Another interesting point is the memory requirements of the two approaches. Exact computations using SR have a O(n + α × k2m) memory complexity where n is the sequence length, k the alphabet size, m the Markov model order and α which depends on the convergence rate of the model towards its stationary distribution. As a consequence, SR is difficult to use in practice with m > 3 for DNA words or m > 1 for protein ones. For FMCI computations, the memory requirements remain very cheap and in practice, any Markov model that fit in memory can be considered.