It would be one of the largest IPOs in tech history — from a company that, by its own numbers, loses more than a dollar for every dollar it bills. Investors are betting that ratio flips before the market runs out of patience.
OpenAI filed a confidential S-1 with the SEC on June 8-9, 2026, marking the formal start of its IPO process. The company is targeting a public market debut in September 2026, with a target valuation range between $730 billion and $850 billion — with room to reach up to $1 trillion depending on market conditions. The public prospectus is expected to appear on the SEC's EDGAR system in mid-to-late August 2026, roughly 15 days before any roadshow. Goldman Sachs and Morgan Stanley were hired to manage the offering.
OpenAI generates roughly $25 billion annualized as of February 2026, with Q1 2026 alone at $5.7 billion — a pace projecting around $30 billion for the full year. However, the company loses approximately $1.22 for every dollar it earns, according to reported quarterly figures. The company was valued at $852 billion in a funding round closed earlier in 2026.
An IPO of this magnitude would be one of the largest in tech history, and its performance in the public market will become the most visible thermometer of whether investors believe the massive spending on AI infrastructure — covered in our article on Nvidia's $250 billion backstop for OpenAI's Ohio data center — eventually translates into real profitability, or whether the market remains willing to finance losses at this scale indefinitely.
A successful IPO at this valuation would cement OpenAI as one of the world's most valuable companies despite its current operating losses, reinforcing the narrative that the AI race is explicitly being financed as a long-term bet. For companies that depend on the OpenAI API in production, a publicly traded OpenAI also means more mandatory financial transparency than existed as a private company — information that until now was practically impossible to obtain reliably.
Carlos Montiel is an enterprise AI solutions architect. He implements LLMs, Agents, RAG, and orchestrators for companies across Guatemala and Latin America. Reach out for a consultation.
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