Overzicht
OpenVINO converts models from supported training frameworks into a deployable representation, compiles them for a selected device, and runs optimized inference. It covers computer vision, speech recognition, natural-language processing, recommendation, diffusion, and generative AI workloads. The primary repository language is C++, while APIs are available for C++, Python, C, and Node.js.
Belangrijkste functies
- Inference optimization for computer vision, speech, NLP, generative AI, and other deep-learning workloads
- Model conversion from PyTorch, TensorFlow, ONNX, TensorFlow Lite, PaddlePaddle, and JAX/Flax
- Hugging Face Transformers and Diffusers integration through Optimum Intel
- Inference on x86 and ARM CPUs, Intel integrated and discrete GPUs, and Intel NPUs
- C++, Python, C, and Node.js APIs
- GenAI API for optimized model pipelines
- Integrations with ONNX Runtime, Keras 3, torch.compile, ExecuTorch, vLLM, LangChain, LlamaIndex, and LLMWare
- Python and C++ samples plus Python notebook tutorials
Vereisten, installatie en snel aan de slag
Gebruik
Modelcompatibiliteit en gebruiksscenario's
The README states support for models originating from PyTorch, TensorFlow, ONNX, TensorFlow Lite, Keras, PaddlePaddle, and JAX/Flax. Transformers and Diffusers models from Hugging Face can be integrated through Optimum Intel. Compatibility depends on supported models, operations, devices, and conversion paths; an exhaustive compatibility matrix is not included in the supplied record.
Licentie- en risiconotities
Apache License 2.0 (SPDX: Apache-2.0). The README states that contributions are released under the project's license and copyright terms. License reference: https://api.github.com/licenses/apache-2.0
Release en onderhoud
No specific release version or changelog entries are included in the supplied record. Release notes are available at https://docs.openvino.ai/2026/about-openvino/release-notes-openvino.html.