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
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.
Jetson Nano Module
- 128-core NVIDIA Maxwell™ GPU
- Quad-core ARM® A57 CPU
- 4 GB 64-bit LPDDR4
- 10/100/1000BASE-T Ethernet
- Micro-USB 5V 2A
- DC power adapter 5V 4A
- USB 3.0 Type A
- USB 2.0 Micro-B
- M.2 Key E
- Gigabit Ethernet
- GPIOs, I2 C, I2 S, SPI, UART
- MIPI-CSI camera connector
- Fan connector
- PoE connector
- 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.
- Jetson Nano Metal Armour - Case with PWM Adjustment Fan $9.90
- Aluminum Case for Nvidia Jetson Nano $29.90
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!
|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|
1 x NVIDIA® Jeston Nano™ Developer Kit
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Very fast and easy to get startedSuper powerful computer considering the form factor. If you dream of painting reality with AR layers, this is the type of node you would need!
ExcellentExcellent product, with excellent seller and shipment (only took 14 days), thanks
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.
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
Hobby market entry done wellCompared 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.