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Getting Started with reComputer J40/ J30 Series (J401 carrier board)

reComputer series for Jetson are compact edge computers built with NVIDIA advanced AI embedded systems: J10 (Nano 4GB), J20 (Jetson Xavier NX 8GB and Jetson Xavier 16GB), J40 (Jetson Orin NX 16GB and Jetson Orin NX 8GB) and J30 (Jetson Orin Nano 8GB and Jetson Orin Nano 4GB) module and reComputer J401 carrier board.

With rich extension modules, industrial peripherals, and thermal management, reComputer for Jetson is ready to help you accelerate and scale the next-gen AI product by deploying popular DNN models and ML frameworks to the edge and inferencing with high performance, for tasks like real-time classification and object detection, pose estimation, semantic segmentation, and natural language processing (NLP).


  • Brilliant AI Performance for production: on-device processing with up to 100 TOPS AI performance with low power and low latency
  • Hand-size edge AI device: compact size at 130mm x120mm x 58.5mm, includes NVIDIA Jetson Orin NX/ Orin Nano production module, a cooling fan with a heatsink, enclosure, and a power adapter. Support desktop, wall mount, fit in anywhere
  • Expandable with rich I/Os: 4x USB 3.2, HDMI 2.1, 2xCSI, 1xRJ45 for GbE, M.2 Key E, M.2 Key M, CAN, and GPIO
  • Accelerate solution to market: pre-installed Jetpack with NVIDIA JetPack™ 5.1.1 on the included 128GB NVMe SSD, Linux OS BSP, 128GB SSD, support Jetson software and leading AI frameworks and software platforms
  • Certifications: FCC, CE, RoHS, UKCA


SpecificationsreComputer J3010reComputer J3011reComputer J4011reComputer J4012
ModuleJetson Orin Nano 4GBJetson Orin Nano 8GBJetson Orin NX 8GBJetson Orin NX 16GB
AI Performance20 TOPS40 TOPS70 TOPS100 TOPS
GPU512-core NVIDIA Ampere architecture GPU with 16 Tensor Cores1024-core NVIDIA Ampere architecture GPU with 32 Tensor Cores1024-core NVIDIA Ampere architecture GPU with 32 Tensor Cores
GPU Max Frequency625 MHz765 MHz918 MHz
CPU6-core Arm® Cortex®-A78AE v8.2 64-bit CPU
1.5MB L2 + 4MB L3
6-core Arm® Cortex®-A78AE v8.2 64-bit CPU 1.5MB L2 + 4MB L38-core Arm® Cortex®-A78AE v8.2 64-bit CPU 2MB L2 + 4MB L3
CPU Max Frequency1.5 GHz2 GHz
Memory4GB 64-bit LPDDR5
34 GB/s
8GB 128-bit LPDDR5
68 GB/s
8GB 128-bit LPDDR5 102.4GB/s16GB 128-bit LPDDR5 102.4GB/s
DL Accelerator/1x NVDLA v22x NVDLA v2
DLA Max Frequency/614 MHz
Vision Accelerator/1x PVA v2
Storage128GB NVMe SSD
Video Encoder1080p30 supported by 1-2 CPU cores1x 4K60 (H.265) | 3x 4K30 (H.265)
6x 1080p60 (H.265) | 12x 1080p30 (H.265)
Video Decoder1x 4K60 (H.265)
2x 4K30 (H.265)
5x 1080p60 (H.265)
11x 1080p30 (H.265)
1x 8K30 (H.265) | 2x 4K60 (H.265) | 4x 4K30 (H.265)
9x 1080p60 (H.265) | 18x 1080p30 (H.265)
Display1* HDMI 2.1
CSI Camera2* CSI (2-lane 15pin)
Networking1* Gigabit Ethernet (10/100/1000M)
USB4* USB 3.2 Type-A (10Gbps); 1* USB2.0 Type-C (Device Mode)
M.2 Key M1* M.2 Key M
M.2 Key E1* M.2 Key E
Fan1* 4 pin Fan Connector(5V PWM)
Multifunctional Port1* 40-Pin Expansion header,1* 12-Pin Control and UART header
RTCRTC 2-pin, RTC socket (supports CR1220 but not included)
Power SupplyPower adapter not included
Mechanical130mm x120mm x 58.5mm

Hardware Overview

Flash JetPack

Here, we will show you how to flash Jetpack to an NVMe SSD connected to the reComputer J4012/ J4011/ J3010 and J3011. All these devices come with J401 carrier board inside and the flashing procedure is the same for all.

reComputer J40/ J30 series comes with JetPack 5.1 pre-installed on the included NVMe SSD, so that you do not need to flash it. However, if you want to flash it again with JetPack, you can follow this guide.


  • Ubuntu Host PC (native or VM using VMware Workstation Player)
  • reComputer J4012/ J4011/ J3010 and J3011
  • USB Type-C data transmission cable

Enter Force Recovery Mode

Before we can move on to the installation steps, we need to make sure that the reComputer is in force recovery mode.

Step 1. Use a jumper wire to connect the FC REC pin and the GND pin.

Button HeaderDescriptionButton HeaderDescription

Step 2. Power up the reComputer by connecting the included cable from the power adapter and connect the board with the Ubuntu host PC with a USB Type-C data transmission cable

Step 3. On the Linux host PC, open a Terminal window and enter the command lsusb. If the returned content has one of the following outputs according to the Jetson SoM you use, then the board is in force recovery mode.

  • For Orin NX 16GB: 0955:7323 NVidia Corp
  • For Orin NX 8GB: 0955:7423 NVidia Corp
  • For Orin Nano 8GB: 0955:7523 NVidia Corp
  • For Orin Nano 4GB: 0955:7623 NVidia Corp

The below image is for Orin NX 16GB

Step 4. Remove the jumper wire

Flash to Jetson


Before moving onto flashing, it should be noted that Jetson Orin NX module only supports JetPack 5.1 and above, while Jetson Orin Nano module only supports JetPack 5.1.1 and above.

Here we will use NVIDIA L4T 35.3.1 to install Jetpack 5.1.1 on the reComputer

Step 1: Download the NVIDIA drivers on the host PC. The required drivers are shown below:

Step 2: Extract Jetson_Linux_R35.3.1_aarch64 and Tegra_Linux_Sample-Root-Filesystem_R35.3.1_aarch64 by navigating to the folder containing these files, apply the changes and install the necessary prerequisites

tar xf Jetson_Linux_R35.3.1_aarch64
sudo tar xpf Tegra_Linux_Sample-Root-Filesystem_R35.3.1_aarch64 -C Linux_for_Tegra/rootfs/
cd Linux_for_Tegra/
sudo ./
sudo ./tools/

Step 3: Configure your username, password & hostname so that you do not need to enter the Ubuntu installation wizard after the device finishes booting

sudo tools/ -u {USERNAME} -p {PASSWORD} -a -n {HOSTNAME} --accept-license

For example (username:"nvidia", password:"nvidia", device-name:"nvidia-desktop"):

sudo tools/ -u nvidia -p nvidia -a -n nvidia-desktop --accept-license

Step 4: Flash the system to the NVMe SSD

sudo ./tools/kernel_flash/ --external-device nvme0n1p1 \
-c tools/kernel_flash/flash_l4t_external.xml -p "-c bootloader/t186ref/cfg/flash_t234_qspi.xml" \
--showlogs --network usb0 p3509-a02+p3767-0000 internal

You will see the following output if the flashing process is successful

Tech Support & Product Discussion

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