I used brainfuck interpreter https://github.com/Beariish/bolt/blob/main/examples/bf.bolt
vs lua / luajit implementations from https://github.com/kostya/benchmarks
Just checked with nbody:
- still 10 times slower than luajit
- 2 times slower than luajit -joff
- but 20% faster than lua 5.4
- but uses 47 Mb RAM vs 2.5 Mb for lua/luajit
In Show HN: Bolt – A super-fast, statically-typed scripting language written in Ckostya
benchmarks
Makefile2014–2025
kostya / benchmarks
benchmarks
Some benchmarks of different languages
62Distinct people
74Mentions
1Explicit recommenders
2.9KGitHub stars
What to know before exploring
What it is
Some benchmarks of different languages
GitHub
Where it is used
No documented product use was verified in the last source check.
What people are saying
I'm surprised you're able to get Turing to run faster, to be honest. I looked at Turing and was impressed by it, but in general my experience with MCMC libraries in Julia is…
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- crystal-lang/crystal · linked in 2 of the same discussions
- nsf/pnoise · linked in 2 of the same discussions
- the-benchmarker/web-frameworks · linked in 2 of the same discussions
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This week on Hacker News
Nov 7–Nov 14 UTC · Direct repository links and separately labeled related project stories. Indexed through 11/14/2026, 3:03:16 PM UTC.
No direct repository links were found in the indexed HN discussions over the past seven days. Older discussions are available below.
Mentions over time
HN mentions by year74 dated mentions
Observed mentions: 2014-11-25 20:25:21 UTC to 2025-08-11 11:33:32 UTC.
Counts come from the repository’s dated source evidence. Index cutoff: 2026-11-02 08:16:59 UTC.
View mention counts and date ranges
| Period | Start (UTC) | End (exclusive, UTC) | Mentions | Submissions | Comments |
|---|---|---|---|---|---|
| 2014 | 2014-01-01 00:00:00 UTC | 2015-01-01 00:00:00 UTC | 1 | 0 | 1 |
| 2015 | 2015-01-01 00:00:00 UTC | 2016-01-01 00:00:00 UTC | 15 | 1 | 14 |
| 2016 | 2016-01-01 00:00:00 UTC | 2017-01-01 00:00:00 UTC | 8 | 3 | 5 |
| 2017 | 2017-01-01 00:00:00 UTC | 2018-01-01 00:00:00 UTC | 13 | 0 | 13 |
| 2018 | 2018-01-01 00:00:00 UTC | 2019-01-01 00:00:00 UTC | 4 | 0 | 4 |
| 2019 | 2019-01-01 00:00:00 UTC | 2020-01-01 00:00:00 UTC | 8 | 0 | 8 |
| 2020 | 2020-01-01 00:00:00 UTC | 2021-01-01 00:00:00 UTC | 9 | 1 | 8 |
| 2021 | 2021-01-01 00:00:00 UTC | 2022-01-01 00:00:00 UTC | 7 | 0 | 7 |
| 2022 | 2022-01-01 00:00:00 UTC | 2023-01-01 00:00:00 UTC | 3 | 0 | 3 |
| 2023 | 2023-01-01 00:00:00 UTC | 2024-01-01 00:00:00 UTC | 2 | 0 | 2 |
| 2024 | 2024-01-01 00:00:00 UTC | 2025-01-01 00:00:00 UTC | 3 | 2 | 1 |
| 2025 | 2025-01-01 00:00:00 UTC | 2026-01-01 00:00:00 UTC | 1 | 0 | 1 |
From the project README
An excerpt from the repository, fetched Nov 13, 2026.
Read the project’s introduction
Table of Content
Overview
Measurements
Test Cases
Brainfuck
bench.b
mandel.b
Base64
Json
Matmul
Primes
Tests Execution
Environment
Using Docker
Manual Execution
Prerequisites
Contribution
Makefile guide
Binary executables
Compiled artifacts
Scripting language
README update
Docker image update
Overview
The benchmarks follow the criteria:
They are written as the average software developer would write them, i.e.
The algorithms are implemented as cited in public sources;
The libraries are used as described in the tutorials, documentation and examples;
The used data structures are idiomatic.
