These are some simple language benchmarks I am running on the following programming languages:
- C/C++ - Apple LLVM version 5.0 (clang-500.2.79)
- Dart VM version: 1.8.5 (Tue Jan 13 13:04:11 2015) on "macos_ia32"
- Java - java version "1.7.0_71"
- JavaScript - v8 (under node v0.10.29)
- Python - both 3.3.0 and 2.7.5
- Ruby - ruby 2.0.0p451 (2014-02-24 revision 45167)
- Swift - Xcode Version 6.1.1 (6A2008a)
- PHP - PHP 5.6.5 (cli)
- Go - go version go1.4 darwin/amd64
- C# - Mono JIT compiler version 3.12.0 + Mono C# compiler version 3.12.0.0
- Rust - rustc 1.18.0-nightly (c58c928e6 2017-04-11)
These benchmarks compare performance characteristics of 10 different programming languages. Each benchmark includes a nearly identical implementation of the same program in each language. The pre-calculated statistics found in this repository were all collected on the same machine with a 2.6GHz Intel Core i7 with 1600 MHz DDR3 RAM. The first set of benchmarks were run under Mac OS X 10.9.3; the second were run under Mac OS X 10.10 (14A389).
Here is a recap of each of the three benchmarks I have done so far. You should really, really read the benchmark-specific README if you notice anything unusual.
| Language | Time (s) |
|---|---|
| C++ (-O2) | 1.892 |
| C++ (-O3) | 1.895 |
| Rust | 2.105 |
| Java | 2.469 |
| Go | 3.581 |
| C++ (-O1) | 5.290 |
| Dart | 5.844 |
| Swift | 7.675 |
| C++ (-O0) | 7.773 |
| C# (-O=all) | 10.639 |
| C# (normal) | 10.712 |
| JavaScript | 16.159 |
| Ruby | 300.4 |
| PHP | 557.2 |
| Python 2 | 717.2 |
| Python 3 | 880.7 |
| Language | Time (s) |
|---|---|
| Java | 3.776 |
| C (-O3) | 4.273 |
| C (-O2) | 4.367 |
| C (-O1) | 4.395 |
| Rust | 5.698 |
| Go | 7.825 |
| C# (-O=all) | 8.378 |
| Dart | 8.988 |
| JavaScript | 13.162 |
| C# (normal) | 14.071 |
| C (-O0) | 17.034 |
| Swift | 25.658 |
| Ruby | 1439 |
| Python 3 | 1466 |
| Python 2 | 1485 |
PHP is not listed in this table because it runs the array-reverse benchmark in O(n^2) complexity rather than O(n) complexity and is thus "infinitely" slower.
| Language | Time (s) |
|---|---|
| C (-O1) | 0.005 |
| C (-O2) | 0.005 |
| C (-O3) | 0.005 |
| Rust | 0.007 |
| Swift | 0.008 |
| Java | 0.463 |
| Go | 0.603 |
| C# (normal) | 0.621 |
| C# (-O=all) | 0.681 |
| Dart | 1.057 |
| JavaScript | 1.312 |
| C (-O0) | 2.763 |
| Ruby | 31.582 |
| PHP | 40.925 |
| Python 2 | 71.550 |
| Python 3 | 81.143 |
In the rolling average README, you will see an explanation of why C and Swift are so much faster than the rest
I tried very hard to make every implementation of each test close in structure. With that being said, some languages have features others don't, and I could have missed a feature along the way. If this is the case, go ahead and make a pull request or file an issue and explain why I tested a certain language unfairly.
None of these tests are the "best way" to do what they do. Instead, the tests are designed to be inefficient in order to get a significant result from various optimizers.
Some looping mechanisms are better than others. For instance, creating an array with 10000 consecutive integers and then iterating over them is not an efficient way to loop. But don't worry, in Python 2 I avoid using range() for large loops in favor of xrange().
Function calls have overhead. In C with optimizations, this overhead is pretty low and sometimes even non-existant (with inlining). However, in other languages like Python and Ruby, function calls may be rather expensive.
Arithmetic operations are (mostly) single CPU instructions. It is up to various languages to leverage this to perform to the best of the CPU's ability.
Accessing elements in arrays and updating variables should both be speedy operations.
Allocating memory through object construction should be very fast. In a langauge like C++, it is sometimes possible to avoid dynamic memory allocation altogether in favor of stack allocation. On the other hand, a langauge like Java forces you to create objects using the new operator.