI’s revenue doubled from $20 billion at the end of 2025 to $40 billion, Bloomberg reported last week. While the two companies may calculate their revenue metrics differently, Anthropic’s growth rate is clearly catching investors’ eyes more. Both companies have filed confidential IPO paperwork, and the market expects Anthropic to beat OpenAI to the public markets, potentially as soon as this fall. The Financial Times notes Anthropic will seek a public market valuation of at least $2 trillion, which would make it the largest IPO in history if it happens. Anthropic’s last valuation was $196.5 billion, set at the end of May when it closed a $65 billion funding round.

💬 JudyAI Lab’s Take

Anthropic’s annualized revenue run rate topped $65 billion as of the end of July, another jump from $47 billion in May — and a rocket ride from $9 billion at the start of the year. That growth rate clearly outpaces OpenAI’s move from $20 billion to $40 billion over the same stretch.

This comparison matters to AI builders not just because of the raw numbers, but because it shows enterprise willingness to pay for AI is shifting fast from “trial” to “at-scale adoption.” When a model developer’s revenue can grow more than 7x in half a year, it means demand for its API, enterprise partnerships, and product integrations has moved well past hype and into real commercial conversion. For teams building AI products or services, this is a signal too: customers are willing to keep paying for stable AI capabilities that plug into their workflows — not just novelty. That’s also the confidence behind both companies filing confidential IPOs, with the market expecting listings before year-end.

Worth asking yourself: is your AI product still stuck at “being tried out,” or has it built a real loop of “being continuously paid for”?

📅 Source Info

🔗 Further Reading