GGUF Quantization

by Orchestra-Research

GGUF Quantization is an AI Engineering skill for Claude Code, published by Orchestra-Research in AI-Research-SKILLs.

11.6K stars844 forkson Orchestra-Research/AI-Research-SKILLsAdded 2026/08/12+1% in starsRepository updated 2026/06/16

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aiai-researchclaudeclaude-codeclaude-skillscodexgeminigpt-5grpohuggingfacemachine-leanringmegatronskillsvllm

Install in seconds

Install GGUF Quantization

Copy GGUF Quantization into your Claude Code skills folder. Run the command in your terminal, or review the source on GitHub before installing.

terminal

npx degit https://github.com/Orchestra-Research/AI-Research-SKILLs/tree/main/10-optimization/gguf ~/.claude/skills/gguf

Requires Node.js. Downloads this skill only — not the rest of the repository — into your Claude Code skills folder.

Without Node.js

git clone https://github.com/Orchestra-Research/AI-Research-SKILLs.git

Clones the whole repository, then copy the skill’s own directory into your skills folder yourself.

In this catalog

Source file: 10-optimization/gguf/SKILL.md in Orchestra-Research/AI-Research-SKILLs
Installs to: ~/.claude/skills/gguf
Collection: One of 50 skills cataloged from this repository
Category: AI Engineering — 2451 skills

What GGUF Quantization does

GGUF Quantization covers GGUF format and llama.cpp quantization for efficient CPU and GPU inference. Use it when converting models for consumer hardware, Apple Silicon, or flexible 2-8 bit local deployment.

GGUF Quantization is cataloged under AI Engineering on DirSkills. GGUF Quantization comes from a repository tagged ai, ai-research, claude, claude-code and claude-skills.

Documentation

README

Excerpt

GGUF - Quantization Format for llama.cpp

The GGUF (GPT-Generated Unified Format) is the standard file format for llama.cpp, enabling efficient inference on CPUs, Apple Silicon, and GPUs with flexible quantization options.

When to use GGUF

Use GGUF when:

Deploying on consumer hardware (laptops, desktops)
Running on Apple Silicon (M1/M2/M3) with Metal acceleration
Need CPU inference without GPU requirements
Want flexible quantization (Q2_K to Q8_0)
Using local AI tools (LM Studio, Ollama, text-generation-webui)

This is the opening of the README. Read the full README on GitHub.

Frequently asked about GGUF Quantization

What else does Orchestra-Research publish alongside GGUF Quantization?
GGUF Quantization is one of 50 skills that DirSkills catalogs from Orchestra-Research/AI-Research-SKILLs, the repository it ships in. Its siblings there include AWQ Quantization, Autoresearch and Axolotl. Each one is a separate skill with its own page in this directory, installs the same way GGUF Quantization does, and is maintained by Orchestra-Research in that same repository. The rest of the collection is listed on the Orchestra-Research/AI-Research-SKILLs page.
How does GGUF Quantization compare to other AI Engineering skills?
GGUF Quantization ranks #333 by stars among the 2451 AI Engineering skills in this catalog. The most-starred ones next to it are Architecture Decision Records, AI-First Engineering and Agentic OS. DirSkills ranks by the star count of the repository each skill ships in, so that order reflects how popular those repositories are rather than any review of GGUF Quantization against them. Open each page to compare what they document and how they install.