Run AI models on your computer
Llama.cpp is a C and C++ based inference library that enables large language models to be run efficiently on standard hardware. The software makes it easier to run artificial intelligence models on local devices with its low memory usage and high performance-oriented structure.
Updates
- November 5, 2026: Stars 132,691 → 133,399, latest release v0.9.0 (November 4, 2026).
- October 29, 2026: Stars 131,352 → 132,691, latest release v0.8.0 (October 28, 2026).
- October 16, 2026: Stars 130,447 → 131,352, latest release v0.7.0 (October 15, 2026).
- October 6, 2026: Stars 129,621 → 130,447, latest release v0.6.0 (October 5, 2026).
What you get
- It runs large language models efficiently on standard hardware.
- Provides high performance with low memory usage.
- Makes it easy to run AI models on local devices.
Installation
git clone https://github.com/ggml-org/llama.cpp.git
cd llama.cppRunning it
llama-cli -m my_model.ggufIf you don't write code
I want to run large language models locally on my computer. How can I run my own model file using the llama.cpp tool with the command 'llama-cli -m my_model.gguf' or download and launch a model directly from Hugging Face with the command 'llama-cli -hf ggml-org/gemma-3-1b-it-GGUF'? Can you help me with the hardware requirements or model selection that I should pay attention to in this process?
Repository: https://github.com/ggml-org/llama.cpp. Follow the official instructions in the README of this repository for setup and execution.
Before starting, check which OS we are on and if the necessary tools (e.g., Python, Node.js, Git, Docker) are installed. Install any missing ones step-by-step according to this system.
Create a new, empty folder to work in. Do not touch any files outside this folder and do not delete anything. Tell me what you are going to do in one sentence before running each command.
Tell me what I should see on the screen at the end of each step. If an error occurs, I will paste the error message to you exactly as it is, and we will fix it together.
Related dictionary terms
Links
TreScout did not build this tool · we found it in GitHub trends and wrote it up. This page describes the repository as of 2026-06-08: The star count and our text belong to that day, the repository may have changed since. Check the repository link for the current state. The introductory text was prepared with AI from the repository's own documentation, and this page was machine-translated from the Turkish original · the Turkish version prevails.