Cyathostomins are the most prevalent parasitic pathogens of equids worldwide. These nematodes have been controlled using broad-spectrum anthelmintics; however, cyathostomin resistance to each anthelmintic class has been reported and populations insensitive to more than one class are relatively commonplace. The faecal egg count reduction test (FECRT) is considered the most suitable method for screening anthelmintic sensitivity in horses, but is subject to variation and is relatively time-consuming to perform. Here, we describe a larval migration inhibition test (LMIT) to assess ivermectin (IVM) sensitivity in cyathostomin populations. This test measures the paralysing effect of IVM on the ability of third stage larvae (L3) to migrate through a pore mesh. When L3 from a single faecal sample were examined on multiple occasions, variation in migration was observed: this was associated with the length of time that the L3 had been stored before testing but the association was not significant. Half maximal effective concentration (EC50) values were then obtained for cyathostomin L3 from six populations of horses or donkeys that showed varying sensitivity to IVM in previous FECRTs. Larvae from populations indicated as IVM resistant by FECRT displayed significantly higher EC50 values in the LMIT than L3 from populations classified as IVM sensitive or L3 from populations that had not been previously exposed to IVM or had limited prior exposure. The analysis also showed that EC50 values obtained using L3 from animals in which IVM faecal egg count reduction (FECR) levels had been recorded as <95% were significantly higher than EC50 values obtained using L3 from animals for which FECR was measured as >95%. For one of the populations, time that had elapsed since IVM administration had an effect on the EC50 value obtained, with a longer time since treatment associated with lower EC50 values. These results indicate that the LMIT has value in discriminating IVM sensitivity amongst cyathostomin populations, but several factors were identified that need to be taken into account when executing the test and interpreting the derived data.