Codon VS Nim benchmarks

Current benchmark data was generated on Tue Mar 25 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
nim 1.nim 1.1ms 0.0ms 1.4MB 0ms 0ms nim 2.2.2
nim 1.nim 1.2ms 0.1ms 1.8MB 0ms 0ms nim/clang 2.2.2
codon 1-m.py 11ms 0.7ms 8.6MB 20ms 0ms codon 0.18.2

nbody

Input: 5000000

lang code time stddev peak-mem mem time(user) time(sys) compiler compiler/runtime
nim 2.nim 320ms 3.2ms 1.8MB 310ms 0ms nim 2.2.2
nim 2.nim 347ms 6.4ms 2.0MB 337ms 0ms nim/clang 2.2.2
codon 1.py 1322ms 1.2ms 8.8MB 1630ms 0ms codon 0.18.2

Input: 500000

lang code time stddev peak-mem mem time(user) time(sys) compiler compiler/runtime
nim 2.nim 35ms 1.0ms 1.8MB 30ms 0ms nim 2.2.2
nim 2.nim 37ms 1.3ms 2.0MB 30ms 0ms nim/clang 2.2.2
codon 1-m.py 176ms 3.4ms 9.0MB 487ms 0ms codon 0.18.2

nsieve

Input: 12

lang code time stddev peak-mem mem time(user) time(sys) compiler compiler/runtime
nim 1.nim 320ms 5.6ms 41.8MB 307ms 0ms nim/clang 2.2.2
nim 1.nim 330ms 8.4ms 41.5MB 317ms 0ms nim 2.2.2
codon 1-m.py 461ms 8.3ms 47.7MB 763ms 0ms codon 0.18.2
codon 2.py 1572ms 19ms 100.8MB 1877ms 27ms codon 0.18.2

Input: 10

lang code time stddev peak-mem mem time(user) time(sys) compiler compiler/runtime
nim 1.nim 56ms 4.0ms 11.5MB 47ms 0ms nim 2.2.2
nim 1.nim 59ms 4.5ms 11.8MB 50ms 0ms nim/clang 2.2.2
codon 1-m.py 125ms 0.2ms 18.6MB 430ms 0ms codon 0.18.2
codon 2-m.py 397ms 1.3ms 27.1MB 707ms 3ms codon 0.18.2