, 2020) has claimed there is no strong evidence that multi-letter graphemes are used in reading tasks with proficient adult readers, with most studies being statistically weak or having confounds in the stimuli used. Here, I used Monte Carlo simulation with data from reading mega-studies to examine the extent to which the number of multi-letter graphemes matters in words when letter length is held constant. This was done by simulating thousands of experiments using different sets of items for each of a small number of comparisons (e.g., words with only single-letter graphemes versus words with one multi-letter grapheme). The results showed that words with two multi-letter graphemes tended to cause slower reaction times than words with one or no multi-letter graphemes, with effects found in both naming and lexical decision tasks. Interestingly, when words with no multi-letter graphemes were compared with words with one multi-letter grapheme, the differences were much weaker. Simulations of naming results using two computer models, the connectionist dual-process (CDP) model and the dual-route cascaded (DRC) model, showed only CDP predicted this pattern. Since CDP learns simple associations between graphemes and phonemes whereas DRC uses a set of grapheme-phoneme rules, this suggests that the results may have been caused by simple associations between spelling and sound being relatively easy to learn with words with one compared with two multi-letter graphemes. More generally, the results suggest that graphemes are used when reading, but they often produce relatively weak effects and thus differences in some studies may not have been found due to a lack of power.