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NVIDIA Jetson Nano 4GB Developer Kit

The  NVIDIA Jetson Nano Developer Kit is a compact, powerful, and accessible entry point into the world of Artificial Intelligence. Makers, students, and developers can run advanced AI frameworks and machine learning models with ease. Simply insert a microSD card with the system image, power the board, and start building intelligent applications.

999.00 AED 999.00 AED Tax Included
999.00 AED Tax Included

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With its integrated system-on-chip (SoC), the Jetson Nano can run multiple neural networks in parallel. It supports popular AI frameworks such as TensorFlow, PyTorch, Caffe/Caffe2, Keras, and MXNet. This enables powerful AI functions like image classification, object detection, segmentation, and speech processing—ideal for robotics, smart devices, automation systems, and advanced AI projects.

Features

  • Supports multiple AI frameworks and neural networks in parallel
  • Capable of real-time image and video processing
  • Includes camera support and multiple display output options
  • Various peripheral connectivity options: PCIe, USB, SPI, I2C, I2S, GPIO
  • Low power consumption with high performance for edge AI projects
  • Suitable for robotics, autonomous vehicles, and smart surveillance systems
  • Supports integration with sensors, actuators, and external hardware

 

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Specifications

  • GPU: 128-core NVIDIA Maxwell GPU
  • CPU: Quad-core ARM A57
  • Memory: 4 GB 64-bit LPDDR4
  • Storage: 16 GB eMMC 5.1 flash
  • Video Encoder: 4K @ 30 fps (H.264/H.265)
  • Video Decoder: 4K @ 60 fps (H.264/H.265)
  • Camera Interface: 12 lanes MIPI CSI-2 (1.5Gbps)
  • Connectivity: Gigabit Ethernet
  • Display Options: HDMI 2.0, DP 1.2, eDP 1.4, DSI (1x2)
  • Peripheral Connectivity: PCIe, USB 3.0, USB 2.0, SPI, I2C, I2S, GPIO
  • Dimensions: 100 × 80 × 29 mm

Usage Notes

This developer kit is ideal for learning AI concepts, experimenting with machine learning models, and building smart embedded projects. It supports hardware-accelerated deep learning and can run multiple neural networks simultaneously. Recommended for users interested in computer vision, autonomous robotics, image classification, and real-time data processing.