The used algorithms are similar between the languages (as the reference implementations), variants are acceptable if the reference implementation exists.
All final binaries are releases (optimized for performance if possible) as debug performance may vary too much depending on the compiler.
My other benchmarks: jit-benchmarks, crystal-benchmarks-game, LangArena
Measurements
The measured values are:
time spent for the benchmark execution (loading required data and code self-testing are not measured);
memory consumption of the benchmark process, reported as base + increase, where base is the RSS before the benchmark and increase is the peak increase of the RSS during the benchmark;
energy consumption of the CPU package during the benchmark: PP0 (cores) + PP1 (uncores like GPU) + DRAM. Currently, only Intel CPU are supported via the powercap interface.
All values are presented as: median±median absolute deviation.
UPDATE: 2026-07-19
Test Cases
Brainfuck
Testing brainfuck implementations using two code samples (bench.b and mandel.b).
Supports two mode:
Verbose (default). Prints the output immediately.
Quiet (if QUIET environment variable is set). Accumulates the output using Fletcher-16 checksum, and prints it out after the benchmark.
Brainfuck
bench.b
Language
Time, s
Memory, MiB
Energy, J
C# (Staged)/.NET Core
0.373±0.009
36.62±00.12 + 0.25±00.00
14.33±00.26
Scala (Staged)
0.409±0.011
229.62±03.27 + 7.00±01.44
26.31±00.71
Racket (Staged)
0.885±0.000
101.37±01.65 + 0.06±00.06
34.39±00.17
V/gcc
0.985±0.001
2.12±00.00 + 0.00±00.00
41.65±00.28
Rust
1.008±0.000
1.88±00.00 + 0.00±00.00
42.93±00.33
D/ldc2
1.078±0.001
3.12±00.00 + 0.00±00.00
45.78±00.24
C++/g++
1.097±0.002
3.38±00.00 + 0.00±00.00
46.21±00.59
C/gcc
1.112±0.001
1.38±00.12 + 0.00±00.00
47.10±00.09
D/gdc
1.116±0.001
6.75±00.00 + 0.00±00.00
48.89±00.28
C/clang
1.136±0.000
1.44±00.06 + 0.00±00.00
48.52±00.33
C++/clang++
1.167±0.002
2.88±00.00 + 0.00±00.00
48.87±00.76
Nim/gcc
1.171±0.001
2.00±00.00 + 0.00±00.00
48.80±00.70
Java
1.191±0.000
41.74±00.09 + 1.00±00.00
49.32±00.60
Vala/gcc
1.202±0.001
5.25±00.12 + 0.00±00.00
50.70±00.44
Kotlin/JVM
1.224±0.002
44.48±00.07 + 1.31±00.25
51.60±00.64
Vala/clang
1.235±0.000
5.19±00.06 + 0.00±00.00
52.40±00.39
Go
1.256±0.000
3.75±00.00 + 0.00±00.00
52.69±00.80
C#/.NET Core
1.280±0.001
36.88±00.06 + 0.00±00.00
54.29±00.22
Go/gccgo
1.287±0.000
23.50±00.38 + 0.00±00.00
54.23±00.16
Zig
1.327±0.000
1.38±00.12 + 0.00±00.00
55.13±00.40
Crystal
1.545±0.001
3.25±00.00 + 0.00±00.00
65.69±00.40
Julia
1.564±0.003
244.00±00.12 + 0.38±00.00
67.80±00.43
F#/.NET Core
1.566±0.002
41.88±00.07 + 0.12±00.00
65.15±00.12
Nim/clang
1.579±0.000
2.25±00.00 + 0.00±00.00
65.59±00.57
OCaml
1.607±0.002
3.25±00.00 + 2.62±00.00
75.45±00.78
MLton
1.737±0.006
1.62±00.00 + 0.38±00.00
74.87±00.28
Chez Scheme
1.758±0.005
25.88±00.29 + 3.25±00.00
74.43±00.21
