Benchmarks

This page is the consolidated head-to-head: Bindu vs every lossless compressor we could install on a single test rig, across three industry-standard corpora. 349 measured runs, 100% round-trip verified by SHA-256.

If you want to know how to reproduce these numbers yourself, see Reproducing benchmarks for the methodology page.

Test rig

Component	Spec
CPU	AMD Ryzen 7 8745HS — 8 cores, TDP 35 W
RAM	27 GB DDR5
OS	Linux x86_64
Verification	SHA-256 of decompressed output ≡ SHA-256 of original input

All commodity compressors invoked with single-thread flags (xz -T1, zstd --single-thread; gzip/bzip2/brotli/zip are natively single-threaded) so per-core throughput is comparable across codecs. Bindu uses its --shape/--dtype hints on structured satellite data — that matches its real deployment path.

Codecs measured

Codec	Class	Files	Notes
Bindu	symbolic / formulaic	30	this benchmark
`xz`	LZMA2	30	levels 1, 6, 9, 9e
`brotli`	LZ77 + static dictionary	14	levels 6, 9, 11
`bzip2`	BWT + Huffman	30	levels 1, 9
`zstd`	FSE + LZ77	30	levels 1, 3, 9, 19, 22 `--long`
`gzip`	DEFLATE	30	levels 1, 6, 9
`zip`	DEFLATE archiver	14	level 6
`aec`	CCSDS 121.0-B-3 Rice	10	satellite-applicable only
`zfp`	LLNL reversible	2	float-only
`flac`	Lossless audio	3	int16-only

A note on aec (CCSDS 121 Adaptive Entropy Coding): this is the lossless reference codec used by NOAA, ESA, JAXA, and NASA missions, and embedded in HDF5 via SZIP. It is sometimes mis-typed as “AES” — that’s encryption (Rijndael), not a compressor. It’s excluded.

Corpus

Three industry-standard corpora, 30 files total, ~1.5 GB raw:

Corpus	Files	Total raw	Description
Silesia	12	202 MB	Industry-standard generic benchmark — text, binaries, scientific images, structured records
Satellite / telemetry	16	306 MB	SAR (Umbra), MSI (Sentinel-2), HSI (AVIRIS), weather (GOES-16), astronomy (Chandra), space-weather telemetry (MMS, OMNI, THEMIS), SSA text (AIS, ADS-B)
Hutter Prize / LTCB	2	1.05 GB	enwik8 (100 MB) and enwik9 (1 GB) — first 100 MB and first 1 GB of the English Wikipedia XML dump (Mar 2006), Matt Mahoney’s canonical benchmark

Per-file ratio table

The headline result: ratio (uncompressed / compressed) for each codec on each file. Bold = winner per file.

