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 Python 2 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 Python 2 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
spectral-norm †	1/12		±
n-body	1/12		±
fib50	1/5		±
fannkuch-redux	1/5		±
richards †	1/5		±
jsonbench	1/5		±
thread-ring	1/3		±
fasta	1/3		±
meteor-contest	1/3		±
fibonacci †	1/3		±
pystone †	1/2	?	±
iobench	1/2		±
k-nucleotide †	±	?	±
pidigits	±		±
binary-trees	2×	6×	±
regex-dna †	4×	?	±

PyPy used what fraction? used how many times more?
Time-used	|-	|---	25%	median	75%	---|	-|
(Elapsed secs)	1/12	1/12	1/5	1/3	±	2×	4×

† 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 Python 2 program.

Program Source Code	CPU secs	Elapsed secs	Memory KB	Code B	≈ CPU Load
spectral-norm
PyPy	0.09	0.09	?	594	0% 0% 0% 100% 18% 0% 0% 0% †
Python 2	4.23	1.13	11,728	595	78% 71% 51% 30% 25% 35% 40% 59% †
n-body
PyPy	3.29	3.29	74,856	1337	0% 100% 1% 0% 1% 1% 1% 1%
Python 2	38.78	38.78	6,684	1337	0% 0% 0% 0% 0% 1% 0% 100%
fib50
PyPy	0.48	0.48	77,576	130	4% 100% 0% 2% 2% 0% 2% 0%
Python 2	2.40	2.40	37,872	130	0% 0% 100% 0% 0% 0% 0% 0%
fannkuch-redux
PyPy	1.68	0.58	322,008	1009	41% 19% 66% 16% 43% 68% 66% 32%
Python 2	11.02	2.85	11,460	1009	6% 4% 97% 95% 94% 0% 1% 96%
richards
PyPy	0.18	0.18	?	2423	18% 5% 100% 0% 0% 5% 5% 0% †
Python 2	0.87	0.87	6,348	2423	1% 0% 100% 0% 1% 0% 0% 0% †
jsonbench
PyPy	0.90	0.90	80,556	322	0% 0% 100% 3% 1% 0% 1% 0%
Python 2	4.25	4.26	15,884	322	0% 0% 100% 0% 0% 0% 0% 0%
thread-ring
PyPy	0.11	0.11	?	407	0% 8% 92% 0% 9% 0% 0% 8%
Python 2	0.38	0.39	2,800	407	3% 3% 97% 0% 0% 0% 0% 0%
fasta
PyPy	1.75	1.75	77,640	900	2% 2% 2% 2% 100% 3% 2% 1%
Python 2	5.87	5.91	12,988	900	0% 0% 1% 0% 0% 99% 0% 0%
meteor-contest
PyPy	0.67	0.67	80,972	1485	4% 0% 1% 99% 0% 4% 0% 0%
Python 2	2.14	2.14	6,828	1485	0% 0% 100% 0% 0% 0% 0% 1%
fibonacci
PyPy	0.17	0.17	?	181	6% 0% 0% 0% 0% 6% 11% 100% †
Python 2	0.49	0.49	6,772	181	0% 100% 2% 0% 0% 0% 0% 0% †
pystone
PyPy	0.08	0.09	?	2301	100% 10% 0% 0% 0% 20% 0% 11% †
Python 2	0.20	0.20	?	2301	0% 0% 0% 0% 0% 100% 0% 0% †
iobench
PyPy	14.73	14.73	80,864	370	0% 0% 100% 0% 0% 0% 1% 0%
Python 2	24.86	24.86	6,336	370	0% 0% 100% 0% 0% 0% 0% 0%
k-nucleotide
PyPy	0.09	0.09	?	593	22% 18% 0% 100% 0% 0% 0% 0% †
Python 2	0.07	0.07	?	593	100% 0% 0% 0% 0% 0% 0% 0% †
pidigits
PyPy	2.98	2.99	81,732	322	100% 0% 0% 0% 1% 0% 0% 0%
Python 2	2.13	2.13	7,128	322	0% 0% 0% 0% 1% 0% 100% 0%
binary-trees
PyPy	2.27	1.04	91,028	743	32% 67% 25% 28% 24% 28% 22% 24%
Python 2	2.02	0.47	16,340	743	54% 57% 56% 54% 64% 57% 63% 54%
regex-dna
PyPy	0.10	0.11	?	501	100% 0% 0% 0% 0% 0% 0% 0% †
Python 2	0.03	0.03	?	501	100% 0% 0% 0% 0% 0% 0% 33% †
templates
PyPy	2.37	2.41	98,384	307	0% 6% 94% 0% 0% 0% 1% 0%
	No program
fasta-redux
PyPy	0.19	0.19	?	1115	0% 0% 5% 100% 5% 5% 0% 0%
	No program
reverse-complement
PyPy	0.06	0.06	?	432	0% 14% 0% 0% 0% 14% 14% 100%
Python 2	0.01		?	432
mandelbrot
	No programs
chameneos-redux
	No programs
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 Python 2 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 Python 2 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 

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