In this paper, we describe the training procedure leading to our own strong mixed models and compare the evaluation results to those achieved by other main OCR engines and their respective models on a variety of Fraktur scripts. In particular, we report results from OCRopus, Tesseract, and ABBYY Finereader each with their own standard Fraktur model as well as OCRopus and Calamari with a mixed model trained on a Fraktur corpus of the 19<hi xmlns="http://www.tei-c.org/ns/1.0" rend="superscript">th</hi> century.