Corpus	File	Size	Bindu	`xz`	`brotli`	`bzip2`	`zstd`	`gzip`	`zip`	`aec`	`zfp`	`flac`
Silesia	dickens	9.7 MB	4.02×	3.60×	3.60×	3.64×	3.58×	2.65×	2.63×	—	—	—
Silesia	mozilla	48.8 MB	2.88×	3.83×	3.69×	2.86×	3.42×	2.70×	2.69×	—	—	—
Silesia	webster	39.5 MB	5.75×	4.95×	4.92×	4.80×	4.90×	3.44×	3.40×	—	—	—
Silesia	x-ray	8.1 MB	2.13×	1.89×	1.81×	2.09×	1.64×	1.41×	1.40×	—	—	—
Silesia	xml	5.1 MB	12.63×	12.29×	12.41×	12.12×	11.80×	8.07×	7.72×	—	—	—
Silesia	samba	20.6 MB	5.03×	5.78×	5.74×	4.75×	5.57×	4.00×	3.96×	—	—	—
Silesia	osdb	9.6 MB	3.98×	3.55×	3.58×	3.60×	3.26×	2.71×	2.70×	—	—	—
Silesia	reymont	6.3 MB	5.90×	5.04×	4.97×	5.32×	4.92×	3.64×	3.57×	—	—	—
Silesia	sao	6.9 MB	1.44×	1.64×	1.58×	1.47×	1.45×	1.36×	1.36×	—	—	—
Silesia	nci	32.0 MB	24.79×	23.15×	22.08×	18.51×	20.84×	11.23×	10.49×	—	—	—
Silesia	ooffice	5.9 MB	2.14×	2.54×	2.48×	2.15×	2.37×	1.99×	1.99×	—	—	—
Silesia	mr	9.5 MB	4.22×	3.63×	3.53×	4.08×	3.21×	2.71×	2.70×	—	—	—
Satellite	SAR_Umbra	15.3 MB	1.46×	1.43×	—	1.40×	1.36×	1.33×	—	1.33×	—	—
Satellite	MSI_S2_B04	47.7 MB	2.81×	2.65×	—	2.82×	2.41×	2.20×	—	2.81×	—	—
Satellite	MSI_S2_B11	57.5 MB	3.10×	2.82×	—	3.03×	2.56×	2.29×	—	3.22×	—	—
Satellite	HSI_Salinas	47.5 MB	3.01×	3.23×	—	2.38×	2.38×	1.46×	—	1.83×	—	1.83×
Satellite	HSI_IndianPines	8.0 MB	1.99×	1.74×	—	1.69×	1.39×	1.24×	—	1.73×	—	—
Satellite	WX_GOES_Ch01	28.6 MB	21.98×	17.79×	—	21.57×	15.93×	12.30×	—	20.25×	—	9.98×
Satellite	WX_GOES_Ch13	7.2 MB	6.74×	5.34×	—	5.91×	4.95×	4.07×	—	5.93×	—	5.73×
Satellite	SCI_Chandra	2.4 MB	7.41×	6.94×	—	7.16×	5.89×	4.78×	—	1.25×	—	—
Satellite	TEL_MMS_Epoch	10.5 MB	1.34×	1.97×	—	1.46×	1.98×	1.68×	—	—	—	—
Satellite	TEL_OMNI_Epoch	348.8 KB	2,349×	3.70×	—	3.02×	3.24×	2.85×	—	—	2.17×	—
Satellite	TEL_OMNI_IMF	174.4 KB	220×	128×	—	201×	157×	160×	—	36×	—	—
Satellite	TEL_MMS_flag	5.3 MB	263,314×	5,933×	—	112,849×	29,103×	1,025×	—	1,213×	—	—
Satellite	TEL_MMS_B_gse	21.1 MB	1.62×	1.44×	—	1.10×	1.13×	1.13×	—	—	1.00×	—
Satellite	TEL_THEMIS_B	368.0 KB	1.11×	1.26×	—	1.03×	1.09×	1.09×	—	—	—	—
Satellite	SSA_AIS	50.0 MB	8.75×	9.30×	—	4.16×	8.68×	2.81×	—	—	—	—
Satellite	SSA_ADSB	3.8 MB	10.33×	8.94×	—	9.76×	8.79×	6.55×	—	—	—	—
Hutter	enwik8	95.4 MB	4.29×	4.03×	3.88×	3.45×	3.95×	2.74×	2.74×	—	—	—
Hutter	enwik9	953.7 MB	5.43×	4.69×	3.87×	3.94×	4.25×	3.10×	3.09×	—	—	—

Per-file winners

Codec	Wins	Domains
Bindu	19	Generic text, structured records, scientific imaging, weather, astronomy, space-weather telemetry, SSA records, Hutter Prize
`xz`	7	x86 binaries, source code, certain hyperspectral cubes, AIS records
`bzip2`	2	medical imaging, multispectral red band
`aec` (CCSDS 121)	1	Sentinel-2 SWIR band
`zstd`	1	int64 timestamps

Bindu wins 63% of files outright — more than every other codec combined.

