CSB1-N10NOrinNano Jetson Orin Nano AI Server

1U rack-mounted computing power server

ARM architecture

10 distributed computing nodes (up to 80 ARM cores) + 1 control node

Hexa-core 64-bit processor NVIDIA Jetson OrinNano, main frequency up to 1.7GHz

Octa-core 64-bit processor RK3588, main frequency up to 2.4GHz, the highest computing power is 6TOPS

670 TOPS (INT8)

6 high-speed cooling fans

NVIDIA Jetson Orin Nano

Hexa-core 64-bit 1.7GHz

670TOPS

1×4K60/2×4K30/5×1080P60/11×1080P30 H.265

8GB LPDDR5 × 10 (Number of compute nodes)

256GB (2242 PCIe NVMe SSD, the server is internally assembled)

3.5-inch/2.5-inch SATA3.0/SSD hard drive slot × 1 (BMC can directly operate the hard drive, and computing child nodes can indirectly access the hard drive through the network sharing method provided by BMC)

550W AC power supply (Input: 90V AC~264V AC, 47 Hz~63 Hz, 8A) (Hot swappable not supported)

494.0mm × 440.5mm × 44.4mm

• Operating Temperature: 0ºC ~ 45ºC
• Storage Temperature: -40ºC ~ 60ºC
• Operating Humidity: 5% ~ 90%RH(non-condensing)

• IEC 297 Universal Cabinet Installation: 19 inches wide and 800 mm deep and above
• Retractable slideway installation: The distance between the front and rear holes of the cabinet is 543.5mm~848.5mm

Server net weight: 8.1kg, total weight with packaging: 10.3kg

The BMC management system is integrated with the web-based management interface, supporting Redfish, VNC, NTP, monitoring advanced and virtual media, and the BMC management system can be redeveloped.

All models support the privatization of ultra-large-scale parametric models under the Transformer architecture, such as Deepseek-R1 series, Gemma series, Llama series, ChatGLM series, Qwen series, Phi series and other large language models

BM1684X: Support the privatization deployment of large visual models such as ViT, Grounding DINO, SAM, etc.
Jetson Orin Nano/Jetson Orin NX: Supports the privatization deployment of large vision models such as EfficientVIT, NanoOWL, NanoSAM, SAM, TAM, etc.

Supports multiple deep learning frameworks accelerated by cuDNN, including PaddlePaddle, PyTorch, TensorFlow, MATLAB, MxNet, Caffe2, Chainer, and Keras.
Supports custom operator development.
Docker containerization: Docker containerization technology is supported, which can be easily used for image deployment.

• 2 × 10G Ethernet (SFP+)
• 2 × Gigabit Ethernet (RJ45)
• 1 × Gigabit Ethernet (RJ45, MGNT is used as BMC management network)

1 × Console (RJ45, BMC debug serial port, baud rate 115200)

1 × VGA (maximum resolution 1080P, BMC management display)

1 × VGA (maximum resolution 1080P, BMC management display)

2 × USB3.0 (The lower USB is USB3.0 OTG, and the BMC can be upgraded OTG by using a USB flash drive)

1 × Reset, 1 × UID, 1 × Power button

1 × RS232 (DB9, baud rate 115200),1 × RS485 (DB9, baud rate 115200)