Jetson Nano 4GB Developer Kit SUB with 16G eMMC, SD Card Slot, Based on Official Jetson Nano 4GB Core Module Expansion Kit Alternative Solution of B01 Kit (Jetson Nano 4GB SUB)
$411.04
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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.”
Our Review
The Jetson Nano 4GB Developer Kit SUB with 16G eMMC, SD Card Slot, Based on Official Jetson Nano 4GB Core Module Expansion Kit Alternative Solution of B01 Kit (Jetson Nano 4GB SUB) delivers solid performance for its category. With GPU: 472 CUDA cores + 16 Tensor cores, CPU: 6-core ARM Carmel, RAM: 8GB LPDDR5, 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.
Overall, the Jetson Nano 4GB Developer Kit SUB with 16G eMMC, SD Card Slot, Based on Official Jetson Nano 4GB Core Module Expansion Kit Alternative Solution of B01 Kit (Jetson Nano 4GB SUB) fills its role well. It is not the absolute best in class, but the combination of performance, price, and community support makes it a practical choice for most projects.
What We Like
- GPIO header for connecting sensors and actuators
- Hardware video encoding/decoding for vision pipelines
- Runs TensorFlow Lite and ONNX models at the edge
- Linux-based OS supports Python and standard ML frameworks
Watch Out For
- Not all popular ML frameworks are fully supported
- Requires active cooling or heatsink for sustained workloads
- Initial setup and SDK installation has a learning curve
Specifications
| GPU | 472 CUDA cores + 16 Tensor cores |
| CPU | 6-core ARM Carmel |
| RAM | 8GB LPDDR5 |
| AI Performance | 21 TOPS |
| Storage | 16GB eMMC + NVMe |
| Power | 15-30W |
| Interfaces | USB 3.0, DisplayPort, PCIe, CSI |
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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