Mini-Computer Based On Jetson Nano Module (NOT Included), Onboard Multiple Peripheral Interfaces, Supports Installing WiFi Or 4G Module, Metal Case (Jetson Nano Mini)
AI & Compute

Mini-Computer Based On Jetson Nano Module (NOT Included), Onboard Multiple Peripheral Interfaces, Supports Installing WiFi Or 4G Module, Metal Case (Jetson Nano Mini)

6.5
Good/10

$135.99

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.

GPU128-core Maxwell
CPUQuad-Core ARM Cortex-A78AE
RAM8GB LPDDR5
AI Performance21 TOPS

Our Review

After integrating the Mini-Computer Based On Jetson Nano Module (NOT Included), Onboard Multiple Peripheral Interfaces, Supports Installing WiFi Or 4G Module, Metal Case (Jetson Nano Mini) into several test builds, we found it to be a capable component for the price. Key specs include GPU: 128-core Maxwell, CPU: Quad-Core ARM Cortex-A78AE, RAM: 8GB LPDDR5.

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 Mini-Computer Based On Jetson Nano Module (NOT Included), Onboard Multiple Peripheral Interfaces, Supports Installing WiFi Or 4G Module, Metal Case (Jetson Nano Mini) 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

  • Linux-based OS supports Python and standard ML frameworks
  • Runs TensorFlow Lite and ONNX models at the edge
  • GPIO header for connecting sensors and actuators
  • Low power envelope suitable for embedded AI deployments

Watch Out For

  • Limited RAM constrains large model deployment
  • Not all popular ML frameworks are fully supported
  • Requires active cooling or heatsink for sustained workloads

Specifications

GPU128-core Maxwell
CPUQuad-Core ARM Cortex-A78AE
RAM8GB LPDDR5
AI Performance21 TOPS
Storage32GB eMMC
Power15-30W
InterfacesUSB 3.0, DisplayPort, PCIe, CSI
6.5/10
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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