900-13767-0030-000｜NVIDIA Jetson Orin Nano 8GB SOM Module

Positioning: NVIDIA edge AI system-on-module (SOM) with SO-DIMM form factor, serving as an embedded AI visual computing core. This is a mass-production model designed for industrial, robotics, and smart device edge applications; it is not automotive-grade.

I. Core Hardware Specifications

GPU: Ampere architecture, 1024 CUDA cores + 32 Tensor Cores, INT8 computing power of 40 TOPS

CPU: 6-core ARM Cortex‑A78AE @ 2.2GHz

Memory: 8GB LPDDR5, 128-bit width

Storage: The module does not include eMMC; external storage is required via a baseboard.

Interface resources:

PCIe Gen3：1×4 + 3×1

Camera: Up to 4-channel MIPI CSI camera inputs

Display: DP1.2 / eDP1.4 / HDMI1.4, supporting 4K@30Hz.

Network Port: 1 Gigabit Ethernet port

Others: Peripheral devices such as GPIO, UART, I2C, SPI, etc.

Power supply: Typical 10V input; Power consumption range: 7W~15W

Form factor: SO-DIMM gold fingers, dimensions 69.6 × 45 mm

Supporting SDK: JetPack (CUDA, TensorRT, VPI, multimedia encoding/decoding)

II. Product Application Scenarios (Customer Orientation)

✅Main Applications

The largest market segment for this model is mobile robots (AGV/AMR, service robots, inspection robots), covering navigation SLAM, obstacle recognition, visual obstacle avoidance, and the robot's onboard AI computing unit.

Industrial vision equipment: industrial quality inspection cameras, machine vision inspection stations, 3D visual scanning, industrial code reading, and edge-end real-time inference.

Intelligent Security & Multi-Camera Vision Box: AI-powered analysis across multiple camera feeds, human/object detection, behavior recognition, local inference to reduce cloud bandwidth usage.

Drone / Onboard Edge Computing Box: Onboard Visual Recognition and Target Tracking (Note: Power consumption and heat dissipation limitations)

Medical embedded vision, smart vending cabinets, and non-safety-domain peripheral multimedia with AI image analysis for smart cockpits.