What’s the Best SoC/Board for Neural Networks on Embedded?

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As artificial intelligence continues to push deeper into edge computing, the demand for running neural networks directly on embedded devices is growing rapidly. From smart cameras and home assistants to industrial robots and autonomous vehicles, running AI locally offers benefits such as lower latency, improved privacy, and independence from cloud connectivity. But this raises a critical question: What’s the best SoC or development board for deploying neural networks on embedded systems?

In this article, we’ll explore the leading SoCs and embedded boards that are well-suited for AI workloads, compare their strengths, and offer suggestions based on specific applications.

Key Requirements for AI on Embedded Devices

Before choosing the right hardware, it’s essential to understand what makes an SoC or board ideal for neural network inference:

  • AI acceleration (NPU, DSP, GPU support)
  • Power efficiency
  • Memory bandwidth
  • Supported AI frameworks (e.g., TensorFlow Lite, ONNX, PyTorch Mobile)
  • Thermal and mechanical design compatibility
  • Longevity and industrial-grade support

Top SoC/Boards for Neural Network Inference

1. NVIDIA Jetson Series (Jetson Nano, Xavier NX, Orin Nano)

  • Strengths: Powerful CUDA cores, TensorRT acceleration, native support for deep learning libraries.
  • Use Cases: Robotics, drones, autonomous machines, smart retail.
  • Why It’s Good: NVIDIA’s Jetson ecosystem is the gold standard for edge AI, with strong developer tools and community support.

2. Rockchip RK3588 / RK3568

  • Strengths: Integrated NPU (0.8-6 TOPS), low power, affordable, strong multimedia support.
  • Use Cases: Smart home panels, vision systems, human-computer interaction, smart IoT gateways.
  • Why It’s Good: Rockchip’s NPU supports popular models like YOLO, MobileNet, ResNet through RKNN toolkit. Boards like the Portworld P6802 (RK3568) or YC-SM10P offer excellent customization for Android/Linux-based AI applications.

3. Google Coral Dev Board (Edge TPU)

  • Strengths: Ultra-efficient Edge TPU for TensorFlow Lite models.
  • Use Cases: Lightweight classification, object detection, mobile robotics, wearables.
  • Why It’s Good: Excels in low-power scenarios with pre-compiled models using TensorFlow Lite. Limited flexibility for complex tasks or large models.

4. NXP i.MX 8M Plus

  • Strengths: Integrated NPU (2.3 TOPS), industrial-grade design, long lifecycle.
  • Use Cases: Industrial vision, automation, medical devices.
  • Why It’s Good: Ideal for industrial and medical use where reliability, longevity, and certifications are essential.

5. Qualcomm QCS610 / Snapdragon Series

  • Strengths: Built-in AI Engine, advanced ISP and DSP capabilities.
  • Use Cases: Smart cameras, voice assistants, AR/VR.
  • Why It’s Good: Qualcomm’s AI Engine supports a broad range of AI models and real-time multimedia processing.

Choosing the Best Fit: Application-Based Recommendation

Use Case Recommended SoC/Board Key Advantage
Smart Home Panel with AI Control Rockchip RK3566/3568 (e.g., Portworld YC-SM08M) Affordable, reliable, supports facial recognition, gesture control
Industrial Vision/Edge AI NVIDIA Jetson Xavier NX / Orin Nano High performance, GPU acceleration
Voice Recognition or NLP Qualcomm QCS Series DSP optimized for audio AI
Low Power, Simple Detection Google Coral Dev Board Fast TFLite model inference, low power
Long-Term Industrial Deployment NXP i.MX 8M Plus Industrial-grade stability and long lifecycle

Why Choose Portworld for AI-Ready Embedded Boards?

At Portworld, we specialize in developing customizable SoM and embedded boards powered by Rockchip RK3566, RK3568, and RK3588 SoCs—designed with built-in NPUs, rich I/O interfaces, and support for Android/Linux OS. Our solutions come with:

  • Full support for RKNN model conversion and deployment
  • OEM/ODM hardware customization
  • BSP and SDK support for AI model integration
  • AI-ready touch panel and HMI solutions (7” to 15.6”)

Whether you’re building a smart building controller, an AIoT gateway, or a computer vision terminal, we provide turnkey solutions that speed up your time to market.