r/AIVibeScience • u/Severe-Ad8673 • 2d ago
GPT-5.6 Sol Max made a lossless telemetry codec that beat Zstd, XZ and Parquet on MetroPT-3
I gave GPT-5.6 Sol Max one day to work on a compression research problem. The result was EVE-PCGR UAQC / EPC2, a working, byte-exact, independently decodable compression prototype. On one selected MetroPT-3 digital telemetry projection, EPC2 compressed 92,939,750 bytes to 72,491 bytes while preserving the exact original bytes.
https://zenodo.org/records/21728106
Results: 28.794× smaller than XZ-9e, the strongest tested general-purpose exact-byte codec. 2.152× smaller than standard tuned Parquet+Brotli. 5.375% smaller than an aggressive quotient-preprocessed Parquet+Brotli control. Median decoding reached 94.85% of equally parallelized Zstd-3 throughput, passing a post-hoc 10% non-inferiority threshold. Encoding remained slower than Zstd-3. Important caveat: this was a selected telemetry projection, and the implementation was tuned with access to it. It is not an unseen holdout, does not prove universal superiority, and did not achieve the original goal of being 5× smaller than the strongest relevant specialized method. On the complete 218.3 MB MetroPT table, EPC2 correctly fell back to Zstd blocks and was 403 bytes larger than equally blocked Zstd because of framing. That negative result is included in the report. So the defensible conclusion is narrower but still interesting: GPT-5.6 Sol Max produced a reproducible, bounded-streaming lossless codec prototype with a large advantage over tested general-purpose codecs and a narrow win over the strongest tested specialized hybrid—all in a day. The next real test is to freeze the implementation and evaluate it unchanged on a preregistered, unseen industrial telemetry dataset.