This Master’s Thesis focuses on the study and comparative analysis of two different implementations of quantum reservoir computing in quantum computers using Qiskit software development kit. The implementations are based on the proposals of two distinct papers in which Noisy Intermediate-scale Quantum (NISQ) computers are considered as platforms for different temporal tasks. We evaluate the performance of each of the reservoirs in learning two benchmark tasks: the Nonlinear AutoRegressive Moving Average of order 2 (NARMA2) and a Linear Memory task. A comparison of their performance and the computational effi- ciency of the simulations is made and the parameters that influence the performance of each reservoir are studied.