Open Formula for IMO Gold: Training Nemotron on Olympiad Math
fine-tuning inference reinforcement-learning training
| Source: HF Papers | Original article
A team of researchers has released a detailed recipe for turning NVIDIA’s Nemotron 3 Ultra into a specialist for International Mathematical Olympiad (IMO)‑level problems. Building on the base model, the authors created two checkpoints – one via supervised fine‑tuning and another using reinforcement learning – and then compared how checkpoint selection, verification and post‑generation refinement affect the quality of natural‑language proofs. The study culminates in an open‑model, test‑time compute pipeline that can be run on publicly available hardware.
The work matters because it shows that high‑performance mathematical reasoning can be achieved without resorting to closed, proprietary systems. By publishing the training data, the fine‑tuned checkpoints and the full evaluation methodology, the authors provide a reproducible baseline for the community. This contrasts sharply with recent controversy surrounding commercial AI attempts to solve elite math problems, which have drawn criticism from leading mathematicians. As we reported on 12 September 2026, a group of Fields Medalists warned that treating AI success on math benchmarks as a proxy for scientific progress can be detrimental to the discipline. An open‑source alternative may alleviate some concerns by allowing independent scrutiny of data, methods and verification steps.
What to watch next is whether the open pipeline gains traction among researchers and educators, and how it performs on future IMO‑style benchmarks. Attention will also focus on the robustness of the verification stage – a key safeguard against spurious proofs – and on any response from the mathematical community, which may see the approach as a tool for teaching or as a new frontier for AI‑assisted discovery. Further releases of specialist checkpoints for other domains could follow, extending the open‑model playbook beyond Olympiad mathematics.
Sources
Back to AIPULSEN