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EC-A3399C(AI) EC-A3399C


Six-core AI Embedded Computer

Based on AIO-3399C (AI version) high-performance open-source platform, industrial-grade metal case and fan-off design configured, with high-efficiency cooling ability, complete interface, strong applicability and computing power and ultrahigh performance. It can be applicable to high-performance edge computing to accelerate in-depth learning computation and AI algorithm. It can be rapidly applied in the field of mobile edge computing, smart home, face recognition, etc.

Six-core 64 bit High-performance Core

ARM Cortex-A72 architecture and six-core 64-bit high-performance processor carried, frequency 1.8GHz reached, integrated quad-core Mali-T860 GPU, H.265 HEVC, VP9 H.264 encoding and 4K HDR supported, with strong ability of hard decoding as high as 4K.

Ultrahigh Performance

Onboard AI embedded neural network processor NPU, with 28000 parallel neural calculation cores, on-chip parallel and in-situ computation supported, with a peak performance reaching up to 5.6 Tops and 2.8 Tops computing performance, with an efficiency energy-consumption ratio reaching up to 9.3 Tops/W. It has strong computing power. In the meantime, extremely low energy consumption is also maintained, making it extremely advantageous in the application of edge computing of terminal device.

Unique AI Architecture

Dedicated MPE matrix engine and APiM (AI processing in Memory) framework for AI adopted, local parallel AI computation integrated with storage and calculation. one-time upgrade network preload with no need for instructions, bus, and external DDR cache. This configuration improves the processing speed hugely and lowers processing energy consumption a lot compared with processors built in traditional architecture approaches.

Supporting Model Training Tool

Complete easy-to-use model-training tool PLAI (People Learn AI) based on PyTorch is offered. It can be developed on Windows 10 and Ubuntu 16.04 system, and user-defined network model is added easier, greatly lowering the technical threshold of using AI.

Provide Network Training Model

Three kinds of network training model sample including GNet1, GNet18 and GNetfc based on VGG are supported. Subsequently, network samples will be continuously added, contributing to easy test of a large amount of in-depth learning application on device.

Configuring Metal Case

High-quality metal case and fanless design configured, heat-conducting aluminum alloy structure, high-efficiency cooling, 60℃high-temperature aging, stable operation for 7x24 hours, various installation ways contributing to its embedding into various smart devices more convenient.

Rich External Interfaces

HDMI2.0, LAN, Type-C, USB3.0, RS485, RS232 and other interfaces owned to make it possible to be widely applied in various industries



RK3399, Dual-core(Cortex-A72)+ Quad-core(Cortex-A53),frequency up to 1.8 GHz


Quad-core ARM Mali-T860

Support OpenGL ES 1.1/2.0 /3.0, OpenVG1.1, OpenCL, Directx11


SPR2801S, Adopt MPE and APiM unique AI architecture

Computing performance up to 2.8Tops and 9.3Tops/W energy efficiency


2GB / 4GB dual-channel LP DDR4


8GB -128GB High-speed eMMC、TF Card Slot


RJ45 interface Gigabit Ethernet

On-board WIFI/BT module, support 2.4GHz/5GHz dual-band WiFi,802.11a/b/g/n/ac protocol

Support Bluetooth 4.1(support BLE)

Mini PCIe(Used to expand 3G/4G modules, use with Micro SIM card slot)


Support 4K VP9 and 4K 10bits H265/H264 video decoding, up to 60fps

1080P Multi-format video decoding(VC-1, MPEG-1/2/4, VP8)

1080P video decoding, support H.264,VP8 formats

Video post processor: deinterlacing, denoising, edge/ detail/ color optimization


Dual VOP: support 4096X2160 and 2560X1600 resolution

HDMI2.0 support 4K 60Hz display, support HDCP 1.4/2.2

Support eDP 1.3(4 line, 10.8Gbps), can directly drive multiple resolutions LCD screen which with eDP interface

Support dual 6/8 bit LVDS interface, up to 24-bit 1920×1200 resolution

Support Rec.2020 and Rec.709 color gamut conversion

1 x DP 1.2 (DisplayPort) , support 4K@60 fps output


Dual ISP pixel processing capability up to 13MPix/s, support simultaneous input of two-way camera data

Support USB3.0 HOST and Type-C

ADC x 1, SPI / GPIO, LED×2, I²C×1, Gravity sensor×1(Scalable)

SD Card

Support SD Card


Support RTC real-time clock


Support timer switch


PHONE x 1, LINE-IN x 1, LINE-OUT x 1, Microphone (left and right channel)


Type-C(OTG), USB3.0 x 1, USB2.0 x 4(interface x 2, socket x 2)


Power Button(Button×1, socket×1), Recover Button(Button×1, socket×1)

Serial port

RS232×1, RS485×1, Debug serial port×1, on-board 2-way TTL


With a one-way infrared receiver, support infrared remote control

Power Supply

DC 12V-2A(DC5.5 × 2.1mm), Support for external connection( Power socket×1) Can power by POE+(802.3 AT, Output Power 30W) Ethernet


Support Android\Linux\Ubuntu system


Support PyTorch , Caffe framework, follow-up support TensorFlow


PLAI model training tool(Support for GNet1, GNet18 and GNetfc network models which based on VGG)

Power Parameter
Type Min Typical Max
Operating Voltage 6v 12v 24v
Operating Current 500mA 1A 2A
Environmental Parameter
Type Mix Typical Max
Operating Temperature -20 ℃ 25 ℃ 60 ℃
Storage Temperature -40 ℃ 25 ℃ 125 ℃
Appearance Structure
Size 160 x 94 x 26 mm