| Specification | Details |
|---|
| Product Name | NVIDIA Jetson Orin Nano 4GB Developer Kit (Y‑C11‑DEV‑ORIN NANO‑4G‑512) |
| Module | NVIDIA Jetson Orin Nano System‑on‑Module (4GB) |
| AI Performance | Approx. 20 TOPS (Tensor Operations Per Second) |
| GPU | 512‑core NVIDIA Ampere GPU with 16 Tensor Cores |
| GPU Max Frequency | ~625 MHz |
| CPU | 6‑core Arm® Cortex‑A78AE v8.2 64‑bit |
| CPU Max Frequency | ~1.5 GHz |
| Memory | 4 GB 64‑bit LPDDR5, ~32 GB/s |
| Storage Support | External NVMe via M.2 slot |
| PCIe | PCIe lanes with x4 + additional lanes |
| USB | Multiple USB 3.2 ports |
| Camera Interface | MIPI CSI‑2 support for camera input |
| Video Encode/Decode | Supports 1080p30 encoding; 4K decode depending on config |
| Display Output | Supports HDMI / DisplayPort through carrier board |
| Networking | 1× Gigabit Ethernet (on carrier board) |
| I/O Interfaces | UART, SPI, I2C, GPIO, CAN, PWM, etc. |
| Power Consumption | Approx. 7–10 W typical |
| Form Factor | SO‑DIMM‑style Jetson Nano module on a developer carrier board |
| Software Support | NVIDIA JetPack SDK (Ubuntu Linux + AI libraries) |
Description:
The NVIDIA Jetson Orin Nano 4GB Developer Kit (Y‑C11‑DEV‑ORIN NANO‑4G‑512) is an entry‑level AI development platform designed for edge computing, robotics, intelligent vision systems, and other embedded AI applications. At its core, the kit features the Jetson Orin Nano 4GB module, which combines a 6‑core Arm® Cortex‑A78AE CPU with a 512‑core NVIDIA Ampere GPU equipped with 16 Tensor Cores, delivering around 20 TOPS of AI performance in a compact and energy‑efficient package.
This developer kit includes a carrier board that exposes essential interfaces such as USB 3.2 ports, Gigabit Ethernet, MIPI CSI‑2 camera inputs, and display outputs (via HDMI/DisplayPort depending on board design), enabling integration with sensors, peripherals, and networking for complex workflows. The board also features common embedded interfaces like UART, SPI, I²C, GPIO, PWM, and CAN, making it suitable for robotics platforms and custom hardware ecosystems.
Powered efficiently with a typical consumption of 7–10 W, the Orin Nano kit runs the NVIDIA JetPack SDK, offering a full Linux environment with support for CUDA, TensorRT, cuDNN, and other AI software stacks. This enables rapid prototype creation and deployment of deep learning models directly on edge devices without relying on cloud compute resources, making it ideal for developers and innovators working on real‑time AI at the edge.