In this paper, we are mainly interested in estimating multicomponent stress- strength reliability. The system is regarded as alive only if at least s out of k (s such a system is obtained when strength, stress variates are given by generalized inverted exponential distribution with different shape parameters and common scale parameter. The research methodology adopted here is to estimate the parameters by using maximum likelihood estimation. The reliability is estimated using the maximum likelihood method of estimation when samples are drawn from strength and stress distributions. The reliability estimators are compared asymptotically. The results of small sample comparison of the reliability estimates are made through Monte-Carlo simulation. The simulation results indicates that the average bias and average MSE are decreases as sample size increases for both methods of estimation in reliability. The length of the confidence interval is also decreases as the sample size increases and coverage probability is close to the nominal value in all sets of parameters considered here. By using real data sets we well illustrate the procedure.