SKU
102110417
Rating:
95% of 100
$99.00
-
+

Join the Revolution and Bring the Power of AI to Millions of Devices. 

The NVIDIA® Jetson Nano™ Developer Kit delivers the compute performance to run modern AI workloads at an 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.

PRODUCT DETAILS

Description

The NVIDIA® Jetson Nano™ Developer Kit delivers the compute performance to run modern AI workloads at an 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

 I/O

  • USB 3.0 Type A
  • USB 2.0 Micro-B
  • HDMI/DisplayPort
  • M.2 Key E
  • Gigabit Ethernet
  • GPIOs, I2C, I2S, 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  

Changes with the B01 Kit

114992260114992261114992262114992263114992264114992265114992270
Diagonal Field of View (FOV) 77° 77° 130° 160° 160° 200° 83°
IR LED Modules None 2 None None 2 None None
Aperture 2.0 2.0 1.8 2.35 2.35 2.0 /
Focal Length 2.96mm 2.96mm 1.88mm 3.15mm 3.15mm 0.87mm 2.6mm
Lens Construction 4P 4P 4E+IR 6G+IR 6G+IR 1G4P+IR /
Distortion <1% <1% <7.6% <14.3% <14.3% <18.6% <1%
EFL 2.93mm 2.93mm 1.85mm 3.15mm 3.15mm 0.9mm /
BFL (Optical) 1.16mm 1.16mm 1.95mm 3.15mm 3.15mm 1.41mm /

Reinforce Your Projects with Grove Pi HAT

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.

 

Note

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!

Specifications

  • 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|(H.264/H.265)
  • Camera: 2x 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

Version Change Information for B01 from A02

  • The B01 revision carrier is compatible with the production specification Jetson Nano module. The A02 revision carrier is not.
  • Removed Button Header [J40] Position
  • Removed Serial Port Header [J44] Position
  • Adjusted the Position of Power Select Jumper [J48]
  • Adjusted the Position of Camera Connector [J13]
  • Added Camera Connector [J49] location
  • Factory JetPack Upgrade from 4.2 SDK to 4.3 SDK

ECCN/HTS

HSCODE 8543709990
UPC

REVIEWS

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  1. Rating
    80%
    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.
    By
  2. Rating
    100%
    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
    By
  3. Rating
    100%
    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.
    By
  4. Rating
    100%
    Excellent
    Excellent product, with excellent seller and shipment (only took 14 days), thanks
    By
  5. Rating
    100%
    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!
    By
  6. Rating
    100%
    if only the product is as good as the revues
    well the product is due to ship in a few weeks, in the meantime.....
    By
  7. Rating
    100%
    Love Seeed and LOVE the new Nvidia Nano Dev Kit
    This is my 1st experience with seeedstudio and they were fantastic from start to finish on this order. Fast DHL shipping and great communication.

    Jetson Nano review:

    Whats not to love FINALLY a NVIDIA Maxwell TX1 devkit for an affordable $99!
    By
  8. Rating
    100%
    Great product
    Regarding the hardness to use an USB camera, the board is excellent and the support for tensorflowRT is amazing,
    By
  9. Rating
    80%
    Very nice unit
    Early days still, but the Nano is going great. DHL delivery took too long, but worth the wait.
    By
  10. Rating
    80%
    Not too bad, nice package
    I'm pretty happy so far. Setting up python enviro nment a little finicky - suggest you use virtualenv.
    Don't try 16GB, you will run out of space quickly. Get a 160MB/s microSD card at least 32GB. I created a 4GB swapfile which improved dev env build speed
    By
  11. Rating
    80%
    Not too bad, nice package
    I'm pretty happy so far. Setting up python enviro nment a little finicky - suggest you use virtualenv.
    Don't try 16GB, you will run out of space quickly. Get a 160MB/s microSD card at least 32GB. I created a 4GB swapfile which improved dev env build speed
    By
  12. Rating
    100%
    Great hardware
    Nice quick quad core arm64 SBC with a decent amount of computing power available from the nVidia GPU.
    It is definitely a specialised board. While it can be used for watching videos, or running OpenGL or GLES games it's really not for that.

