Objective To explore the application areas of rapid detection technology for core quality indicators in cheese and its products using near-infrared spectroscopy (NIRS), and validating the feasibility of NIRS for rapid testing of cheese quality parameters. Methods Four types of common processed cheese products (cheese sticks, cheese slices, cream cheese, Mozzarella) were selected for experimentation and divided into modeling and validation sets; modeling experiments were conducted using samples from the modeling set on a single-brand instrument; synchronous national standard detection and multi-instrument NIRS detection comparative analysis were performed using instruments from 4 different manufacturers on the validation sets. Results For modeling, multidimensional prediction models for core indicators (protein, fat, moisture, pH) were successfully constructed by comparing the modeling mechanisms of algorithms like partial least squares regression (PLSR), with the coefficient of determination exceeding 0.85. For validation, the average deviations between the NIRS detection results (protein, fat, moisture) obtained using 4 kinds of NIRS spectrometers on different cheese products and those determined by national standard methods met equivalence requirements except for the protein deviation (>10%) of Mozzarella on instrument No.1; precision also met the requirements of national standard methods. Conclusion The application of NIRS spectroscopy equipment for rapid detection of core quality indicators in cheese and its products is feasible; NIRS spectroscopy technology can serve as an effective supplement to traditional chemical detection methods for rapid analysis of cheese composition, offering greater potential for high-efficiency, low-cost, and environmentally friendly testing.