We developed a high-throughput targeted quantification strategy for intact glycopeptides (HTiGQs-Target) to diagnose and differentiate the malignancy of liver diseases. The method involves two-step labeling. This step derivatization makes the same parent ions in different samples produce sufficient mass differences in primary mass spectrometry detection, and finally expands the sample detection throughput to 20 (2*10) samples per run. We used this method to analyze serum samples from patients with different types and stages of liver diseases, and found some glycopeptide features with diagnostic and differential significance. This project provides a new and efficient proteomics method for early diagnosis and treatment of liver diseases.