OpenAI Wants Another $30 Billion Before It Goes Public
OpenAI is talking to investors about raising at least $30 billion before going public, at a value of about $1.4 trillion. TechCrunch
Bloomberg reported the target on September 29, 2026. It would be a bridge round to an IPO, money raised privately to wait for a public sale, not the sale itself. The $1.4 trillion does not include the new money. AOL
That would reset its private value in under six months. In March 2026, it raised $122 billion at an $852 billion valuation. That was meant to be its last private raise before an IPO.
The IPO timing has slipped. A debut was expected in 2026 until recently. CEO Sam Altman has ruled out a 2026 listing to focus on AI safety.
Sales growth helps explain the talks. OpenAI reached $40 billion in run-rate revenue in August 2026. Run rate takes one month of sales as a yearly pace, like guessing yearly pay from one paycheck. That was up 70% since July 2026, driven by a focus on coding.
Competition is part of the story. Anthropic briefly passed OpenAI at the start of 2026.
The broader context here is fast-changing AI funding. A bridge this big normally means cash is needed before public markets are ready. At $30 billion, the gap beats most primary venture rounds, and the climb from $852 billion to $1.4 trillion squeezes what once took several private cycles into months. For builders of large models, that is training, running systems for users, and keeping staff costs rising with sales.
In my view, sales matter more than the big price tag. A 70% jump in about a month from coding points to paid developer tools where demand and seat growth are clear. That differs from building on hoped-for company use. It suggests investors value paid, repeated use that needs a lot of computing over model skill alone.
Worth flagging for what comes next is the IPO path. A pre-IPO round after the supposed last private raise raises disclosure and price questions. Public buyers will look to bridge terms, starting value, and August sales as guides. The long-term promise is simple. If coding sales keep growing near this pace, computing costs have paying customers.
