
Jetson Orin Nano SUPER 8GB Development Kit *1, Power Adapter *1, Antenna *1, Wireless Network Card (pre-installed) *1, 256GB Solid State Drive (pre-flashed with system image) *1, DP to HDMI Cable *1, Type-C Cable *1, IMX219 Camera *1, Acrylic Case *1
Product Specifications
Pre-installed SSD with system image including AI vision applications, ROS examples, AI large model cases, and OpenClaw.
Comprehensive OpenClaw deployment and application tutorials covering file management, browser control, AI autonomous programming, hardware driver development, and sensor integration.
Supports interaction via Feishu and voice modules.
Continuous updates with latest system images based on Ubuntu 22.04, supporting NVIDIA CUDA 12.6, TensorRT 10.7.0, cuDNN 9.6.0, OpenCV 4.10.0.
NVIDIA Isaac ROS support with practical cases in DNN stereo depth, 3D scene reconstruction and mapping, object detection, and 3D pose estimation.
NVIDIA Jetson Orin Nano SUPER Developer Kit with significant performance upgrades over previous generation:
| Item | Detail |
|---|---|
| AI computing power up to 67 TOPS (sparse), 33 TOPS (dense). | — |
| CPU | 6-core Arm Cortex-A78AE v8.2 64-bit, up to 1.7 GHz (13% frequency increase). |

TYPEC interface 168P chip soldered + cable
CN¥22.68
| GPU | NVIDIA Ampere architecture with 1024 CUDA cores and 32 Tensor cores, max frequency 1020 MHz. |
| Memory | 8GB LPDDR5 128-bit, 102 GB/s bandwidth (50% increase). |
| Power consumption | configurable 7W, 15W, 25W modes. |
Jetson Orin Nano SUPER offers approximately 70% increase in AI computing power compared to previous Orin Nano.
Large language model (LLM) performance improvements ranging from 1.28x to 1.63x across various models (Llama 3.1/3.2, Qwen2.5, Gemma2, Phi 3.5, SmolILM2).
Visual Transformer and Visual Language Model (VLM) performance significantly enhanced.
Power mode configurable up to 25W for maximum performance.
ROS2 environment with NVIDIA Isaac ROS for robotic AI applications.
Support for TensorFlow, PyTorch, Torchvision, DeepStream, OpenRouter large model API platform.
Extensive tutorials covering GPIO control, camera calibration, AI model deployment, multi-modal vision and speech interaction, offline and online speech recognition and synthesis.
Support for YOLO object detection, instance segmentation, pose estimation, and multi-modal vision-language applications.
VSCode and VMware usage guides included.
Supports up to 2x 4-lane CSI cameras.
Compatible with JETSON mini metal chassis designed for enthusiasts.
Continuous firmware and software updates with 3D model files available.
Supports multiple power modes and thermal management.
Extensive documentation and tutorials for hardware and software development.
All kits come with pre-installed system images and continuous update support from yahboom.