NVIDIA Jetson Nano Development Kit-B01
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NVIDIA Jetson Nano Development Kit-B01

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$159.99 $208.99
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Tip
Raspberry Pi Camera Module V2 is released recently, it is perfectly compatible with NVIDIA Jetson Nano Developer Kit. High resolution in images and videos and easy to be plugged in, get one and have the best experience for your media project.
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, 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.

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

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!
Specification
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: 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

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