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I wanted to know if WebAssembly runtimes are getting faster. This is a follow-up to the earlier libsodium WebAssembly benchmarks from 2019, 2021 and 2023. Not “does the newest version beat native code in one microbenchmark?”, and not “which runtime has the prettiest benchmark chart?”, but something more boring and more useful: If I take the same C crypto code, compile it to WebAssembly, and run it on the latest runtime, a runtime from one year ago, and a runtime from two years ago, are things actually improving? So I benchmarked libsodium on WebAssembly runtimes released around June 2024, June 2025, and June 2026.
The short version: wasmer is the best performer, but WAVM, WAMR and Wasmtime are close. WAVM has the best optimizer, and is able to generate very fast code out from baseline, portable WebAssembly The new WebAssembly wide_arithmetic instructions are a big deal for crypto code when runtimes support them. What I measured The test program is libsodium’s benchmark suite, built from libsodium commit 8e3be8615ba6adcd7babaecf5e76f516890ba5fb.
I built one native baseline and several WebAssembly variants: native x86-64, compiled with Zig using the local CPU target plain WebAssembly WebAssembly with lime1 WebAssembly with lime1 and simd128 WebAssembly with lime1, simd128, and wide_arithmetic For the native reference, libsodium was built with -Dcpu=native. For wasm2c, the generated C was compiled with zig cc -O3 -march=native. For WAMR, I used AOT mode: wamrc compiled each .wasm file to an .aot file, and iwasm ran the resulting AOT file. wamrc doesn’t accept --cpu=native, so I used --target=x86_64 --cpu=x86-64-v4 --opt-level=3, which matches the host’s available x86-64 feature level and works across the WAMR versions that could compile these modules.
The native command was: zig build -Denable_benchmarks -Doptimize=ReleaseFast -Dcpu=native -Diterations=3 The WebAssembly commands were the same shape, with a wasm32-wasi target and the feature-specific CPU strings: zig build -Denable_benchmarks -Dtarget=wasm32-wasi -Doptimize=ReleaseFast -Diterations=3 zig build -Denable_benchmarks -Dtarget=wasm32-wasi -Doptimize=ReleaseFast -Dcpu=lime1 -Diterations=3 zig build -Denable_benchmarks -Dtarget=wasm32-wasi -Doptimize=ReleaseFast -Dcpu=lime1+simd128 -Diterations=3 zig build -Denable_benchmarks -Dtarget=wasm32-wasi -Doptimize=ReleaseFast -Dcpu=lime1+simd128+wide_arithmetic -Diterations=3 The host was an AMD Ryzen AI 9 HX 470 with 12 cores and 24 threads. CPU boost was disabled and the maximum CPU frequency was 2 GHz. The OS was Linux 7.1.0-rc7, and Zig was 0.17.0-dev.948+e949341b7.
The numbers below are the geometric mean of per-benchmark slowdowns relative to the native build. Lower is better. A value of 2.0 means “twice as slow as native” on this machine. I used ITERATIONS=3, so the very small libsodium tests are noisy and quantized. Rows reporting zero time were excluded from the aggregate. Versions For every runtime except WAVM, I used the latest stable release available on June 23, 2026, plus a stable release from roughly one year earlier and one from roughly two years earlier.
Runtime 2024 2025 2026 Bun 1.1.16 1.2.17 1.3.14 Node 22.3.0 24.2.0 26.3.1 WAMR 2.1.0 2.3.1 2.4.4 WABT wasm2c 1.0.35 1.0.37 1.0.41 WasmEdge 0.14.0 0.14.1 0.17.0 Wasmer 4.3.2 6.0.1 7.1.0 Wasmtime 22.0.0 34.0.0 46.0.0 WAVM n/a n/a nightly/2026-04-05 Wazero 1.7.3 1.9.0 1.12.0 WAVM is awkward to compare historically. The old available nightly collapsed to a 2022 binary for both the 2024 and 2025 slots, and that binary refused to run on this machine. I only kept the 2026 nightly. WAMR 2.1.0, the selected 2024 release, installed fine but its AOT compiler failed on these Zig-generated modules with invalid WASM stack data type. I kept the version in the matrix, but didn’t include an aggregate for it. Baseline WebAssembly This is the plain WebAssembly build, without lime1, SIMD, or wide arithmetic. There isn’t one universal trend. Wasmtime steadily improved: 2.67x native in 2024, 2.54x in 2025, 2.41x in 2026. It got faster every year, and the gains land in the tenths place, above the noise. Node also improved slowly, from 8.60x native to 7.95x native. Wazero was basically flat: 4.84x, 4.70x, 4.72x native.
No real movement over two years. WAMR in AOT mode was already fast in 2025 and stayed there in 2026: 1.59x native, then 1.57x native, the same within this benchmark’s noise.
I don’t have a complete 2024 WAMR number because WAMR 2.1.0 couldn’t compile these modules. Wasmer regressed in the 2025 release I tested, then recovered in 2026. The 2026 baseline barely beats 2024. wasm2c improved modestly in 2026.
It remains one of the best options if ahead-of-time translation to native C is acceptable for your deployment model. Bun is the outlier. Its 2024 and 2025 results were far behind, but the 2026 result is about three times faster than the 2025 result. It’s still slower than Node on this benchmark, but the direction is excellent. WasmEdge is fast too, but its command-line behavior changed enough to matter. My first 0.17.0 run accidentally used interpreter mode for compiled modules and looked catastrophically slow. Running the compiled modules with --run-mode=aot fixed it: the 2026 baseline was 1.74x native, between the 2024 and 2025 baseline results. Best supported build by year The baseline table is useful because it compares the same WebAssembly target everywhere. But if you’re choosing a runtime for your own deployment, you probably care about the fastest build that runtime can actually run.
So for each runtime and year, I also selected the best complete result among the supported builds: baseline, lime1, lime1+simd128, and lime1+simd128+wide_arithmetic. Looks similar to the previous graph, except for Wasmtime and Wasmer that really benefit from wide_arithmetic. Ranked by the best supported build, the complete current-year results are: CPU feature variants The WebAssembly feature story is more interesting than the year-to-year runtime story. For the 2026 releases, these were the aggregate slowdowns: lime1 and simd128 alone aren’t magic here.
Sometimes they help, sometimes they hurt, and sometimes the difference is lost in benchmark noise. wide_arithmetic is different. Only Wasmtime and Wasmer could run the full wide_arithmetic build among the complete stable rows I tested. WAMR rejected it with unsupported opcode 0xfc13.
But when wide_arithmetic worked, it was the biggest speedup in the whole experiment: Wasmtime 46.0.0: 2.41x native without it, 1.46x native with it. Wasmer 7.1.0: 2.08x native without it, 1.33x native with it.