Recent OpenAI announcements, including a September claim resolving a Navier-Stokes variant and an early October release of 722 papers detailing solutions or substantial progress on over 370 open problems, have driven trader sentiment in the "Which math problems will AI solve in 2026?" market. Frontier large language models combined with formal verification tools like Lean have enabled autonomous proof search, as seen in AlphaProof Nexus results on multiple Erdős problems and a Chinese Intern-S2 proof of the Ghys conjecture. Leading outcomes such as the Hodge Conjecture and Ramsey number R(5,5) reflect implied probabilities around 18-20%, amid competitive positioning among OpenAI, DeepMind, Meta, and others. Key catalysts ahead include further model releases, Clay Institute reviews of Millennium Prize claims, and human verification of Lean-formalized results before year-end.