# llama.cpp review

> llama.cpp is a plain C/C++ library and set of tools for running LLM and VLM inference locally or in the cloud on many kinds of hardware.

Devtoolwatch Board, the week of Oct 25–31, 2026. Canonical page: https://index.devtoolwatch.com/tools/llama-cpp/

## TL;DR

llama.cpp runs large language and vision models with minimal setup across CPUs, GPUs and NPUs. It suits developers who want local inference, quantized models, or an OpenAI-compatible server. It is a dependency-free C/C++ implementation built on the ggml library, with many hardware backends.

## llama.cpp at a glance

- **Category:** [Inference and training](https://index.devtoolwatch.com/categories/inference-and-training/)
- **Maintained by:** ggml (organization, [@ggml-org](https://github.com/ggml-org) on GitHub)
- **License:** MIT
- **Language:** C++, C, Python
- **Repository:** [github.com/ggml-org/llama.cpp](https://github.com/ggml-org/llama.cpp)
- **Website:** [llama.app](https://llama.app)
- **Latest release:** [b11887](https://github.com/ggml-org/llama.cpp/releases/tag/b11887) on GitHub, Oct 25, 2026
- **First published:** Mar 10, 2023

## What llama.cpp does

- llama.cpp downloads and runs GGUF models directly from Hugging Face through its command-line tool.
- llama.cpp launches an OpenAI-compatible API server with a built-in web UI through llama serve.
- llama.cpp supports 1.5-bit to 8-bit integer quantization for faster inference and reduced memory use.
- llama.cpp runs CPU+GPU hybrid inference to partially accelerate models larger than total VRAM capacity.
- llama.cpp supports backends including CUDA, HIP, Metal, Vulkan, SYCL, MUSA, CANN, OpenCL, WebGPU and RPC.
- llama.cpp handles vision-language model sessions in its CLI, using a multimodal subsystem for image and audio decoding.
- llama.cpp supports GBNF grammars to constrain model output.

### How it works

llama.cpp is built on the ggml library and ships as a CLI and a server. You run llama cli or llama serve with a Hugging Face model. The server exposes an OpenAI-compatible API, so apps can connect to it. The Llama desktop app for Mac and Windows wraps llama.cpp and serves an API at localhost:9931/v1.

## How to install llama.cpp

**With curl (macOS/Linux)**

```
curl -LsSf https://llama.app/install.sh | sh
```

**With PowerShell (Windows)**

```
irm https://llama.app/install.ps1 | iex
```

### Requirements

- The Llama desktop app runs on Mac and Windows 11; Linux users install the command-line version.
- GPU acceleration requires a supported backend, such as CUDA for Nvidia, HIP for AMD, or Metal for Apple Silicon.

### First steps

1. Install llama.cpp with the install script, Docker, pre-built binaries, or by building from source.
2. Run a model from Hugging Face with: llama cli -hf ggml-org/Qwen3.5-0.8B-GGUF
3. Start an OpenAI-compatible server with: llama serve -hf ggml-org/Qwen3.5-0.8B-GGUF
4. Point an OpenAI-compatible app or SDK at the local server's API endpoint.

## Who llama.cpp is for

- Developers running open models locally on their own hardware, including Apple silicon.
- Teams needing a local OpenAI-compatible API for coding agents, editors, and scripts.
- Running models on limited memory through quantization or CPU+GPU hybrid inference.
- Developers targeting varied hardware such as NPUs, Snapdragon, RISC-V, or IBM Z.

### Limitations

- llama.cpp's OpenVINO backend for Intel CPUs, GPUs and NPUs is marked as in progress.
- llama.cpp's frequent builds are published as pre-releases.
- llama.cpp's KleidiAI-enabled macOS Apple Silicon build is currently disabled in releases.

## Usage data (the week of Oct 25–31, 2026)

- Board rank: #109 overall, #12 in Inference and training, momentum score 61
- New GitHub stars per week (last 12 weeks): Aug 9: 992; Aug 16: 1.2k; Aug 23: 1.1k; Aug 30: 956; Sep 6: 879; Sep 13: 891; Sep 20: 801; Sep 27: 695; Oct 4: 808; Oct 11: 851; Oct 18: 806; Oct 25: 844

