Intel

Intel OpenVINO toolkit

Apache 2.0 licensed toolkit for optimising and deploying inference across Intel CPUs, GPUs and NPUs.

Code editor showing a model optimisation script

Overview

OpenVINO converts and optimises trained models, then runs them across Intel CPUs, integrated and discrete GPUs and NPUs from a single API. It covers computer vision, general deep learning and generative workloads including diffusion models, and is developed openly on GitHub.

Typical use cases

  • AI PC and client inference
  • Industrial vision on x86
  • Model conversion and quantisation

Deployment environment

Any Intel-based edge client, industrial PC or server

Key specifications

Type
Model optimisation and inference toolkit
Licence
Apache 2.0
Targets
Intel CPUs, integrated and discrete GPUs, and NPUs
Workloads
Computer vision, deep learning, generative and diffusion models
Development
Open source, actively maintained on GitHub

Specifications taken from current manufacturer documentation and last checked on 2026-09-08.

Source: manufacturer documentation

Specifications are summarised from publicly published manufacturer material and are provided for orientation only. Always confirm current figures directly with the manufacturer before purchasing or designing in.

Developer workspace with a single-board computer, sensors and code on screen
NVIDIA

NVIDIA JetPack SDK

Official Jetson software stack combining the Linux board support package with CUDA-accelerated AI libraries.

Type
Board support package plus AI software stack
Components
Jetson Linux (bootloader, kernel, Ubuntu, drivers, OTA) and the Jetson AI stack
Targets
NVIDIA Jetson modules and developer kits
Deployment
Development host plus target Jetson device
Jetson application development
Device provisioning and updates
Robotics software stacks
Profiler output on a dark developer screen
NVIDIA

NVIDIA TensorRT

Inference compiler and runtime family that optimises models for NVIDIA GPUs, including Jetson.

Type
Inference compiler and runtime ecosystem
Components
TensorRT compiler, TensorRT-LLM, Model Optimizer, TensorRT for RTX, TensorRT Cloud
Optimisations
Graph optimisation, layer fusion, FP16 and INT8 calibration
Deployment
Jetson device, workstation or GPU server
Latency-critical inference
Local LLM serving on GPUs
Jetson deployment optimisation
Terminal showing an inference session starting
Microsoft

ONNX Runtime

MIT-licensed cross-platform inference accelerator with hardware-specific execution providers.

Type
Cross-platform inference and training accelerator
Licence
MIT
Model sources
PyTorch, TensorFlow and Keras, TensorFlow Lite, scikit-learn and others via ONNX
Deployment
Edge device, client PC or server
Cross-vendor edge deployment
AI PC applications
Server and device parity