Benchmarks

Processing time varies with the CPU, thread count, image characteristics, resolution, and codec implementation. We do not claim that zenpix is generally faster than Sharp or always produces higher quality.

Status of the numbers

The following summary comes from measurements made on 2026-05-25 with zenpix 1.0.0. Some input images cannot be redistributed, so these numbers are historical observations rather than evidence that a third party can reproduce immediately after cloning the repository.

• PNG decode → resize → AVIF encode
• quality=60, speed=6
• two warm-ups, ten measured runs, wall-clock median
• ratio = Sharp median ÷ zenpix median
• ratio > 1 means zenpix was faster in that measurement; ratio < 1 means Sharp was faster

Results change with the workload

Environment and image	Observed tendency
Ubuntu VPS, 2 vCPU, selected character and impasto illustrations	zenpix produced ratios from 1.29 to 1.63
The same VPS, tiled images and high-resolution bright images	Sharp was faster
Apple M4 Pro, zenpix single-threaded	Sharp was faster in every measured cell
Apple M4 Pro, zenpix threads=14	zenpix led on selected FHD images; Sharp led on most WQHD / 4K cases

Because the fixtures are not redistributable, these observations are not generalized into a claim that zenpix is faster than Sharp. The benchmark code is available under bench/ for measurements with images you are allowed to use.

Quality settings

The zenpix AVIF implementation requests YUV 4:4:4 from libavif and sets its alpha-quality option to lossless; actual output also depends on codec implementation and version. The same numeric quality value does not mean equal visual quality across different encoders, and output sizes differ. The current comparison script does not calculate SSIM or PSNR, so sample images are visual references only.

Try AVIF encoding in the browser

This demo uses zenpix-wasm to encode raw RGB / RGBA pixels to AVIF in the browser. It does not contain native zenpix decoding, resizing, or the CLI.

Drop or click to select

JPEG / PNG / WebP · max 2MP

Quality 60

Speed

Standard (speed=6) Fast (speed=10)

Convert

In-browser only. No data is sent to a server.

Run locally

Place fixtures that you have permission to use under test/fixtures/, then run:

npm run build
npm run bench
BENCH_FIXTURES=bench_input npm run bench
AVIF_THREADS=4 npm run bench:threads
bun bench/quality-compare.ts

Published results should include the OS, CPU, memory, dependency versions, thread count, and whether the fixtures can be redistributed.