The human reference proteome is routinely modelled with predictive tools such as AlphaFold2. We recently released a database in which, for each human protein, the AlphaFold2 model is paired with its ESMFold counterpart. The two predictive methods take advantage of different procedures and it is interesting to compare them in relation to their quality, particularly when an experimental protein structure is not available. Here, we select three state-of-the-art quality assessment methods and we adopt them to compare 42,942 pairs of models. This procedure helps to find the most reliable models for human proteins, particularly for the set of proteins for which structure prediction methods give dissimilar results. We obtain that when predicted structures are similar, AlphaFold2 models consistently receive higher scores than the ESMFold counterparts. When predicted structures differ, the ESMFold model is the best choice for 49 % of the proteins according to a consensus of the three QA tools.