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Jetson SUB Mini PC-Blue with Jetson Xavier NX module, Aluminium case with cooling fan, 128GB SSD, WiFi, Antennas and pre-installed JetPack System

SKU
102110637

Jetson SUB Mini PC-Blue is based on Jetson Xavier NX module, which delivers up to 21 TOPS, making it ideal for high-performance compute and AI in embedded and edge systems. Jetson Sub mini PC blue is pre-installed Wifi module and antenna. The carrier board comes with rich peripherals including Gigabit Ethernet port, 4 USB 3.1 Type-A ports, HDMI and DP.

Check out more NVIDIA Jetson-powered edge devices comparison!

reComputer J2021 built with Jetson Xavier NX

PRODUCT DETAILS

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 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

Description

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 capability to all your embedded AI and edge systems. Jetson Xavier NX delivers up to 21 TOPS, making it ideal for high-performance compute 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, 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 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.

Seeed Jetson Ecosystem

Seeed is a reseller of NVIDIA embedded systems and a preferred partner of the NVIDIA Jetson ecosystem for edge AI. Explore more carrier boards, full system devices, customization services, use cases, and developer tools at Seeed Jetson Ecosystem! Welcome to check out our free Edge AI partner program. We are looking forward to leveraging local and global resources to accelerate next-gen AI product together with you.

Application

For both beginners and experts, it is designed to help you to build your next-gen autonomous machine at the edge.

Edge AI Applications

Jetson Sub Mini PC powered by Xavier NX is ideal for building autonomous applications and complex AI tasks of image recognition, object detection, pose estimation, semantic segmentation, video processing, and many more.

Find in the Jetson Community Resources page tools and tutorials the community has created to power your development experience, and check out the Community Projects page to inspire your next project!

Note:

  • The top acrylic cover is removable. If you want to add a HAT or Cape on your SBC inside the case, there is no need to re-screw the whole case because the top acrylic layer is designed to be removed easily.

Specifications

Jetson SUB Mini PC-Blue Jetson SUB Mini PC-Black Jetson SUB Mini PC-Silver Jetson EX1 Mini PC-Ubuntu
Module NVIDIA JETSON XAVIER NX
AI Performance 21 TOPs(INT8)
OS JetPack 4.6 Ubuntu 18.04
CPU 6-core 64-bit CPU, NVIDIA Carmel ARMv8.2
GPU 384-core NVIDIA Volta GPU
Memory 8 GB 128-bit LPDDR4x 59.7GB/s
Module Storage 16 GB eMMC 5.1
Carrier Board Storage 128GB M.2 NVME SSD 256GB SATA 128GB M.2 NVME SSD 256GB M.2 NVME SSD
Wifi Pre-installed M.2 E Wifi Pre-installed USB 2.0 Wifi Pre-installed M.2 E Wifi \
Power 19V DC 19V DC 19V DC 12V DC
Display 1* HDMI / 1* DP 1* HDMI / 1* DP 1* HDMI / 1* DP 1* HDMI / 1* DP
1* OLED screen
USB 4* USB3.0(USB 2.0 Integrated), 4*USB3.0(USB 2.0 Integrated), 4*USB3.0(USB 2.0 Integrated), 1*USB3.0(USB 2.0 Integrated)
1*Micro USB 1*USB Type C 1*Micro USB 1*Micro USB,
1*USB2.0
Network 1* Gigabit Lan 2* Gigabit Lan*2 1* Gigabit Lan 2* Gigabit Lan
Dimension 130mm x120mm x 50mm 205mm x 130mm x 65mm 130mm x90mm x60mm 134mm x135mm x46mm
Key feature Blue Aluminum Case; Whole Black Aluminium Frame; Whole Silver Aluminium Frame; Whole Black Aluminium Frame;
Removable transparent Cover; Big passive dissipation ; Portable Oval Size Narrow space fit,
Mounting hole design OLED screen Multiple software
drivers installed
Reference application Indoor AIoT, Home development, etc. Industry IoT,
Harsh environment applications, etc.
Smart Office, Smart Home, Education, etc. Industry control, Lab, etc.