    It takes a while to load what it needs to utilise CUDA as a compute device, so the overhead on short tests is large. Once it is loaded it's quite fast, so it's good in real world application.

    One thing to be wary of is the OS image is set to full speed 10 watt mode, but the hardware is configured to use MicroUSB for power ie 5W mode. Either set the OS to lower power mode or use a jumper (not included) to set the board to use a higher wattage power supply via the barrel connector.
    If either of these is not done, the board will crash under load because of insufficient available curre
    By
  13. Rating
    80%
    Fast sucker
    This is hands down the fastest ARM-based device ever used with Ubuntu running on it.

    It has to use a 4amp power support like https://www.amazon.com/gp/product/B01N4HYWAM

    And also have to set the power jumper to use that jack with these
    https://www.amazon.com/gp/product/B00N552DWK
    By
  14. Rating
    100%
    Funciona perfectamente!
    Llegué temprano y estaba completamente sellado. Debido a la potencia de los gráficos, se calentará un poco, por lo que requiere un ventilador
    By
  15. Rating
    80%
    Funciona perfectamente!
    Llegué temprano y estaba completamente sellado. Debido a la potencia de los gráficos, se calentará un poco, por lo que requiere un ventilador.
    By
  16. Rating
    100%
    Great products
    It is important to connect both the usb and network when setting it up as the USB connection is used for flashing the OS onto Xavier whereas the network connection is needed for building the other Nvidia components.
    By default it runs with only 4 cores enabled and the other 4 need to be enabled.
    Note that the device gets hot and the fan does not kick in so if you added the m2 pci storage then get a small fan to cool the device as the heat will kill the m2 module.
    By
  17. Rating
    100%
    Perfect match robotics projects
    This is by far my favorite in this price range. I use object detection on 4 cameras, all at HD and motion-triggered video recording with no hiccups. Very few SBCs have the NVidia hardware-accelerated 3D built-in so this is now my goto for video analysis/recording solutions.
    By
  18. Rating
    100%
    Solid for AI study
    Nvidia provides an impressive dev board for delving into AI at an affordable price. But it does not include onboard wifi, Bluetooth or audio. However, you can get USB dongles to remedy that very easily.
    I would recommend this dev board for AI tinkering for the curious at heart.
    By
  19. Rating
    100%
    Great
    Excellent tool for my AI projects!
    By
  20. Rating
    80%
    Excellent support resources
    It is a reat unit, very powerful and flexible. Excellent support resources are available with a very helpful community.
    By
  21. Rating
    100%
    Excellent support resources.
    It is a reat unit, very powerful and flexible. Excellent support resources are available with a very helpful community.
    By
  22. Rating
    100%
    Excellent support resources.
    It is a reat unit, very powerful and flexible. Excellent support resources are available with a very helpful community.
    By
  23. Rating
    100%
    Excellent support resources.
    It is a reat unit, very powerful and flexible. Excellent support resources are available with a very helpful community.
    By
  24. Rating
    100%
    Easy setup
    Very cool mini supercomputer. Great kit for beginners in machine learning, really easy to set up and quality components from one of the best.
    By
  25. Rating
    100%
    Really good equipment,Value for the price
    Much like how Nvidia optimizes ubuntu and deploys it on this device.
    By
  26. Rating
    100%
    Really good equipment,Value for the price
    Much like how Nvidia optimizes ubuntu and deploys it on this device.
    By
  27. Rating
    100%
    Really good equipment,Value for the price
    Much like how Nvidia optimizes ubuntu and deploys it on this device.
    By
  28. Rating
    100%
    Really good equipment,Value for the price
    Much like how Nvidia optimizes ubuntu and deploys it on this device.
    By
  29. Rating
    100%
    Good CoM to learn AI
    I'm very satisfied with this CoM on price over performance, with US$99 its absolutely the best Dev Kit ever to learn Deep Learning and Computer Vision, even better it lets you run multiple neural networks in parallel for applications like image classification, object detection, and segmentation.
    Only one problem that bother me, even though it has 2 MIPI CSI camera connector, its not synchronized with each other and cannot do depth disparity, maybe in later release NVIDIA should consider about this, so we can have 3D stereo depth synchronized camera capability using these MIPI CSI connectors onboard without using special shield or hat. Cheers!
    By

FAQ