macOS
brew install openvinolocal Homebrew formula metadata
brew
Open Visual Inference And Optimization toolkit for AI inference. Version 2026.2.1 via Homebrew; verified 2026-06-20.
install
brew install openvinolocal Homebrew formula metadata
sudo dnf install intel-npu-compilerFedora Rawhide package metadata · intel-npu-compiler · source: dl.fedoraproject.org
nix profile install nixpkgs#openvinonixpkgs package indexes · pkgs/by-name/op/openvino/package.nix · source: api.github.com
sudo zypper install libopenvino2620openSUSE Tumbleweed package metadata · libopenvino2620 · source: download.opensuse.org
overview
Open Visual Inference And Optimization toolkit for AI inference
history
OpenVINO, short for Open Visual Inference and Neural Network Optimization, is Intel's open source toolkit for optimizing and deploying AI inference. It grew from a computer-vision inference toolkit into a broader runtime for conventional deep learning, generative AI, model serving, and Intel CPU, GPU, and NPU deployment.
Intel introduced OpenVINO as a distribution for taking trained neural-network models and running them efficiently on Intel hardware. The project standardized a workflow around model conversion, graph optimization, a runtime API, and device plugins rather than training models from scratch.
Early OpenVINO packaging centered on the Model Optimizer and Inference Engine. The 2022 release line introduced OpenVINO API 2.0, aligning inputs and outputs more closely with common framework tensor conventions while retaining older Inference Engine and nGraph APIs during the transition.
The 2023 and 2024 release notes show the toolkit expanding beyond classic computer vision into speech, recommendation systems, natural language processing, Stable Diffusion, transformer models, LLM-oriented optimizations, OpenVINO GenAI, model-serving workflows, JavaScript access, and NPU support for Intel Core Ultra systems.
OpenVINO's adoption path follows Intel's hardware platform strategy: give developers one inference API and deployment stack across laptops, edge devices, servers, and AI PCs. The public GitHub organization includes the main runtime, NNCF compression tooling, notebooks, GenAI libraries, and OpenVINO Model Server, which indicates a package family rather than a single binary.
It became a package-manager concern because AI applications increasingly need native runtimes, Python wheels, CLI tools such as ovc and benchmark_app, device plugins, and framework bridges. OpenVINO packages are used by developers who want to benchmark models, convert framework artifacts, reduce inference cost with quantization or compression, and deploy on Intel hardware without binding directly to one training framework.
Developers use OpenVINO to load or convert models from frameworks such as PyTorch, TensorFlow, ONNX, TensorFlow Lite, PaddlePaddle, and JAX/Flax; optimize or compress them; then run inference through C++, Python, C, Node.js, server, or GenAI APIs. Operators also use benchmark_app to measure throughput and latency on target devices.
The package is most visible in edge AI, AI PC, industrial vision, local LLM, and model-serving workflows where deployment constraints matter more than model training.
OpenVINO is the kind of package that turns dependency management into hardware enablement: a formula or distro package can decide whether an AI app has CPU, GPU, or NPU acceleration and whether model artifacts from several ML ecosystems can share one runtime.
It is also a moving example of AI packaging churn: native C++ libraries, Python and JavaScript bindings, command-line converters, release-year documentation, and device plugins all need to stay aligned.
security posture
narrow executable package without higher-risk signals.
green risk · low confidence · appliance
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 |
|---|---|---|---|
benchmark_app | cli | global executable | |
ovc | 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/openvinotoolkit/openvino
install metadata
| Package key | brew:openvino |
|---|---|
| Version | 2026.2.1 |
| Package manager | Homebrew |
| Package manager page | https://formulae.brew.sh/formula/openvino |
| Homepage | https://docs.openvino.ai |
| Repository | https://github.com/openvinotoolkit/openvino |
| Upstream docs | https://docs.openvino.ai/ |
| License | Apache-2.0 |
| Source archive | https://github.com/openvinotoolkit/openvino/archive/refs/tags/2026.2.1.tar.gz |
| Last updated | 2026-06-20T05:07:44Z |
| Pulse | updated |
| Dependencies | abseil, nlohmann-json, numpy, onnx, protobuf, pugixml, snappy, tbb |
| Build dependencies | cmake, flatbuffers, pkgconf, pybind11, python@3.14, scons |
| 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 | openvino |
| Version Scheme | 0 |
| Revision | 1 |
| 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.
openvino
nix profile install nixpkgs#openvinointel-npu-compiler 2025.1.0-14.fc44
OpenVINO NPU Compiler
https://github.com/openvinotoolkit/openvino
sudo dnf install intel-npu-compilerlibopenvino-ir-frontend 2025.1.0-14.fc44
OpenVINO IR Frontend
https://github.com/openvinotoolkit/openvino
sudo dnf install libopenvino-ir-frontendlibopenvino-onnx-frontend 2025.1.0-14.fc44
OpenVINO ONNX Frontend
https://github.com/openvinotoolkit/openvino
sudo dnf install libopenvino-onnx-frontendlibopenvino-paddle-frontend 2025.1.0-14.fc44
OpenVINO Paddle Frontend
https://github.com/openvinotoolkit/openvino
sudo dnf install libopenvino-paddle-frontendlibopenvino-pytorch-frontend 2025.1.0-14.fc44
OpenVINO PyTorch Frontend
https://github.com/openvinotoolkit/openvino
sudo dnf install libopenvino-pytorch-frontendlibopenvino-tensorflow-frontend 2025.1.0-14.fc44
OpenVINO Tensorflow Frontend
https://github.com/openvinotoolkit/openvino
sudo dnf install libopenvino-tensorflow-frontendlibopenvino-tensorflow-lite-frontend 2025.1.0-14.fc44
OpenVINO Tensorflow-lite Frontend
https://github.com/openvinotoolkit/openvino
sudo dnf install libopenvino-tensorflow-lite-frontendopenvino 2025.1.0-14.fc44
Toolkit for optimizing and deploying AI inference
https://github.com/openvinotoolkit/openvino
sudo dnf install openvinoopenvino-devel 2025.1.0-14.fc44
Development files for openvino
https://github.com/openvinotoolkit/openvino
sudo dnf install openvino-developenvino-plugins 2025.1.0-14.fc44
OpenVINO Plugins
https://github.com/openvinotoolkit/openvino
sudo dnf install openvino-pluginspython3-openvino 2025.1.0-14.fc44
OpenVINO Python API
https://github.com/openvinotoolkit/openvino
sudo dnf install python3-openvinolibopenvino2620 2026.2.0-1.1
Shared library for OpenVINO toolkit
https://github.com/openvinotoolkit/openvino
sudo zypper install libopenvino2620libopenvino_c2620 2026.2.0-1.1
Shared C library for OpenVINO toolkit
https://github.com/openvinotoolkit/openvino
sudo zypper install libopenvino_c2620libopenvino_ir_frontend2620 2026.2.0-1.1
Paddle frontend for Intel OpenVINO toolkit
https://github.com/openvinotoolkit/openvino
sudo zypper install libopenvino_ir_frontend2620libopenvino_onnx_frontend2620 2026.2.0-1.1
Onnx frontend for OpenVINO toolkit
https://github.com/openvinotoolkit/openvino
sudo zypper install libopenvino_onnx_frontend2620source trail
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