Package: llama.cpp (8064+dfsg-2 and others)

[ Source: llama.cpp  ]

LLM inference in C/C++ - metapackage

The main goal of llama.cpp is to enable LLM inference with minimal setup and state-of-the-art performance on a wide range of hardware - locally and in the cloud.

 * Plain C/C++ implementation without any dependencies
 * Apple silicon is a first-class citizen - optimized via ARM NEON, Accelerate
   and Metal frameworks
 * AVX, AVX2, AVX512 and AMX support for x86 architectures
 * 1.5-bit, 2-bit, 3-bit, 4-bit, 5-bit, 6-bit, and 8-bit integer quantization
   for faster inference and reduced memory use
 * Custom CUDA kernels for running LLMs on NVIDIA GPUs (support for AMD GPUs
   via HIP and Moore Threads MTT GPUs via MUSA)
 * Vulkan and SYCL backend support
 * CPU+GPU hybrid inference to partially accelerate models larger than the
   total VRAM capacity

The compute functionality is provided by ggml. By default, ggml's CPU backend is installed, but there are many other backends for CPUs and GPUs.

This is a meta-package that either depends on all of the relevant binary packages.

Other Packages Related to llama.cpp

• dep: libc6 (>= 2.38) [sparc64]

  GNU C 라이브러리: 공유 라이브러리
  also a virtual package provided by libc6-udeb

• dep: libc6.1 (>= 2.38) [alpha]

  GNU C 라이브러리: 공유 라이브러리
  also a virtual package provided by libc6.1-udeb

• dep: libcurl4t64 (>= 7.16.2) [not all]

  사용하기 쉬운 클라이언트측 URL 전송 라이브러리 (OpenSSL 지원)

• dep: libgcc-s1 (>= 3.4) [alpha]

  GCC 기능 지원 라이브러리

  dep: libgcc-s1 (>= 4.3) [sparc64]

• dep: libggml-cpu (<< 0.0~git20250713) [not all]

  Tensor library for machine learning - CPU backend

  or libggml-backend (<< 0.0~git20250713)

  Package not available

  dep: libggml-cpu (>= 0.0~git20250712) [not all]

  or libggml-backend (>= 0.0~git20250712)

• dep: libstdc++6 (>= 14) [not all]

  GNU 표준 C++ 라이브러리 v3

• dep: llama.cpp-tools [all]

  LLM inference in C/C++ - main utilities

• dep: python3 [not all]

  interactive high-level object-oriented language (default python3 version)

• rec: llama.cpp-tools-extra

  LLM inference in C/C++ - extra utilities

• rec: python3-gguf

  Python library for working with GGUF files

• sug: llama.cpp-examples

  LLM inference in C/C++ - example programs

Download llama.cpp

Download for all available architectures

Architecture	Version	Package Size	Installed Size	Files
all	8064+dfsg-2	8.0 kB	22.0 kB	[list of files]
alpha (unofficial port)	5882+dfsg-2	7,704.8 kB	67,836.0 kB	[list of files]
sparc64 (unofficial port)	5882+dfsg-2	6,809.5 kB	101,618.0 kB	[list of files]