Luckfox Aura High-Performance Linux Development Board, Rockchip RV1126B Quad-Core 1.6GHz Processor, 3 Tops Computing Power, 4K Encoding and Decoding, 4GB RAM 0GB eMMC Flash
AI & Compute

Luckfox Aura High-Performance Linux Development Board, Rockchip RV1126B Quad-Core 1.6GHz Processor, 3 Tops Computing Power, 4K Encoding and Decoding, 4GB RAM 0GB eMMC Flash

7.4
Great/10

$115.19

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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.

ProcessorRISC-V 1.0GHz
RAM512MB DDR3
StorageMicroSD (up to 128GB)
ConnectivityEthernet 1Gbps

Our Review

The Luckfox Aura High-Performance Linux Development Board, Rockchip RV1126B Quad-Core 1.6GHz Processor, 3 Tops Computing Power, 4K Encoding and Decoding, 4GB RAM 0GB eMMC Flash delivers solid performance for its category. With Processor: RISC-V 1.0GHz, RAM: 512MB DDR3, Storage: MicroSD (up to 128GB), it covers the essentials that most makers and engineers need for their projects.

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 Luckfox Aura High-Performance Linux Development Board, Rockchip RV1126B Quad-Core 1.6GHz Processor, 3 Tops Computing Power, 4K Encoding and Decoding, 4GB RAM 0GB eMMC Flash delivers what you need without unnecessary complexity. Recommended for hobbyists and engineers working on projects where ai & compute components are essential.

What We Like

  • CSI camera interface for real-time computer vision
  • Runs TensorFlow Lite and ONNX models at the edge
  • Active developer community with pre-trained model zoo
  • Linux-based OS supports Python and standard ML frameworks

Watch Out For

  • Draws significant power under full inference load
  • Limited RAM constrains large model deployment
  • Camera interface limited to specific sensor modules

Specifications

ProcessorRISC-V 1.0GHz
RAM512MB DDR3
StorageMicroSD (up to 128GB)
ConnectivityEthernet 1Gbps
Video OutputHDMI 1.4
Power12V / 2A barrel jack
7.4/10
Great

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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