
RDK X3 AI Module Kit, 5 Tops Computing Power, for Raspberry Pi Compute Module 4, CM4-IO-BASE-B Included, with 7inch Display and Camera (RDK X3 MD Vision ACCE)
$140.85
Disclosure: CircuitTrail earns from qualifying purchases as an Amazon Associate. Prices and availability may change.
“A budget-friendly option that covers the basics. Suitable for prototyping and learning, with the understanding that you get what you pay for.”
Our Review
After integrating the RDK X3 AI Module Kit, 5 Tops Computing Power, for Raspberry Pi Compute Module 4, CM4-IO-BASE-B Included, with 7inch Display and Camera (RDK X3 MD Vision ACCE) into several test builds, we found it to be a capable component for the price. Key specs include AI Performance: 1 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 RDK X3 AI Module Kit, 5 Tops Computing Power, for Raspberry Pi Compute Module 4, CM4-IO-BASE-B Included, with 7inch Display and Camera (RDK X3 MD Vision ACCE) delivers what you need without unnecessary complexity. Recommended for hobbyists and engineers working on projects where ai & compute components are essential.
What We Like
- Dedicated hardware acceleration for neural network inference
- CSI camera interface for real-time computer vision
- GPIO header for connecting sensors and actuators
- Runs TensorFlow Lite and ONNX models at the edge
Watch Out For
- Camera interface limited to specific sensor modules
- Requires active cooling or heatsink for sustained workloads
- Limited RAM constrains large model deployment
Specifications
| AI Performance | 1 TOPS |
| Processor | Dual-Core ARM Cortex-A72 + NPU |
| RAM | 2GB LPDDR4 |
| Frameworks | OpenVINO, ONNX |
| Interfaces | GPIO 40-pin, USB, Ethernet |
| Power | 12V / 2A |
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.”



