Aiming at the problems of the existing agricultural equipment digital twin system development difficulty, high configuration requirements and poor portability, a lightweight network-based digital twin system construction method for combine harvester was proposed, which contained the realization of multiple subsystems such as physical, virtual, data interaction, model computation and human-computer interaction. Based on the technical characteristics of digital twin and the operational characteristics of combine harvester, a lightweight digital twin system framework was designed based on JavaScript language. By adopting Solidworks and CMdevelopment kit tools for the model lightweight processing and coordinate system integration of the digital twin system, it achieved a significant reduction of the system’s hardware requirements and memory occupation without affecting the model’s accuracy and functionality. The lightweight network-based combine harvester digital twin system was developed by using a Lovol GM100 combine harvester as an object to provide a joint simulation, analysis, and validation platform for performance analysis, real-time monitoring, instantaneous computation, and remote manipulation of the combine harvester digital twin system. To verify the performance and functionality of the digital twin system, twin system performance tests and fuel consumption prediction experiments were conducted. Tests showed that the response speed was within 78ms at a data update frequency of 20Hz, and the memory occupation was within 331MB in the performance test, and the average occupancy of the system’s CPU and GPU in the running state was 17% and 30%, respectively; and the system’s frame rate can be maintained at 75.6f/s even under high-intensity operation. Under normal operation, the average error of the fuel consumption prediction model was 0.34L/h, with an average relative error of only 2.51%. This system can provide a low-cost, high-efficiency digital twin lightweight construction scheme, which provided a useful reference for the further promotion and application of digital twins in the field of agricultural equipment.