NVIDIA Jetson AGX Xavier Developer Kit (32GB)

Kind of silly even having reviews on these Jetson products. It's Nvidia Jetson. Great stuff. It is what it is. If you're not an engineer and don't know what this is for already, don't buy one! The negative reviews on these products are hysterical. Nvidia did a super job designing this hardware, it comes complete with solid examples and support, I'm a hardware systems guy, not software, and I still got it up and running without any issues and was able to build and benchmark their examples on the CUDA cores. I was able to build and run an existing FFTW benchmark that uses the Linux cores, and then compare that to the CUDA cuFFT examples to see the improvement--really awesome and impressive product!

Overall, I like Agx Xiavier a lot better because it allows me to develop as if I am on a regular desktop. The nano is just way too slow and it even have hard time running VScode.I got a bad board on my first purchase. It does run but crashes randomly when left idle. The log message from the system indicates "kernel oops". After digging through NVIDIA forum, I was sure I got a lemon. In addition to crash problem, the fan is making an random "clicking" noise. At first I am not sure if this is a typical thing for PWM fans but after I made my second purchase I know for sure that is abnormal. If your fan does not produce a consistent sound, something might be wrong.Here is my advice to make sure your board is good. After you receive the product, load the OS, attach internet, open a browser text editor or something, and let it sit for at least 6 hours or more (over night is better). After that, if there is no sign of rebooting, then you should be good to go. If you do notice rebooting, check if there is any kernel crash file under "/var/log". Open crash file and search for "kernel oops". If it does show up, don't waste your time and just return the product.

First, I own a few Jetson products. I have a few Nanos and they are great for the price, but as I am using python and tensorflow, it takes a TON of RAM and starts a lot of processes (duplicating the RAM usage). Not sure what is going on, but that is a tensorflow problem, not an Nvidia problem. I bought this unit to run many AI models in parallel, and with the memory issues I needed a lot of RAM. If you have low memory usage and are not training models with the device, go with one of the cheaper Jetsons. The Nano is a great value and does AI prediction extremely well. I am using a tornado server and am evaluating three networks in less than 50ms.I am not a typical use case for this device. I wouldn't say this is a bad buy, but unless you need the RAM, go with the lower models which are amazing for the price. Train your models on a 2070 or higher (if you want speed of the tensor cores).UPDATE: I am now running a docker swarm with the Nanos and the Xavier. I got the RAM under control and my findings are this: for simple AI prediction I am getting about 2x the performance of the Nanos and double the RAM usage (as TF starts processes by core count and this is 8 vs 4 on Nano). For my small neural networks, this is overkill. I still think this is an amazing device, I just don't require the power at this time. This unit does get very warm. Also, it does NOT auto power on when you have an electrical event. There is a way to jumper some pins to get it to auto power on but I haven't done it yet. If you are training networks or doing video AI this is the Jetson for you. If you are doing less frequent prediction and don't need the RAM, get the NX.

This device is screaming with potential!It's the current state of Linux ARM64 at it's finest.It's rough, you'll end up compiling many things from source, and you'll find a lot of things won't work.But what works is amazing, I cannot believe the amount of raw power this device has at 30W!Also, unit currently ship with "quiet" mode on and it will passively cool with noticeable throttling.Very quiet running on "cool" mode with great performance.- Shawn Khameneh