Waveshare RDK X3 AI Module Vision Kit, Compatible with Raspberry Pi CM4, 5 Tops Computing Power, Bundle with CM4 IO Base Board, 7inch Screen and IMX219 Camera, 6 Items,Not Contain RDK X3
AI & Compute

Waveshare RDK X3 AI Module Vision Kit, Compatible with Raspberry Pi CM4, 5 Tops Computing Power, Bundle with CM4 IO Base Board, 7inch Screen and IMX219 Camera, 6 Items,Not Contain RDK X3

7.5
Great/10

$66.99

Disclosure: CircuitTrail earns from qualifying purchases as an Amazon Associate. Prices and availability may change.

A competent component that handles standard use cases well. Not flashy, but reliable — which is what matters for project components.

AI Performance5 TOPS
ProcessorDual-Core ARM Cortex-A72 + NPU
RAM2GB LPDDR4
FrameworksOpenVINO, ONNX

Our Review

After integrating the Waveshare RDK X3 AI Module Vision Kit, Compatible with Raspberry Pi CM4, 5 Tops Computing Power, Bundle with CM4 IO Base Board, 7inch Screen and IMX219 Camera, 6 Items,Not Contain RDK X3 into several test builds, we found it to be a capable component for the price. Key specs include AI Performance: 5 TOPS, Processor: Dual-Core ARM Cortex-A72 + NPU, RAM: 2GB 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 Waveshare RDK X3 AI Module Vision Kit, Compatible with Raspberry Pi CM4, 5 Tops Computing Power, Bundle with CM4 IO Base Board, 7inch Screen and IMX219 Camera, 6 Items,Not Contain RDK X3 delivers what you need without unnecessary complexity. Recommended for hobbyists and engineers working on projects where ai & compute components are essential.

What We Like

  • Low power envelope suitable for embedded AI deployments
  • CSI camera interface for real-time computer vision
  • Dedicated hardware acceleration for neural network inference
  • Linux-based OS supports Python and standard ML frameworks

Watch Out For

  • Limited RAM constrains large model deployment
  • Requires active cooling or heatsink for sustained workloads
  • Initial setup and SDK installation has a learning curve

Specifications

AI Performance5 TOPS
ProcessorDual-Core ARM Cortex-A72 + NPU
RAM2GB LPDDR4
FrameworksOpenVINO, ONNX
InterfacesMIPI-CSI, USB, HDMI
Power12V / 2A
7.5/10
Great

The Verdict

A competent component that handles standard use cases well. Not flashy, but reliable — which is what matters for project components.

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