Keyboard shortcuts

Press ← or → to navigate between chapters

Press S or / to search in the book

Press ? to show this help

Press Esc to hide this help

Compression level 14

Benchmark index · Median overview · ← Level 13 · Level 15 →

Recorded run: long-20261109 (2026-11-09). Raw results · Environment · Run analysis.

Median across all datasets

Each of the 8 datasets has equal weight, including empty and tiny input. Speed / C = C mean latency / implementation mean latency; output / C = implementation bytes / C bytes. We take the median of these 8 per-dataset ratios separately for speed and size. 1× matches C; higher speed and lower output are better. These are medians across datasets, not median sample latencies, and do not imply statistical significance.

ImplementationMedian speed / C ↑Median output / C ↓Datasets
zstd C1.000×1.000×8
mzstd1.111×1.000×8
Measurement setup and interpretation

zstd 1.5.7 (the C library built by zstd-ffi) and mzstd at the recorded working tree compress identical bytes at this level. Every frame was checked byte-identical to zstd’s and decoded back to its input before any timing.

These are cold native API measurements: construction, allocation, compression, and disposal. Complete known input; 50 samples, 3 s warmup, at least 6 s measurement. Host: AMD Ryzen 9 7950X, Linux KVM guest with two vCPUs: the encoder suite, then the decoder suite, each in one Criterion process pinned to vCPU 1; nothing else ran in the guest. Other tenants loaded the host: a fixed C decode varied by 8-43% (p10-p90 wall time) through the day, so sampling was lengthened to average over the noise. unset; Cargo release defaults (bench profile), runtime SIMD dispatch (AVX-512 level on this host; the decoder runs its block loops at the AVX2 level).

Chart whiskers and table intervals describe 95% confidence bounds on mean timing. They do not capture all host or allocator variation. Throughput bounds are transformed latency bounds. Output / input is compressed bytes divided by input bytes; smaller is better, and values above 100% mean expansion. For empty input, throughput and output / input are undefined (—). See the run analysis for measurement limitations.

Dataset details

Ordered by mzstd speed / C, highest first; all 8 datasets are shown. This order uses recorded mean latency, not statistical significance. Bars start at zero.

empty · repeated-1m · tiny-text · binary-64k · text-1m · alice29 · random-1m · random-64k

empty

Empty input; measures API overhead. Input: 0 bytes.

mzstd speed / C: 6.560×; output: 9 / 9 bytes.

Exact measurements and confidence bounds
ImplementationMean, ns95% mean interval, nsMiB/sOutput bytesOutput / inputSpeed / C
zstd C2,2862,230–2,349—9—1.000×
mzstd348.5335.7–363.2—9—6.560×

repeated-1m

1 MiB of repeated a bytes. Input: 1,048,576 bytes.

mzstd speed / C: 3.326×; output: 50 / 50 bytes.

Exact measurements and confidence bounds
ImplementationMean, µs95% mean interval, µsMiB/sOutput bytesOutput / inputSpeed / C
zstd C1,5331,454–1,618652.35500.005%1.000×
mzstd460.9452.5–469.42,169.62500.005%3.326×

tiny-text

44-byte quick-brown-fox sentence. Input: 44 bytes.

mzstd speed / C: 1.513×; output: 53 / 53 bytes.

Exact measurements and confidence bounds
ImplementationMean, µs95% mean interval, µsMiB/sOutput bytesOutput / inputSpeed / C
zstd C6.626.519–6.746.3453120.455%1.000×
mzstd4.3754.215–4.5519.5953120.455%1.513×

binary-64k

64 KiB of structured binary bytes: ((i / 16) XOR i) modulo 256. Input: 65,536 bytes.

mzstd speed / C: 1.200×; output: 1,259 / 1,259 bytes.

Exact measurements and confidence bounds
ImplementationMean, µs95% mean interval, µsMiB/sOutput bytesOutput / inputSpeed / C
zstd C121.9118.1–126.3512.851,2591.921%1.000×
mzstd101.598.42–105.5615.551,2591.921%1.200×

text-1m

Alice text repeated cyclically to 1 MiB. Input: 1,048,576 bytes.

mzstd speed / C: 1.023×; output: 51,818 / 51,818 bytes.

Exact measurements and confidence bounds
ImplementationMean, µs95% mean interval, µsMiB/sOutput bytesOutput / inputSpeed / C
zstd C7,5147,284–7,749133.0951,8184.942%1.000×
mzstd7,3477,163–7,532136.1251,8184.942%1.023×

alice29

Alice in Wonderland text from the Canterbury corpus (testdata/alice29.txt). Input: 152,089 bytes.

mzstd speed / C: 1.007×; output: 49,635 / 49,635 bytes.

Exact measurements and confidence bounds
ImplementationMean, µs95% mean interval, µsMiB/sOutput bytesOutput / inputSpeed / C
zstd C1.275e+041.243e+04–1.309e+0411.3849,63532.635%1.000×
mzstd1.267e+041.241e+04–1.293e+0411.4549,63532.635%1.007×

random-1m

1 MiB of deterministic xorshift64 pseudorandom bytes. Input: 1,048,576 bytes.

mzstd speed / C: 0.953×; output: 1,048,609 / 1,048,609 bytes.

Exact measurements and confidence bounds
ImplementationMean, µs95% mean interval, µsMiB/sOutput bytesOutput / inputSpeed / C
zstd C2,9572,823–3,117338.231,048,609100.003%1.000×
mzstd3,1032,961–3,246322.231,048,609100.003%0.953×

random-64k

64 KiB prefix of the deterministic pseudorandom corpus. Input: 65,536 bytes.

mzstd speed / C: 0.915×; output: 65,546 / 65,546 bytes.

Exact measurements and confidence bounds
ImplementationMean, µs95% mean interval, µsMiB/sOutput bytesOutput / inputSpeed / C
zstd C1,2341,193–1,27850.6665,546100.015%1.000×
mzstd1,3491,298–1,40046.3365,546100.015%0.915×