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How to use llama.cpp: what you can do with it

llama.cpp is a dependency-free C/C++ engine for running LLMs and vision language models locally or in the cloud, with quantization, many GPU backends, a CLI and an OpenAI-compatible server.

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What do you want to do?

3 use cases

  • Run an open model locally in one command

    Install llama.cpp and chat with a GGUF model pulled straight from Hugging Face.

    View prompt
    Install ggml-org/llama.cpp and run `llama cli -hf ggml-org/Qwen3.5-0.8B-GGUF`. Ask it <question> and report tokens per second shown, confirming the model ran locally.

  • Serve a local model behind an OpenAI-compatible API

    Start llama serve to give your apps an OpenAI-style endpoint and a built-in web UI.

    View prompt
    Start `llama serve -hf ggml-org/Qwen3.5-0.8B-GGUF`, then send one chat completion from <app> to it. Confirm the response came from the local server, not a cloud API.

  • Fit a bigger model on limited hardware

    Use low-bit quantized GGUF models and CPU plus GPU hybrid inference to run models larger than your VRAM.

    View prompt
    Run a 4-bit GGUF of <model> with llama.cpp on a machine with <VRAM> GB VRAM using CPU+GPU hybrid inference. Report tokens per second and confirm the model loaded fully.

Quick start with llama.cpp

  1. Check you have what it needs: macOS, Linux or Windows; Enough RAM or VRAM for the chosen GGUF model.
  2. Open ggml-org/llama.cpp on GitHub and read the README and license.
  3. Install with curl -LsSf https://llama.app/install.sh | sh (or irm https://llama.app/install.ps1 | iex on Windows)
  4. Run llama cli -hf ggml-org/Qwen3.5-0.8B-GGUF
  5. Chat in the terminal
  6. Try a larger GGUF model if your hardware allows

These steps come from our top use case, Run an open model locally in one command, which also has a copy-paste agent prompt.

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llama.cpp alternatives · Best AI repos for Software and DevOps

About this repo

  • Who it is forDevelopers who want to run open models locally on laptops, workstations or servers with minimal setup.
  • Why it is hot132k stars, talked about in 2 AI sources we track
  • LanguageC++
  • Sourcegithub.com/ggml-org/llama.cpp · Back to Hot repos

Requirements

  • macOS, Linux or Windows
  • Enough RAM or VRAM for the chosen GGUF model

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Questions about llama.cpp

What is llama.cpp?

llama.cpp is a dependency-free C/C++ engine for running LLMs and vision language models locally or in the cloud, with quantization, many GPU backends, a CLI and an OpenAI-compatible server. It is an open-source project on GitHub: https://github.com/ggml-org/llama.cpp.

Who is llama.cpp for?

Developers who want to run open models locally on laptops, workstations or servers with minimal setup.

What can I do with llama.cpp?

3 use cases so far, for example: Run an open model locally in one command; Serve a local model behind an OpenAI-compatible API; Fit a bigger model on limited hardware. Each has steps and a copy-paste agent prompt.

What do I need to run llama.cpp?

macOS, Linux or Windows; Enough RAM or VRAM for the chosen GGUF model.

What are alternatives to llama.cpp?

Other hot AI repos in Software and DevOps: Deep Infer, Harness2, Orca, Opencode, Graphify.

Is llama.cpp safe to run?

Deduped does not own, audit or vouch for it. Read the README and license, run it on your own systems first and review every command before you run it.