The migration of artificial intelligence from cloud computing to intelligent edge devices has become one of the most important trends in embedded AI development. As large AI models continue moving toward practical applications, the key challenge for hardware manufacturers is no longer only computing power, but whether embedded devices can provide sufficient processing capability, memory bandwidth, and system flexibility for efficient local inference.

Shenzhen Techvision Intelligent Technology Co., Ltd. (Techvision), a Beijing Stock Exchange-listed company and National-Level Specialized and Innovative “Little Giant” Enterprise, provides an effective solution through its embedded motherboard solution based on the SMARC standard. By combining RK3588/RK3576 CPU core modules with RK1828 AI acceleration modules, Techvision creates a CPU + AI dual-engine architecture designed to overcome the “memory wall” challenge in large model inference.

In this architecture, the CPU module focuses on system operation, device interaction, multimedia processing, and overall platform management, while the dedicated AI acceleration module is responsible for large language model (LLM) and vision-language model (VLM) inference tasks. Through modular hardware design, the solution enables intelligent terminals to achieve high-performance, scalable, and reliable edge AI capabilities.

1. Solution Overview: CPU + AI Dual-Engine Architecture

With the rapid development of edge AI applications, embedded platforms need to provide not only powerful computing performance but also flexible expansion capability and long-term upgrade potential. Traditional embedded systems often face difficulties when deploying large AI models because general-purpose processors must simultaneously handle system operations and complex AI inference workloads.

Techvision’s CPU + AI dual-engine architecture solves this problem by separating different computing tasks. The CPU module provides a stable system foundation for device control and application processing, while the AI acceleration module delivers dedicated computing resources for large model inference.

This architecture improves computing efficiency, reduces system workload pressure, and enables faster response for intelligent terminals. By combining general-purpose processing with specialized AI acceleration, the solution provides a practical approach for deploying advanced AI models directly on edge devices.

CPU Core Module: RK3588/RK3576, An All-Purpose System Foundation

Based on the SMARC standard, the RK3588/RK3576 CPU core module provides a powerful and flexible computing foundation for embedded applications. It supports operating system deployment, multi-channel video encoding and decoding, high-resolution multimedia processing, human-machine interaction, sensor data integration, and system communication.

Equipped with a built-in 6 TOPS NPU, RK3588/RK3576 can also support lightweight AI vision tasks, including image recognition, object detection, and computer vision analysis. With rich I/O interfaces and strong system integration capabilities, the module can meet the requirements of various intelligent devices and embedded platforms.

As the main control unit of the system, RK3588/RK3576 provides a balance between computing performance, power efficiency, and application flexibility, allowing manufacturers to develop compact and reliable intelligent terminals.

AI Acceleration Module: RK1828, Dedicated for Large Model Inference

As AI models continue becoming larger and more complex, dedicated AI acceleration hardware has become increasingly important for edge deployment. The RK1828 AI acceleration module is designed specifically for large language model (LLM) and vision-language model (VLM) inference acceleration.

Featuring a dedicated 20 TOPS NPU and high-bandwidth DRAM options of 2.5GB or 5GB, RK1828 provides additional AI computing resources for demanding edge applications. Combined with RK3588/RK3576, the platform supports local inference of 3B and 7B-scale large language models and multimodal AI models.

This enables intelligent applications such as natural language interaction, AI assistants, image understanding, and multimodal analysis to operate directly on edge devices. With optimized model deployment, the system can achieve inference speeds exceeding 100 tokens/s and supports multi-module expansion for future computing requirements.

Instead of replacing the entire hardware platform, customers can integrate RK1828 AI acceleration modules into existing designs, allowing products to quickly gain advanced AI capabilities.

Software Ecosystem: Full-Stack RKNN3 SDK Support with 30+ Mainstream Models Ready to Deploy

Successful edge AI implementation requires not only powerful hardware but also a complete software ecosystem. To simplify AI application development, this solution is supported by Rockchip RKNN3 SDK, providing comprehensive tools for model conversion, optimization, and deployment.

The platform supports more than 30 mainstream AI models, including Qwen, Llama, MiniCPM, YOLO, and other popular AI frameworks. It provides C/Python APIs and supports OpenAI API-compatible interfaces, helping developers efficiently build AI applications for embedded devices.

The solution also supports model conversion from mainstream deep learning frameworks such as PyTorch and TensorFlow. This significantly reduces the difficulty of migrating cloud-based AI models to edge environments and helps manufacturers accelerate product development.

With complete software support, customers can integrate AI capabilities into existing products more efficiently while reducing development costs and improving market competitiveness.

SMARC Architecture: Balancing Current Performance and Future Upgrades

The SMARC architecture provides both current performance advantages and long-term upgrade flexibility. Compared with traditional integrated motherboard designs, modular architecture allows customers to upgrade computing modules without redesigning the entire hardware platform.

Through this embedded motherboard solution, manufacturers can replace or upgrade CPU modules and AI acceleration modules according to future application requirements while keeping existing carrier boards and structural designs. This approach significantly reduces product iteration costs and extends the lifecycle of intelligent terminal products.

For enterprises developing AI-powered devices, the SMARC-based architecture provides an effective balance between performance, cost efficiency, and future scalability.

2. Which Products Are Suitable for This Solution?

For products requiring local AI capabilities, especially large model inference, the RK3588/RK3576 + RK1828 platform provides strong application value. Local processing, data security, and real-time response make this solution suitable for a wide range of intelligent terminal scenarios.

Typical applications include:

Robot Embedded Solutions: Supporting local voice interaction, visual understanding, and intelligent decision-making for service robots and inspection robots.

Smart Security Terminals: Enabling real-time video analysis, intelligent behavior recognition, and abnormal event detection without relying entirely on cloud computing.

Smart Education Terminals: Providing local AI computing support for intelligent recording systems, classroom analysis, and interactive learning applications.

Industrial Control Terminals: Improving production line inspection efficiency through local AI vision inference while ensuring sensitive manufacturing data remains within the factory.

Smart Office and Medical Terminals: Supporting local meeting summary generation, intelligent services, and privacy-focused AI processing.

Compared with cloud-based AI solutions, edge AI provides advantages including local inference, data protection, and offline availability. These capabilities are becoming increasingly important factors for enterprises selecting intelligent hardware platforms.

3. About Techvision

Shenzhen Techvision Intelligent Technology Co., Ltd. (Techvision) is a Beijing Stock Exchange-listed company and a National-Level Specialized and Innovative “Little Giant” Enterprise focusing on AIoT embedded system solutions.

With extensive experience in embedded hardware development, software integration, and intelligent terminal manufacturing, Techvision provides global customers with one-stop ODM services covering product design, engineering development, and mass production.

The RK3588/RK3576 + RK1828 embedded motherboard solution represents an important step in Techvision’s development of edge AI technologies. Through modular hardware architecture, powerful AI acceleration capability, and comprehensive software support, Techvision helps enterprises transform traditional embedded devices into intelligent AI-powered terminals.

As artificial intelligence continues moving closer to end devices, local inference will become a critical capability for future smart products. Techvision provides reliable edge AI solutions that help customers achieve efficient, scalable, and secure intelligent applications.