7.2 TOPS
Computing Power
Private Deployment of
Large Models
Supports Multiple Deep
Learning Frameworks
Supports 16-Channel
Video Decoding
AIO-186JD4 equipped with the SOPHON CV186AH hexa-core chip, featuring six ARM Cortex-A53 cores, it delivers 7.2 TOPS of
computing power and is widely used in AI inference and computer vision applications.
Supports the private deployment of expansive parameter models based on the Transformer framework, including substantial
language models like Gemma-2B, ChatGLM3-6B, Qwen1.5-1.8B, and Llama2-7B.
Supports full-process handling of 16 channels of 1080P
high-definition video (decoding + AI analysis), meeting the
needs of various AI application scenarios such as video
stream facial recognition, license plate recognition, and
smart city initiatives.
It supports multiple algorithms porting such as "person/
vehicle/object" recognition, video structuring, and
trajectory behavior, with high security and reliability. It
can be flexibly applied to various product development
Provides a one-stop deep learning SDK with a complete
toolkit of software utilities, encompassing driver
environments, compilers, and deployment tools for
inference.
AIO-186JD4 | ||
Basic Specifications |
SOC |
SOPHON CV186AH |
CPU |
Hexa-core 64-bit ARM Cortex-A53 @ 1.6GHz |
|
TPU |
Built-in SOPHGO neural network acceleration engine TPU, computing power up to 7.2T@INT8, 12T@INT4, 1.5T@FP16/BF16 |
|
ISP |
Time-sharing multiplexing for up to 6 sensor input videos, with maximum widths of 4608 (non-tile mode) and 8192 (tile mode) Supports Sensor self-band dynamic and 2-frame wide dynamic range, and the maximum performance supports: 12M@30 HDR or 8K@15 SDR or 16M@30 SDR Support RGB-IR, AI ISP interface, 3A (AE/AWB/AF, 3A control user adjustable) Support fixed mode noise removal, dead pixel correction, shadow correction, lens distortion correction, purple edge correction, Bayer noise reduction, 3D denoising, image edge enhancement, dehazing, dynamic contrast enhancement, image video Mirror, Flip and other functions |
|
VPU |
Video decoding: H.265/H.264 decoding (maximum performance: 1920×1080@480fps or 8192×4320@30fps) Video encoding: H.265/H.264 encoding (maximum performance: 1920×1080@300fps or 8192×4320@15fps) Image codec: JPEG/MJPEG Baseline codec (JPEG codec: 1080P@480fps, maximum resolution 32768×32768) |
|
RAM |
4GB LPDDR4(4GB/8GB 可选) |
|
Storage |
32GB eMMC (32GB/64GB/128GB/256GB optional) |
|
Expand storage |
1 × TF Card, 1 × M.2 (expandable M.2 NVME 2242/2260/2280 SSD), 1 × SATA3.0 (expandable SATA3.0 SSD) |
|
OS |
Linux OS(Ubuntu) |
|
Software Support |
・ The private deployment of ultra-large-scale parameter models under the Transformer architecture, including large language models such as Gemma-2B, LlaMa2-7B, ChatGLM3-6B, Qwen1.5-1.8B ・ Traditional network architectures such as CNN, RNN, and LSTM; a variety of deep learning frameworks, including TensorFlow, Pytorch, PaddlePaddle, Caffe and ONNX, as well as custom operator development ・ Docker container management technology |
|
Power |
DC 12V (5.5mm × 2.1mm, support 9V~24V wide voltage input) |
|
Power consumption |
Normal: 6.6W (12V/550mA), Max: 12W (12V/1000mA) |
|
Size |
122.89mm × 85.04mm × 22.7mm |
|
Weight |
≈122g |
|
Environment |
Operating Temperature: -20℃~60℃ , Storage temperature: -20°C~70°C, Storage Humidity:10%~90%RH(non-condensing) |
|
Interface Specifications |
Internet |
Ethernet: 2 × RJ45 (1000Mbps) WiFi: Expand WiFi/Bluetooth module via M.2 E-KEY (2230), Supports 2.4GHz/5GHz dual-band WiFi6(802.11a/b/g/n/ac/ax) and Bluetooth 5.2 4G: Extend 4G LTE via Mini PCIe |
Video input |
3 × MIPI CSI DPHY(1×4 lanes 或 2×2 lanes,30Pin-0.5mm) |
|
Video output |
1 × HDMI2.0(4K@60fps) 1 × MIPI DSI DPHY(1×4 lanes,30Pin-0.5mm) |
|
Audio output |
1 × 3.5mm Audio jack (support MIC recording, American standard CTIA) |
|
SATA |
1 × SATA3.0 (expandable SATA3.0 SSD) |
|
USB |
2 × USB3.0 (Max: 1A) |
|
Other interfaces |
1 × Type-C (USB2.0/DEBUG), 1 × FAN (4Pin-1.25mm), 1 × SIM Card 1 × Double-row pin headers(2×10-20PIN-2.0mm): USB2.0, SPI, 2×I2C, Line in, Line out, GPIO 1 × Phoenix connector (2×4Pin, 3.5mm Pitch): 1 × RS485, 1 × RS232, 1 × CAN 2.0 |