EC-A3588JD4 Rockchip RK3588 Embedded Computing PC

Rockchip RK3588

Octa-core 64-bit processor (4×Cortex-A76+4×Cortex-A55) , main frequency up to 2.4GHz

ARM Mali-G610 MP4 quad-core GPU, support OpenGL ES3.2/OpenCL 2.2/Vulkan1.1, 450 GFLOPS

The computing power is up to 6TOPS (INT8), support INT4/INT8/INT16 mixed operations

LPDDR4/LPDDR4x (4GB/8GB/16GB optional, up to 32GB)

eMMC (32GB/64GB/128GB/256GB optional)

1 × TF Card, M.2 SATA3.0/PCIe NVMe SSD 2242/2260/2280 (Inside the computer)

DC 12V (5.5mm × 2.1mm, support 9V~24V wide voltage input)

1 × HDMI2.1 (8K@60fps or 4K@120fps)

Android, Linux OS

• Support the privatization deployment of ultra-large-scale parametric models under the Transformer architecture, such as Gemma-2B, ChatGLM3-6B, Qwen-1.8B, Phi-3-3.8B and other large language models
• It supports traditional network architectures such as CNN, RNN, and LSTM, and supports the import and export of RKNN models; Support a variety of deep learning frameworks, including TensorFlow, TensorFlow Lite, PyTorch, Caffe, ONNX and Darknet. It also supports the development of custom operators
• Support Docker container management technology

188.0mm × 88.44mm × 50.65mm

Net weight of computer: 0.79kg, Total weight with package: 1.12kg

• Operating Temperature: -20℃～60℃
• Storage Temperature: -20℃～70℃
• Storage Humidity: 10%～90%RH(non-condensing)

• Ethernet: 2 × RJ45 (1000Mbps)
• WiFi: Extend WiFi/Bluetooth module through M.2 E-KEY (2230), support 2.4GHz/5GHz dual band WiFi6 (802.11a/b/g/n/ac/ax), Bluetooth5.2
• 4G: Extend 4G LTE via Mini PCIe

2 × USB3.0 (Max: 1A)

• 1 × Type-C (OTG), 1 × SIM Card
• 1 × Phoenix connector (2×4PIN, 3.5mm pitch): 1 × RS485, 1 × RS232, 1 × CAN 2.0