
EC-ThorT5000

CSB1-N4AGXOrin

CSR2-N72R3399

EC-ThorT5000

CT36L/CT36B

EC-ThorT5000
· High-Performance AI Processor QCS8550
· Deployment of Large AI Models
· Supports Ray Tracing Technology
· 8K Video Encoding and Decoding
· Powerful Network Capabilities
· Metal Casing for Efficient Heat Dissipation
· Rich Expansion Interfaces
· Comprehensive Development Toolchain
Qwen
Llama
DeepSeek
Gemma
Features the Qualcomm QCS8550 octa-core AI processor with an integrated 48 TOPS NPU, supporting mainstream AI models and deep learning frameworks. The built-in Adreno 740 GPU enables ray tracing and 8K video codec. Housed in an industrial-grade all-metal casing for efficient heat dissipation, it ensures 24/7 stable operation to meet rigorous industrial demands.
AI Processor QCS8550
Private Deployment
Ray Tracing Technology
8K Video Codec Support
Network Capabilities
All-Metal Enclosure
Rich Expansion Interfaces
Development Toolchain
Integrated 48 TOPS NPU supports mixed-precision computation (INT4 to FP16), enabling powerful edge AI capabilities such as intelligent data processing, voice recognition, and image analysis for most terminal devices.
Widely applicable in industries such as intelligent surveillance, AI education, computing power services, edge computing, private deployment of large models, data security, and privacy protection.

AIBOX-8550 |
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Basic Specifications |
SOC |
Qualcomm QCS8550 |
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CPU |
Qualcomm Kryo® CPU: Octa-core 64-bit (1×GoldPlus@3.2GHz + (2+2)Gold@2.8GHz + 3×Silver@2.0GHz), 4nm advanced process, maximum frequency up to 3.36GHz |
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GPU |
Adreno 740 GPU: Supports ray tracing technology, OpenGL ES 3.2, Vulkan 1.2, full-profile OpenCL 3.0, and Adreno NN Direct |
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ISP |
Equipped with Qualcomm Spectra Cognitive ISP (Image Signal Processor), featuring three 18-bit 36MP ISPs |
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NPU |
Dual eNPU V3: Equipped with 4 HVX (Hexagon Vector Extensions), 1 HMX (Hexagon Matrix Extension); Computing power up to 48 TOPS (INT8), 12 TOPS (FP16) |
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Codec |
Video decoding: 8K@60fps/4K@240fps H.265/H.264/VP9/AV1 Video encoding: 8K@30fps/4K@120fps H.265/H.264 Supports concurrent 4K@60fps decoding and 4K@60fps encoding for wireless display scenarios |
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RAM |
16GB LPDDR5x |
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Storage |
256GB UFS4.0 |
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Storage expansion |
1 × M.2 (Expandable PCIe NVMe SSD/SATA SSD, supports 2242/2260/2280 specifications; Inside the device), 1 × TF Card |
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Power |
DC 12V/5A (5.5 × 2.1mm) |
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Power consumption |
Normal: 4.32W(12V/360mA), Max: 20W(12V/1670mA), Min(Sleep): 0.6W(12V/50mA) |
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OS |
Ububtu |
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Software support |
Supports on-premises deployment of large-scale parameter models based on the Transformer architecture, such as large language models (LLMs) including the Deepseek-R1 series, Gemma series, Llama series, Qwen series, Phi series, etc. Supports the QNN AI inference framework, as well as various deep learning frameworks including TensorFlow, TensorFlow Lite, PyTorch, ONNX, etc. |
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Size |
93.4mm × 93.4mm × 50.0mm |
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Weight |
≈ 500g |
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Environment |
Operating Temperature: -20℃~60℃, Storage Temperature: -20℃~70℃, Operating Humidity: 10%~90%RH (No condensation) |
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Interface Specifications |
Ethernet |
2 × Gigabit Ethernet (1000Mbps/RJ45) |
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Video output |
1 × HDMI2.0 (1080P) |
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USB |
2 × USB3.0 (Max: 1A), 1 × Type-C (For download) |
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Console |
1 × Console (Debug serial) |
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Button |
1 × Power, 1 × Recovery |
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