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NVIDIA SBC Jetson Nano Version: B01 Development Kit, Quad - Core ARM A57, 4GB 128 - Core NVIDIA Maxwell GPU, 64-Bit LPDDR4

NVIDIA SBC Jetson Nano Version: B01 Development Kit, Quad - Core ARM A57, 4GB 128 - Core NVIDIA Maxwell GPU, 64-Bit LPDDR4
PB Tech price: PB Tech price:
$164 34  +GST $188 99  inc GST

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NVIDIA SBC Jetson Nano Version: B01 Development Kit, Quad - Core ARM A57, 4GB 128 - Core NVIDIA Maxwell GPU, 64-Bit LPDDR4

Get started today with the Jetson Nano Developer Kit!
Part #: SBCNV0001
3
PB Tech price: PB Tech price:
$164 34 $188 99
 +GST  inc GST


Click & Collect: Click & Collect unavailable
Delivery: Order now and it ships on 09/11/2021 When will I receive it?
Due to Alert Level 3, Auckland stores are
open for Click & Collect only

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What PB Tech customers are saying about this product...

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"Fantastic entry level device for GPU usage. Wouldn't replace your PC with it but there is nothing else like it on the market. In terms of running YOLO on it like the previous revie ...view more"

G
By: Guest 01/07/21

"excellent development board for Ai work"

G
By: Guest 20/01/21

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Features

NOTE: Recommended Micro-USB Power Supplies: Raspberry Pi 5.1V 2.5A Raspberry Pi Universal Power Supply

NOTE: PLEASE READ Jetson Nano Developer Kit User Guide CAREFRULLY BEFORE TURN IT ON!



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.

Pinout diagram for J41 expansion header on Jetson Nano developer kit

Specifications

Developer Kit Contents:

NVIDIA Jetson Nano module and carrier board
Small paper card with quick start and support information
Folded paper stand

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 Encode

4K @ 30 | 4x 1080p @ 30 | 9x 720p @ 30 (H.264/H.265)

Video Decode

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 and display port

USB

4x USB 3.0, USB 2.0 Micro-B

Others

GPIO, I2C, I2S, SPI, UART

Mechanical

69 mm x 45 mm, 260-pin edge connector

Manufacturer Part No:
-
Brand:
Product Type:
Version: B01
UPC
192876667897
Product Family:
SBC
Shipping Weight:
0.15 kg
PB Part No:
SBCNV0001
Product Model:
Jetson Nano
Warranty: 12 months *
* Warranty period is as stated above unless the manufacturer has chosen to specify a longer period.
All warranties are return to base unless otherwise specified.

Reviews

4 out of 5 Stars Based on 3 Reviews
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Displaying 1 - 3 of 3 reviews

Runs Yolo very slowly

What are most people going to do with an AI edge device? Probably run some sort of object detection. Currently the most popular object detector is Yolo. Do any of the Nvidia Jetson Nano tutorials use Yolo?, Nope. Guess why: Some Yolo models after they are converted with TensorRT, don't fit in the Nano's 4GB of RAM. Others that do fit, run like a dog i.e. 2FPS.

G
By: Guest 06/04/21
1 out of 1 user found this review helpful
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The Raspberry Pi of GPUs

Fantastic entry level device for GPU usage. Wouldn't replace your PC with it but there is nothing else like it on the market. In terms of running YOLO on it like the previous reviewer said, for starters one just allocate more swap memory and second of all that is not an edge detection algorithm. Nvidia have great tutorial content and you can definitely run real time inference (see https://github.com/dusty-nv/jetson-inference for a fantastic starter to object detection).

G
By: Guest 01/07/21
0 out of 0 users found this review helpful
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Great product

excellent development board for Ai work

G
By: Guest 20/01/21
0 out of 1 user found this review helpful
Did you find it helpful?

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