The C implementation of sum() contains this comment:

        /* It's tempting to use PyNumber_InPlaceAdd instead of
           PyNumber_Add here, to avoid quadratic running time
           when doing 'sum(list_of_lists, [])'.  However, this
           would produce a change in behaviour: a snippet like
             empty = []
             sum([[x] for x in range(10)], empty)
           would change the value of empty. */

But that doesn't hold after PyNumber_Add has been called once,
because from that point onward the accumulator value is something
we got from an __add__, and the caller can't know if we reuse it.

The in-place version is substantially faster for some workloads--
the example in the comment is an obvious one, but the context in
which I ran into this was using a sum of Counters in a one-liner
a bit like this:

    sum((Counter({line.split("|", 3): len(line)}) for line in sys.stdin), Counter())

in which significant time seems to be spent adding the contents
of the previous accumulator value to the new one.

# before
; ./python -m timeit 'sum(([x] for x in range(1000)), [])'
500 loops, best of 5: 888 usec per loop

# after
; ./python -m timeit 'sum(([x] for x in range(1000)), [])'
5000 loops, best of 5: 65.3 usec per loop


; cat test_.py 
from collections import Counter
import timeit
import random

data = [Counter({random.choice(['foo', 'bar', 'baz', 'qux']): random.randint(1,1000000)}) for _ in range(10000)]

print(min(timeit.repeat('sum(data, Counter())', 'from collections import Counter', number=100, globals={'data': data})))
print(min(timeit.repeat('reduce(Counter.__iadd__, data, Counter())', 'from collections import Counter; from functools import reduce', number=100, globals={'data': data})))

# before
; ./python test_.py
1.8981186050223187
0.7094596439856105

# after
; ./python test_.py 
0.715508968976792
0.7050370009965263