Developer Kits with 9th Generation Intel® Core™ Processors

Develop and deploy solutions on Intel's latest high-performance platforms.

  • Up to 46% better deep learning inference performance
  • Preinstalled tools and SDKs included on kits
  • Quick setup with preloaded samples
  • Accelerate workloads on CPUs and GPUs
  • Offload multiple workloads to optional Intel® Vision Accelerator products

Get Started   Hardware

Preinstalled Software Stack

Get the most out of your hardware performance with the Intel® Distribution of OpenVINO™ toolkit, Intel® Media SDK, Ubuntu* 18.04 desktop LTS, and libraries.

Pretrained Models for Acceleration

Choose from a variety of optimized detection and recognition models for developing deep learning applications.

Training Extensions for Deep Learning

Modify, customize, train, and extend computer vision models for deep learning and inference optimization.

Virtual Testing with Intel® DevCloud for the Edge

Quickly prototype and develop AI applications in the cloud using the latest Intel® hardware and software tools.

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IEI Flex-BX200 AIoT Developer Kit

Optional: IEI* Mustang-V100-MX8 with Intel® Vision Accelerator Design

Kit Details | Datasheet


Intel® Distribution of OpenVINO™ Toolkit

  • Enable convolutional neural network-based deep learning inference on the edge.
  • Support heterogeneous execution across various accelerators—CPU, GPU, Intel® Movidius™ Neural Compute Stick, and Intel Vision Accelerator Design products—using a common API.
  • Speed up time to market via a library of functions and preoptimized kernels.

Training | Documentation | Get Started

Free Download

Intel® Media SDK

  • Accelerate rich media performance. Speed up video playback, encoding, processing, and media formatting conversion.
  • Prototype, optimize, and productize your media pipelines with a comprehensive, convenient API.
  • Debug and customize your products quickly.

Get Started

Free Download

Intel® oneAPI Base & IoT Toolkit

The combination of Intel® oneAPI Base Toolkit and Intel® oneAPI IoT Toolkit provides developers what they need to implement efficient, reliable, cross-architecture IoT solutions that run at network’s edge. It delivers a core set of high-performance build tools and libraries and analysis tools to simplify IoT system design, development and deployment across CPU, GPU, FPGA, and other accelerator architectures.

Product and Performance Information


As measured by a ResNet-50 network with a batch size of 1 and int8 precision on Intel® Core™ i7-9700E vs. Intel® Core™ i7-7700 processor Intel® Core™ i7-9700E processor, PL1= 65 W TDP, 8C8T, Turbo up to 4.4 GHz, Intel® UHD Graphics 630, Motherboard: Asus* Prime Q370M-C, Memory: 2 times 8 GB DDR4-2666, Storage: 512 GB Intel® SSD 545s Series, OS: Ubuntu* 18.04 LTS (Bionic Beaver). Intel® Core™ i7-7700 processor, PL1=65W TDP, 4C8T, Turbo up to 4.2 GHz, Intel® HD Graphics 630, Motherboard: Asus* Prime Q270M-C, Memory: 2 times 8 GB DDR4-2400, Storage: 512 GB Intel® SSD 545s Series, OS: Ubuntu 18.04 LTS (Bionic Beaver). ResNet-50 is a popular CNN (Convoluted Neural Network) architecture that uses inception modules for computer vision recognition tasks (such as image classification). Image classification is the task of classifying a given image into one of the predefined categories. Reported metrics: Performance = Images/Second Performance results are based on testing as of May 24, 2019 and may not reflect all publicly available security updates. No product can be absolutely secure.