macOS
brew install llama.cpplocal Homebrew formula metadata
sudo port install llama.cppMacPorts ports tree · llm/llama.cpp/Portfile · source: api.github.com
brew / rank 206
LLM inference in C/C++. Version 0.4.1 via Homebrew; verified 2026-09-18. Also installable with nix: nix profile install nixpkgs#llama-cpp.
install
brew install llama.cpplocal Homebrew formula metadata
sudo port install llama.cppMacPorts ports tree · llm/llama.cpp/Portfile · source: api.github.com
sudo dnf install llama-cppFedora Rawhide package metadata · llama-cpp · source: dl.fedoraproject.org
nix profile install nixpkgs#llama-cppnixpkgs package indexes · pkgs/by-name/ll/llama-cpp/package.nix · source: api.github.com
sudo pacman -S llama-cppArch Linux sync databases · llama-cpp · source: geo.mirror.pkgbuild.com
sudo apk add llama-batchedAlpine Linux edge package indexes · llama-batched · source: dl-cdn.alpinelinux.org
winget install --id ggml.llamacpp -eWindows Package Manager source index · ggml.llamacpp · source: cdn.winget.microsoft.com
overview
LLM inference in C/C++
history
llama.cpp is one of the defining packages of the local-LLM era: a C/C++ inference stack that made it practical to run quantized transformer models on laptops, desktops, servers, and small devices without a heavyweight Python runtime.
The repository was created on GitHub on March 10, 2023, shortly after Meta's LLaMA model release changed the center of gravity for local language-model experimentation. The README states the project goal as LLM inference with minimal setup and strong performance across local and cloud hardware.
The project is closely tied to ggml. Its README describes llama.cpp as the main playground for developing new ggml features, and the implementation grew around plain C/C++, integer quantization, CPU backends, and hardware accelerators such as Metal, CUDA, Vulkan, SYCL, HIP, and related GPU paths.
As model support broadened beyond the original LLaMA family, llama.cpp became a runtime and tooling umbrella: converters, quantizers, benchmarking tools, embedding tools, an OpenAI-compatible server, multimodal support, and many model-family loaders are represented in the command set and documentation.
Package adoption spread because llama.cpp lowered the cost of trying local inference: build from source, install from Homebrew, Nix, winget, conda-forge, Docker, or download release binaries, then run a model file or fetch one from Hugging Face-oriented workflows.
The README's bindings list shows the surrounding ecosystem that formed around the C/C++ core, including Python, Go, Node.js, Ruby, browser/Wasm, editor-completion plugins, and server clients. That ecosystem made llama.cpp both an end-user CLI and a library/runtime target for other packages.
Its high-frequency build-tag release pattern reflects active downstream pressure: package managers, bindings, model hubs, and local-AI applications all depend on fast propagation of backend, quantization, and model-format changes.
Users run llama-cli for local prompts, llama-server for an OpenAI-compatible HTTP API, llama-bench for performance testing, llama-quantize for smaller model files, and many auxiliary tools for embeddings, perplexity, retrieval, tokenization, and model-file manipulation.
The package is especially useful when a developer wants a self-contained inference engine: compile once, point it at a model, and choose a CPU/GPU backend without adopting a full ML framework stack.
For package maintainers, llama.cpp is unusually dynamic: hardware backend flags, model-format transitions, CLI renames, bundled tools, and release cadence all matter. It turned local AI into something package managers had to treat like a fast-moving systems tool rather than a single Python application.
It is also a packaging bridge between model hubs and Unix tooling. The same project can be installed as a formula, used as a server daemon, linked by language bindings, wrapped by desktop apps, or embedded in another inference product.
security posture
No matching local secret-handling manifest was found for llama.cpp. Package metadata is still published here so future coverage has a stable package URL.
Before unattended agent use, check whether the tool reads plaintext credentials, writes remote state, publishes artifacts, or shells out to plugins.
executables
| Command | Kind | Exposure | Note |
|---|---|---|---|
llama | cli | global executable | |
llama-batched | cli | global executable | |
llama-batched-bench | cli | global executable | |
llama-bench | cli | global executable | |
llama-cli | cli | global executable | |
llama-completion | cli | global executable | |
llama-debug | cli | global executable | |
llama-diffusion-cli | cli | global executable | |
llama-embedding | cli | global executable | |
llama-eval-callback | cli | global executable | |
llama-finetune | cli | global executable | |
llama-fit-params | cli | global executable | |
llama-gen-docs | cli | global executable | |
llama-gguf | cli | global executable | |
llama-gguf-hash | cli | global executable | |
llama-gguf-split | cli | global executable | |
llama-idle | cli | global executable | |
llama-imatrix | cli | global executable | |
llama-lookahead | cli | global executable | |
llama-lookup | cli | global executable | |
llama-lookup-create | cli | global executable | |
llama-lookup-merge | cli | global executable | |
llama-lookup-stats | cli | global executable | |
llama-mtmd-cli | cli | global executable | |
llama-parallel | cli | global executable | |
llama-passkey | cli | global executable | |
llama-perplexity | cli | global executable | |
llama-quantize | cli | global executable | |
llama-results | cli | global executable | |
llama-retrieval | cli | global executable | |
llama-server | cli | global executable | |
llama-simple | cli | global executable | |
llama-simple-chat | cli | global executable | |
llama-speculative | cli | global executable | |
llama-speculative-simple | cli | global executable | |
llama-tokenize | cli | global executable | |
llama-tts | cli | global executable |
freshness
These signals separate page generation age, package-manager activity, and upstream release comparison. Version lag is warned only when an evidence URL and comparable versions are present.
