AIBOX-1688 Overview Specifications Wiki Technical Case Download
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Comprehensive private AI deployment

16 TOPS AI processor BM1688

BM1688, the SOPHON AI processor, features an octa-core ARM Cortex-A53 with up to 1.6 GHz of frequency. Equipped with a neural network
acceleration engine TPU, it delivers peak performance of 32T@INT4 and 16T@INT8, 4T@FP16/BF16, and 0.5T@FP32. With support for
mainstream programming frameworks, this processor can be widely used in AI inference, computer vision, and more.

Multi-channel video AI performance

The AI box supports up to 16 channels of H.265 / H.264 1080P video decoding, 10 channels of H.265 / H.264 1080P video encoding,
and 16 channels of 1080P HD video processing (decoding + AI analysis). This meets the needs of various AI applications
such as face detection on video streaming, license plate recognition, and smart cities.

Strong network communication capability

With dual 1000Mbps Ethernet, the AI box ensures high-speed and stable network communication,
meeting the needs of various application scenarios.

All-aluminum alloy enclosure for heat dissipation

The AI box features an industrial-grade all-metal enclosure with an aluminum alloy structure for thermal conduction.
The side of the top cover features a grille design for external airflow and efficient heat dissipation,
ensuring computing performance and stability even under high-temperature operating conditions.

Exquisite ingenious design

Its top cover is a porous hexagonal design, combining elegance with high efficiency. The compact,
exquisite device operates stably and meets the needs of various industrial-grade applications.

Abundant resources

We offer SDKs, tutorials, technical documentation, and development tools to streamline and improve the development process.

A wide range of applications

AIBOX-1688 is widely used in intelligent surveillance, AI education, services based on computing power, edge computing,
private deployment of large models, and data security and privacy protection.

Intelligent
surveillance
AI education
Computing
services
Edge computing
Large models
Data security

Specifications

Specifications
Basic
Specifications		 SOC

SOPHON BM1688

Octa-core ARM Cortex-A53 @ 1.6GHz
TPU

Built-in SOPHGO neural network acceleration engine TPU, 32T@INT4 peak computing power,

16T@INT8 peak computing power, 4T@FP16/BF16computing power, 0.5T@FP32 computing power
Decoding/
Encoding

Video decoding: H.264 / H.265 decoding (Max performance: 1920 * 1080@480FPS or 3840 * 2160 @120FPS)

Video encoding: H.264 / H.265 encoding (Max performance: 1920 * 1080@300FPS or 3840 * 2160 @75 FPS)

Image codec: JPEG/MJPEG Baseline codec (JPEG codec with a maximum resolution of 1080P@480 FPS)
RAM

8GB LPDDR4 (4GB/8GB/16GB optional)
Storage

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

1*M.2 (Expandable PCIe NVMe SSD(default support)/ SATA SSD(supported after software update),

supports 2242/2260/2280) (inside the device),1*TF Card
Power

DC 12V/3A（DC 5.5*2.1mm）
Power
consumption

Normal: 7.2W(12V/600mA), Max: 14.4W(12V/1200mA)
OS

Linux
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, MXNet, PaddlePaddle, and ONNX, as well as custom operator development

・ Docker container management technology
Size

93.4mm * 93.4mm * 50 mm
Weight

≈ 500g
Environment

Operating Temperature: -20℃～60℃,

Storage Temperature: -20℃～70℃,

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

2*1000Mbps Ethernet
Video output

1*HDMI2.0（4K@60fps)

USB

2*USB3.0 (Current Limit: 1A)
Other

1*Type-C (USB 2.0 device mode only), 1*Console (Debug serial), 1*Power button, 1*Recovery