Python Interpreters Benchmarks
x64 ArchLinux : AMD® Ryzen 7 4700U®

- all benchmarks - n-body fannkuch-redux meteor-contest fasta fasta-redux fibonacci fib50 spectral-norm reverse-complement mandelbrot k-nucleotide regex-dna pidigits chameneos-redux templates thread-ring binary-trees-redux binary-trees pystone richards iobench jsonbench - all languages - Python 2 PyPy Python 3 Python dev PyPy 3 Jython IronPython Cython Nuitka Shedskin Numba Pyston MicroPython Grumpy Graal RustPython

vs Python 2 PyPy Python 3 Python dev PyPy 3 Jython IronPython Cython Nuitka Shedskin Numba Pyston MicroPython Grumpy Graal RustPython x64 octa-core

 1 : Are the PyPy programs faster? At a glance.

Each chart bar shows, for one unidentified benchmark, how much the fastest PyPy program used compared to the fastest Nuitka program.

(Memory use is only compared for tasks that require memory to be allocated.)

These are not the only compilers and interpreters. These are not the only programs that could be written. These are not the only tasks that could be solved. These are just 10 tiny examples.

 2 : Are the PyPy programs faster? Approximately.

Each table row shows, for one named benchmark, how much the fastest PyPy program used compared to the fastest Nuitka program.

(Memory use is only compared for tasks that require memory to be allocated.)

PyPy used what fraction? used how many times more?
Benchmark	Time	Memory	Code
n-body	1/8		±
fib50	1/6		±
richards †	1/3		±
thread-ring †	1/3		±
jsonbench	1/2		±
meteor-contest	1/2		±
pystone †	1/2	?	±
fasta †	±		1/2
spectral-norm	±	?	2×
fannkuch-redux	±		±
fasta-redux	±	?	±
k-nucleotide	±	?	±
regex-dna	2×	?	±
reverse-complement †	2×	?	±
templates	4×		±
binary-trees	5×	40×	±
iobench	5×		±
pidigits	100×	?	±

PyPy used what fraction? used how many times more?
Time-used	|-	|---	25%	median	75%	---|	-|
(Elapsed secs)	1/8	1/8	1/2	±	2×	5×	100×

† possible mismatch - one-core program compared to multi-core program.

± read the measurements and then read the program source code.

 3 : Are the PyPy programs faster? Measurements.

These are not the only tasks that could be solved. These are just 10 tiny examples. These are not the only compilers and interpreters. These are not the only programs that could be written.

For each named benchmark, measurements of the fastest PyPy program are shown for comparison against measurements of the fastest Nuitka program.

