Visual-inertial fusion is frequently used for state estimation in aerial robotic applications due to the low-cost, simple hardware setup as well as the high accuracy. This work proposes a stereo visual-inertial fusion system based on the monocular method VINS-Mono, which tightly combines the visual and inertial measurements. Timing statistics are provided for the system running on an Intel NUC Mini-PC. The system real-time capability fulfills the requirements of the closed-loop control for a UAV. The proposed fusion system is evaluated in the public EuRoC MAV dataset and compared with several representative state-of-the-art open-sourced state estimators. According to the results, our method achieves competitive performance with relative low estimation errors in a computationally efficient manner.