The present study investigated whether dividing information between the hemispheres becomes more advantageous to task performance as computational complexity increases. We hypothesized that interhemispheric processing would benefit performance especially for computationally complex tasks, whereas it would hinder performance for relatively simple ones. A letter-matching task was given to 23 subjects at three levels of computational complexity. Complexity was varied either by increasing the number of inputs to be processed or by the nature of the decision to be made. The results indicated that each of these manipulations of complexity influenced performance by making it more advantageous to have both hemispheres involved in processing rather than just one. Furthermore, the effects of each manipulation were separable.