Osteosarcoma is a type of bone cancer commonly found in the elongated bones found in the upper and lower limbs. The precise cause is unknown, but experts believe it’s linked to changes in the DNA of the bones, resulting in the growth of abnormal and harmful bone tissue. If caught early, osteosarcoma is treatable, with about 75% people cured when the cancer hasn’t spread to other body parts. Analyzing biopsy samples can be time-consuming, but there are advanced computer programs, known as supervised deep learning methods, that can help speed up the process and enhance the efficiency of the diagnosis. Previous studies have already evaluated the performance of deep learning models such as VGG16, VGG19, DenseNet201, and ResNet101, among which ResNet101 performed better with 90.36% accuracy. When it comes to understanding complex image features, previous models lack behind. We propose EfficientNetV2, Xception, and InceptionV3 models, among which Xception outperformed other models with 94.5% accuracy on the image dataset.