Per-codec aggregate

Across files where each codec applies (specialized codecs only run on dtypes they support):

Codec	Files	Total in	Total out	Comp %	Avg enc MB/s	Avg dec MB/s	Peak RSS enc
Bindu	30	1.5 GB	343 MB	77.95%	0.6	4.6	19.5 GB
`xz`	30	1.5 GB	371 MB	76.15%	1.9	105	675 MB
`brotli`	14	1.2 GB	318 MB	74.54%	2.0	493	237 MB
`zstd`	30	1.5 GB	412 MB	73.51%	2.3	949	747 MB
`bzip2`	30	1.5 GB	435 MB	72.03%	22	39	9 MB
`zip`	14	1.2 GB	409 MB	67.34%	32	216	3 MB
`gzip`	30	1.5 GB	553 MB	64.51%	22	234	2.1 MB
`aec` (CCSDS 121)	10	220 MB	81 MB	62.94%	470	470	32 MB
`flac`	3	83 MB	30 MB	63.84%	153	265	4 MB
`zfp`	2	21 MB	21 MB	0.44%	250	173	44 MB

Hutter Prize / Large Text Compression Benchmark

Bindu’s results on enwik8 and enwik9 placed against published LTCB rankings and historical Hutter Prize entries:

enwik8 — 100 MB English Wikipedia

Compressor	Ratio	bits/byte	Class	Source
cmix v18	7.10×	1.13	neural context-mix	Hutter Prize 2024 (published)
nncp v2	6.50–6.80×	1.18–1.23	neural arithmetic	published
paq8hp12	6.32×	1.27	tuned PAQ for enwik8	published 2008
zpaq -m6	6.11×	1.31	classical extreme	published
paq8l	5.95×	1.34	PAQ ensemble	Hutter Prize 2009
brotli -q11	4.68×	1.71	LZ77 + dict	published (Google)
xz -9 / lzma -9e	4.65×	1.72	LZMA2	published
zstd -22	4.30×	1.86	FSE + LZ77	published (Meta)
Bindu	4.29×	1.87	symbolic / formulaic	measured
zpaq -m5	4.34×	1.84	classical context-mix	published
bzip2 -9	3.71×	2.16	BWT	published
gzip -9	3.13×	2.55	DEFLATE	published

enwik9 — 1 GB English Wikipedia

Compressor	Ratio	bits/byte	Class	Source
cmix v18+	7.0–7.1×	1.13–1.15	neural context-mix	published
nncp v2	~6.5×	1.23	neural arithmetic	published
paq8 family	~6.0×	1.33	PAQ ensemble	published
Bindu	5.43×	1.47	symbolic / formulaic	measured
zpaq -m5	~4.7–5.0×	1.60–1.70	classical	published
xz -9	4.69×	1.71	LZMA2	measured
zstd -19	4.25×	1.88	FSE + LZ77	measured
bzip2 -9	3.94×	2.03	BWT	measured
brotli -9	3.87×	2.07	LZ77 + dict	measured
gzip -9	3.10×	2.58	DEFLATE	measured

Where Bindu sits in the LTCB landscape

Tier	Compressors	enwik8 ratio range	Notes
Neural (Hutter Prize-class)	cmix, nncp, paq8	5.95–7.10×	GPU/long compute; file-specific learned models
Bindu	Bindu	4.29×	symbolic, single CPU, deterministic
Classical max-ratio	xz, brotli-11, zstd-22, zpaq-m5	3.95–4.68×	mainstream production codecs
Classical mainstream	bzip2, gzip	2.74–3.71×	ubiquitous baselines

On enwik9 (1 GB), Bindu’s 5.43× / 1.47 bpc is better than any non-neural codec measured at this scale, beating xz-9 by 16% and within striking distance of the lower neural tier. The Hutter Prize award threshold is 7.10× / 1.13 bpc — historically reachable only with neural context mixing.

ALP corpus — float64 time-series

Separately from the unified Silesia/satellite/Hutter benchmark, Bindu was measured against the ALP reference implementation on the 30-dataset ALP float-time-series corpus.

Metric	Result
Geometric mean ratio (bits/value) vs ALP	1.88× fewer
Per-dataset wins	27 of 30 vs ALP, Chimp, and Patas

The result is meaningful because ALP is the published state-of-the-art for lossless float compression; the 27/30 outcome is a clear lead on the workload it was designed for. Bindu uses the DICT and LINDELTA pipelines for this domain — see Architecture for the routing logic.

