OpenAI sent millions of messages to solve a $1 million math problem. They say they won't ask for the prize. Sean Rayford/Getty Images On Tuesday, OpenAI said it had solved the Navier-Stokes equations, a 90-year-old math problem. OpenAI said its agents used 130 billion output tokens and sent 2.7 million messages in the process. The company won't accept the cash prize, it says. "AI is such a bubble," its CEO joked. Math is hard. And, apparently, expensive. On Tuesday, OpenAI said its agents had solved the Navier-Stokes equations, a 90-year-old set of mathematical formulas that can predict how liquids and gases move. It's so complicated that the Clay Mathematics Institute has offered a $1 million prize to any mathematician who finds the solution. OpenAI said that finding the solution required a lot of resources. Its coordinating AI agents sent 2.7 million messages while working on the proof. The effort involved about 10,000 concurrent agents and reached a resolution after 88 hours. Verification took another 17 hours. Such intensive use of AI doesn't come cheap. In a post on X, LisanBench, an LLM benchmark evaluator, estimated that the output tokens alone would cost about $6.5 million at OpenAI's average consumer price. Including the far larger volume of input tokens, the post estimated the total could reach $10 million to $40 million. OpenAI CEO Sam Altman replied, joking that AI was a bubble. ugh AI is such a bubble, i heard they are selling tokens at a loss, did they know this was only worth $1 million? — Sam Altman (@sama) September 8, 2026 OpenAI's announcement that it solved the age-old mathematics problem was celebrated within the AI industry. It's also been widely criticized after two mathematicians — Tristan Buckmaster and Levent Alpöge — raised questions about how OpenAI used their related research data to train its models. OpenAI denied direct access to their work, but said that it "cannot rule out that de-identified data derived from their usage of our products helped improve our models." The company didn't immediately respond to a request for comment from Business Insider. Read the original article on Business Insider
OpenAI sent millions of messages to solve a $1 million math problem. They say they won't ask for the prize.Sean Rayford/Getty Images On Tuesday, OpenAI said it had solved the Navier-Stokes equations, a 90-year-old math problem. OpenAI said its agents used 130 billion output tokens and sent 2.7 million messages in the process. The company won't accept the cash prize, it says. "AI is such a bubble," its CEO joked. Math is hard. And, apparently, expensive. On Tuesday, OpenAI said its agents had solved the Navier-Stokes equations, a 90-year-old set of mathematical formulas that can predict how liquids and gases move. It's so complicated that the Clay Mathematics Institute has offered a $1 million prize to any mathematician who finds the solution. OpenAI said that finding the solution required a lot of resources. Its coordinating AI agents sent 2.7 million messages while working on the proof. The effort involved about 10,000 concurrent agents and reached a resolution after 88 hours. Verification took another 17 hours. Such intensive use of AI doesn't come cheap. In a post on X, LisanBench, an LLM benchmark evaluator, estimated that the output tokens alone would cost about $6.5 million at OpenAI's average consumer price. Including the far larger volume of input tokens, the post estimated the total could reach $10 million to $40 million. OpenAI CEO Sam Altman replied, joking that AI was a bubble. ugh AI is such a bubble, i heard they are selling tokens at a loss, did they know this was only worth $1 million? — Sam Altman (@sama) September 8, 2026 OpenAI's announcement that it solved the age-old mathematics problem was celebrated within the AI industry. It's also been widely criticized after two mathematicians — Tristan Buckmaster and Levent Alpöge — raised questions about how OpenAI used their related research data to train its models. OpenAI denied direct access to their work, but said that it "cannot rule out that de-identified data derived from their usage of our products helped improve our models." The company didn't immediately respond to a request for comment from Business Insider. Read the original article on Business Insider
