EC-A1688JD4 is powered by the SOPHON octa-core AI processor BM1688, delivering up to 16 TOPS of INT8 computing
power. It supports
16 channels of H.264 1080p@30fps video decoding. This computer provides mainstream programming frameworks
and the SOPHON SDK,
a one-stop deep learning development toolkit. Its complete, easy-to-use toolchain features easy deployment of
algorithm applications and
a low cost of algorithm migration. The device can be applied to AI servers, edge AI boxes, industrial PCs,
smart IP cameras, AIOT, and intelligent security, improving various industries through AI.
This computer is equipped with the BM1688 SOPHON AI processor, featuring an octa-core ARM Cortex-A53 with a max
frequency of 1.6 GHz.
With an integrated TPU, a neural network acceleration engine, it delivers 32T@INT4 peak computing power,
16T@INT8 peak computing power,
4T@FP16/BF16, and 0.5T@FP32. With support for mainstream programming frameworks,
this device can be widely used in AI inference and computer vision.
It supports up to 16-channel H.264 1080P video decoding, 10-channel H.264 1080P video encoding,
and 16-channel 1080P HD video processing (decoding + AI analysis). This makes it ideal for various AI
application
scenarios such as facial detection on video streaming, license plate recognition, smart cities, and more.
This computer features two Gigabit Ethernet, and offers expansion capabilities for WiFi/BT modules via the M.2
E-KEY (2230) interface,
supporting WiFi 6 and BT5.0. It also provides 4G LTE expansion (Mini PCIe) and 5G (M.2),
enabling higher network communication speeds.
Featuring an industrial-grade aluminum alloy enclosure, this device boasts efficient fanless passive
dissipation,
ensuring reliable 24/7 operation to meet various industrial application requirements. Designed for saving space,
it supports wall-mounting for flexible installation on walls or industrial automation machinery.
A wide range of interface options includes HDMI 2.0, USB 3.0, Type-C (Debug), RS485, RS232, CAN, M.2 (5G), Mini
PCIe (4G), M.2 (WiFi), and M.2
(SSD). These interfaces facilitate the connection of peripheral devices, enabling different product applications
across
various fields.
We offer SDKs, tutorials, technical documentation, and development tools to streamline
and improve the development process.
The computer is widely used in AI servers, edge AI boxes, industrial PCs,
smart IP cameras, AIOT, intelligent security, and more.
AI servers
Edge AI boxes
AIOT
industrial PCs
IP cameras
Security
| EC-A1688JD4 | EC-A186JD4 | ||
Basic Specifications |
SOC |
SOPHON BM1688 |
SOPHON CV186AH |
CPU |
Octa-core ARM Cortex-A53 @ 1.6GHz |
Hexa-core ARM Cortex-A53 @ 1.6GHz |
|
TPU |
16T@INT8, 32T@INT4, 4T@FP16/BF16, and 0.5T@FP32 computing power |
7.2T@INT8, 12T@INT4, and 1.5T@FP16/BF16 computing power |
|
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. |
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Decoding/ Encoding |
Video decoding: H.264 decoding (Max performance: 1920×1080@480fps or 8192×4320@30fps) Video encoding: H.264 encoding (Max performance: 1920×1080@300fps or 8192×4320@15fps) Image codec: JPEG/MJPEG Baseline codec (JPEG codec capability: 1080P@480fps, maximum resolution of 32768×32768) |
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RAM |
8GB LPDDR4 (4GB/8GB/16GB optional) |
4GB LPDDR4 (4GB/8GB/16GB optional) |
|
Storage |
32GB eMMC (32GB/64GB/128GB/256GB optional) |
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Storage expansion |
1 × TF Card, M.2 SATA3.0/PCIe NVMe SSD 2242/2260/2280 (inside the device), scalable SATA3.0 SSD (inside the device) |
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OS |
Linux OS |
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Software Support |
Supports private deployment of ultra-large-scale Transformer-based models, including large language models such as Deepseek-R1, Gemma, Llama, ChatGLM, Qwen, and Phi series. Supports traditional network architectures including CNN, RNN, and LSTM, as well as mainstream deep learning frameworks: TensorFlow, PyTorch, PaddlePaddle, Caffe, and ONNX. Supports custom operator development and Docker-based containerized management. |
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Power |
DC 12V (5.5mm × 2.1mm, support 9V~24V wide voltage input) |
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Power consumption |
Normal: 7.2W(12V/600mA), Max: 12W(12V/1000mA) |
Normal: 8.5W(12V/710mA), Max: 14W(12V/1170mA) |
|
Size |
188.0mm × 88.44mm × 50.65mm |
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Weight |
Net weight: 0.79kg, Total weight with packaging: 1.14kg |
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Environment |
Operating Temperature: -20℃~60℃, Storage Temperature: -20℃~70℃, Storage Humidity: 10%~90%RH (non-condensing) |
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Interface Specifications |
Internet |
Ethernet: 2 × RJ45 (1000Mbps) WiFi: Extend 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 (Reused with 5G) 5G: Extend 5G via M.2 B-KEY (Reused with 4G and USB3.0(1), not pasted by default) |
|
Video output |
1 × HDMI2.0 (4K@60Hz) |
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Audio output |
1 × 3.5mm Audio jack (Support MIC recording, American standard CTIA) |
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USB |
2 × USB3.0 (Max: 1A; Top: USB3.0(1), reused with 5G; Bottom: USB3.0(2)), 1 × Type-C (Debug) |
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Others |
1 × SIM Card, 1 × Phoenix connector (8Pin, 3.5mm pitch): 1 × RS485, 1 × RS232, 1 × CAN 2.0 |
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