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brew

Install ncnn with Homebrew, dnf, Nix, pacman, zypper

High-performance neural network inference framework. Version 20260526 via Homebrew; verified 2026-06-25.

Install commandSecurity notes

install

Additional install commands

macOS

Homebrewverified · 100%
brew install ncnn

local Homebrew formula metadata

Linux

Fedora dnfverified · 92%
sudo dnf install ncnn

Fedora Rawhide package metadata · ncnn · source: dl.fedoraproject.org

Nixverified · 92%
nix profile install nixpkgs#ncnn

nixpkgs package indexes · pkgs/by-name/nc/ncnn/package.nix · source: api.github.com

Arch Linux pacmanverified · 92%
sudo pacman -S ncnn

Arch Linux sync databases · ncnn · source: geo.mirror.pkgbuild.com

openSUSE zypperverified · 92%
sudo zypper install libncnn1

openSUSE Tumbleweed package metadata · libncnn1 · source: download.opensuse.org

overview

Package summary

High-performance neural network inference framework

Commands and aliases

  • caffe2ncnn
  • darknet2ncnn
  • mxnet2ncnn
  • ncnn2int8
  • ncnn2mem
  • ncnn2table
  • ncnnmerge
  • ncnnoptimize

history

Project history and usage

ncnn is Tencent's open-source neural-network inference runtime for mobile, embedded, desktop, browser, and edge deployment. Its niche is small, dependency-light inference: the upstream README emphasizes no third-party runtime dependencies, CPU and Vulkan GPU backends, explicit low-memory allocator design, and conversion tools such as pnnx for PyTorch and ONNX workflows.

Project history

Tencent presentations describe the ncnn project as dating from 2017, with open collaboration and Vulkan acceleration as central design points. That timing put it in the wave of mobile inference runtimes that appeared after deep-learning deployment moved from server GPUs into phones and edge devices.

Adoption history

Upstream states that ncnn is used in Tencent applications including QQ, Qzone, WeChat, and Pitu. Outside Tencent, its adoption pattern is typical for low-level ML infrastructure: package-manager availability, examples for object detection and vision models, and use by developers who want a C++ runtime without TensorFlow Lite or ONNX Runtime-sized baggage.

How it is used

Package users usually install ncnn for the converter and optimizer executables as much as for the library. A common flow is export from PyTorch through pnnx, produce .param and .bin model files, run optimization or int8 tooling, and embed the resulting model in a C++ or mobile application using ncnn::Net.

Why package nerds care

For package maintainers, ncnn is interesting because it is a fast-moving C++/Vulkan project that exposes both libraries and many small CLI tools. It is also a useful example of a Homebrew formula where the command-line surface is mostly build/deployment tooling around a library rather than one end-user command.

Timeline

  • 2017: Tencent presentation material describes ncnn as active since 2017.
  • 2020s: README documents pnnx-based PyTorch/ONNX conversion and CPU/Vulkan deployment across mobile, desktop, browser, and edge targets.

Related projects

  • PyTorch, ONNX, pnnx, Vulkan, TensorFlow, Caffe, MXNet, Darknet

security posture

Risk level: blue

broad file, network, media, or database tool signal.

Risk classifier

blue risk · medium confidence · tool

Why

  • broad file, network, media, or database tool signal

Signals

  • text:network

Install behavior

  • No Homebrew post-install hook is recorded in formula metadata.
  • Homebrew bottle metadata is available for 6 platform targets.
  • Installs with 6 runtime dependencies.
  • Build metadata lists 1 build dependencies.

