**[OpenAI Internal Model Solves Millennium Math Problem in 88 Hours]** Reported by Jinse Finance, on Tuesday, September 9 (local time), OpenAI announced a solution to one of the Millennium Prize Problems—the Navier-Stokes equation-related issue. This equation is used to describe the motion of fluids such as air, water, and blood. OpenAI also revealed for the first time that the breakthrough was achieved using a next-generation internal model significantly more capable than GPT-6 Astra. Charts indicate that on a curated set of open mathematical problems, this internal model achieved a pass rate of nearly 48%, approximately three times the highest performance of Astra. OpenAI stated that this mathematical breakthrough incurred computational costs amounting to millions of dollars. The research team deployed approximately 10,000 collaborative AI agents, arriving at the solution within about 88 hours of the initial activation of the first batch of agents. OpenAI's research shows that three-dimensional fluid motion may produce singularities within finite time, leading to a breakdown in the equation's ability to describe fluids as a continuous medium. Previously, New York University mathematician Tristan Buckmaster and Anthropic researcher Levent Alpöge had just published an AI-assisted study on related fluid dynamics equations. Buckmaster subsequently issued a statement questioning whether OpenAI began addressing the problem only after learning of their research and adopted their rare research methodology, which took months to develop. OpenAI responded by stating that its team had not accessed or interacted with their work in any way prior to the public release of their research, nor had it accessed any specific user data. OpenAI also emphasized that the proof methods employed by the two parties were significantly different.