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This algorithm, then, requires O(''n'') additions plus O(''n'' log ''n'') time for the convolution. In practice, the O(''n'') additions can often be performed by absorbing the additions into the convolution: if the convolution is performed by a pair of FFTs, then the sum of ''x''<sub>''k''</sub> is given by the DC (0th) output of the FFT of ''a''<sub>''q''</sub>, and ''x''<sub>0</sub> can be added to all the outputs by adding it to the DC term of the convolution prior to the inverse FFT. Still, this algorithm requires intrinsically more operations than FFTs of nearby composite sizes, and typically takes 3-10 times as long in practice.
If Rader's algorithm is performed by using FFTs of size ''n''-1 to compute the convolution, rather than by zero padding as mentioned above, the efficiency depends strongly upon ''n'' and the number of times that Rader's algorithm must be applied recursively. The worst case would be if ''n''-1 were 2''n''<sub>2</sub> where ''n''<sub>2</sub> is prime, with ''n''<sub>2</sub>-1 = 2''n''<sub>3</sub> where ''n''<sub>3</sub> is prime, and so on. In such cases, supposing that the chain of primes extended all the way down to some bounded value, the application of Rader's algorithm would actually require O(''n''<sup>2</sup>) time. Such ''n''<sub>j</sub> are called [[Sophie Germain prime|Sophie Germain primes]], and
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