PCST: A Systematic Study of Extreme Low-Bit LLaMA-7B Compression Without Retraining

This preprint presents a systematic experimental study of extremelow-bit compression of LLaMA-7B without retraining, distillation,pruning, or architectural changes. More than 60 documented compression methods and variants were evaluated,including Product Quantization, selective low-rank residuals,activation- and Hessian-aware approaches, function-preserving gaugetransformations, additive quantization, sparse corrections, andnetwork-level output calibration. The final PCST v5 artifact occupies 2.05 GiB. On a document-resetWikiText-2 evaluation with 6,688 prediction positions, it achievesperplexity 15.56 and 59.59% Top-10 overlap with the Q8 reference.Although the result remains behind standard Q3_K_M quantization inquality and speed, the study identifies reproducible positive results,documents negative results, and demonstrates that local weight or blockreconstruction error often fails to predict end-to-end language-modelbehavior.

Authors

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-09-04
DOI
https://doi.org/10.5281/zenodo.22304196
Primary Topic
Advanced Data Compression Techniques
Type
preprint
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
preprint

PCST: A Systematic Study of Extreme Low-Bit LLaMA-7B Compression Without Retraining

Ilia Luzhetsky
Zenodo (CERN European Organization for Nuclear Research)
Advanced Data Compression Techniques
preprint

PCST: A Systematic Study of Extreme Low-Bit LLaMA-7B Compression Without Retraining

Ilia Luzhetsky
preprint en

Abstract

This preprint presents a systematic experimental study of extremelow-bit compression of LLaMA-7B without retraining, distillation,pruning, or architectural changes. More than 60 documented compression methods and variants were evaluated,including Product Quantization, selective low-rank residuals,activation- and Hessian-aware approaches, function-preserving gaugetransformations, additive quantization, sparse corrections, andnetwork-level output calibration. The final PCST v5 artifact occupies 2.05 GiB. On a document-resetWikiText-2 evaluation with 6,688 prediction positions, it achievesperplexity 15.56 and 59.59% Top-10 overlap with the Q8 reference.Although the result remains behind standard Q3_K_M quantization inquality and speed, the study identifies reproducible positive results,documents negative results, and demonstrates that local weight or blockreconstruction error often fails to predict end-to-end language-modelbehavior.

Zenodo (CERN European Organization for Nuclear Research)
Advanced Data Compression Techniques
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.