For scientific code I've seen slowdowns, but in the end they turn out to be unrelated to Python 3 - e.g. numpy compiled against different BLAS libraries in Python 2.x and 3.x.

There also was a gotcha with replacing cStringIO with io.BytesIO: the latter copied the data even for read-only cases (when you want to have a file-like interface for a binary object), so it can be much slower.

To make things worse, Python 3.x didn't have cStringIO alternative which can be used to provide file-like interface without overhead, and most porting guides suggest using io.BytesIO instead of cStringIO in Python 3. So libraries like tornado, django and flask are affected, and likely some scientific libraries as well.

This problem should be fixed in Python 3.5: io.BytesIO becomes as efficient as cStringIO for read-only cases since Python 3.5.