Quantization recipe for fitting a 27-billion-parameter model on a 24 GB GPU

qwen38-27b-rtx3090 re-quantizes two untied 2.5 GB embedding matrices to int8, freeing 2.6 GB for larger batch sizes.

From Github AwesomeGitHub Trending Weekly #47: utopia, neo, slotstream, Codewhale, TokensBurned, mono-color-skill at 13:46

Problem: A 27-billion-parameter model may load on a 24 GB card but leave insufficient memory for useful batched inference.

For: Local-inference users and developers trying to run large language models on single gaming GPUs.

Products from this video

ABYSSAL cc-prune CDAF (Cached Descriptive Asset Files) Codewhale defragger Editable Visual Design FixAnything genart-skill h3-storyboard-skill HexStellar hqtui Keyword Pro LightNav-0 loadersz markdown-graphs Monocolor Editorial Print Noty Omakade Procedura qwen38-27b-rtx3090 Shrimply Skill Cabinet SkillRadar skin-tokens.cpp slotstream Strata TokensBurned TrustMeBro Utopia vol-rs

Examples

🔒 Full analysis locked

Unlock more videos and the full analysis

A credit unlocks one video's full analysis for good — the build steps, the tools and how each was used, the methods behind every use case. Pro opens the whole library instead, and raises how many videos you can analyse a day.

Unlock full analysis — free

Related ideas