Jetson TX2 NX Developer Kit with Official core Module for Learning Programming (TX2-NX Full Kit)
$1,307.76
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.”
Our Review
For $1307.76 CAD, the Jetson TX2 NX Developer Kit with Official core Module for Learning Programming (TX2-NX Full Kit) packs respectable specs: GPU: 128-core Maxwell, CPU: 6-core ARM Carmel, RAM: 8GB LPDDR5. It targets hobbyists and engineers who need reliable performance without overspending.
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 TX2 NX Developer Kit with Official core Module for Learning Programming (TX2-NX Full Kit) 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
- GPIO header for connecting sensors and actuators
- Low power envelope suitable for embedded AI deployments
- Dedicated hardware acceleration for neural network inference
Watch Out For
- Community smaller than Raspberry Pi ecosystem
- Requires active cooling or heatsink for sustained workloads
- Camera interface limited to specific sensor modules
Specifications
| GPU | 128-core Maxwell |
| CPU | 6-core ARM Carmel |
| RAM | 8GB LPDDR5 |
| AI Performance | 40 TOPS |
| Storage | MicroSD |
| Power | 15-30W |
| Interfaces | USB 3.0, DisplayPort, PCIe, CSI |
The Verdict
“A competent component that handles standard use cases well. Not flashy, but reliable — which is what matters for project components.”
Related AI & Compute Components
