Abstract Semantic automata were developed to compare the complexity of generalized quantifiers based on the complexity of the string languages that describe their truth conditions. An important point that has gone unnoticed so far is that the generated string languages are remarkably simple for monomorphemic quantifiers. Whereas complex quantifiers such as mph{an even number of} correspond to specific regular languages, monomorphemic mph{every}, mph{no}, mph{some} as well as numerals do not reach this level of complexity. Instead, they all stay close to the bottom of the so-called subregular hierarchy. This poster defines relevant quantifier languages in subregular terms and sketches an experimental design for testing the cognitive predictions of the subregular perspective for quantifier complexity.