QED-Nano: Teaching a Tiny Model to Prove Hard Theorems

Researchers developed QED-Nano, a 4B parameter AI model that achieves competitive performance on Olympiad-level mathematical proofs despite being much smaller than proprietary systems. The model uses a three-stage training approach including supervised fine-tuning, reinforcement learning, and reasoning cache expansion to match larger models at a fraction of the inference cost.