llama.cpp is a C++ library designed for running large language models (LLMs) with high performance, particularly on consumer hardware. It emphasizes portability, ease of use, and efficient use of resources, allowing LLMs to be run on CPUs and GPUs with limited resources. The project focuses on inference rather than training.
One of the key features of llama.cpp is its support for quantization, which reduces the memory footprint and computational requirements of LLMs. This enables deployment on devices with limited RAM, such as laptops and mobile devices. It also leverages techniques like CPU offloading and GPU acceleration (via technologies like Metal, CUDA, and OpenCL) to optimize performance.
llama.cpp aims to be a simple, dependency-free implementation, making it relatively straightforward to build and deploy across different platforms. The library is commonly used for research, experimentation, and running LLMs locally without relying on cloud services. Its permissive license (typically MIT) fosters community contributions and allows for broad usage.