[citation needed] You're mostly talking nonsense. PyPy is usually 20-100x faster on the numeric workloads I measured than CPython, while the difference is significantly smaller on non-numeric workloads. The difference between C++ and CPython is also smaller.
Well, faster or equal, eventually in everything. Anything that pypy does slower than cpython is considered a bug as far as a I know. But I was not making a definitive academic statement or anything, just saying that it is, in general, faster. After all, it is faster in mother of all benchmarks, the fib function :) (edit: on my computer)
As for the PS; RPython is statically typed Python (perhaps some other extra restrictions apply). Not type-annotated or anything, just pure python written in a certain way. So it is a subset. As for what "Python" should have been "RPython", it was the first one. The pypy interpreter is written in RPython. But my statement was still correct because RPython is Python.
I'm not sure why you think pypy is slower than cpython "at pretty much everything" after looking at this site. Out of the 21 benchmarks given, 10 are 2x or more faster than cpython, 10 are between 2x faster and 2x slower and only 1 is more than 2x slower.
PyPy definitely shows that python could be 5x faster than it is, however this would still be ~10x slower than Julia/C/C++ (and R is roughly 5-10x slower than python now)
Actually, my experience with PyPy, while generally positive, has exhibited many of the characteristics that article talks about in terms of downsides to "sufficiently-smart compilers." It's almost always much faster than cpython, but how much faster is highly variable, and not especially predictably so; seemingly-insignificant changes can have large and unexpected performance implications, and it's difficult as a developer to have the proper mental model to figure out what's actually going on.
In CPython land, Python is slower, but performs predictably, and if you want to speed it up you write C, which is much faster, and also performs predictably, though it takes some developer effort. In PyPy, you get some of the speed of C without the effort, but without the predictability either.
Currently, PyPy is faster than CPython at pretty much anything (except when C is involved, for example, but they are working on that, too). You can see their benchmarks and comparisons at http://speed.pypy.org/.
What I think they mean by those statements is that this will improve performance over the previous version of PyPy - therefore - improve over CPython as well.
I think in general, programs written in "Python" will perform better in PyPy then CPython, but the current submissions are hyper-optimised for the implementation details of CPython.
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