Jetson Xavier NX is based on the Xavier SoC and is pin-compatible with the Nano form-factor. It has 10/15W power modes, with up to 21 TOPS of AI performance. High-level features and specifications include:
384-core Volta GPU with 48 Tensor Cores
6-core NVIDIA Carmel 64-bit ARMv8.2 CPU
8GB 128-bit LPDDR4x @ 1600MHz | 51.2GB/s
Dual NVIDIA Deep Learning Accelerators
260-pin SODIMM edge connector, 70x45mm
10W / 15W modes, 5V input
The Jetson Xavier NX module is available for order now for $399 USD in volume and will be available March 2020 the 2nd half of April 2020. You can also get started today with the Jetson AGX Xavier Developer Kit and a patch for JetPack that emulates the configuration of the Jetson Xavier NX. Documentation and design collateral for Jetson Xavier NX is also available to download through the URL below and the following list:
As with the commercial Nano module, the Xavier NX module will ship without a TTP, and like previous Jetson’s we will make a thermal design guide available in addition to the module CAD model which is already available. Ecosystem partners may also offer cooling solutions for the Xavier NX module like they have with the Nano module.
We don’t have info to share about a devkit at this time, but for now it is recommended to get started with the Jetson AGX Xavier devkit for software development using the emulation patch, and since Xavier NX is pin-compatible with Nano, you can use the Nano form-factor as a hardware reference in addition to the Xavier NX hardware design docs and collateral listed above.
Would anyone explain the reason why the Xaiver NX is better AI DL performance than Xavier 8GB even though the number of CPU and GPU cores are the same and the memory performance of Xavier is better than NX?
NX: 21 TOPS
Xavier 8GB: 20 TOPS https://developer.nvidia.com/embedded/develop/hardware