At 70 mm x 45 mm, Jetson Xavier NX packs the power of the NVIDIA Xavier SoC into a module the size of a Jetson Nano™. This compact module combines exceptional performance and power advantage with a rich set of IOs—from high-speed CSI and PCIe to low-speed I2Cs and GPIOs. Take advantage of the small form factor, sensor-rich interfaces, and big performance to bring new capabilities to all your embedded AI and edge systems. Jetson Xavier NX delivers up to 21 TOPS, making it ideal for high-performance computing and AI in embedded and edge systems.
You get the performance of 384 NVIDIA CUDA® Cores, 48 Tensor Cores, 6 Carmel ARM CPUs, and two NVIDIA Deep Learning Accelerators (NVDLA) engines. Combined with over 59.7GB/s of memory bandwidth, video encoded and decoded, these features make Jetson Xavier NX the platform of choice to run multiple modern neural networks in parallel and process high-resolution data from multiple sensors simultaneously.
Powerful carrier board and heatsink
The NVIDIA® Jetson Xavier NX™ module has assembled with a carrier board and cooling fan and they together called a ‘Kit’. It brings supercomputer performance to the edge. It includes a Jetson Xavier NX module for developing multi-modal AI applications with the NVIDIA software stack in as little as 10 W. You can also now take advantage of cloud-native support to more easily develop and deploy AI software to edge devices.
The kit is supported by the entire NVIDIA software stack, including accelerated SDKs and the latest NVIDIA tools for application development and optimization. Meanwhile, we install a Wifi module (M.2 KEY E), 128GB SSD(M.2 M NVME), and two antennas. Users could just power the product, log in, and use it directly.
Compatible enclosure
With an overall dimension of 130mm*120mm*50mm, it is only around 1/10 of the size of an ordinary computer case which makes it possible to be placed on a table, on a shelf, or on any surface you want it to be. The back screw holes allow you to hang the product on the back of your Computer Screen. The neat structure of our mini PC kit also makes it simple to access the SSD and PCIe slots which allow for easy installation, upgrade, and maintenance.
Ready for development
Jetson Sub Mini PC is pre-installed with Jetpack, 128GB SSD, the full system ideal for developing AI systems deployed at smart factories, automated optical inspection, and other AIoT embedded systems with an entire Jetson software stack and various developer tools for building fast and robust AI applications provided by Seeed Edge AI partners.
Edge Deployment made easy
Jetson Sub Mini PC built with Jetson Xavier NX module supports alwaysAI Accelerated Edge Deployment. You can train a brand new custom model just in hours, or you can even use choose one of 130+ pre-trained models from the always dashboard, deploy it to edge devices, and build a computer vision application within minutes! alwaysAI removes barriers to machine learning expertise requirements and makes creating computer vision apps easy, fast and effective.
With the deployment engine, you can OTA containerization and device monitoring in production mode, Run the application in offline mode and Auto-start the application on boot.
With an extensive library of Python APIs, you can also customize any AI application, and also push real-time analytics to platforms such as Data Lakes and BI tools for further data visualization.
Documentation
Highlighted Features
- Compact design for a mini PC with an overall dimension of 130mm*120mm*50mm
- Powered by the6-core NVIDIA Carmel ARM®v8.2 64-bit CPU 6MB L2 + 4MB L3
- 384-core NVIDIA Volta™ GPU with 48 Tensor Cores provides 21 TOPS AI performance
- Rich peripherals including a Gigabit Ethernet port, 4 USB 3.1 Type-A ports, HDMI port, and DP port
- Pre-installed Wifi module and antenna
- Pre-installed 128GB (M.2 key M) SSD
- Mounting design
- Easy to install, upgrade and maintain with ease of access to the internal components after opening the enclosure
- Pre-installed NVIDIA official JetPack software, ready to use！
- Compatible with Nimbus: connect your ROS project to the cloud