OpenVINO is an open-source toolkit from Intel that helps developers optimize and deploy deep learning models for efficient inference on CPUs, GPUs and AI accelerators.
Key features
- Cross-platform inference: supports CPU (x86/ARM), Intel GPUs and NPUs.
- Broad framework support: works with PyTorch, TensorFlow, ONNX, Keras and integrates with Hugging Face/Optimum.
- Performance toolkit: model conversion, quantization, pruning and benchmark tools for deployment tuning.
Use cases
- Computer vision and speech inference: real-time object detection, segmentation and ASR.
- Generative AI and LLM inference: improve throughput and latency for large models on constrained hardware.
- Edge and cloud deployments: optimize models for devices from edge to data center.
Technical notes
- Multiple language APIs: C++, Python, C and NodeJS interfaces with compilation/runtime optimizations.
- GenAI support: dedicated workflows and examples for running LLMs and generative pipelines.
- Ecosystem: official tutorials, notebooks and community extensions (OpenVINO Tools, model server, sample repos).