VIT (Vision Transformer) is a deep learning model architecture that applies transformer models, originally designed for natural language processing, to image recognition tasks. It has shown state-of-the-art performance in computer vision tasks by treating image patches as sequences, allowing the model to capture long-range dependencies across an image.