In response to the narrow hot working temperature range of GH4169 superalloy and the high risk of significant grain size disparity and mixed crystals in different sections during the preparation of large forged bars, which adversely affect its mechanical properties and service life, a large GH4169 superalloy bar with a diameter of 260 mm was used as the research object. The samples at the center, 1/2 radius and edge were subjected to low-cycle fatigue tests by an INSTRON fatigue testing machine at 650 ℃. OM, SEM, TEM and other tissue characterizations were combined to explore the influence of grain size on the high-temperature and low-cycle fatigue properties of GH4169 superalloy and its deformation damage mechanism. The results indicate that the grain size gradually decreases from the center to the edge of the sampling position. There are mixed crystals in the microstructure at 1/2 radius, and the grain size difference between the center and the edge is 4.5. Under the control of the total strain amplitude, the fatigue life of the sample at 1/2 radius is the lowest, while the fatigue life of the sample at the edge with a uniform distribution of fine grains is the highest. When the total strain amplitude is less than 0.6%, the alloy is cyclically stable, and when the total strain amplitude is greater than or equal to 0.6%, the cyclic softening stage predominates. With the increase in grain size, the cyclic strength coefficient and the cyclic plasticity coefficient initially decrease and then increase, but the cyclic strength index and the plasticity index show the opposite trend. The Coffin-Manson relationship between the plastic strain amplitude and the fatigue life of the alloy is monotonically linear. The fatigue crack sources of the alloy are located on the surface, and there are numerous secondary cracks in the crack propagation zone, and the fatigue deformation mode is deformation twins. This research results reveal the correlation between grain size and fatigue life, providing theoretical reference for microstructure optimization and fatigue life prediction of superalloys.