Install openvino with Homebrew

Project links

• Homepage
• Repository

Commands and aliases

• benchmark_app
• ovc

Project history

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.

Adoption history

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.

How it is used

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.

Why package nerds care

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.

Timeline

• 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

• https://docs.openvino.ai/
• https://docs.openvino.ai/2024/about-openvino.html
• https://github.com/openvinotoolkit
• https://github.com/openvinotoolkit/openvino
• https://www.intel.com/content/www/us/en/developer/articles/release-notes/openvino/2022-2.html
• https://www.intel.com/content/www/us/en/developer/articles/release-notes/openvino/2023-1.html
• https://www.intel.com/content/www/us/en/developer/articles/release-notes/openvino/2024-1.html