Various existing computer models of evolution attempt to demonstrate the efficacy of Darwinian evolution by solving simple problems. These typically use per-nucleotide (or nearest analogue) mutation rates orders of magnitude higher than biological rates. This paper compares models using typical rates for genetic algorithms with the same models using a realistic mutation rate. It finds that the models with the realistic mutation rates lose the ability to solve the simple problems. This is shown to be the result of the difficulty of evolving mutations that only provide a benefit in combination with other mutations.