Module Technical Specifications
AI Performance 21 TOPS
GPU 384-core NVIDIA Volta™ GPU with 48 Tensor Cores
CPU 6-core NVIDIA Carmel ARM®v8.2 64-bit CPU, 6MB L2 + 4MB L3
Memory 8 GB 128-bit LPDDR4x, 59.7GB/s
Storage 16 GB eMMC 5.1
Power 10 W | 15 W | 20W
PCIe 1 x1 (PCIe Gen3) + 1 x4 (PCIe Gen4), total 144 GT/s*
CSI Camera Up to 6 cameras (24 via virtual channels)
12 lanes (3x4 or 6x2) MIPI CSI-2
D-PHY 1.2 (up to 30 Gbps)
Video Encode 2x 4K60 | 4x 4K30 | 10x 1080p60 | 22x 1080p30 (H.265)
2x 4K60 | 4x 4K30 | 10x 1080p60 | 20x 1080p30 (H.264)
Video Decode 2x 8K30 | 6x 4K60 | 12x 4K30 | 22x 1080p60 | 44x 1080p30 (H.265)
2x 4K60 | 6x 4K30 | 10x 1080p60 | 22x 1080p30 (H.264)
Display 2 multi-mode DP 1.4/eDP 1.4/HDMI 2.0
DL Accelerator 2x NVDLA Engines
Vision Accelerator 7-Way VLIW Vision Processor
Networking 10/100/1000 BASE-T Ethernet
Mechanical 69.6 mm x 45 mm
260-pin SO-DIMM connector

Carrier board Connector Description
HDMI Port

1* HDMI / 1* DP

USB 3.0 Type A 4*USB 3.0 Type A Connector
NVIDIA Gigabit Ethernet 1*RJ45 Gigabit Ethernet Connector (10/100/1000)
DC Power 1*DC Input Power TE Connector
FAN Connect 1*Picoblade Header
M.2 KEY E 2230

Pre-installed Wifi module

(802.11ac, Dual Band, 80MHZ, MU-MIMO & Bluetooth 4.2)

CSI Camera Connect 2*CSI Camera (15 pos, 1mm pitch, MIPI CSI-2 )
Multifunctional port 2.0 Pitch 40 PIN
M.2 KEY M 2280 Pre-installed 128GB NVME SSD
NVIDIA Jetson Nano/NX/TX2 NX connector 1*Jetson SODIMM connector, 260-pin
CAN 1*CAN Bus Header (1x4, 2.54mm pitch, RA)
Button Header 1*Button Header (1x12, 2.54mm pitch, RA)
USB Micro Type B 1*USB Micro B, RA Female
RTC 1*RTC Back-up Coin Cell Socket (CR1225)

Part List

  • 1 x Acrylic Cover
  • 1 x Aluminium Frame
  • 1 x Jetson Xavier NX module
  • 1 x Heatsink
  • 1 x Carrier board
  • 1 x 19V/4.74A (MAX 90W) Power Adapter (Power cable not included)
  • 2 x Antennas

  • Note

    • The power cord and 3V RTC battery (CR1220) are not included, please choose a suitable form according to your country.

    • Pre-installed JetPack™ system, the login password is 'nvidia'. If you want to reflash the system, you need to enter recovery mode, check wiki for more details.

    • Before using it, you need to open a terminal and execute the following:

    1. cd /home/nvidia
    2. sudo./ssd extern.sh
    to make sure the roof expands to take the unallocated 110GB space.

ECCN/HTS

HSCODE 8471504090
USHSCODE 8471410150
UPC
EUHSCODE 8471800000
COO CHINA
CE 1
EU DoC 1
FCC 1
RoHS 1
UK DoC 1

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  1. Product Quality
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    Perfect platform for robotics, highly recommended.
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  2. Product Quality
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    Perfect platform for robotics, highly recommended.
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  3. Product Quality
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    This is a great idea and about 90% "there" - the clear case lid sits directly on the SOC fan blocking the air - and the cables can be tricky to insert in to the carrier board. Neither are a deterrent, but definitely something to be improved.
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