Cancer cell invasion is a critical cause of fatality in cancer patients. Physiologically relevant tumor models play a key role in revealing the mechanisms underlying the invasive behavior of cancer cells. However, most existing models only consider interactions between cells and extracellular matrix (ECM) components while neglecting the role of matrix stiffness in tumor invasion. Here, we propose an effective approach that can construct stiffness-tunable substrates using digital mirror device (DMD)-based optical projection lithography to explore the invasion behavior of cancer cells. The printability, mechanical properties, and cell viability of three-dimensional (3D) models can be tuned by the concentration of prepolymer and the exposure time. The invasion trajectories of gastric cancer cells in tumor models of different stiffness were automatically detected and tracked in real-time using a deep learning algorithm. The results show that tumor models of different mechanical stiffness can yield distinct regulatory effects. Moreover, owing to the biophysical characteristics of the 3D in vitro model, different cellular substructures of cancer cells were induced. The proposed tunable substrate construction method can be used to build various microstructures to achieve simulation of cancer invasion and antitumor screening, which has great potential in promoting personalized therapy.