NVIDIA Jetson Nano 2GB Brings Arm and CUDA for $59

NVIDIA Jetson Nano In 3D Printed Case
NVIDIA Jetson Nano In 3D Printed Case

If you saw our piece this weekend on the NVIDIA Jetson Nano 4GB, TX2, and NX Hands-on you will see NVIDIA is filling out a product line of embedded devices. At GTC 2020 (#2) the company is announcing a new lower-cost option. The NVIDIA Jetson Nano 2GB brings Arm cores together with NVIDIA GPU IP in a $59 developer board.

NVIDIA Jetson Nano 2GB

We already covered the Jetson Nano a few times. Effectively what NVIDIA is launching today is a 2GB model instead of 4GB on the standard Jetson Nano 4GB.

NVIDIA Jetson Nano 2GB Dev Kit Small
NVIDIA Jetson Nano 2GB Dev Kit Small

Taking a step back, that is an extremely expensive 2GB of memory. We have been purchasing 8GB DDR4 modules for some time in the $25 range for our Project TinyMiniMicro Home Lab series, so $40 for 2GB feels like a lot.

At the same time, as the Raspberry Pi 4 and other boards are looking to scale up memory on their platforms to get to larger and higher-value applications, NVIDIA is moving in the opposite direction halving RAM capacity. We wonder whether 2GB of memory will be enough. The system still needs to run the OS which leaves very little RAM available for applications in a 2GB footprint.

Final Words

Bringing the Jetson line into Raspberry Pi range price levels is indeed a great goal for NVIDIA. To put this in perspective, getting NVIDIA GPU cores years ago required purchasing an expensive and power-hungry GPU in many cases. Now, we can get it in a lower-end package. Still, these are still Maxwell cores versus Pascal cores in the Jetson TX2 and Volta in the Xavier NX. After Volta came Turing and now Ampere so these are four generation old cores not the latest technology.

Still, this is where the market is going and is showing more of the synergies and possible directions in NVIDIA’s plan to acquire Arm. We will work to get a review for STH readers as soon as we can of this new 2GB model and compare it to the other models we have.


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