Researchers have unveiled VibeThinker-3B, a three-billion parameter small language model that outperforms Opus 4.5 in complex reasoning tasks. The model achieves this frontier-level performance through a novel training approach combining supervised fine-tuning with group relative policy optimization. This breakthrough highlights the growing capability of compact models to execute verifiable reasoning without relying on massive parameter counts.