Core-3588JD4 RK3588 System on Module

8K@30fps H.265/H.264

8K@60fps H.265/VP9/AVS2, 8K@30fps H.264 AVC/MVC, 4K@60fps AV1, 1080P@60fps MPEG-2/-1/VC-1/VP8

Rockchip RK3588

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

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

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

1 × PCIe3.0 (2 × 2 lanes, 1 × 4 lanes, 4 × 1 lanes), 3 × PCIe 2.1 (1 lane)

3 × SATA3.0 (Multiplexed with PCIe 2.1)

5V (voltage tolerance ± 5%)

Max: 13W(5V/2600mA), Normal: 2.8W(5V/560mA), Min: 0.175W(5V/35mA)

1 × HDMI2.1 TX/eDP1.3 TX (8K@60Hz, HDMI supports HDCP2.3; upports eDP1.3, 4K@60Hz, supports HDCP1.3; HDMI and eDP cannot work at the same time)

MIPI CSI (2 × 4Lanes/4 × 2Lanes/1 × 4Lanes + 2 × 2Lanes)

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; it also supports a variety of deep learning frameworks, including TensorFlow, TensorFlow Lite, PyTorch, Caffe, ONNX, and Darknet. It also supports the development of custom operators
• Supports Docker container management technology

69.6mm × 45.0mm × 4.6mm

≈18g

Operating Temperature: -20℃～60℃

Storage Temperature: -20℃～70℃

Storage Humidity: 10%～90%RH(non-condensing)

Independent watchdog

2 × USB3.1（Gen1）OTG, 1 × USB3.1（Gen1）HOST, 2 × USB2.0 HOST, 2 × USB2.0 OTG