I should also add: Suppose PyPy was twice as fast as CPython for a given workload, but it also used twice as much memory.

I doubt Google or Dropbox would use it in that case. On large clusters, memory usage probably contributes to the need to buy machines more than CPU usage (CPU utilization can be low; memory utilization is higher).

I've personally rewritten some Python code as a C++ extension module and gotten 5x decrease in memory usage across thousands of machines.

(As far as I understand, this is the typical tradeoff for PyPy: it's faster but uses more memory. I'm happy to hear more detail on this though.)