tSNE (or t-Distributed Stochastic Neighbour Embedding) is a stochastic technique (i.e based on randomness). We would no expect to get exactly the same result multiple times, unless we fix the random seed. Actaully, what you'll notice here is that mostly the bottom plot is pretty close to just being a rotation of the top one.
For a myriad of reasons, you shouldn't use tSNE for clustering. You derive your clusters by some other method, and then visualise the clusters using tSNE. Because most clustering algos are more stable than tSNE on repeated runs, you would expect the memberships of the clusters to be the same.