EC-A3588SJD4 AI Fanless ARM Computer

EC-A3588SJD4 AI Fanless ARM Computer

$819.00

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EC-A3588SJD4 AI Computers

Equipped with Rockchip octa-core 64-bit RK3588S processor with a maximum frequency of 2.4GHz and a built-in 6 TOPS NPU, it supports up to 32GB LPDDR5 memory and is compatible with private deployment of mainstream large AI models as well as multiple deep learning frameworks. The device also enables 8K video encoding and decoding with simultaneous encode/decode capability, and supports operating systems such as Android and Ubuntu.

AI Processor RK3588S

Equipped with Rockchip RK3588S octa-core 64-bit processor built on 8nm LP process technology, it achieves a maximum frequency of 2.4GHz. The integrated ARM Mali-G610 MP4 quad-core GPU delivers enhanced performance for diverse AI application scenarios.

Private Deployment

Supports private deployment of large-scale parameter models based on Transformer architecture, including Gemma, ChatGLM, Qwen, Phi series and other large language models. It is also compatible with traditional network architectures like CNN, RNN, and LSTM, as well as multiple deep learning frameworks including TensorFlow, TensorFlow Lite, PyTorch, and Caffe.

32GB LPDDR5 Memory

LPDDR5 offers larger memory capacity, higher bandwidth, faster data transfer rates, lower power consumption, and more advanced Error Correction Code (ECC) technology. Meets the memory space and response speed requirements for private deployment of large models.

8K Video Encoding and Decoding

Supports 8K@60fps video decoding and 8K@30fps video encoding with simultaneous processing capabilities, delivering up to 32 channels of 1080P@30fps decoding and 16 channels of 1080P@30fps encoding. The powerful video codec performance enables crystal-clear 8K visual presentation with exceptionally refined image quality.

Multiple Operating Systems

Supports multiple operating systems including Android, Ubuntu Desktop, Ubuntu Server, Debian, Buildroot, and Kylin, with UEFI boot capability to provide a secure and stable system environment for product development and manufacturing.

Full aluminum alloy shell

Featuring an industrial-grade all-aluminum alloy casing with fanless cooling design, it ensures stable 24/7 operation to meet diverse industrial application requirements.

Rich Expansion Interfaces

Equipped with expansion interfaces including Gigabit Ethernet, HDMI 2.1, USB 3.0, RS485, RS232, CAN, Type-C, and SIM card slots for seamless peripheral connectivity.

Development Materials

Includes complete source code, tutorials, technical documentation, and development tools, enabling users to efficiently perform secondary development and quickly create independently controllable products.

6 TOPS NPU Computing Power

Built-in powerful NPU with computing power of up to 6 TOPS, supporting INT4/INT8/INT16/FP16/BF16/TF32 mixed operations. Capable of intelligent data processing, voice recognition, and image analysis, meeting the edge computing AI application needs of most terminal devices.

Application Scenarios

Widely used in edge computing, private deployment of large models, computing power services, intelligent security, smart home, smart industry, and other fields.

Edge Computing

Private Deployment of Large Models

Computing Power Services

Intelligent Security

Smart Home

Smart Industry

Interfaces

Specifications

EC-A3588SJD4 AI
Basic Specifications	SOC	Rockchip RK3588S
	CPU	Octa-core 64-bit (4×Cortex-A76 + 4×Cortex-A55), 8nm advanced process, with a frequency of up to 2.4GHz
	GPU	ARM Mali-G610 MP4 quad-core GPU, support OpenGL ES3.2/OpenCL 2.2/Vulkan1.1, 450 GFLOPS
	NPU	6 TOPS, support INT4/INT8/INT16/FP16 hybrid computing
	Codec	Video decoding: 8K@60fps VP9, 8K@30fps H.264 AVC/MVC, 4K@60fps AV1, 1080P@60fps MPEG-2/-1/VC-1/VP8 Video encoding: 8K@30fps H.264
	RAM	8GB/16GB/32GB 64-bit LPDDR5
	Storage	16GB/32GB/64GB/128GB eMMC
	Storage expansion	1 × M.2 M-KEY (Supports SATA3.0/PCIe NVMe 2242/2260/2280 SSDs, shared with USB3.0(1); Located at the bottom of the computer), 1 × TF Card
	OS	Android, Ubuntu Desktop, Ubuntu Server, Debian, Buildroot, RTLinux, Kirin Linux * Supports UEFI boot mode
	Software support	Support the privatization deployment of ultra-large-scale parametric models under the Transformer architecture, such as Deepseek-R1 series, Gemma series, Llama series, ChatGLM series, Qwen series, Phi series and other large language models. It supports traditional network architectures, such as CNN, RNN, and LSTM, and facilitates the import and export of RKNN models. Additionally, it supports 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.
	Power	DC 12V (5.5mm × 2.1mm, support 9V~24V wide voltage input)
	Power consumption	Normal: 2.76W(12V/230mA), Max: 11.39W(12V/950mA), Min(Sleep): 0.6W(12V/50mA)
	Dimension	188.0mm × 88.44mm × 50.65mm
	Weight	Net weight of computer: 0.79kg, Total weight with package: 1.15kg
	Environment	Operating Temperature: -20℃～60℃, Storage Temperature: -20℃～70℃, Storage Humidity: 10%～90%RH (non-condensing)
Interface Specifications	Internet	Ethernet: 1 × 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 (Shared with 5G) 5G: Extend 5G via M.2 B-KEY (Shared with 4G and USB3.0(1), not mounted by default)
	Video output	1 × HDMI2.1 (8K@60Hz)
	Audio output	1 × 3.5mm Audio jack (Support MIC recording, American Standard CTIA)
	USB	2 × USB3.0 (Max: 1A; UP: USB3.0(1), shared with 5G; DOWN: USB3.0(2)), 1 × Type-C (Flash)
	Other interfaces	1 × SIM Card 1 × Phoenix connector (2×4PIN, 3.5mm pitch): 1 × RS485, 1 × RS232, 1 × CAN 2.0