## llama.cpp alternatives

| Rank | Tool | Stars | Downloads/wk |
|---|---|---|---|
| #1 | [dsh-our-free-model](https://index.devtoolwatch.com/tools/ebony-vinyl-dsh-our-free-model/) | 54.3k | – |
| #2 | [magpie](https://index.devtoolwatch.com/tools/yetone-magpie/) | 26.9k | – |
| #3 | [Strata](https://index.devtoolwatch.com/tools/niko1221-strata/) | 37.1k | – |
| #4 | [edge0](https://index.devtoolwatch.com/tools/edge0-ai-edge0/) | 8.9k | – |
| #5 | [OmniRoute](https://index.devtoolwatch.com/tools/diegosouzapw-omniroute/) | 83.2k | 106k |
| #6 | [CLIProxyAPI](https://index.devtoolwatch.com/tools/router-for-me-cliproxyapi/) | 57.1k | – |

## llama.cpp FAQ

### Is llama.cpp free and open source?

Yes. llama.cpp's source code is on GitHub (ggml-org/llama.cpp) under the MIT license, so you can use it for free.

### How do I install llama.cpp?

Run `curl -LsSf https://llama.app/install.sh | sh`. The install section above has the other options from the project's README.

### Is llama.cpp still maintained?

Yes. The ggml-org/llama.cpp repository was last updated on Oct 25, 2026, and the latest release, b11887 on GitHub, came out on Oct 25, 2026.

### How popular is llama.cpp?

llama.cpp has 133k GitHub stars as of Nov 1, 2026. It gained 844 new stars in the week of Oct 25–31, 2026, against a 12-week average of 906 a week. That made it #12 among LLM inference and training tools on the Devtoolwatch Board.

### llama.cpp vs Ollama: how do they compare?

llama.cpp and Ollama are both tracked by Devtoolwatch as LLM inference and training tools. llama.cpp has 133k GitHub stars and Ollama has 185.5k. Ollama is a tool for running and building with open AI models locally or in the cloud on macOS, Windows, and Linux. [Ollama review](https://index.devtoolwatch.com/tools/ollama/)

### llama.cpp vs vLLM: how do they compare?

llama.cpp and vLLM are both tracked by Devtoolwatch as LLM inference and training tools. llama.cpp has 133k GitHub stars and vLLM has 96k. vLLM is an open-source Python library and engine for high-throughput, memory-efficient inference and serving of large language models. [vLLM review](https://index.devtoolwatch.com/tools/vllm/)

### What are the best alternatives to llama.cpp?

Other LLM inference and training tools on the Devtoolwatch Board in the week of Oct 25–31, 2026, by momentum: dsh-our-free-model (#1), magpie (#2), Strata (#3), edge0 (#4), OmniRoute (#5). The alternatives table above has their numbers.

### Is llama.cpp OpenAI compatible?

Yes. llama.cpp's llama serve command launches an OpenAI-compatible API server. The Llama app exposes the same kind of API at localhost:9931/v1, so apps that work with OpenAI can connect to it.

### Does llama.cpp have a GUI?

Yes. llama.cpp's server includes a built-in web UI. The Llama app for Mac and Windows adds a menu bar or system tray app with a browser chat and model picker.

### How do I use llama.cpp on Mac?

llama.cpp treats Apple silicon as a first-class platform, optimized via ARM NEON, Accelerate and Metal. Install it with the curl script or download the Llama Mac app, then run or serve a model.

### How do I use llama.cpp on Windows?

llama.cpp installs on Windows with the PowerShell command irm https://llama.app/install.ps1 | iex. You can also download the Llama app for Windows 11 or pre-built binaries from the releases page.

### How do I use the llama.cpp server?

llama.cpp starts its server with llama serve -hf followed by a Hugging Face model, such as ggml-org/Qwen3.5-0.8B-GGUF. The server provides an OpenAI-compatible REST API and a built-in web UI.

## Sources

1. [ggml-org/llama.cpp on GitHub](https://github.com/ggml-org/llama.cpp)
2. [llama.cpp README](https://github.com/ggml-org/llama.cpp/blob/master/README.md)
3. [llama.cpp website](https://llama.app)
4. [Release b11887 (Oct 25, 2026)](https://github.com/ggml-org/llama.cpp/releases/tag/b11887)
5. [Release b11886 (Oct 25, 2026)](https://github.com/ggml-org/llama.cpp/releases/tag/b11886)
6. [Release b11884 (Oct 25, 2026)](https://github.com/ggml-org/llama.cpp/releases/tag/b11884)
7. [Hacker News: Ggml.ai joins Hugging Face to ensure the long-term progress of Local AI](https://news.ycombinator.com/item?id=47088037)
8. [Hacker News: Vision Now Available in Llama.cpp](https://news.ycombinator.com/item?id=43943047)
9. [Hacker News: llama.cpp](https://news.ycombinator.com/item?id=49267928)
10. [Devtoolwatch Board, the week of Oct 25–31, 2026](https://index.devtoolwatch.com/)