Support Vector Machine (SVM) is a classical statistical learning algorithm operating on Euclidean features. Less is known when moving to statistical learning on non-Euclidean spaces, such as hyperbolic spaces. We propose and solve a large-margin solution on hyperbolics using gradient descent.