InternVL2-8B-MPO is a multimodal large language model (MLLM) that enhances multimodal inference capabilities by introducing a Mixed Preference Optimization (MPO) process. The model features an automated pipeline for preference data construction and builds the MMPR, a large-scale multimodal inference preference dataset. Based on the InternVL2-8B model, InternVL2-8B-MPO is fine-tuned using the MMPR dataset, demonstrating stronger multimodal inference capabilities with fewer hallucinations. The model achieved an accuracy of 67.0% on MathVista, surpassing the InternVL2-8B by 8.7 points, and performing closely to the much larger InternVL2-76B model.