Lots of Face recognition technology has seen significant advancements in these years. It offers many applications such as in security systems, surveillance, and biometric authentication. With all these deep learning techniques spreading around, the performance of face recognition algorithms has got better. But the computational demands still back from getting all the way there. Processing large datasets or real-time video streams can be a real challenge sometimes. Anyhow, this project brings right off a new way to face recognition by using GPU support besides Python libraries like OpenCV and face_recognition. By stepping into the world of parallel processing power provided by GPUs, our system just speeds up the process of face recognition by miles compared to the old-fashioned CPU-based setups. The real deal is that GPU support can do parallel computation of some complex neural network operations, speeding up the inference times vastly. This is a huge plus for the applications that crave real-time or like-real-time performance, like surveillance systems and video analytics.