With lst = [0] * 10**6 I get times like these:

  5.4 ± 0.4 ms  bytearray(lst)
  5.6 ± 0.4 ms  bytes(bytearray(lst))
 13.1 ± 0.7 ms  bytes(lst)

Python:
3.13.0 (main, Nov  9 2024, 10:04:25) [GCC 14.2.1 20240910]
namespace(name='cpython', cache_tag='cpython-313', version=sys.version_info(major=3, minor=13, micro=0, releaselevel='final', serial=0), hexversion=51183856, _multiarch='x86_64-linux-gnu')

I would’ve expected bytes(lst) and bytearray(lst) to be equally fast or bytearray(lst) to be the slower one, since it’s the more complicated type (has more functionality, as it’s mutable). But it’s the other way around. And even the detour bytes(bytearray(lst)) is much faster than bytes(lst)! Why is bytes(lst) so slow?

Benchmark script (Attempt This Online!):

from timeit import timeit
from statistics import mean, stdev
import random
import sys

setup = 'lst = [0] * 10**6'

codes = [
    'bytes(lst)',
    'bytearray(lst)',
    'bytes(bytearray(lst))'
]

times = {c: [] for c in codes}
def stats(c):
    ts = [t * 1e3 for t in sorted(times[c])[:5]]
    return f'{mean(ts):5.1f} ± {stdev(ts):3.1f} ms '
for _ in range(25):
    random.shuffle(codes)
    for c in codes:
        t = timeit(c, setup, number=10) / 10
        times[c].append(t)
for c in sorted(codes, key=stats):
    print(stats(c), c)

print('nPython:')
print(sys.version)
print(sys.implementation)

Inspired by an answer that also found bytearray to be faster.