Toxic comment classification has become an active research field with many recently proposed approaches. However,while these approaches address some of the task’s challenges others still remain unsolved and directions for further research are needed. To this end, we compare different deep learning and shallow approaches on a new, large comment dataset and propose an ensemble that outperforms all individual models.Further, we validate our findings on a second dataset