Recommended review

Before unattended agent use, check whether the tool reads plaintext credentials, writes remote state, publishes artifacts, or shells out to plugins.

executables

Installed executables

CommandKindExposureNote
caffe2ncnncliglobal executable
darknet2ncnncliglobal executable
mxnet2ncnncliglobal executable
ncnn2int8cliglobal executable
ncnn2memcliglobal executable
ncnn2tablecliglobal executable
ncnnmergecliglobal executable
ncnnoptimizecliglobal executable

freshness

Version and 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.

page generated2026-07-08
manager version20260526
manager updated2026-06-25
local dataok
upstreamnot checked
latest detectednot detected

https://github.com/Tencent/ncnn

install metadata

Package metadata

Package keybrew:ncnn
Version20260526
Package managerHomebrew
Package manager pagehttps://formulae.brew.sh/formula/ncnn
Homepagehttps://github.com/Tencent/ncnn
Repositoryhttps://github.com/Tencent/ncnn
Upstream docshttps://github.com/Tencent/ncnn
LicenseBSD-3-Clause
Source archivehttps://github.com/Tencent/ncnn/archive/refs/tags/20260526.tar.gz
Last updated2026-06-25T13:37:56+02:00
Pulseupdated
Dependenciesabseil, glslang, libomp, molten-vk, protobuf, spirv-tools
Build dependenciescmake
Bottleavailable (on arm64_linux, arm64_sequoia, arm64_sonoma, arm64_tahoe, sonoma, x86_64_linux)
Homebrew post-installnot defined
Servicenone declared

registry facts

Source database details

Source DatabaseHomebrew formula API
Taphomebrew/core
Full Namencnn
Version Scheme0
Revision1
Head VersionHEAD
Bottle Stable Root URLhttps://ghcr.io/v2/homebrew/core
Deprecatedno
Disabledno
Keg Onlyno
URL Keys
  • head
  • stable

source database matches

Other package-manager records

Matches are pulled from external package-manager indexes and kept separate from local Automic Vault package links.

Nix95%

ncnn

nix profile install nixpkgs#ncnn
  • normalized package name match
  • Matched by: Ncnn
nixpkgs package indexes · api.github.com · nixpkgs package indexes: pkgs/by-name/nc/ncnn/package.nix from https://api.github.com/repos/NixOS/nixpkgs/git/trees/master?recursive=1
dnf95%

ncnn 20250916-3.fc45

A high-performance neural network inference framework

https://github.com/Tencent/ncnn

sudo dnf install ncnn
  • License: BSD-3-Clause AND BSD-2-Clause AND Zlib
  • Category: Unspecified
  • Architecture: i686
  • Source Package: ncnn
  • 9 dependencies
  • 2 provides
  • normalized package name match
  • Matched by: Ncnn
Fedora Rawhide package metadata · dl.fedoraproject.org · Fedora Rawhide package metadata: ncnn from https://dl.fedoraproject.org/pub/fedora/linux/development/rawhide/Everything/x86_64/os/repodata/e5ca8ce900cd68f5419e1c39ae517343100b306336cbaeb70a3c153121d95094-primary.xml.zst
dnf95%

ncnn-devel 20250916-3.fc45

Development files for ncnn

https://github.com/Tencent/ncnn

sudo dnf install ncnn-devel
  • License: BSD-3-Clause AND BSD-2-Clause AND Zlib
  • Category: Unspecified
  • Architecture: i686
  • Source Package: ncnn
  • 13 dependencies
  • 3 provides
  • normalized package name match
  • Matched by: Ncnn
Fedora Rawhide package metadata · dl.fedoraproject.org · Fedora Rawhide package metadata: ncnn-devel from https://dl.fedoraproject.org/pub/fedora/linux/development/rawhide/Everything/x86_64/os/repodata/e5ca8ce900cd68f5419e1c39ae517343100b306336cbaeb70a3c153121d95094-primary.xml.zst
pacman95%

ncnn 20260113-6

High-performance neural network inference framework optimized for the mobile platform

https://github.com/Tencent/ncnn

sudo pacman -S ncnn
  • License: BSD-3-Clause
  • Architecture: x86_64
  • 6 dependencies
  • 1 optional deps
  • normalized package name match
  • Matched by: Ncnn
Arch Linux sync databases · geo.mirror.pkgbuild.com · Arch Linux sync databases: ncnn from https://geo.mirror.pkgbuild.com/extra/os/x86_64/extra.db.tar.gz
zypper95%

