# Installer openvino avec Homebrew, dnf, Nix, zypper Consultez les chemins d'installation, exécutables, métadonnées et notes de sécurité de openvino pour les workflows d'agents IA. ## installation ```sh sudo av install brew:openvino ``` Commandes d'installation supplémentaires: ### macOS - Homebrew (100%): ```sh brew install openvino ``` Preuve: local Homebrew formula metadata ### Linux - dnf (92%): ```sh sudo dnf install openvino ``` Preuve: Fedora Rawhide package metadata: openvino from https://dl.fedoraproject.org/pub/fedora/linux/development/rawhide/Everything/x86_64/os/repodata/07190dc5ae9f35ae73866675fed6d95fe6e8d9fe22c9d7cdf85862cb2ed24a4c-primary.xml.zst - Nix (92%): ```sh nix profile install nixpkgs#openvino ``` Preuve: nixpkgs package indexes: pkgs/by-name/op/openvino/package.nix from https://api.github.com/repos/NixOS/nixpkgs/git/trees/master?recursive=1 - zypper (92%): ```sh sudo zypper install libopenvino2621 ``` Preuve: openSUSE Tumbleweed package metadata: libopenvino2621 from https://download.opensuse.org/tumbleweed/repo/oss/repodata/50b07339cb64c8ed4091bdbabddadc1ff5737b090e478818a195b40d8a3292861a879139b4a3987c31109699fde9fbf4a716367ddf4eef77da75f96e3193d6ed-primary.xml.zst ## Faits du paquet - **Clé du paquet:** brew:openvino - **Gestionnaire de paquets:** Homebrew - **Version:** 2026.2.1 - **Résumé source:** Open Visual Inference And Optimization toolkit for AI inference - **Page d'accueil:** - **Dépôt:** - **Dernière mise à jour:** 2026-07-11T09:50:50+09:00 - **Généré:** 2026-08-03T19:37:03+00:00 ## exécutables - benchmark_app (alias) - ovc (alias) ## Comportement d'installation - Bouteille: non disponible ## Version et fraîcheur - page générée: 2026-08-03 - version du gestionnaire: 2026.2.1 ## Historique du projet et usages 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. ### Historique du projet 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. ### Historique d'adoption 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. ### Modes d'utilisation 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. ### Pourquoi les passionnés de paquets s'y intéressent 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. ### Chronologie - 2018: Intel releases OpenVINO as an open source toolkit for deep-learning inference deployment. - 2022: OpenVINO API 2.0 is introduced with cleaner tensor-oriented APIs and a migration path from older Inference Engine and nGraph APIs. - 2023: OpenVINO release notes add wider generative-AI model support, including Stable Diffusion and transformer-family workloads. - 2023-2024: OpenVINO GenAI, OpenVINO Model Server, JavaScript access, and NPU support broaden the toolkit beyond the original computer-vision focus. - 2026: OpenVINO documentation describes runtime support across Linux, Windows, and macOS with Python, C++, and C APIs. ### Related projects - OpenVINO is related to Intel oneAPI, OpenCV, NNCF, OpenVINO Model Server, OpenVINO GenAI, ONNX, PyTorch, TensorFlow, PaddlePaddle, JAX/Flax, and hardware plugin stacks for Intel CPU, GPU, and NPU devices. ### Sources - - - - - - - ## Notes de sécurité narrow executable package without higher-risk signals. - **Risque Geiger:** vert / faible - narrow executable package without higher-risk signals ## Autres enregistrements de gestionnaires de