OpenAI's Token Price Slash Threatens Its Own IPO Valuation 🪙

OpenAI is weighing significant reductions to the prices it charges for tokens, a move that comes as rival Anthropic rapidly closes the revenue gap, according to a Wall Street Journal report dated June 10. The discussions are described as still in flux, but reflect OpenAI's recognition that Anthropic has emerged as a credible competitor in frontier AI services.

The revenue trajectory separating the two companies has narrowed sharply over the past 18 months. Anthropic's annualized run rate stood at roughly $1 billion at the start of 2025. By April 2026, that figure had reached $30 billion, a path that CEO Dario Amodei described as outstripping the company's own forecasts by a factor of eight. Some analysts estimate Anthropic's annualized revenue may have crossed $47 billion by May 2026. OpenAI, by comparison, reported a revenue run rate of approximately $13 billion in 2025 and does not expect to turn a profit or generate positive free cash flow until 2030.

Anthropic's Claude Code, an AI coding agent launched publicly in May 2025, hit $1 billion in annualized revenue within six months and surpassed $2.5 billion by February 2026. Business subscriptions to the product quadrupled in the first quarter of 2026 alone. Anthropic projects higher revenue than OpenAI in 2029 and targets turning free cash flow positive by 2028, a milestone OpenAI has said it will not reach before 2030.

Both companies are understood to be preparing for public listings. OpenAI has been in discussions for a funding round that would value the company at $750 billion. Anthropic closed a $30 billion Series G in February 2026 at a $380 billion post-money valuation. Cutting prices on a core product shortly before an IPO process is a decision many observers view as risky to the listing's perceived economics, though lower prices can also expand volume if demand proves elastic.

The economics of frontier AI complicate that volume case. OpenAI's own leadership has acknowledged that the cost of training a single competitive model is approaching, and in some projections, far exceeding, $1 billion. In an industry where serving costs are already substantial, price cuts do not automatically produce higher profits and can instead distribute losses across a larger customer base.