File size: 3,623 Bytes
0081600 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 | # Benchmark Results
The release package includes two JSON outputs:
- `benchmark_results_v4_full.json`
- `benchmark_results_v4_quick.json`
The full local release run used deterministic generated corpora and compared:
- HVCE v4 fast
- HVCE v4 balanced
- HVCE v4 balanced + 10% recovery
- ZIP/Deflate level 9
- TAR+gzip level 9
- TAR+xz level 9
- TAR+zstd level 19 when the `zstd` CLI is installed
## Full run snapshot
```text
small_office raw=212,158 bytes
TAR-xz9 10,596 ratio=0.049944
TAR-zstd19 11,795 ratio=0.055595
HVCE-v4-fast 11,961 ratio=0.056378
HVCE-v4-balanced 11,969 ratio=0.056416
HVCE-v4-balanced+recovery10 20,722 ratio=0.097672
TAR-gzip9 23,529 ratio=0.110903
ZIP-deflate9 155,545 ratio=0.733156
```
HVCE does not beat xz on this particular tiny synthetic office corpus, but it is in the same range as zstd and massively beats ordinary ZIP/Deflate. The key v4 improvement is closing the earlier small-folder gap relative to ZIP-style archivers.
```text
photonic_generators raw=531,072 bytes
HVCE-v4-balanced 132,243 ratio=0.249011
TAR-xz9 141,544 ratio=0.266525
HVCE-v4-balanced+recovery10 146,799 ratio=0.276420
TAR-zstd19 235,182 ratio=0.442844
ZIP-deflate9 362,163 ratio=0.681947
TAR-gzip9 363,154 ratio=0.683813
```
This is the intended nanophotonic/generative win: separable fields and polynomial streams are represented by compact exact recipes rather than generic byte statistics.
```text
versioned_media raw=4,194,304 bytes
TAR-zstd19 1,049,535 ratio=0.250229
HVCE-v4-fast 1,049,957 ratio=0.250329
HVCE-v4-balanced 1,049,961 ratio=0.250330
TAR-xz9 1,050,784 ratio=0.250526
ZIP-deflate9 4,196,038 ratio=1.000413
```
The versioned-media result shows the near-duplicate archive-state branch. Locally high-entropy streams become compressible when multiple versions are archived together.
```text
already_compressed raw=918,000 bytes
TAR-zstd19 918,865 ratio=1.000942
ZIP-deflate9 918,948 ratio=1.001033
HVCE-v4-fast 919,110 ratio=1.001209
HVCE-v4-balanced 919,113 ratio=1.001212
TAR-gzip9 920,056 ratio=1.002240
TAR-xz9 924,224 ratio=1.006780
```
The correct result is near-raw size. HVCE does not waste extreme CPU trying to compress entropy-saturated containers.
```text
random_control raw=1,572,864 bytes
TAR-zstd19 1,573,526 ratio=1.000421
HVCE-v4-fast 1,573,609 ratio=1.000474
HVCE-v4-balanced 1,573,613 ratio=1.000476
ZIP-deflate9 1,573,666 ratio=1.000510
TAR-gzip9 1,574,225 ratio=1.000865
TAR-xz9 1,576,664 ratio=1.002416
```
Random data cannot be universally compressed losslessly. HVCE stays near raw size and beats ZIP/gzip/xz by small header-level margins in this run, while zstd remains slightly smaller.
## Reproduce
```bash
python benchmark_hvce.py --out-dir benchmarks/local_run
```
## Honest conclusion
HVCE v4 has strong, reproducible wins over ZIP/Deflate and meaningful structured-data wins over xz/zstd on generated corpora that match its exact recipes. It is not yet faster than native C compressors. Speed dominance requires the planned Rust/C kernel.
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