Anthropic, the AI company behind the Claude chatbot, has reached a $1.2 trillion valuation on secondary markets, overtaking rival OpenAI and marking a 550% year-over-year increase. The figure, confirmed by Caplight co-founder Javier Avalos and Rainmaker Securities CEO Glen Anderson, makes Anthropic the most sought-after private company in venture secondary history. Despite the staggering demand, actual trades are rare because almost no existing shareholders are willing to sell, and opportunistic buyers have offered everything from cash to homes in exchange for shares. Most transactions occur through special purpose vehicles (SPVs), a practice Anthropic openly opposes, warning investors to “assume it is invalid.” The company’s last official round, a $965 billion Series H in late May 2026, now sits well below its secondary market price, and Anthropic filed a confidential IPO prospectus with the SEC in early June 2026.
Meanwhile, Sequoia Capital partner David Cahn warns that the AI industry’s infrastructure spending has escalated into a $3 trillion problem. In 2023, Cahn calculated a $200 billion revenue gap to justify Nvidia’s GPU sales; by 2026, total AI infrastructure spending is projected at $1.5 trillion, requiring roughly $3 trillion in revenue to break even—a figure he considers an underestimate due to rising memory and inference chip costs. On the revenue side, Anthropic is reported to generate $60 billion in annual recurring revenue, while OpenAI’s 2025 revenues reached $13 billion, with a $20 billion annualized run rate. However, this leaves a massive shortfall. Apollo chief economist Torsten Slok flags additional risks: organizations are shifting to cheaper open-weight AI models, token prices are declining (OpenAI’s latest model is 54% more token-efficient), and hyperscalers—Google, Meta, Microsoft, and Amazon—must deliver ambitious free cash flow targets by 2028. Slok cautions that failure could trigger an economic downturn and an S&P 500 correction. The disconnect between soaring valuations and the actual revenue math remains the central question for the AI industry’s next chapter.
