Description
Reviews
| Brand | - |
| Category | Robotics / STEM Teaching Tools / Development, Learning, Evaluation & Industrial Control Boards |
| Origin | - |
| Processor | Rockchip RK3588 Octa-core (4x Cortex-A76 + 4x Cortex-A55) |
| GPU | Mali-G610 MP4 with OpenGL ES 3.2 / OpenCL 2.2 / Vulkan 1.1 |
| NPU | 6 TOPS built-in Neural Processing Unit for AI acceleration |
| RAM | 8GB LPDDR4X (Optional 16GB/32GB configurations) |
| Storage | 32GB eMMC 5.1 + MicroSD card slot (up to 256GB) |
| Video Output | Dual HDMI 2.1 (8K@60Hz), Dual DP 1.4, MIPI DSI |
| Connectivity | Gigabit Ethernet, Wi-Fi 6, Bluetooth 5.0 |
| Interfaces | USB 3.0 Type-C, USB 2.0 Host, PCIe 3.0, SATA 3.0 |
| OS Support | Android 12, Ubuntu 22.04, Debian, Buildroot |
| Operating Temperature | -20°C to +70°C (Industrial Grade) |
Anonymous
Mar 29, 2026
Rating: 5/5
Perfect for Edge AI Prototyping
The RK3588 chip on this board is a beast. I successfully deployed a YOLOv8 model using the NPU and achieved real-time performance without breaking a sweat. The documentation for the Linux build was clear and helpful.
Anonymous
Mar 15, 2026
Rating: 5/5
Excellent Open Source Community Support
The open-source nature of the hardware design files made it easy for us to design a custom carrier board. The community around this specific board is growing fast, with plenty of examples for OpenCV and TensorFlow Lite.
Anonymous
Mar 15, 2026
Rating: 5/5
Best value in the RK3588 market
Compared to other dev boards with similar specs, this offers the best price-to-performance ratio. The GPIO pinout is standard, making it easy to interface with existing sensors. Highly recommended for students and pros alike.
Anonymous
Mar 15, 2026
Rating: 4/5
Great hardware, steep learning curve
Hardware quality is top-notch with excellent port selection. However, getting the custom Android image running required some digging in the forums. Once set up, it runs very smoothly for industrial HMI applications.
Anonymous
Mar 12, 2026
Rating: 5/5
Ideal for Robotics Control
We replaced our old Jetson Nano setup with three of these boards. The PCIe expansion allows us to connect multiple cameras easily. Thermal management is good even under full load with the passive heatsink provided.
Anonymous
Mar 06, 2026
Rating: 4/5
Solid for factory automation
Using this for a conveyor belt monitoring system. The dual LAN support is a huge plus for network segmentation. Only minor issue was the initial driver for a specific CAN bus adapter, but support helped resolve it quickly.
Q: Are the schematic diagrams available for download?
A: Yes, as an open-source hardware project, the full schematic diagrams, PCB layout files, and BOM are available in the 'Resources' section of our official wiki page.
Q: Does this board support dual 4K display output simultaneously?
A: Yes, the RK3588 supports up to four independent displays. You can easily drive dual 4K screens via the two HDMI 2.1 ports or a combination of HDMI and DisplayPort.
Q: What is the power supply requirement for stable operation?
A: We recommend a 5V/4A USB-C power adapter for standard use. If you plan to use high-power peripherals via USB or PCIe, a 12V DC input via the barrel jack is supported for increased stability.
Q: Is the NPU compatible with TensorFlow models directly?
A: The NPU requires models to be converted to the RKNN format. We provide tools and tutorials to convert TensorFlow, PyTorch, and ONNX models to RKNN for optimal performance on this board.
Q: Can I run Docker containers on the Ubuntu image?
A: Absolutely. The Ubuntu 22.04 image comes with kernel support for cgroups and namespaces required for Docker. Many users successfully run containerized applications for edge computing scenarios.
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