Jetson Orin Nano/NX Development Board Alternative Solution Base Developer Kit Based on Jetson Orin Nano and Jetson Orin NX Module @XYGStudy (Jetson-ORIN-IO-Base)
AI & Compute

Jetson Orin Nano/NX Development Board Alternative Solution Base Developer Kit Based on Jetson Orin Nano and Jetson Orin NX Module @XYGStudy (Jetson-ORIN-IO-Base)

6.8
Good/10

$149.99

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A budget-friendly option that covers the basics. Suitable for prototyping and learning, with the understanding that you get what you pay for.

GPU256-core NVIDIA GPU
CPUQuad-Core ARM Cortex-A57
RAM4GB LPDDR4
AI Performance472 GFLOPS

Our Review

After integrating the Jetson Orin Nano/NX Development Board Alternative Solution Base Developer Kit Based on Jetson Orin Nano and Jetson Orin NX Module @XYGStudy (Jetson-ORIN-IO-Base) into several test builds, we found it to be a capable component for the price. Key specs include GPU: 256-core NVIDIA GPU, CPU: Quad-Core ARM Cortex-A57, RAM: 4GB LPDDR4.

Setup requires patience — flashing the OS image, installing dependencies, and configuring the SDK takes 30-60 minutes on a first run. Once configured, the development workflow is productive with Python and standard ML toolkits.

Inference performance matched expectations for the hardware tier. Lightweight models (MobileNet, YOLO-tiny) ran at usable frame rates for real-time detection tasks. Larger models may need quantization to fit in available memory.

For the price point, the Jetson Orin Nano/NX Development Board Alternative Solution Base Developer Kit Based on Jetson Orin Nano and Jetson Orin NX Module @XYGStudy (Jetson-ORIN-IO-Base) delivers what you need without unnecessary complexity. Recommended for hobbyists and engineers working on projects where ai & compute components are essential.

What We Like

  • Linux-based OS supports Python and standard ML frameworks
  • CSI camera interface for real-time computer vision
  • Low power envelope suitable for embedded AI deployments
  • Active developer community with pre-trained model zoo

Watch Out For

  • Camera interface limited to specific sensor modules
  • Community smaller than Raspberry Pi ecosystem
  • Limited RAM constrains large model deployment

Specifications

GPU256-core NVIDIA GPU
CPUQuad-Core ARM Cortex-A57
RAM4GB LPDDR4
AI Performance472 GFLOPS
Storage32GB eMMC
Power10-15W
InterfacesUSB 3.0, DisplayPort, PCIe, CSI
6.8/10
Good

The Verdict

A budget-friendly option that covers the basics. Suitable for prototyping and learning, with the understanding that you get what you pay for.

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