node2vec random walks are tuneable random walks that come from the popular computer science algorithm node2vec which is used for feature learning on networks. The transition probabilities of the random walks depend on the previous visited node and on the triangles that contain the current and the previous node. Even though the algorithm is very popular in the field of computer science, mathematical properties of the random walks almost have not been explored. We will present results on the stationary distribution of these random walks on household models and compare it with the simple random walk.