https://github.com/ggml-org/llama.cpp
install metadata
| Package key | brew:llama.cpp |
|---|---|
| Version | 0.4.1 |
| Package manager | Homebrew |
| Package manager page | https://formulae.brew.sh/formula/llama.cpp |
| Homepage | https://llama.app |
| Repository | https://github.com/ggml-org/llama.cpp |
| Upstream docs | https://llama.app |
| License | MIT |
| Source archive | https://github.com/ggml-org/llama.cpp.git |
| Last updated | 2026-09-18T13:15:15+02:00 |
| Pulse | updated |
| Dependencies | ggml, openssl@3 |
| Build dependencies | cmake |
| Bottle | available (on arm64_linux, arm64_sequoia, arm64_sonoma, arm64_tahoe, sonoma, x86_64_linux) |
| Homebrew post-install | not defined |
| Service | none declared |
registry facts
| Source Database | Homebrew formula API |
|---|---|
| Tap | homebrew/core |
| Full Name | llama.cpp |
| Version Scheme | 1 |
| Revision | 0 |
| Head Version | HEAD |
| Bottle Stable Root URL | https://ghcr.io/v2/homebrew/core |
| Deprecated | no |
| Disabled | no |
| Keg Only | no |
| URL Keys |
|
source database matches
Matches are pulled from external package-manager indexes and kept separate from local Automic Vault package links.
llama-cpp
nix profile install nixpkgs#llama-cppllama-batched 0.2.0-r1
llama-batched tool from llama.cpp
https://github.com/ggml-org/llama.cpp
sudo apk add llama-batchedllama-batched-bench 0.2.0-r1
llama-batched-bench tool from llama.cpp
https://github.com/ggml-org/llama.cpp
sudo apk add llama-batched-benchllama-completion 0.2.0-r1
llama-completion tool from llama.cpp
https://github.com/ggml-org/llama.cpp
sudo apk add llama-completionllama-debug 0.2.0-r1
llama-debug tool from llama.cpp
https://github.com/ggml-org/llama.cpp
sudo apk add llama-debugllama-diffusion-cli 0.2.0-r1
llama-diffusion-cli tool from llama.cpp
https://github.com/ggml-org/llama.cpp
sudo apk add llama-diffusion-clillama-embedding 0.2.0-r1
llama-embedding tool from llama.cpp
https://github.com/ggml-org/llama.cpp
sudo apk add llama-embeddingllama-eval-callback 0.2.0-r1
llama-eval-callback tool from llama.cpp
https://github.com/ggml-org/llama.cpp
sudo apk add llama-eval-callbackllama-finetune 0.2.0-r1
llama-finetune tool from llama.cpp
https://github.com/ggml-org/llama.cpp
sudo apk add llama-finetunellama-fit-params 0.2.0-r1
llama-fit-params tool from llama.cpp
https://github.com/ggml-org/llama.cpp
sudo apk add llama-fit-paramsllama-gen-docs 0.2.0-r1
llama-gen-docs tool from llama.cpp
https://github.com/ggml-org/llama.cpp
sudo apk add llama-gen-docsllama-gguf 0.2.0-r1
llama-gguf tool from llama.cpp
https://github.com/ggml-org/llama.cpp
sudo apk add llama-ggufllama-gguf-hash 0.2.0-r1
llama-gguf-hash tool from llama.cpp
https://github.com/ggml-org/llama.cpp
sudo apk add llama-gguf-hashllama-gguf-split 0.2.0-r1
llama-gguf-split tool from llama.cpp
https://github.com/ggml-org/llama.cpp
sudo apk add llama-gguf-splitllama-idle 0.2.0-r1
llama-idle tool from llama.cpp
https://github.com/ggml-org/llama.cpp
sudo apk add llama-idlellama-imatrix 0.2.0-r1
llama-imatrix tool from llama.cpp
https://github.com/ggml-org/llama.cpp
sudo apk add llama-imatrixsource trail
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View the package source record on GitHub.