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 How big is the difference between programming languages?

This chart shows 1 or 2 or 3 comparisons - Time-used and/or Memory-used and/or Code-used ~ speed and size.

Remember - these measurements are just of the fastest programs for each of these programming language implementations, measured on this OS/machine.

Selected and weighted "how many times more compared to the program that used least scores" are compressed into one number - ↓ a weighted geometric mean.

Select the weights you want to give each comparison and each benchmark then click the chart button.

Or follow the links to compare 2 language implementations directly - one-against-another for all the benchmarks - on Time-used, Memory-used and Code-used.

  compare 2 GM missing

C++ GNU g++ 1.34 

Fortran Intel 1.413

C GNU gcc 1.43 

Java 7 -server 1.87 

ATS 1.88 

Ada 2005 GNAT 1.95 

Scala 2.76 

Haskell GHC 2.97 

Lisp SBCL 3.06 

OCaml 3.30 

Go 3.82 

C# Mono 4.11 

Pascal Free Pascal 4.371

Clojure 5.17 

F# Mono 6.061

Racket 7.28 

Erlang HiPE 12.01 

Erlang 23.31 

Python 3 27.89 

PHP 34.932

Ruby 1.9 46.97 

Ruby JRuby 47.33 

Perl 52.47 
measureweight
Time secs
Memory KB
Code B
benchmarkweight
n-body

fannkuch-redux

meteor-contest

fasta

fasta-redux

spectral-norm

reverse-complement

mandelbrot

k-nucleotide

regex-dna

pidigits

chameneos-redux

thread-ring

binary-trees

 Which programming language is best? The Weighted Geometric Mean

Read "How not to lie with statistics: the correct way to summarize benchmark results" (pdf).

For each benchmark, B is the best measurement.
For each language implementation, the best measurement L is then normalized to L ÷ B

GM is the Weighted Geometric Mean of those L ÷ B ratios.

missing : Language implementations with more than a couple of Timeouts (at the largest workload) distort the ranking - so they have been excluded. They can still be compared directly against another language implementation.


There are other ways to analyse and present this data: ask Which programming languages are fastest? or look for patterns in Code-used Time-used Shapes or take the Summary Data and do your own analysis!

Revised BSD license

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