(macOS Ventura, x64)
- System python 3.9.6: 26.80s user 0.27s system 99% cpu 27.285 total
- MacPorts python 3.9.25: 23.83s user 0.32s system 98% cpu 24.396 total
- MacPorts python 3.13.11: 15.17s user 0.28s system 98% cpu 15.675 total
- MacPorts python 3.14.2: 15.31s user 0.32s system 98% cpu 15.893 total
Wish I'd thought to try this test sooner now. (I generally haven't bothered with Python upgrades much, on the basis that the best version will be the one that's easiest to install, or, better yet, is there already. I'm quite used to the language and stdlib as the are, and I've just assumed the performance will still be as limited as it always has been...!)
$ hyperfine "mise exec [email protected] -- python e.py" "mise exec [email protected] -- python e.py" "mise exec [email protected] -- python e.py" "mise exec [email protected] -- python e.py"
Benchmark 1: mise exec [email protected] -- python e.py
Time (mean ± σ): 148.1 ms ± 1.8 ms [User: 132.3 ms, System: 17.5 ms]
Range (min … max): 146.7 ms … 154.7 ms 19 runs
Benchmark 2: mise exec [email protected] -- python e.py
Time (mean ± σ): 1.933 s ± 0.007 s [User: 1.913 s, System: 0.023 s]
Range (min … max): 1.925 s … 1.948 s 10 runs
Benchmark 3: mise exec [email protected] -- python e.py
Time (mean ± σ): 1.375 s ± 0.011 s [User: 1.356 s, System: 0.022 s]
Range (min … max): 1.366 s … 1.403 s 10 runs
Benchmark 4: mise exec [email protected] -- python e.py
Time (mean ± σ): 1.302 s ± 0.003 s [User: 1.284 s, System: 0.022 s]
Range (min … max): 1.298 s … 1.307 s 10 runs
Summary
mise exec [email protected] -- python e.py ran
8.79 ± 0.11 times faster than mise exec [email protected] -- python e.py
9.28 ± 0.13 times faster than mise exec [email protected] -- python e.py
13.05 ± 0.16 times faster than mise exec [email protected] -- python e.py
Historically CPython performance has been so bad, that massive speedups were quite possible, once someone seriously got into it.
Sorry but unless your workload is some C API numpy number cruncher that just does matmuls on the CPU, that's probably false.
In 3.11 alone, CPython sped up by around 25% over 3.10 on pyperformance for x86-64 Ubuntu. https://docs.python.org/3/whatsnew/3.11.html#whatsnew311-fas...
3.14 is 35-45% faster than CPython 3.10 for pyperformance x86-64 Ubuntu https://github.com/faster-cpython/benchmarking-public
These speedups have been verified by external projects. For example, a Python MLIR compiler that I follow has found a geometric mean 36% speedup moving from CPython 3.10 to 3.11 (page 49 of https://github.com/EdmundGoodman/masters-project-report)
Another academic benchmark here observed an around 1.8x speedup on their benchmark suite for 3.13 vs 3.10 https://youtu.be/03DswsNUBdQ?t=145
CPython 3.11 sped up enough that PyPy in comparison looks slightly slower. I don't know if anyone still remembers this: but back in the CPython 3.9 days, PyPy had over 4x speedup over CPython on the PyPy benchmark suite, now it's 2.8 on their website https://speed.pypy.org/ for 3.11.
Yes CPython is still slow, but it's getting faster :).
Disclaimer: I'm just a volunteer, not an employee of Microsoft, so I don't have a perf report to answer to. This is just my biased opinion.