Running open models across varied hardware usually stumbles on formats and memory. llama.cpp is an open-source C++ inference project on GitHub built around GGUF quantization for conversion and cross-platform execution, with command-line tools and a server form, and it underpins many local apps. It targets developers: build it or take a release, and follow the repository README for usage and supported hardware.
What it does
- A C++ inference library with several hardware backends
- Works around quantized formats to cut memory use
- Compiles and runs on servers, desktops and mobile
- Command-line tools and a server form included
- A dependency under many local inference apps
Who it is for
- Running models on limited resources or uncommon GPUs
- Embedding inference into a tool you are building
- Converting weights to quantized formats for distribution
- Debugging format compatibility in other clients
How to get started
- Build from the repository instructions or take a release for your platform
- Verify with a smaller quantized model first
- Then tune parameters for serving and concurrency