Racket
1.761±0.013
112.86±00.03 + 0.50±00.38
72.49±02.28
V/clang
1.846±0.009
2.06±00.06 + 0.00±00.00
80.00±00.53
Scala
2.379±0.003
66.03±00.14 + 196.44±00.12
108.88±00.92
Node.js
2.954±0.060
49.57±00.06 + 5.78±00.12
126.35±03.17
D/dmd
3.010±0.001
3.50±00.00 + 0.00±00.00
113.43±01.11
Haskell (MArray)
3.497±0.001
4.00±00.00 + 4.00±00.00
144.74±00.32
Haskell (FP)
3.819±0.008
4.12±00.06 + 4.06±00.06
163.47±01.56
Ruby/truffleruby (JVM)
4.645±0.070
354.81±05.59 + 478.37±54.20
221.41±05.66
Ruby/truffleruby
5.169±0.461
197.19±00.69 + 693.00±117.12
252.03±23.51
Swift
5.497±0.001
17.00±00.12 + 0.00±00.00
205.09±04.14
Lua/luajit
5.686±0.024
2.50±00.00 + 0.00±00.00
235.32±01.30
Python/pypy
9.398±0.038
60.19±00.19 + 30.10±00.05
419.65±03.72
Idris
15.088±0.032
21.55±00.26 + 8.00±00.00
677.49±01.79
Elixir
20.456±0.025
90.88±00.30 + 0.00±00.00
814.83±07.69
Ruby (--jit)
30.807±0.033
21.88±00.13 + 4.62±00.00
1275.90±04.28
PHP
34.055±0.041
17.61±00.06 + 0.00±00.00
1447.00±15.80
Lua
37.051±0.168
2.62±00.00 + 0.00±00.00
1528.23±05.85
Ruby/jruby
38.543±0.745
255.48±00.77 + 70.31±00.25
1732.28±34.61
Python
61.009±0.870
11.38±00.00 + 0.00±00.00
2601.10±34.54
Ruby
74.107±0.332
12.12±00.06 + 0.00±00.00
3209.85±28.74
Tcl (FP)
189.615±0.465
4.62±00.00 + 0.00±00.00
8409.77±69.18
Perl
225.517±1.873
7.06±00.06 + 0.12±00.00
9777.03±135.29
Tcl (OOP)
373.095±1.341
4.62±00.00 + 0.00±00.00
16604.13±190.89
mandel.b
Mandel in Brainfuck
Language
Time, s
Memory, MiB
Energy, J
C# (Staged)/.NET Core
2.917±0.001
36.75±00.00 + 3.25±00.00
109.82±00.22
Scala (Staged)
7.118±0.079
228.10±04.74 + 71.23±06.06
356.09±07.48
C++/g++
10.143±0.051
3.50±00.00 + 0.62±00.00
434.41±04.03
C/gcc
12.544±0.019
1.62±00.00 + 0.25±00.00
509.37±03.30
Vala/gcc
12.718±0.010
5.25±00.06 + 0.50±00.00
511.94±00.90
C++/clang++
12.803±0.022
3.00±00.00 + 0.62±00.00
545.25±01.09
Zig
13.030±0.017
1.50±00.00 + 1.00±00.00
556.10±03.71
Java
13.041±0.020
41.77±00.15 + 1.94±00.06
537.41±01.88
C/clang
13.120±0.021
1.50±00.06 + 0.25±00.00
579.20±04.21
Kotlin/JVM
13.463±0.052
44.46±00.06 + 2.56±00.06
571.73±03.08
D/ldc2
14.340±0.012
3.06±00.06 + 0.75±00.00
591.01±03.53
Rust
14.460±0.021
1.94±00.06 + 0.25±00.00
577.37±02.52
Go
14.540±0.007
3.75±00.00 + 0.00±00.00
584.48±01.83
Vala/clang
14.802±0.012
5.12±00.00 + 0.50±00.00
595.99±01.53
Crystal
14.891±0.054
3.38±00.06 + 0.38±00.00
631.17±02.60
D/gdc
15.17
Read the full README on GitHubWhat Hacker News says
74 sources> I don’t where these myths get started, but someone needs to justify the Ruby-is-slow thing with actual data.
As an outside observer of the Ruby world,
I have an impression that it was Ruby MRI that was slow.
CPU-bound synthetic benchmarks like the much-criticized Benchmarks Game showed Ruby ≤ 1.8 a good deal slower than CPython 2.
Here is an illustrative comment from that time: https://news.ycombinator.com/item?id=253310.
