AIBOX-1684X Embedded PC Edge Computing Video Analysis
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- Stock: In Stock
- Model: aibox-1684x-ai-box-up-to-32-tops-of-computing-power
- SKU: aibox-1684x-ai-box-up-to-32-tops-of-computing-power
190 samples sold
$659.00
AIBOX-1684X adopts SOPHON AI processor BM1684X, which can be configured with 16GB large memory and 128GB eMMC; supports 32TOPS (INT8) peak computing power, 16TFLOPS (FP16/BF16) computing power, and 2TFLOPS (FP32) high-precision computing power; supports 32-channel H.265/H.264 1080p@25fps video decoding; supports mainstream programming frameworks, has a complete tool chain and high ease of use, and low algorithm migration cost; suitable for a variety of AI computing scenarios such as visual computing, edge computing, general computing services, smart transportation, unmanned supermarkets, drones, etc.
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Feature
- The Private Deployment of Large Models: Large language Models; Traditional network architectures; Docker container
- 32TOPS BM1684X AI Processor: The SOPHON AI processor BM1684X uses an octa-core ARM Cortex-A53 with a main frequency of up to 2.3GHz and adopts a 12nm lithography process.
- Powerful Multi-channel Video AI Performance: The embedded PC supports up to 32-channel 1080P H.264/H.265 video decoding and 32-channel 1080P HD video processing (decoding + AI analysis), which is very suitable for various AI applications such as face detection and license plate recognition in video streams.
- Powerful Network Communication Capabilities: With dual 1000Mbps Ethernet, the AI box ensures high-speed and stable network communication, meeting the needs of various application scenarios.
- All-aluminum Alloy Shell: Industrial-grade all-metal body, aluminum alloy structure, excellent thermal conductivity. The grille design on the top cover effectively conducts heat, ensuring computing performance and stability even under high-temperature operating conditions. The top cover adopts a hexagonal porous design, which is both elegant and efficient.
Applications
- Surveillance
- AI Education
- Computing Services
- Edge Computing
- Private Deployment of Large Models
- Data Security
Hardware Overview
