llama.cpp
Efficient, open-source C/C++ library for local LLM inference on diverse hardware.
Visit websitegithub.com/ggml-org/llama.cpp
Overview
llama.cpp is an open-source C/C++ library for efficient inference of large language models (LLMs) on diverse hardware. It serves as a local engine, allowing AI models to run on CPUs, GPUs, and Apple M-series chips without cloud connections or specialized accelerators. Optimized for state-of-the-art performance with minimal setup, it's ideal for developers and enterprises building local or private LLM deployments. The tool uniquely supports offline operation and offers various quantization methods for reduced memory and faster inference.
Quick Info
Features
Pure C/C++ implementation with zero external dependencies
Supports 1.5-bit to 8-bit integer quantization for faster inference and reduced memory use
Enables running LLMs entirely offline on diverse hardware
Includes `llama-server` for OpenAI-compatible API workflows
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Yes, llama.cpp offers a free plan. Efficient, open-source C/C++ library for local LLM inference on diverse hardware.
llama.cpp is an open-source C/C++ library for efficient inference of large language models (LLMs) on diverse hardware. It serves as a local engine, allowing AI models to run on CPUs, GPUs, and Apple M...
Key features of llama.cpp include: Pure C/C++ implementation with zero external dependencies, Supports 1.5-bit to 8-bit integer quantization for faster inference and reduced memory use, Enables running LLMs entirely offline on diverse hardware, Includes `llama-server` for OpenAI-compatible API workflows.
llama.cpp is primarily designed for businesses and professionals. Efficient, open-source C/C++ library for local LLM inference on diverse hardware.
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llama.cpp remains relevant in 2026. llama.cpp is an open-source C/C++ library for efficient inference of large language models (LLMs) on diverse hardware. It serves as a local engine, al The pricing model is free. Check reviews and comparisons on Decod.tech to decide.
llama.cpp offers a free plan. You can start for free and upgrade as your needs grow. Visit the official pricing page for details.