The UltraMedical project aims to develop specialized general-purpose models for the biomedical field. These models are designed to answer questions related to exams, clinical scenarios, and research questions while maintaining a broad base of general knowledge to effectively handle cross-domain issues. By utilizing advanced alignment techniques, including supervised fine-tuning (SFT), direct preference optimization (DPO), and odds ratio preference optimization (ORPO), training large language models on the UltraMedical dataset creates powerful and versatile models that effectively serve the needs of the biomedical community.