InternVL2_5-26B-MPO-AWQ is a multimodal large language model developed by OpenGVLab, designed to enhance model reasoning capabilities through hybrid preference optimization. This model excels in multimodal tasks, effectively managing the complex relationships between images and text. It utilizes cutting-edge model architecture and optimization techniques, providing significant advantages in handling multimodal data. The model is ideal for scenarios requiring efficient processing and understanding of multimodal data, such as image description generation and multimodal question answering. Its main advantages include powerful reasoning capabilities and an efficient model architecture.