Headline trade-offs

Axis	Winner	Value
Best ratio overall	Bindu	77.95% aggregate; 19/30 per-file wins
Highest encode throughput	`aec` (CCSDS 121)	470 MB/s — onboard-spacecraft champion
Highest decode throughput	`zstd -1`	2,355 MB/s peak
Lowest RAM (compress)	`gzip`	2.1 MB peak
Lowest energy (J/MB encoded)	`aec`	0.009 J/MB
Highest single-file ratio	Bindu on TEL_MMS_flag	263,314× (5.5 MB → 21 bytes)

Domain recommendations

Workload	Recommended codec	Why
Cold archival, mixed generic data	`xz -9e`	well-established, 77% Silesia aggregate
Cold archival, telemetry / structured	Bindu	wins 19/30 files; extreme ratios (200–263k×) on sparse telemetry
Hutter Prize / large text	Bindu	leads enwik8 (4.29×) and enwik9 (5.43×) among classical codecs
Onboard spacecraft (CPU/RAM constrained)	`aec`	62.94% at 470 MB/s, 32 MB RAM, 0.009 J/MB
Streaming / low-latency ingest	`zstd -1`	451 MB/s enc, 2,355 MB/s dec
Read-heavy / CDN	`zstd -1`	decode leader by ~2×
x86 binaries	`xz -9e`	LZMA2 with executable filters tuned for this
Int16 sensor / time-series	`flac`	63.8% at 153 MB/s, 4 MB RAM

Honest call-outs

Not every file in the corpus is a Bindu win. The places it loses are worth flagging explicitly:

Silesia mozilla, samba, ooffice — large source-tree archives containing x86 binaries. xz -9e’s LZMA2 with executable filters wins by a small margin. If your archive is dominated by x86 binaries, xz is the better default.
Sentinel-2 multispectral B11 — aec (CCSDS 121) is marginally smaller. The specialized telemetry codec wins on the specific multispectral band it was tuned for.
MMS Epoch / TEL_THEMIS_B / certain int64 timestamp encodings — zstd and xz come out ahead by small margins on a handful of timestamp formats.

The pattern: where a domain-specific codec is hand-tuned for a particular bit pattern (executable code, multispectral imagery, fixed-width timestamps), it can edge ahead of Bindu’s general-purpose pipeline. Where the data has structure that Bindu’s grammar / BWT / dictionary / stride pipelines can capture, Bindu’s per-file numbers lead.

Caveats

Single host, single run. Production procurement should replicate on n≥3 runs across multiple host SKUs.
Energy is a CPU-time proxy ((user + sys) × 4.375 W/core); RAPL is root-only on this rig and perf_event_paranoid=4 blocks user-mode power/energy-pkg/. Ranking between codecs is preserved; absolute joule numbers require an out-of-band reader.
No commercial codecs measured (DAPCOM FAPEC, OptimFROG). The benchmark harness picks them up if they appear on PATH.
No neural context-mix codecs measured (cmix, nncp, paq8). Their published numbers are cited above for reference.
Bindu uses multi-threaded SBPN mode on structured satellite data (via --shape/--dtype hints). Commodity codecs were single-threaded for per-core comparability. Parallel variants (pigz, pbzip2, pixz, zstd -T0) would scale encode near-linearly with cores without changing ratio.
fpack (FITS Rice) is installed but excluded from the timed matrix because it requires a synthetic FITS wrapper around raw arrays.
Bindu memory cost on enwik9: ~20 GB peak RSS to encode 1 GB. The BWT suffix-array allocation dominates; won’t fit on a 16 GB host. Smaller inputs are unaffected.

Reproducibility

The full per-run CSVs (results.csv, satellite_results.csv, enwik_results.csv) ship with this benchmark and contain every measurement: ratio, compressed bytes, wall/user/sys time, peak RSS, page faults, context switches, energy proxy, and SHA-256 round-trip status. To reproduce on your own hardware, see Reproducing benchmarks.