{"categories":[{"label":"Software Development","url":"https://skillfed.io/packages/category/software-development/17"},{"label":"Libraries","url":"https://skillfed.io/packages/category/software-development-libraries/9"},{"label":"Scientific/Engineering","url":"https://skillfed.io/packages/category/scientific-engineering/8"},{"label":"Python Modules","url":"https://skillfed.io/packages/category/software-development-libraries-python-modules/20"},{"label":"Artificial Intelligence","url":"https://skillfed.io/packages/category/scientific-engineering-artificial-intelligence/10"},{"label":"Mathematics","url":"https://skillfed.io/packages/category/scientific-engineering-mathematics/3"}],"enrichment":{"capability":"Enables ONNX Runtime to accelerate machine learning model inference on Intel hardware (CPUs, integrated/discrete GPUs, and NPUs) using OpenVINO optimizations.","skillfed_tags":["inference-acceleration","intel-hardware","onnx-runtime"],"use_cases":["Accelerate ONNX model inference on Intel CPUs or integrated GPUs without changing application code","Deploy ML models to Intel discrete GPU hardware for higher throughput inference workloads","Route inference to Intel integrated NPUs on supported platforms to reduce power consumption","Optimize existing ONNX Runtime applications for Intel hardware with minimal refactoring"],"what_it_does":"onnxruntime-openvino is an execution provider plugin for ONNX Runtime that routes inference workloads to Intel hardware accelerators. It integrates OpenVINO inline optimizations into ONNX Runtime with minimal code changes\u2014typically a single provider argument\u2014enabling developers to accelerate ONNX models across Intel CPUs, integrated GPUs, discrete GPUs, and integrated NPUs without rewriting inference logic.\n\nThe package ships with prebuilt OpenVINO libraries on Linux (version 2025.4.1), eliminating separate installation steps there; Windows users must install OpenVINO separately. It supports Python 3.11\u20133.14 on 64-bit Linux and Windows, and depends on flatbuffers, numpy, packaging, protobuf, and sympy for runtime operation.","worth_installing":"Yes, if you run ONNX models on Intel hardware and want to accelerate inference with minimal code changes. The permissive MIT license, active maintenance, and inclusion of prebuilt OpenVINO libraries on Linux reduce friction. Windows users should verify OpenVINO installation requirements before committing. No known security vulnerabilities as of the query date."},"id":"onnxruntime-openvino","links":{"html":"https://skillfed.io/packages/onnxruntime-openvino","md":"https://skillfed.io/packages/onnxruntime-openvino.md","pypi":"https://pypi.org/project/onnxruntime-openvino/"},"maintenance":{"status":"active"},"meta":{"latest_release":"2026-02-26","license_spdx":null,"license_treatment":"permissive","name":"onnxruntime-openvino","python_support":"supports_current","summary":"ONNX Runtime is a runtime accelerator for Machine Learning models"},"popularity":{"monthly_downloads":98109,"position":13108,"tier":"top_15000"},"security":{"n_vulnerabilities":0},"version":"1.24.1"}