13, but not really. You need to provide room for things to go wrong and memory fragmentation. Assuming you’re comfortable with a 70% HWM you’d need 13/0.7=~ 19G for each node.
Based on the data model, first size the “cluster” which has n nodes, allow for overheads - such as high water mark etc. Then based on the instances you want to use, decide n. n = (Cluster sizing value / Instance capacity value) plus 1 - to allow for rolling upgrades. Plan for 1 node down at a minimum.