The latest version NVIDIA® Jetson Nano™ Developer Kit-B01 with upgraded functionality is now available. There are now 2-lanes CSI, instead of the previous 1-lane on the carrier board, which allows users to easily play around with binocular vision 


Raspberry Pi Camera Module V2 is released recently, it is perfectly compatible with NVIDIA Jetson Nano Development Kit-B01. High resolution in images and videos and easy to be plugged in, get one and have the best experience for your media project.  


The NVIDIA® Jetson Nano™ Developer Kit delivers the compute performance to run modern AI workloads at unprecedented size, power, and cost. Developers, learners, and makers can now run AI frameworks and models for applications like image classification, object detection, segmentation, and speech processing.


The developer kit can be powered by micro-USB and comes with extensive I/Os, ranging from GPIO to CSI. This makes it simple for developers to connect a diverse set of new sensors to enable a variety of AI applications. It’s incredibly power-efficient, consuming as little as 5 watts.


Jetson Nano is also supported by NVIDIA JetPack, which includes a board support package (BSP), Linux OS, NVIDIA CUDA®, cuDNN, and TensorRT™ software libraries for deep learning, computer vision, GPU computing, multimedia processing, and much more. The software is even available using an easy-to-flash SD card image, making it fast and easy to get started.


The same JetPack SDK is used across the entire NVIDIA Jetson™ family of products and is fully compatible with NVIDIA’s world-leading AI platform for training and deploying AI software. This proven software stack reduces complexity and overall effort for developers. 


Key Features

 Jetson Nano Module

  • 128-core NVIDIA Maxwell™ GPU
  • Quad-core ARM® A57 CPU
  • 4 GB 64-bit LPDDR4
  • 10/100/1000BASE-T Ethernet


 Power Options

  • Micro-USB 5V 2A
  • DC power adapter 5V 4A



  • USB 3.0 Type A
  • USB 2.0 Micro-B
  • HDMI/DisplayPort
  • M.2 Key E
  • Gigabit Ethernet
  • GPIOs, I2 C, I2 S, SPI, UART
  • MIPI-CSI camera connector
  • Fan connector
  • PoE connector

 Kit Contents

  • NVIDIA Jetson Nano module and carrier board
  • Quick Start Guide and Support Guide  

Create more AI possibilities with Grove PiHAT and NVIDIA Jetson Nano

If you want to use Grove sensors with Jetson Nano, grab the grove.py Python library and get your sensors up in running in minutes! Currently, there are more than 20 Grove modules supported on Jetson Nano and we will keep adding more. You can connect Grove modules using Base HAT for Raspberry Pi or Raspberry Pi Zero with Jetson Nano.

Cooling solution for your Jetson Nano

Here we prepared the cooling solution for your Jetson Nano! Over-heating sometimes may cause a shutdown problem. These two cases will help to improve the stability of Jetson Nano.

Add A Camera

The Raspberry Pi Camera Module V2 can work with Jetson Nano well, it will be a perfect camera in your AI project.



We provide a wide selection of AI related products including Machine Learning, Computer Vision, Edge Computing, Speech Recognition & NLP and Neural Networks Acceleration. Check here for more products you may need

We are also calling for feedback and inputs from the developers. Any suggestions on the product features are welcomed at Seeed Forum!


GPU 128-core Maxwell
CPU Quad-core ARM A57 @ 1.43 GHz
Memory 4 GB 64-bit LPDDR4 25.6 GB/s
Storage microSD (not included)
Video Encoder 4K @ 30 | 4x 1080p @ 30 | 9x 720p @ 30 (H.264/H.265)
Video Decoder 4K @ 60 | 2x 4K @ 30 | 8x 1080p @ 30 | 18x 720p @ 30|
Camera 1x MIPI CSI-2 DPHY lanes
Connectivity Gigabit Ethernet, M.2 Key E
Display HDMI 2.0 and eDP 1.4
USB 4x USB 3.0, USB 2.0 Micro-B
Others GPIO, I2C, I2S, SPI, UART
Mechanical 100 mm x 80 mm x 29 mm

Part List:

1 x NVIDIA® Jeston Nano™ Developer Kit


If you are looking for open source SBC for commercial and industrial needs. Seeed provides customization service based on BeagleBone series boards. Seeed Studio BeagleBone® Green(BBG) and Seeed Studio BeagleBone® Green Wireless (BBGW) provide more stable industrial deployment scenarios.


HSCODE 8543709990
USHSCODE 8471410150



Explore and learn from Jetson projects created by us and our community. These projects will help you quickly get started with Jetson Nano.
If you want to use Grove sensors with Jetson Nano, grab the grove.py Python library and get your sensors up and running in minutes!



Write Your Own Review
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  1. Rating
    Very fast and easy to get started
    Super powerful computer considering the form factor. If you dream of painting reality with AR layers, this is the type of node you would need!
  2. Rating
    Excellent product, with excellent seller and shipment (only took 14 days), thanks
  3. Rating
    Works perfectly!
    I was impressed with all the tools that were installed and configured, and I was impressed with the performance of the graphics. Great buy & worth the money.
  4. Rating
    Great SBC!
    I am an experienced embedded guy and excited to try Jetson nano. I want to try to learn more and do more CUDA development. I was impressed with all the tools that were installed and configured, and I was impressed with the performance of the graphics. The file is very good. I like 4GB of RAM and like the ability to use a barreled power supply. I installed the file system on a (USB) SSD, which significantly improved boot time and application development
  5. Rating
    Hobby market entry done well
    Compared with my experience with the introduction of the Intel Edison, this is beautifully done. The web information is clear, organized, and skillfully edited. So far, a great learning experience.


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