Compression level 1

Benchmark index · Median overview · ← Level -1 · Level 2 →

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.

Median speed and output relative to C at level 1

Implementation	Median speed / C ↑	Median output / C ↓	Datasets
zstd C	1.000×	1.000×	8
mzstd	1.380×	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 · tiny-text · repeated-1m · binary-64k · random-64k · text-1m · random-1m · alice29

empty

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

mzstd speed / C: 11.256×; output: 9 / 9 bytes.

Level 1: empty speed and compressed size

Exact measurements and confidence bounds

Implementation	Mean, ns	95% mean interval, ns	MiB/s	Output bytes	Output / input	Speed / C
zstd C	2,216	2,169–2,271	—	9	—	1.000×
mzstd	196.9	191.8–202.7	—	9	—	11.256×

tiny-text

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

mzstd speed / C: 7.708×; output: 53 / 53 bytes.

Level 1: tiny-text speed and compressed size

Exact measurements and confidence bounds

Implementation	Mean, µs	95% mean interval, µs	MiB/s	Output bytes	Output / input	Speed / C
zstd C	2.41	2.366–2.465	17.41	53	120.455%	1.000×
mzstd	0.3127	0.2992–0.3274	134.20	53	120.455%	7.708×

repeated-1m

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

mzstd speed / C: 2.871×; output: 51 / 51 bytes.

Level 1: repeated-1m speed and compressed size

Exact measurements and confidence bounds

Implementation	Mean, µs	95% mean interval, µs	MiB/s	Output bytes	Output / input	Speed / C
zstd C	83.3	79.45–87.75	12,004.13	51	0.005%	1.000×
mzstd	29.02	28.67–29.43	34,461.55	51	0.005%	2.871×

binary-64k

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

mzstd speed / C: 1.501×; output: 2,537 / 2,537 bytes.

Level 1: binary-64k speed and compressed size

Exact measurements and confidence bounds

Implementation	Mean, µs	95% mean interval, µs	MiB/s	Output bytes	Output / input	Speed / C
zstd C	10.72	10.61–10.86	5,829.12	2,537	3.871%	1.000×
mzstd	7.143	6.886–7.438	8,750.08	2,537	3.871%	1.501×

random-64k

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

mzstd speed / C: 1.259×; output: 65,546 / 65,546 bytes.

Level 1: random-64k speed and compressed size

Exact measurements and confidence bounds

Implementation	Mean, µs	95% mean interval, µs	MiB/s	Output bytes	Output / input	Speed / C
zstd C	8.784	8.64–8.964	7,115.37	65,546	100.015%	1.000×
mzstd	6.979	6.796–7.18	8,955.37	65,546	100.015%	1.259×

text-1m

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

mzstd speed / C: 1.153×; output: 61,206 / 61,206 bytes.

Level 1: text-1m speed and compressed size

Exact measurements and confidence bounds

Implementation	Mean, µs	95% mean interval, µs	MiB/s	Output bytes	Output / input	Speed / C
zstd C	465.5	456.7–474.6	2,148.34	61,206	5.837%	1.000×
mzstd	403.6	390.3–417.6	2,477.63	61,206	5.837%	1.153×

random-1m

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

mzstd speed / C: 1.094×; output: 1,048,610 / 1,048,610 bytes.

Level 1: random-1m speed and compressed size

Exact measurements and confidence bounds

Implementation	Mean, µs	95% mean interval, µs	MiB/s	Output bytes	Output / input	Speed / C
zstd C	85.17	84.34–86.05	11,741.62	1,048,610	100.003%	1.000×
mzstd	77.86	77.01–78.81	12,843.85	1,048,610	100.003%	1.094×

alice29

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

mzstd speed / C: 0.993×; output: 59,657 / 59,657 bytes.

Level 1: alice29 speed and compressed size

Exact measurements and confidence bounds

Implementation	Mean, µs	95% mean interval, µs	MiB/s	Output bytes	Output / input	Speed / C
zstd C	366.9	360.8–375.2	395.31	59,657	39.225%	1.000×
mzstd	369.4	360.6–380.4	392.62	59,657	39.225%	0.993×

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