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LLAMA.CPP

LLM inference in C/C++

MIT

ABOUT

Running modern language models locally often requires heavyweight infrastructure, GPU-specific stacks, or custom serving code that is hard to port across laptops, servers, and edge devices. llama.cpp gives developers a fast, portable inference runtime with quantization support and a built-in API server, so they can run and serve GGUF models efficiently on a wide range of CPU and GPU hardware.

INSTALL
brew install llama.cpp

INTEGRATION GUIDE

1. Run GGUF language models locally on laptops, desktops, or servers without a large cloud stack 2. Serve open models behind an OpenAI-compatible API for apps, agents, and internal tooling 3. Use quantized models to reduce memory usage and make inference feasible on constrained hardware 4. Deploy private offline inference workflows for regulated or air-gapped environments

TAGS

llm-inferencelocal-llmggufquantizationopenai-compatiblecppedge-deployment
llama.cpp — AI Tool | Agentic AI For Good