paquets - Nix - openvino: normalized package name match | nixpkgs package indexes: pkgs/by-name/op/openvino/package.nix from https://api.github.com/repos/NixOS/nixpkgs/git/trees/master?recursive=1 - dnf - libopenvino-auto-batch-plugin - 2026.0.0-12.fc45: normalized package name match | Fedora Rawhide package metadata: libopenvino-auto-batch-plugin from https://dl.fedoraproject.org/pub/fedora/linux/development/rawhide/Everything/x86_64/os/repodata/07190dc5ae9f35ae73866675fed6d95fe6e8d9fe22c9d7cdf85862cb2ed24a4c-primary.xml.zst | Automatic batch software plugin for OpenVINO | https://github.com/openvinotoolkit/openvino - dnf - libopenvino-auto-plugin - 2026.0.0-12.fc45: normalized package name match | Fedora Rawhide package metadata: libopenvino-auto-plugin from https://dl.fedoraproject.org/pub/fedora/linux/development/rawhide/Everything/x86_64/os/repodata/07190dc5ae9f35ae73866675fed6d95fe6e8d9fe22c9d7cdf85862cb2ed24a4c-primary.xml.zst | Auto / Multi software plugin for OpenVINO | https://github.com/openvinotoolkit/openvino - dnf - libopenvino-devel - 2026.0.0-12.fc45: normalized package name match | Fedora Rawhide package metadata: libopenvino-devel from https://dl.fedoraproject.org/pub/fedora/linux/development/rawhide/Everything/x86_64/os/repodata/07190dc5ae9f35ae73866675fed6d95fe6e8d9fe22c9d7cdf85862cb2ed24a4c-primary.xml.zst | Development files for openvino | https://github.com/openvinotoolkit/openvino - dnf - libopenvino-hetero-plugin - 2026.0.0-12.fc45: normalized package name match | Fedora Rawhide package metadata: libopenvino-hetero-plugin from https://dl.fedoraproject.org/pub/fedora/linux/development/rawhide/Everything/x86_64/os/repodata/07190dc5ae9f35ae73866675fed6d95fe6e8d9fe22c9d7cdf85862cb2ed24a4c-primary.xml.zst | Hetero plugin for OpenVINO | https://github.com/openvinotoolkit/openvino - dnf - libopenvino-intel-cpu-plugin - 2026.0.0-12.fc45: normalized package name match | Fedora Rawhide package metadata: libopenvino-intel-cpu-plugin from https://dl.fedoraproject.org/pub/fedora/linux/development/rawhide/Everything/x86_64/os/repodata/07190dc5ae9f35ae73866675fed6d95fe6e8d9fe22c9d7cdf85862cb2ed24a4c-primary.xml.zst | Intel CPU plugin for OpenVINO | https://github.com/openvinotoolkit/openvino - dnf - libopenvino-intel-gpu-plugin - 2026.0.0-12.fc45: normalized package name match | Fedora Rawhide package metadata: libopenvino-intel-gpu-plugin from https://dl.fedoraproject.org/pub/fedora/linux/development/rawhide/Everything/x86_64/os/repodata/07190dc5ae9f35ae73866675fed6d95fe6e8d9fe22c9d7cdf85862cb2ed24a4c-primary.xml.zst | Intel GPU plugin for OpenVINO | https://github.com/openvinotoolkit/openvino - dnf - libopenvino-ir-frontend - 2026.0.0-12.fc45: normalized package name match | Fedora Rawhide package metadata: libopenvino-ir-frontend from https://dl.fedoraproject.org/pub/fedora/linux/development/rawhide/Everything/x86_64/os/repodata/07190dc5ae9f35ae73866675fed6d95fe6e8d9fe22c9d7cdf85862cb2ed24a4c-primary.xml.zst | OpenVINO IR Frontend | https://github.com/openvinotoolkit/openvino - dnf - libopenvino-onnx-frontend - 2026.0.0-12.fc45: normalized package name match | Fedora Rawhide package metadata: libopenvino-onnx-frontend from https://dl.fedoraproject.org/pub/fedora/linux/development/rawhide/Everything/x86_64/os/repodata/07190dc5ae9f35ae73866675fed6d95fe6e8d9fe22c9d7cdf85862cb2ed24a4c-primary.xml.zst | OpenVINO ONNX Frontend | https://github.com/openvinotoolkit/openvino - dnf - libopenvino-paddle-frontend - 2026.0.0-12.fc45: normalized package name match | Fedora Rawhide package metadata: libopenvino-paddle-frontend from https://dl.fedoraproject.org/pub/fedora/linux/development/rawhide/Everything/x86_64/os/repodata/07190dc5ae9f35ae73866675fed6d95fe6e8d9fe22c9d7cdf85862cb2ed24a4c-primary.xml.zst | OpenVINO Paddle Frontend | https://github.com/openvinotoolkit/openvino - dnf - libopenvino-pytorch-frontend - 2026.0.0-12.fc45: normalized package name match | Fedora Rawhide package metadata: libopenvino-pytorch-frontend from https://dl.fedoraproject.org/pub/fedora/linux/development/rawhide/Everything/x86_64/os/repodata/07190dc5ae9f35ae73866675fed6d95fe6e8d9fe22c9d7cdf85862cb2ed24a4c-primary.xml.zst | OpenVINO PyTorch Frontend | https://github.com/openvinotoolkit/openvino - dnf - libopenvino-tensorflow-frontend - 2026.0.0-12.fc45: normalized package name match | Fedora Rawhide package metadata: libopenvino-tensorflow-frontend from https://dl.fedoraproject.org/pub/fedora/linux/development/rawhide/Everything/x86_64/os/repodata/07190dc5ae9f35ae73866675fed6d95fe6e8d9fe22c9d7cdf85862cb2ed24a4c-primary.xml.zst | OpenVINO TensorFlow Frontend | https://github.com/openvinotoolkit/openvino - dnf - libopenvino-tensorflow-lite-frontend - 2026.0.0-12.fc45: normalized package name match | Fedora Rawhide package metadata: libopenvino-tensorflow-lite-frontend from https://dl.fedoraproject.org/pub/fedora/linux/development/rawhide/Everything/x86_64/os/repodata/07190dc5ae9f35ae73866675fed6d95fe6e8d9fe22c9d7cdf85862cb2ed24a4c-primary.xml.zst | OpenVINO TensorFlow Lite Frontend | https://github.com/openvinotoolkit/openvino - dnf - openvino - 2026.0.0-12.fc45: normalized package name match | Fedora Rawhide package metadata: openvino from https://dl.fedoraproject.org/pub/fedora/linux/development/rawhide/Everything/x86_64/os/repodata/07190dc5ae9f35ae73866675fed6d95fe6e8d9fe22c9d7cdf85862cb2ed24a4c-primary.xml.zst | Toolkit for optimizing and deploying AI inference | https://github.com/openvinotoolkit/openvino - dnf - openvino-samples - 2026.0.0-12.fc45: normalized package name match | Fedora Rawhide package metadata: openvino-samples from https://dl.fedoraproject.org/pub/fedora/linux/development/rawhide/Everything/x86_64/os/repodata/07190dc5ae9f35ae73866675fed6d95fe6e8d9fe22c9d7cdf85862cb2ed24a4c-primary.xml.zst | C and C++ samples for OpenVINO | https://github.com/openvinotoolkit/openvino - dnf - python3-openvino - 2026.0.0-12.fc45: normalized package name match | Fedora Rawhide package metadata: python3-openvino from https://dl.fedoraproject.org/pub/fedora/linux/development/rawhide/Everything/x86_64/os/repodata/07190dc5ae9f35ae73866675fed6d95fe6e8d9fe22c9d7cdf85862cb2ed24a4c-primary.xml.zst | OpenVINO Python API | https://github.com/openvinotoolkit/openvino ## Combined YAML source View the package source record on GitHub. [combined/openvino.yml](https://github.com/mxcl/pkgdb/blob/main/combined/openvino.yml) ## Sources - pkg.so package database - Geiger risk classifier - curated package history - pkgdb category and tag curation - external package-manager database matches - cross-ecosystem install command graph