![NVIDIA Jetson AGX Orin Developer Kit, Nano ITX]({"https://m.media-amazon.com/images/I/714DRkY4EkL._AC_SS115_.jpg":[115,115],"https://m.media-amazon.com/images/I/714DRkY4EkL._AC_SS230_.jpg":[230,230],"https://m.media-amazon.com/images/I/714DRkY4EkL._AC_SS345_.jpg":[345,345]})
![Makeronics Developer Kit for Jetson Nano -7inch Touch| IMX 219-77 Camera with Case| 64GB Class 10 TF Card with Card Reader |]({"https://m.media-amazon.com/images/I/718XRDRhH9L._AC_SS115_.jpg":[115,115],"https://m.media-amazon.com/images/I/718XRDRhH9L._AC_SS230_.jpg":[230,230],"https://m.media-amazon.com/images/I/718XRDRhH9L._AC_SS345_.jpg":[345,345]})
![NVIDIA 945-82771-0000-000 Jetson TX2 Development Kit,Black]({"https://m.media-amazon.com/images/I/916hJaWBVKL._AC_SX569_.jpg":[427,569],"https://m.media-amazon.com/images/I/916hJaWBVKL._AC_SX355_.jpg":[266,355],"https://m.media-amazon.com/images/I/916hJaWBVKL._AC_SX522_.jpg":[392,522],"https://m.media-amazon.com/images/I/916hJaWBVKL._AC_SX679_.jpg":[509,679],"https://m.media-amazon.com/images/I/916hJaWBVKL._AC_SX450_.jpg":[338,450],"https://m.media-amazon.com/images/I/916hJaWBVKL._AC_SX466_.jpg":[350,466],"https://m.media-amazon.com/images/I/916hJaWBVKL._AC_SX425_.jpg":[319,425]})
![Waveshare Accessory Compatible with Raspberry Pi 4 Model B 4GB RAM with Powerful Processor Faster Networking Support Dual 4K]({"https://images-na.ssl-images-amazon.com/images/I/71Mpsx2f0WL._AC_UL165_SR165,165_.jpg":[165,165],"https://images-na.ssl-images-amazon.com/images/I/71Mpsx2f0WL._AC_UL330_SR330,330_.jpg":[330,330],"https://images-na.ssl-images-amazon.com/images/I/71Mpsx2f0WL._AC_UL495_SR495,495_.jpg":[495,495]})
![Amlogic A311D2 Single Board Computer-khadas VIM4 with 3.2 Tops NPU with Active Cooling Kit Supports 4K UI and HDMI Input, 4 D]({"https://images-na.ssl-images-amazon.com/images/I/81OE4WU74EL._AC_UL165_SR165,165_.jpg":[165,165],"https://images-na.ssl-images-amazon.com/images/I/81OE4WU74EL._AC_UL330_SR330,330_.jpg":[330,330],"https://images-na.ssl-images-amazon.com/images/I/81OE4WU74EL._AC_UL495_SR495,495_.jpg":[495,495]})
![Raspberry Pi 400 Unit - US]({"https://images-na.ssl-images-amazon.com/images/I/61KlnD5eE2L._AC_UL165_SR165,165_.jpg":[165,165],"https://images-na.ssl-images-amazon.com/images/I/61KlnD5eE2L._AC_UL330_SR330,330_.jpg":[330,330],"https://images-na.ssl-images-amazon.com/images/I/61KlnD5eE2L._AC_UL495_SR495,495_.jpg":[495,495]})
![Raspberry Pi 4 Model B (8gb)]({"https://images-na.ssl-images-amazon.com/images/I/51MBHS4+IkL._AC_UL165_SR165,165_.jpg":[165,165],"https://images-na.ssl-images-amazon.com/images/I/51MBHS4+IkL._AC_UL330_SR330,330_.jpg":[330,330],"https://images-na.ssl-images-amazon.com/images/I/51MBHS4+IkL._AC_UL495_SR495,495_.jpg":[495,495]})
![16GB eMMC Module for NanoPi M4/NanoPi K2 Single Board Computer]({"https://images-na.ssl-images-amazon.com/images/I/51ERYD+h5bL._AC_UL165_SR165,165_.jpg":[165,165],"https://images-na.ssl-images-amazon.com/images/I/51ERYD+h5bL._AC_UL330_SR330,330_.jpg":[330,330],"https://images-na.ssl-images-amazon.com/images/I/51ERYD+h5bL._AC_UL495_SR495,495_.jpg":[495,495]})
![Waveshare Accessory Compatible with Raspberry Pi 4 Model B 2GB RAM with Powerful Processor Faster Networking Support Dual 4K]({"https://images-na.ssl-images-amazon.com/images/I/71LyOcmPOZL._AC_UL165_SR165,165_.jpg":[165,165],"https://images-na.ssl-images-amazon.com/images/I/71LyOcmPOZL._AC_UL330_SR330,330_.jpg":[330,330],"https://images-na.ssl-images-amazon.com/images/I/71LyOcmPOZL._AC_UL495_SR495,495_.jpg":[495,495]})
This is the cutting edge AI deep learning single board processor based on NVidia GPU technology which happens to be very nicely optimized for various forms of AI. For what it is, it's amazing.
Some of the other reviews are making me laugh. What this is NOT (or at least not its strength):
* It's not a general purpose computer - if that's what you're looking for, don't buy this
* It's not a raspberry pi like device - if that's what you're looking for, don't buy this
* It's not a highly user friendly gadget - if that's what you're looking for, don't buy this
It's somewhat harder for beginners to use, but even f you've never trained a deep learning net and never used one for classification, you might still buy this.
I'm using this to run (and even train) deep nets for image recognition using Tensorflow. The nets were originally trained using Tensorflow using Amazon AWS computers. The nets transferred flawlessly (but with some effort) to the TX2. For that, this is an amazing processor.
At this point, I've thrown away the motherboard and mounted the TX2 on a different carrier (orbitty).
| Standing screen display size | 0.7 Inches |
|---|---|
| Max Screen Resolution | 4K Pixels |
| Processor | 1.2 GHz tegra_4 |
| Memory Speed | 60 MHz |
| Hard Drive | Flash Memory Solid State |
| Chipset Brand | nvidia |
| Graphics Card Ram Size | 58.3 GB |
| Wireless Type | Bluetooth |
