Powder bed fusion (PBF) process is capable of producing a complex geometrical part with less material and energy consumption compared with conventional manufacturing methods. The performance of PBF processed part is mainly controlled by many process parameters such as scanning speed, scanning pattern, scanning strategy, and layer thickness. Usually, these parameters are optimized through detailed experiments which are time-consuming and costly. Therefore, numerical methods have been widely adopted to investigate the effects of these process parameters on temperature fields and thermal stress fields. As the laser/electron beam introduces huge temperature gradients within the irradiated region, which will result in the distortion even delamination of solidified layers, the study of the history of temperature distribution is the basic and crucial step in the modeling of PBF process. Most of the current research utilizes moving Gaussian point heat source as heat input to model the temperature distribution of a part. However, due to the small diameter of laser/electron beam, a small enough time step size is required to accurately model the real heat input, which will lead to significant computational burden. In this research, a hybrid of moving Gaussian point and line heat source model is developed, which makes the modeling of PBF process efficient without losing too much accuracy. In addition, an adaptive mesh scheme, which is capable of dynamically refining the mesh near the beam spot and coarsening the mesh far away from the beam spot, is adopted to accelerate the simulation process. Specifically, moving Gaussian point heat source is applied to the region of interest where accuracy is more concerned such as the temperature field within overhang feature. While the line heat source is applied to the region of interest where efficiency is more concerned such as temperature field within the inner region of a square. The simulation result shows that the temperature fields by using hybrid source model are comparable to the temperature fields by using the moving Gaussian point heat source model, and much less central processing unit time is required when the hybrid heat source is applied.