Nvidia Jetson Nano Vs Google Coral

Google coral edge tpu vs nvidia jetson nano.

Nvidia jetson nano vs google coral. Otherwise if it is standard object detection or classification then the edge tpu wins. Nvidia google and intel. Perhaps unsurprisingly results show that the two dedicated boards the coral dev board from google and the jetson nano developer kit from nvidia are the best performing out of our surveyed. Since the topics machine learning and artificial intelligence in general are growing bigger and bigger dedicated ai hardware starts popping up from a number of companies.

Looks like the jetson nano is good if you have a really non standard use case that won t run on the edge tpu. Posted by 1 year ago. The board comes with ubuntu 18 04 based environment. Nvidia jetson nano vs google coral vs intel ncs.

Original article was published on artificial intelligence on medium. Google edge tpu coral vs. According to nvidia docs nano can do 472 gflops gigaflops per second and supports 5w and 10w power consumption modes. To get an overview over the current state of ai platforms we took a closer look at two of them.

Nano has more ram 4gb ram vs 1gb better cpu and probably gpu and runs ubuntu. At the gtc conference in san jose nvidia has announced jetson nano an edge computing platform to run machine learning and ai models with a price tag of 99 jetson nano developer kit is the most. The jetson som is slightly bigger 69 6 mm x 45 mm. For some applications more than 4 fps could also be a good performance metric considering the cost difference.

A quick deep dive into edgeai performance. It is evident from the latency point of view nvidia jetson nano is performing better 25 fps as compared to 9 fps of google coral and 4 fps of intel ncs. Nvidia s jetson nano and google s new coral usb accelerator. Who is in the race.

Movidius ncs with raspberry pi vs. The coral is more like a raspberry pi with an ai accelerator while the jetson nano is more like a mini computer. Nvidia jetson nano models. More importantly you can use full size tensorflow models while the coral only accepts tensorflow lite.

Nvidia jetson nano dev kit.