CSB1-N4AGXOrin Jetson AGX Orin 1U AI Server

CSB1-N4AGXOrin Jetson AGX Orin 1U AI Server

$14,119.00

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CSB1-N4AGXOrin AI Server

CSB1-N4AGXOrin can be configured with up to 4 NVIDIA Jetson AGX Orin (64 GB) compute modules, delivering a maximum computing power of 1100 TOPS (INT8). It supports the private deployment of mainstream AI models and various deep learning frameworks. Equipped with four 10-gigabit network ports, it also allows for expansion with SATA 3.0 hard drives.

Private Deployment

Supports private deployment of mainstream large language models (such as Gemma, Llama, Qwen, etc.), vision large models (such as EfficientVIT, SAM, TAM, etc.), image generation models (such as Flux, Stable Diffusion, etc.), and other large-scale models.

Deep Learning Frameworks

Supports the Ollama local large model and ComfyUI graphical deployment framework; compatible with multiple deep learning frameworks accelerated by cuDNN, including PaddlePaddle, PyTorch, TensorFlow, MATLAB, MXNet, and Keras; supports custom operator development and Docker containerization management technology.

8K Decoding ＆ 4K Encoding

Supports decoding of up to 1 channel of 8K@30fps, 3 channels of 4K@60fps, and 11 channels of 1080P@60fps video, as well as encoding of 2 channels of 4K@60fps and 8 channels of 1080P@60fps video, meeting the demands of various AI application scenarios.

3.5-inch SATA 3.0 HDD/SSD

Features a 3.5-inch (or 2.5-inch) drive bay supporting SATA 3.0 HDD/SSD expansion, enabling seamless capacity scaling to terabyte-level storage. With hot-swappable capability for rapid drive replacement, it fulfills integrated deployment requirements for file management, data backup, video surveillance, and similar applications.

4-port 10 Gigabit SFP+

Equipped with four 10-gigabit SFP+ network ports for high-speed, stable communication to meet high-bandwidth application scenarios. A dedicated BMC management network interface is included to separate management and data traffic, ensuring network security and reliability.

Standard 1U Rack Server Size

Features a standard 1U rack-mounted chassis design with flexible deployment capabilities, fully compatible with most data center cabinet types. The robust construction incorporates 6 high-efficiency cooling fans to ensure 7×24 continuous stable operation.

aBMC Management System

Equipped with an advanced aBMC intelligent management system that enables real-time monitoring, software/hardware configuration, troubleshooting, anomaly alerts, system upgrades, and remote maintenance. Supports secondary development for customized requirements.

Efficient and Low-Cost

Server highly integrates computing units, storage, universal serial bus, network controller, power controller, and sensors into one, providing SDK all-in-one deep learning development toolkit, underlying driver environment, compiler, inference deployment tool, and a series of software tools to reduce users' procurement, development, and operation costs.

1100 TOPS Computing Power

Configured with up to four NVIDIA Jetson AGX Orin (64GB) compute nodes, delivering a peak performance of 1100 TOPS (INT8) to provide robust computing power for AI and deep learning applications.

Application Scenarios

Widely applicable in fields such as edge computing, large model localization, smart cities, smart healthcare, smart industry, and smart agriculture.

Edge Computing

Private Deployment of Large Models

Smart City

Intelligent Security

Smart Industry

Smart Agriculture

Interfaces

Specifications

CSB1-N4AGXOrin
Technical Specifications	Server form	1U rack-mounted computing power server
	Architecture	ARM architecture
	Number of nodes	4 distributed computing nodes + 1 control node
	Compute nodes	12-core 64-bit processor NVIDIA Jetson AGX Orin (64GB), main frequency up to 2.2GHz
	Control nodes	Octa-core 64-bit processor RK3588, main frequency up to 2.4GHz, the highest computing power is 6TOPS
	AI computing power	1100TOPS (275T × 4, INT8)
	Fan module	6 high-speed cooling fans
Basic Specifications	Video encoding	2×4K@60fps, 4×4K@30fps, 8×1080P@60fps, 16×1080P@30fps
	Video decoding	1×8K@30fps, 3×4K@60fps, 7×4K@30fps, 11×1080P@60fps, 22×1080P@30fps
	RAM	64GB LPDDR5 × 4
	Storage	64GB eMMC × 4
	Storage expansion	3.5-inch/2.5-inch SATA3.0 SSD hard drive slot × 1 (Supports hot swapping; 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)
	Power	550W AC power supply (Input: 90V AC~264V AC, 47 Hz~63 Hz, 8A; Hot swappable not supported)
	Power consumption	Normal: 135W, Max: 400W
	Dimension	494.0mm × 469.3mm × 44.4mm
	Weight	Server net weight: 8.8kg, total weight with packaging: 11kg
	Environment	Operating Temperature: 0ºC ~ 40ºC, Storage Temperature: -40ºC ~ 60ºC, Operating Humidity: 5% ~ 80%RH (non-condensing)
Physical Specifications	Installation requirements	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
Physical Specifications	Full weight	Server net weight: 8.8kg, total weight with packaging: 11kg
Software Specifications	BMC	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.
	Large language models	Support the privatization deployment 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.
	Vision large models	Support the privatization deployment of large visual models such as EfficientVIT, NanoOWL, NanoSAM, SAM and TAM.
	AI Painting	Supports the private deployment of Flux, Stable Diffusion, and Stable Diffusion XL image generation models.
	Deep learning	Support Ollama local large model deployment framework and ComfyUI graphical deployment framework. Support for a variety of deep learning frameworks supported by cuDNN acceleration, including PaddlePaddle, PyTorch, TensorFlow, MATLAB, MXNet, Keras. Support custom operator development and Docker containerization management technology.
Interface Specifications	Internet	4 × 10G Ethernet (SFP+), 1 × Gigabit Ethernet (RJ45, MGMT is used as BMC management network)
	Console	1 × Console (RJ45, BMC debug serial port, baud rate 115200)
	Display	1 × HDMI (maximum resolution 1080P, BMC management display)
	USB	2 × USB3.0 (The lower USB is USB3.0 OTG, and the BMC can be upgraded OTG by using a USB flash drive)
	Button	1 × Reset, 1 × UID, 1 × Power
	Other interfaces	1 × RS232 (DB9, baud rate 115200),1 × RS485 (DB9, baud rate 115200)