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A transformer is also known as a transpiler, similar to Babel transform.

The purpose of this benchmark is for people who wants to evaluate and compare the performance characteristics of the two transformer.

The benchmark measures the whole parse -> transform -> codegen pipeline as a real-word scenario.

The numbers indicate that Oxc is at least 3 times faster than Swc.

Codspeed measures performance by cpu instructions.

Run the following command on your machine for replication.

cargo bench

Generate the table

pnpm ipnpm run table

./memory.sh./files/cal.com.tsxoxc 26.3 mbswc 30.9 mb./files/typescript.jsoxc 137.8 mbswc 148.5 mb

• Usesmimalloc as the global allocator
• Uses the following release profile

[profile.release]opt-level     =3lto           ="fat"codegen-units =1strip         ="symbols"debug         =falsepanic         ="abort"

This is the standard benchmark run in a single thread.

group.bench_with_input(id,&source, |b, source|{    b.iter(||Self::run(source))});

This uses theiter_with_large_drop function, which does not take AST drop time into account.

AST drop time can become a bottleneck in applications such as as bundler,where there are a few thousands of files need to be parsed.

group.bench_with_input(id,&source, |b, source|{    b.iter_with_large_drop(||Self::run(source))});

This benchmark uses the total number of physical cores as the total number of files to parse per bench iteration. For example it parses 6 files in parallel on my Mac i7 6 cores.

This can indicate the existence of resource contention.

let cpus = num_cpus::get_physical();group.bench_with_input(id,&source, |b, source|{    b.iter(||{(0..cpus).into_par_iter().for_each(|_|{Self::run(source);});})});