Llama.cpp

Llama.cpp is an open-source LLM inference engine written in pure C/C++ by Georgi Gerganov, released in March 2023, that enables CPU and consumer-GPU inference of quantized LLMs with minimal dependencies. The project pioneered the GGUF file format (originally GGML) for storing quantized model weights, supporting precisions from 2-bit to 8-bit and full FP16/BF16. Llama.cpp powered the wave of consumer LLM adoption in 2023 by making models like Llama, Mistral, and Mixtral runnable on personal laptops without GPUs. The engine has grown to support hundreds of architectures, vision-language models, embedding models, and even Whisper-style speech recognition. Ollama, LM Studio, GPT4All, Jan, and many other consumer LLM apps are built on top of Llama.cpp. The framework's CPU inference performance is exceptional thanks to hand-optimized SIMD kernels for x86, ARM (Apple Silicon especially), and other architectures. AI governance teams adopt Llama.cpp for edge deployments, air-gapped environments, and per-employee local inference where cloud APIs are inappropriate.

Llama.cpp endpoints through Centralpoint: Centralpoint routes generation to Llama.cpp-served models alongside cloud LLMs in one model-agnostic platform — useful for air-gapped, edge, and privacy-sensitive deployments. Tokens are metered per skill, prompts stay local, and chatbots deploy through one line of JavaScript with full audit logs.


Related Keywords:
Llama.cpp,,