Codon VS Kotlin benchmarks

Current benchmark data was generated on Sun Jun 01 2025, full log can be found HERE

CONTRIBUTIONS are WELCOME!

[x86_64][4 cores] AMD EPYC 7763 64-Core Processor (Model 1)

* -m in a file name stands for multi-threading or multi-processing

* -i in a file name stands for direct intrinsics usage. (Usage of simd intrinsics via libraries is not counted)

* -ffi in a file name stands for non-stdlib FFI usage

* (You may find time < time(user) + time(sys) for some non-parallelized programs, the overhead is from GC or JIT compiler, which are allowed to take advantage of multi-cores as that's more close to real-world scenarios.)

helloworld

Input: QwQ

lang code time stddev peak-mem mem time(user) time(sys) compiler compiler/runtime
kotlin 1.kt 2.2ms 0.1ms 3.1MB 0ms 0ms kotlin/native 2.1.20
codon 1-m.py 11ms 0.4ms 8.8MB 20ms 0ms codon 0.18.2
kotlin 1.kt 62ms 0.6ms 47.7MB 74ms 16ms kotlin/jvm 21

nbody

Input: 5000000

lang code time stddev peak-mem mem time(user) time(sys) compiler compiler/runtime
kotlin 1n.kt 349ms 0.4ms 3.5MB 340ms 0ms kotlin/native 2.1.20
kotlin 1.kt 446ms 2.7ms 49.3MB 490ms 20ms kotlin/jvm 21
codon 1.py 1352ms 60ms 9.1MB 1657ms 0ms codon 0.18.2

Input: 500000

lang code time stddev peak-mem mem time(user) time(sys) compiler compiler/runtime
kotlin 1n.kt 38ms 0.7ms 3.5MB 30ms 0ms kotlin/native 2.1.20
kotlin 1-m.kt 119ms 0.7ms 49.6MB 163ms 20ms kotlin/jvm 21
codon 1-m.py 175ms 4.2ms 8.8MB 487ms 0ms codon 0.18.2

nsieve

Input: 12

lang code time stddev peak-mem mem time(user) time(sys) compiler compiler/runtime
codon 1-m.py 444ms 8.1ms 67.3MB 743ms 7ms codon 0.18.2
codon 2.py 1520ms 13ms 100.8MB 1830ms 17ms codon 0.18.2

Input: 10

lang code time stddev peak-mem mem time(user) time(sys) compiler compiler/runtime
codon 1-m.py 128ms 1.7ms 18.5MB 437ms 0ms codon 0.18.2
codon 2-m.py 392ms 4.2ms 27.4MB 703ms 7ms codon 0.18.2