Program Source Code	CPU secs	Elapsed secs	Memory KB	Code B	≈ CPU Load
n-body
PyPy	3.29	3.29	74,856	1337	0% 100% 1% 0% 1% 1% 1% 1%
Nuitka	27.09	27.10	11,136	1315	2% 1% 0% 0% 1% 0% 100% 0%
fib50
PyPy	0.48	0.48	77,576	130	4% 100% 0% 2% 2% 0% 2% 0%
Nuitka	2.92	2.92	11,136	136	2% 1% 1% 1% 100% 0% 0% 0%
richards
PyPy	0.18	0.18	?	2423	18% 5% 100% 0% 0% 5% 5% 0% †
Nuitka	0.58	0.58	11,264	2434	2% 2% 0% 0% 2% 2% 100% 0% †
thread-ring
PyPy	0.11	0.11	?	407	0% 8% 92% 0% 9% 0% 0% 8% †
Nuitka	0.35	0.35	1,152	406	17% 3% 3% 0% 100% 14% 16% 9% †
jsonbench
PyPy	0.90	0.90	80,556	322	0% 0% 100% 3% 1% 0% 1% 0%
Nuitka	2.16	2.16	14,896	322	0% 0% 0% 100% 0% 0% 0% 0%
meteor-contest
PyPy	0.67	0.67	80,972	1485	4% 0% 1% 99% 0% 4% 0% 0%
Nuitka	1.35	1.35	11,392	1443	1% 0% 0% 0% 1% 100% 0% 0%
pystone
PyPy	0.08	0.09	?	2301	100% 10% 0% 0% 0% 20% 0% 11% †
Nuitka	0.15	0.15	?	2300	7% 6% 6% 0% 0% 100% 0% 0% †
fasta
PyPy	1.75	1.75	77,640	900	2% 2% 2% 2% 100% 3% 2% 1% †
Nuitka	5.59	2.59	72,224	2016	69% 14% 2% 63% 38% 7% 23% 5% †
spectral-norm
PyPy	0.09	0.09	?	594	0% 0% 0% 100% 18% 0% 0% 0%
Nuitka	0.10	0.11	?	394	8% 0% 91% 0% 0% 0% 0% 0%
fannkuch-redux
PyPy	1.68	0.58	322,008	1009	41% 19% 66% 16% 43% 68% 66% 32%
Nuitka	4.48	0.62	102,152	894	92% 90% 98% 89% 92% 84% 92% 90%
fasta-redux
PyPy	0.19	0.19	?	1115	0% 0% 5% 100% 5% 5% 0% 0%
Nuitka	0.19	0.19	?	1115	5% 0% 100% 0% 0% 0% 0% 0%
k-nucleotide
PyPy	0.09	0.09	?	593	22% 18% 0% 100% 0% 0% 0% 0%
Nuitka	0.08	0.06	?	801	14% 71% 14% 17% 0% 17% 17% 0%
regex-dna
PyPy	0.10	0.11	?	501	100% 0% 0% 0% 0% 0% 0% 0%
Nuitka	0.04	0.05	?	524	17% 0% 0% 0% 0% 100% 0% 0%
reverse-complement
PyPy	0.06	0.06	?	432	0% 14% 0% 0% 0% 14% 14% 100% †
Nuitka	0.03	0.03	?	458	0% 0% 0% 0% 0% 0% 100% 0% †
templates
PyPy	2.37	2.41	98,384	307	0% 6% 94% 0% 0% 0% 1% 0%
Nuitka	0.63	0.63	19,200	322	3% 100% 0% 0% 2% 3% 2% 0%
binary-trees
PyPy	2.27	1.04	91,028	743	32% 67% 25% 28% 24% 28% 22% 24%
Nuitka	1.06	0.22	2,304	741	70% 62% 59% 59% 59% 82% 59% 55%
iobench
PyPy	14.73	14.73	80,864	370	0% 0% 100% 0% 0% 0% 1% 0%
Nuitka	2.75	2.76	11,008	367	100% 0% 0% 0% 0% 0% 1% 0%
pidigits
PyPy	2.98	2.99	81,732	322	100% 0% 0% 0% 1% 0% 0% 0%
Nuitka	0.03	0.03	?	379	0% 75% 0% 0% 0% 0% 0% 0%
mandelbrot
	No program
Nuitka	36.89	4.88	300,640	3852	100% 95% 97% 94% 94% 95% 95% 95%
fibonacci
PyPy	0.17	0.17	?	181	6% 0% 0% 0% 0% 6% 11% 100%
	No program
chameneos-redux
	No program
Nuitka	188.65	274.40	15,268	1191	8% 5% 5% 5% 9% 8% 8% 9%
binary-trees-redux
	No programs

† possible mismatch - one-core program compared to multi-core program.

 4 : Are there other PyPy programs for these benchmarks?

Remember - those are just the fastest PyPy and Nuitka programs measured on this OS/machine. Check if there are other implementations of these benchmark programs for PyPy.

Python 2 PyPy Python 3 Python dev PyPy 3 Jython IronPython Cython Nuitka Shedskin Numba Pyston MicroPython Grumpy Graal RustPython

Maybe one of those other PyPy programs is fastest on a different OS/machine.

 5 : Are there other faster programs for these benchmarks?

Remember - those are just the fastest PyPy and Nuitka programs measured on this OS/machine. Check if there are faster implementations of these benchmark programs for other programming languages.

n-body fannkuch-redux meteor-contest fasta fasta-redux fibonacci fib50 spectral-norm reverse-complement mandelbrot k-nucleotide regex-dna pidigits chameneos-redux templates thread-ring binary-trees-redux binary-trees pystone richards iobench jsonbench

Maybe one of those other programs is fastest on a different OS/machine.

 PyPy : the old PyPy 

  Home   Conclusions   License   Play