Llama.cpp

by Orchestra-Research

Llama.cpp 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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Install in seconds

Install Llama.cpp

Copy Llama.cpp 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/12-inference-serving/llama-cpp ~/.claude/skills/llama-cpp

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: 12-inference-serving/llama-cpp/SKILL.md in Orchestra-Research/AI-Research-SKILLs
Installs to: ~/.claude/skills/llama-cpp
Collection: One of 50 skills cataloged from this repository
Category: AI Engineering — 2451 skills

What Llama.cpp does

Llama.cpp runs LLM inference locally on CPU, Apple Silicon, and non-NVIDIA GPUs with GGUF quantization. Use it for edge deployment, low-memory setups, or when CUDA is unavailable.

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

Documentation

README

Excerpt

llama.cpp

Pure C/C++ LLM inference with minimal dependencies, optimized for CPUs and non-NVIDIA hardware.

When to use llama.cpp

Use llama.cpp when:

Running on CPU-only machines
Deploying on Apple Silicon (M1/M2/M3/M4)
Using AMD or Intel GPUs (no CUDA)
Edge deployment (Raspberry Pi, embedded systems)
Need simple deployment without Docker/Python

Use TensorRT-LLM instead when:

Have NVIDIA GPUs (A100/H100)
Need maximum throughput (100K+ tok/s)
Running in datacenter with CUDA

Use vLLM instead when:

Have NVIDIA GPUs
Need Python-first API
Want PagedAttention

Quick start

Installation

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

Frequently asked about Llama.cpp

What else does Orchestra-Research publish alongside Llama.cpp?
Llama.cpp 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 Llama.cpp 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 Llama.cpp compare to other AI Engineering skills?
Llama.cpp ranks #340 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 Llama.cpp against them. Open each page to compare what they document and how they install.