OpenVINO

What it does

OpenVINO is an open source toolkit for AI inference. It takes models trained with popular frameworks such as TensorFlow and PyTorch, converts and optimizes them, and deploys them across Intel hardware and environments, including on-premise, on-device, in the browser, or in the cloud. It aims to deliver lower latency and higher throughput while maintaining accuracy and reducing model footprint, for computer vision, large language model, and generative AI workloads.

Teams typically use it as a development toolkit: convert a trained model, optimize it with the included model optimizer and runtime, and then deploy it. Supporting resources include Jupyter Notebook workshops, benchmark graphs, documentation, and a collection of open-source AI Reference Kits with ready-to-use notebooks and sample applications. It is powered by oneAPI.

OpenVINO suits developers and teams building or deploying AI models on Intel hardware who want an open source option. The toolkit itself is offered as a free download. Buyers should verify the cost of the compute and models used at run time, and confirm that their target hardware is supported.

What it can do

• Convert and optimize models trained with TensorFlow and PyTorch
• Deploy inference across Intel hardware, on-premise, on-device, browser, or cloud
• Accelerate computer vision, LLM, and generative AI inference
• Provide a runtime and development tools via the included model optimizer

Before you choose

• Hardware fit: the toolkit emphasizes Intel hardware; confirm your target devices are supported.
• Run-time costs: compute and model costs for deployment must be verified separately from the free toolkit download.
• Support channels include a community forum, GitHub issues, and Intel Support.

Listed under

• Coding
• AI inference
• Computer vision
• Deep learning
• Developers
• Edge AI
• Generative AI

Get started

Free download, with a Get Started guide.

1. Review the Get Started guide to learn the toolkit basics.
2. Download the free OpenVINO toolkit from the download page.
3. Convert a model trained in TensorFlow or PyTorch and run it with the included runtime; try the Jupyter Notebook samples.

The toolkit download is free. Compute and model costs for running deployed applications are separate and should be verified by the buyer.

OpenVINO is free to use. See their pricing page ↗

Sources for this overview

Product pages, documentation, and pricing checked 30 Oct 2026. Each source supports part of the overview; availability and prices can change.

• Intel® Distribution of OpenVINO™ Toolkit ↗www.intel.com
• Explore Intel® Artificial Intelligence Solutions ↗www.intel.com
• How to Implement Retrieval-Augmented Generation (RAG) – Intel ↗www.intel.com
• Intel Inside - Built for AI ↗www.intel.com

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intel.com: product, pricing and policy pages

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Last checked 30 Oct 2026. Every field keeps its source and date; unknown means we couldn’t confirm it.