I'm using it in production, and speedups tend to be on the order of 4-5x for my app (the compute-intensive part involves hierarchical agglomerative clustering of documents by text similarity, so it's data/numbers-heavy). Obviously it'll depend on your individual application (and non-CPU-bound tasks won't benefit much), but we switched to PyPy because it showed major improvements in profiling of our app on production data (and we switched around PyPy's 1.9 release, so it's even better now). It's not like everyone's just imagining the speed improvements...

Help us make your code faster, report it please :)

You do remember that it's a jit and the first run is not fast? You have to let it run for a while to generate fast code and only benchmark after that.

You might try again since things have changed. If you don't get any kind of speedup, the PyPy project would likely consider it a bug and it would be helpful to document that it was slower. Please consider finding some way of reporting the specific measurable issues you find!