NVIDIA released a lower cost 2GB version of the NVIDIA Jetson Nano Development Kit that also includes Wifi. This new Jetson Nano Developer Kit is priced at $59 USD putting it in direct competition with the Raspberry Pi 4, and it can be pre-ordered for deliveries to start by the end of October 2020. This new board makes it more affordable for developers to get started prototyping AI and Machine Learning solutions that target the NVIDIA Jetson Nano compute module. It’s also a great board to use for hands-on learning and teaching!



NVIDIA Jetson Nano 2GB vs Raspberry Pi 4

The NVIDIA Jetson Nano 4GB Developer Kit was originally released in 2019 and it was positioned in direct competition to the Raspberry Pi in terms of performance of its ARM CPU and Memory allocation, but the price was still higher than the Raspberry Pi 4. The new NVIDIA Jetson Nano 2GB Developer Kit brings with it a few improvements that will help it compete more directly with the Raspberry Pi 4 on projects.

One advantage the NVIDIA Jetson Nano has always had above the Raspberry Pi is the dedicated GPU for running AI and Machine Learning workloads. This obviously put the NVIDIA Jetson Nano on top in regards to AI & ML work when comparing to the Raspberry Pi. However, the Raspberry Pi’s lower price was part of the distinguishing difference between the two boards; in addition to the built-in Wifi support on the Raspberry Pi 4.

One advantage the NVIDIA Jetson Nano has always had above the Raspberry Pi is the dedicated GPU for running AI and Machine Learning workloads.

With the introduction of the NVIDIA Jetson Nano 2GB Development Kit there are a couple improvements being made to the Jetson Nano Development Kit platform:

  • Lower price as $59 USD (~$40 lower than the 4G Jetson Nano) and similar to the ~$55 price of the 4G Raspberry Pi 4 and ~$40 for the 2GB Raspberry Pi 4.
  • Includes Wifi 802.11ac wireless support via included USB wireless adapter (similar to the onboard Wifi of the Raspberry Pi 4)

The NVIDIA Jetson Nano 2GB Development Kit can be purchased on Amazon, as well as a few other retailers.

Other ports and features of the NVIDIA Jetson Nano are very similar to the Raspberry Pi 4; such as booting from microSD card, 4K display support, USB ports, 40-pin GPIO, integrated Ethernet, and more. However, there are also other differences between the boards like the NVIDIA GPU on the Jetson Nano giving it much more AI and ML compute capabilities.

Related: For more information on the Ports and Connectors supported on the board, we recommend you go check out the “Discover NVIDIA Jetson Nano Developer Kit Ports and Connectors” article written by Chris Pietschmann.


NVIDIA Jetson Nano 2GB Specs Compared to 4GB version

Here’s a comparison of the specifications of the 2GB and 4GB NVIDIA Jetson Nano Development Kits:

2GB Jetson Nano 4GB Jetson Nano
GPU 128-core NVIDIA Maxwell 128-core NVIDIA Maxwell
CPU Quad-core ARMv8-A A57 @ 1.42 Ghz Quad-core ARM A57 @ 1.42 Ghz
Memory 2 GB 64-bit LPDDR4 4 GB 64-bit LPDDR4
Storage microSD microSD
Display HDMI HDMI
Camera 1x MIPI CSI-2 connector 1x MIPI CSI-2 connector
USB 1x USB 3.0 Type A, 2x USB 2.0, 1x USB 2.0 micro-B 1x USB 3.0 Type A, 2x USB 2.0, 1x USB 2.0 micro-B
Networking Integrated Ethernet, USB wireless adapter included* Integrated Ethernet, Wifi w/ add-on M.2 Key E card
Other 40-pin header (GPIO, I2C, I2S, SPI, UART), 12-pin header (Power and related signals, UART), 4-pin fan header 40-pin header (GPIO, I2C, I2S, SPI, UART), 12-pin header (Power and related signals, UART), 4-pin fan header

* USB wireless adapter not initially available in all regions

The NVIDIA Jetson Nano 2GB Development Kit can be purchased on Amazon, as well as a few other retailers.

Microsoft MVP

Chris is the Founder of Build5Nines.com and a Microsoft MVP in Azure & IoT with 20 years of experience designing and building Cloud & Enterprise systems. He is also a Microsoft Certified: Azure Solutions Architect, developer, Microsoft Certified Trainer (MCT), and Cloud Advocate. He has a passion for technology and sharing what he learns with others to help enable them to learn faster and be more productive.