People also complained about early Rails,
and the perception of Ruby's performance got mixed up with that of Rails.
Then YARV came out, and Ruby became several times faster than its MRI former self on different benchmarks (https://en.wikipedia.org/wiki/YARV#Performance).
With YARV, Ruby gradually caught up to "fast" interpreted languages.
Now interpreted Ruby seems as fast as CPython 3 or faster in synthetic benchmarks
Read the rest
(for example, https://github.com/kostya/benchmarks/blob/7bf440499e2b1e81fb...), though still behind the fastest mainstream interpreters like Lua's.
Ruby is even faster with YJIT.
Kostya/benchmarks: Some benchmarks of different languages
1 points · Open discussionSome Benchmarks of Different Languages
2 points · Open discussionWhat is faster? According to https://github.com/kostya/benchmarks#json nothing is.
In Building a high performance JSON parserIn all the language comparisons I've found over the years, Python consistently comes out slightly slower, for example:
https://github.com/kostya/benchmarks
Bearing in mind these are probably not even using YJIT, which makes Ruby considerably faster in some scenarios.
In Ruby 3.2.0 is from another dimensionAccording to these benchmarks, pure Python is about 100 times slower than C and other fast languages: https://github.com/kostya/benchmarks
In The computers are fast, but you don't know itI think the basic idea is to cross energy use of a language with ubiquity of existing deployments.
So take energy use benchmarks from things like this
https://haslab.github.io/SAFER/scp21.pdf
https://github.com/kostya/benchmarks
and cross it with popularity?
https://spectrum.ieee.org/top-programming-languages/
In Programming in the ApocalypseYes, as far as I can tell [1]. It's a simple Tape algorithm. Neither had any crazy SIMD, threads, no custom containers, etc. They use almost the same function names (and look the same as the Go version too). I used `time -l` https://stackoverflow.com/a/30124747 for memory usage.
Note I ran the benchmarks locally (MacBook Air M1) because the reported benchmark uses the older (default) Nim GC while I only use Nim+ARC. I also had to fix the Zig code and it took a few tries to get the signed/unsigned int conversions working. I tried tweaking flags for both a bit as well to see how stable they were. Zig's memory usage was pretty constant. Nim had a small speed vs memory tradeoff that could be tweak-able, but the defaults used the least memory.
Overall I'd expect exact memory usage by language(s) to vary some by benchmark and one random benchma
Read the rest
rk isn't conclusive. Still I didn't find anything to indicate Zig is clearly better than other new generation languages. Manual memory management might actually be worse than letting a compiler manage it in some cases.
1: https://github.com/kostya/benchmarks/tree/master/brainfuck
> They seem to invest a lot in JavaScript which is not what I’d call a performant language
JavaScript (V8 at least) is extremely performant, near native code performance. Considering how dynamic it is, it's not an easy feat but Google, Apple and Mozilla work a lot on it.
Here's a benchmark where JS is 50x faster than Python: https://github.com/kostya/benchmarks
Note that PyPy does much better.
In Faster Python with Guido van RossumIf anyone is interested to see how Nim fares against some other programming languages, here are some benchmarks: https://github.com/kostya/benchmarks
In Why I Use Nim instead of Python for Data ProcessingPerhaps these other projects are a better match with what you expect to see —
https://programming-language-benchmarks.vercel.app/
https://github.com/kostya/benchmarks
In Golang vs. C# (.NET 5.0) at Benchmarks GameThe problem is a minor placement issue for the `@simd` macro: https://github.com/kostya/benchmarks/pull/317
In Julia 1.6 HighlightsAre the performance claims of Julia greatly exaggerated?
Julia loses almost consistently to Go, Crystal, Nim, Rust, Kotlin, Python (PyPy, Numpy):
https://github.com/kostya/benchmarks
Is this because of bad typing or they didn't use Julia properly in idiomatic manner?
In Julia 1.6 HighlightsYou can find some benchmarks here: https://github.com/kostya/benchmarks
With the caveat of course being that benchmarks don't always reflect real world performance.
In Crystal 1.0 – What to expectShowing the 15 most recent of 74 sources. Enable JavaScript to search and browse every indexed mention.