We compare the performance of different acoustic modeling techniques on the task of distributed speech recognition (DSR). The DSR technology is interesting for speech recognition tasks in mobile environments, where features are sent from a thin client to a server where the actual recognition is performed. The evaluation is done on the TI digits database which consists of single digits and digit-chains spoken by American-English talkers. We investigate clean speech and speech added with white noise. Our results show that new hybrid or discrete modeling techniques can outperform standard continuous systems on this task.