This varies tremdously with the geometry of the problem. What you shoudl be seeing is that if you run it for twice as many iterations, you get twice as large an n_eff. It may be mixing slowly, but that will show you if it’s mixing.
In the works for Stan 3. Mitzi coded up the basic I/O, but we’re waiting on refactoring some of the interface code so we don’t have to code this all up twice.
This is only going to matter if (a) you have really long autocorrelation times in an otherwise well-behaved model, and (b) you don’t have enough memory. You always lose information by thinning.