Here is the statistics for all pyc-files (not only in Lib/__pycache__). This includes encoding tables and tests. I count also memory usage for some types (for tuples shared size is estimated upper limit).
type count % size shared %
UNICODE 622812 58% 26105085 14885090 57%
TUPLE 224214 21% 8184848 3498300 43%
STRING 90992 8.4% 6931342 832224 12%
INT 52087 4.8% 715400 58666 8.2%
CODE 42147 3.9% 2865996 0 0%
NONE 39777 3.7%
BINARY_FLOAT 3120 0.29%
TRUE 2363 0.22%
FALSE 1976 0.18%
LONG 1012 0.094%
ELLIPSIS 528 0.049%
BINARY_COMPLEX 465 0.043%
FROZENSET 24 0.0022%
Total 1081517 100% 44802671 19274280 ~43%
Yet some statistics. If we import all standard modules, we can save using object sharing 2.3 MB of total 4.6 MB (50%) memory size for unicode objects, up to 0.47 MB of 1.25 MB for tuples (approximate upper limit), 84 KB of 117 KB (7%) for bytes objects, and only 2 KB of 101 KB for integers (most integers already interned). None of code objects can be shared (because code object contains almost unique first line number).
Therefore there is a sense to share unicode objects, tuples, and may be bytes objects. Most integers (in range -5..257) already interned. None of code objects can be shared (because code object contains almost unique first line number). Floats, complexes and frozensets unlikely save much of memory.