llama-cpp
✓Runs LLM inference on CPU, Apple Silicon, and consumer GPUs without NVIDIA hardware. Use for edge deployment, M1/M2/M3 Macs, AMD/Intel GPUs, or when CUDA is unavailable. Supports GGUF quantization (1.5-8 bit) for reduced memory and 4-10× speedup vs PyTorch on CPU.
Installation
SKILL.md
Pure C/C++ LLM inference with minimal dependencies, optimized for CPUs and non-NVIDIA hardware.
| Format | Bits | Size (7B) | Speed | Quality | Use Case |
| Q4KM | 4.5 | 4.1 GB | Fast | Good | Recommended default | | Q4KS | 4.3 | 3.9 GB | Faster | Lower | Speed critical | | Q5KM | 5.5 | 4.8 GB | Medium | Better | Quality critical | | Q6K | 6.5 | 5.5 GB | Slower | Best | Maximum quality | | Q80 | 8.0 | 7.0 GB | Slow | Excellent | Minimal degradation | | Q2K | 2.5 | 2.7 GB | Fastest | Poor | Testing only |
Runs LLM inference on CPU, Apple Silicon, and consumer GPUs without NVIDIA hardware. Use for edge deployment, M1/M2/M3 Macs, AMD/Intel GPUs, or when CUDA is unavailable. Supports GGUF quantization (1.5-8 bit) for reduced memory and 4-10× speedup vs PyTorch on CPU. Source: ovachiever/droid-tings.
Facts (cite-ready)
Stable fields and commands for AI/search citations.
- Install command
npx skills add https://github.com/ovachiever/droid-tings --skill llama-cpp- Source
- ovachiever/droid-tings
- Category
- </>Dev Tools
- Verified
- ✓
- First Seen
- 2026-02-01
- Updated
- 2026-02-18
Quick answers
What is llama-cpp?
Runs LLM inference on CPU, Apple Silicon, and consumer GPUs without NVIDIA hardware. Use for edge deployment, M1/M2/M3 Macs, AMD/Intel GPUs, or when CUDA is unavailable. Supports GGUF quantization (1.5-8 bit) for reduced memory and 4-10× speedup vs PyTorch on CPU. Source: ovachiever/droid-tings.
How do I install llama-cpp?
Open your terminal or command line tool (Terminal, iTerm, Windows Terminal, etc.) Copy and run this command: npx skills add https://github.com/ovachiever/droid-tings --skill llama-cpp Once installed, the skill will be automatically configured in your AI coding environment and ready to use in Claude Code or Cursor
Where is the source repository?
https://github.com/ovachiever/droid-tings
Details
- Category
- </>Dev Tools
- Source
- skills.sh
- First Seen
- 2026-02-01