As fast as CPython (for carefully taken benchmarks)

Good news everyone. A tuned PyPy compiled to C is nowadays as fast as CPython on the richards benchmark and slightly faster on the gcbench benchmark.
IMPORTANT: These are very carefully taken benchmarks where we expect pypy to be fast! PyPy is still quite slower than CPython on other benchmarks and on real-world applications (but we're working on it). The point of this post is just that for the first time (not counting JIT experiments) we are faster than CPython on *one* example :-)
The exact times as measured on my notebook (which is a Core Duo machine) are here:
Compiled pypy with options:
./translate.py --gcrootfinder=asmgcc --gc=generation targetpypystandalone.py --allworkingmodules --withmod-_rawffi --faassen (allworkingmodules and withmod-_rawffi are very likely irrelevant to those benchmarks)
CPython version 2.5.1, release.

• richards 800ms pypy-c vs 809ms cpython (1% difference)
• gcbench 53700ms pypy-c vs 60215ms cpython (11% difference)

PyPy shines on gcbench, which is mostly just about allocating and freeing many objects. Our gc is simply better than refcounting, even though we've got shortcomings in other places.
About richards, there is a catch. We use a method cache optimization, and have an optimization which helps to avoid creating bound methods each time a method is called. This speeds up the benchmark for about 20%. Although method cache was even implemented for CPython, it didn't make its way to the core because some C modules directly modify the dictionary of new-style classes. In PyPy, the greater level of abstraction means that this operation is just illegal.