We outline two different techniques for OCR of machine printed, multi-font Devanagari text. In the first design, words are segmented along linear boundaries. Subsequently, classification is performed with the assumption of accurate segmentation. The second approach uses classifiers to obtain preliminary hypothesis for each segment of the word. These results are used to guide further segmentation of certain pieces, While the former technique is segmentation driven, the latter method follows the paradigm of recognition driven segmentation. The two approaches are compared by using a standard data set.