libncnn1 20250916-1.8

NCNN library

https://github.com/Tencent/ncnn

sudo zypper install libncnn1
  • License: BSD-2-Clause AND BSD-3-Clause AND Zlib
  • Category: System/Libraries
  • Architecture: x86_64
  • Source Package: ncnn
  • 7 dependencies
  • 2 provides
  • normalized package name match
  • Matched by: Ncnn
openSUSE Tumbleweed package metadata · download.opensuse.org · openSUSE Tumbleweed package metadata: libncnn1 from https://download.opensuse.org/tumbleweed/repo/oss/repodata/be8d3611d25469107f32075a1697e69ec57a2b850b42348a658cc671ad5ec2b50760d02c3e59524d50da9a11d5be799bdaffba2e166e8ca8858512e3c0bd665d-primary.xml.zst
zypper95%

ncnn 20250916-1.8

A high-performance neural network inference framework

https://github.com/Tencent/ncnn

sudo zypper install ncnn
  • License: BSD-2-Clause AND BSD-3-Clause AND Zlib
  • Category: Development/Tools/Other
  • Architecture: x86_64
  • Source Package: ncnn
  • 7 dependencies
  • 1 provides
  • normalized package name match
  • Matched by: Ncnn
openSUSE Tumbleweed package metadata · download.opensuse.org · openSUSE Tumbleweed package metadata: ncnn from https://download.opensuse.org/tumbleweed/repo/oss/repodata/be8d3611d25469107f32075a1697e69ec57a2b850b42348a658cc671ad5ec2b50760d02c3e59524d50da9a11d5be799bdaffba2e166e8ca8858512e3c0bd665d-primary.xml.zst
zypper95%

ncnn-devel 20250916-1.8

Development tools for ncnn

https://github.com/Tencent/ncnn

sudo zypper install ncnn-devel
  • License: BSD-2-Clause AND BSD-3-Clause AND Zlib
  • Category: Development/Libraries/C and C++
  • Architecture: x86_64
  • Source Package: ncnn
  • 2 dependencies
  • 3 provides
  • normalized package name match
  • Matched by: Ncnn
openSUSE Tumbleweed package metadata · download.opensuse.org · openSUSE Tumbleweed package metadata: ncnn-devel from https://download.opensuse.org/tumbleweed/repo/oss/repodata/be8d3611d25469107f32075a1697e69ec57a2b850b42348a658cc671ad5ec2b50760d02c3e59524d50da9a11d5be799bdaffba2e166e8ca8858512e3c0bd665d-primary.xml.zst

package graph

Links come from deterministic package relationships, av.db category and tag curation, ecosystem matches, and package hub membership.

Related tools

  • glslangRuntime dependency declared by Homebrew.
  • molten-vkRuntime dependency declared by Homebrew.
  • protobufRuntime dependency declared by Homebrew.
  • spirv-toolsRuntime dependency declared by Homebrew.
  • cmakeBuild dependency declared by Homebrew.

Same workflow

  • djl-servingShares av.db curated category or tags: cli, data, inference, machine-learning.
  • classifierShares av.db curated category or tags: cli, data, machine-learning.
  • lightgbmShares av.db curated category or tags: cli, data, machine-learning.
  • malletShares av.db curated category or tags: cli, data, machine-learning.
  • rgfShares av.db curated category or tags: cli, data, machine-learning.
  • vowpal-wabbitShares av.db curated category or tags: cli, data, machine-learning.

source trail

Generated from repository data

This page is generated by av-web from the private package SQLite artifact built by scripts/generate-pkg-sqlite.py.

Used sources

  • Geiger risk classifier
  • Nucleus package database
  • av.db category and tag curation
  • cross-ecosystem install command graph
  • curated package history
  • external package-manager database matches
  • package relationship graph
  • package version freshness
  • package-page enrichment