Jetson Orin NANO 8GB RAM Development Board based on NVIDIA Core Module for AI Deep Learning

YahboomSKU: RM-YAHB-02M
Manufacturer #: YB-A084

Price  :
Sale price $779.00

Shipping calculated at checkout

Stock  :
In stock (497 units), ready to be shipped

Payments and Security

American Express Apple Pay Diners Club Discover Google Pay Mastercard PayPal Shop Pay Venmo Visa

Your payment information is processed securely. We do not store credit card details nor have access to your credit card information.

Description

  • Jetson Orin NANO 8GB RAM Development Board
  • Based on NVIDIA Core Module for AI Deep Learning
  • Compatible with Nvidia's Jetson Orin Nano core module
  • Includes a 128GB M.2 SSD, a WiFi network card, two antennas, and a power adapter
  • Ideal for users who want to learn AI in depth or create challenging projects

The Jetson Orin NANO 8GB RAM Development Board based on NVIDIA Core Module for AI Deep Learning consists of NVIDIA's Jetson Orin Nano core module and the Jetson Orin Nano carrier board. The computing power of the 8GB board can reach 40TOPS.

The Jetson Orin Nano interface resources are optimized and upgraded, improving the performance by ~80 times compared to the entry-level Jetson Nano B01. Yahboom provides a wide range of tutorials and open source codes related to ROS and AI vision, based on the Ubuntu 20.04 system.

The performance, on-board resources, size, and interface layout of the Yahboom carrier board are consistent with the official NVIDIA carrier board. Additionally, the package includes a 128GB M.2 SSD that has already been written into the system, a WiFi network card and antenna, and a power supply, all provided free of charge.

1x Orin Nano 8GB Development Kit (SUB Version)

1x Power Adapter

1x Antenna

1x Wireless Network Card

1x 128G SSD (with system image)

Note: The NANO-SUB kit uses an external antenna, and it is recommended to use it with a case.

Customer Reviews

Be the first to write a review
0%
(0)
0%
(0)
0%
(0)
0%
(0)
0%
(0)

Estimate shipping

You may also like