What’s the Best SoC Board for Neural Networks on Embedded?
As AI continues to shape the future of edge computing, selecting the right System on Chip (SoC) or development board for running neural networks in embedded systems is critical. Whether you’re building smart cameras, voice assistants, autonomous robots, or industrial IoT systems, the performance, efficiency, and compatibility of your hardware can make or break your AI application.
So, what’s the best SoC/board for neural networks on embedded systems? The answer depends on your use case — but here are the top contenders and considerations.
NVIDIA Jetson Series – Best for High-Performance AI at the Edge
- Boards: Jetson Orin Nano, Xavier NX
- Why Choose It: Excellent GPU acceleration, rich SDK support
- Use Cases: Robotics, vision, autonomous machines
Google Coral – Best for Edge TPU Acceleration
- Boards: Coral Dev Board, USB Accelerator
- Why Choose It: Compact, low-power, great for TensorFlow Lite
- Use Cases: AI on microcontrollers, smart cameras
3. Rockchip RK3588 – Performance Meets Affordability
Portworld Recommendation:
PortPi RK3588 SOM Board — High-performance AI module with integrated NPU (6 TOPS)
PortPi Embedded Panel with RK3588 — Ideal for smart home, retail, and signage applications
- Features: 8-core CPU, up to 32GB RAM, 8K decoding, powerful AI acceleration
- Why Choose It: Balanced power and cost, supports Android/Linux, ideal for real-time vision
4. Qualcomm Snapdragon – AI Meets Connectivity
Portworld Recommendation:
Portworld Embedded Snapdragon Panel (QRB5165) — Designed for edge AI and high-speed communication
Snapdragon 845 Smart Display Module
- Features: Hexagon DSP, ISP, 5G/4G support, powerful AI Engine
- Why Choose It: Ideal for advanced imaging, computer vision, voice assistants
MTK AI Solutions – Cost-Effective Smart Modules
Portworld Recommendation:
MTK MT6761 SoM — Lightweight and stable, for Android-based AI applications
Portworld AI Tablet with MTK SoC
- Why Choose It: Optimized for Android, great for AI GUI interfaces and control panels
- Use Cases: Smart control panels, voice interfaces, home automation
Key Considerations:
| Factor | Why It Matters |
|---|---|
| TOPS (AI compute) | Determines neural network speed |
| Framework Support | TensorFlow, PyTorch, ONNX |
| Power Consumption | Especially vital for mobile/IoT |
| I/O Interfaces | USB, GPIO, MIPI CSI/DSI for cameras/screens |
| SDK & BSP Support | Ensures fast development and stability |
