# Llama.cpp v0.1.0 Ships on GitHub

> Published 2026-08-18 · https://www.promptzone.com/xiu_hassan/llamacpp-v010-ships-on-github-427b

Llama.cpp v0.1.0 appeared on [Hacker News](https://github.com/ggml-org/llama.cpp/releases/tag/v0.1.0) last week and collected 42 points with 8 comments in the first day.

The project reached its first tagged release after months of commits focused on GGUF model loading and CPU inference.

## What It Is

Llama.cpp is a C++ library and CLI tool that runs quantized large language models locally without external dependencies. Version 0.1.0 marks the first official release tag on the GitHub repository.

It supports Llama, Mistral, and other GGUF-format models through a single binary that compiles on Linux, macOS, and Windows.

## How to Try It

Clone the repository and build with CMake or make. The basic command sequence is:

```shell
git clone https://github.com/ggml-org/llama.cpp
cd llama.cpp
make
./main -m model.gguf -p "Hello"
```

Pre-built binaries are not yet provided in v0.1.0, so users compile from source.

## Benchmarks and Numbers

The HN thread contains no official benchmark numbers. Early comments reference prior llama.cpp builds achieving 30–50 tokens per second on M2 MacBook Air CPUs with 7B Q4 models.

No VRAM or parameter counts appear in the release tag itself.

## Pros and Cons

- Single-binary deployment with no Python runtime required
- Direct GGUF support reduces conversion steps
- Limited to CPU and Metal backends in the tagged version
- No built-in server mode or API yet

## Alternatives and Comparisons

| Tool       | Backend     | Install     | Server API | License    |
|------------|-------------|-------------|------------|------------|
| Llama.cpp v0.1.0 | C++ / Metal | Compile     | No         | MIT        |
| Ollama     | llama.cpp   | One command | Yes        | MIT        |
| LM Studio  | llama.cpp   | GUI         | Yes        | Proprietary|

Ollama wraps llama.cpp and adds model management and an OpenAI-compatible endpoint. LM Studio provides a graphical interface on top of the same core.

## Who Should Use This

Developers who need a minimal C++ dependency for embedding LLM inference in other applications will find v0.1.0 useful. Users wanting immediate server APIs or one-click installs should start with Ollama instead.

> **Bottom line:** v0.1.0 gives the first stable reference point for the llama.cpp codebase but still requires manual compilation and lacks higher-level features present in wrappers.

The release signals that the core inference engine has reached a point where downstream tools can pin to a tagged version rather than tracking main.