CSB1-N10S1684X BM1684X AI 1U Server

CSB1-N10S1684X BM1684X AI 1U Server

$9,319.00

Taxes included. Shipping calculated at checkout.

ManualWikiDownload

Brand Firefly

Availability

1 in stock

CSB1-N10 AI Server

Features 10 built-in distributed computing nodes, with each node delivering computing power ranging from 6T-157T. It supports multiple platforms such as Rockchip, SOPHGO, NVIDIA, Qualcomm, and SpacemiT. CSB1-N10 servers enables private deployment of mainstream AI models and It equipped with two 10-gigabit network ports and a gigabit network port, while also supporting expandable SATA 3.0 hard drives.

Private Deployment

Supports private deployment of mainstream large language models (such as Gemma, Llama, Qwen, etc.), large vision 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 traditional network architectures such as CNN, RNN, and LSTM, along with multiple deep learning frameworks including TensorFlow, PyTorch, PaddlePaddle, and ONNX. It also enables custom operator development and Docker containerization management.

Processing for 196 Video Streams

Supports AI processing for 196 video streams (specific processing performance may vary depending on the specifications of the core board and the type of AI model running). It features powerful multi-task concurrent processing capabilities and can be widely applied in AI application scenarios such as intelligent security and edge computing.

3.5-inch SATA 3.0 HDD/SSD

Configured with one 3.5-inch (or 2.5-inch) drive bay that supports SATA 3.0 HDD/SSD expansion, the device can be easily scaled to terabyte-level capacity. It supports hot-swapping for fast drive replacement, meeting the one-stop deployment requirements for file management, data backup, video surveillance, and other applications.

Dual 10-Gigabit SFP+ ports

Featuring dual 10-Gigabit SFP+ and dual Gigabit Ethernet ports, it delivers the high-speed, stable connectivity required for high-bandwidth application scenarios.

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.

Up to 1570 TOPS Computing Power

CSB1-N10 Integrates 10 distributed computing nodes with comprehensive processor support, including Rockchip, SOPHGO, NVIDIA, Qualcomm, and SpacemiT. Each node delivers 6-157 TOPS of computing power, with configurable node quantities to provide robust acceleration for AI and deep learning workloads.

Application Scenarios

Widely applicable to products and fields such as edge computing, private deployment of large models, smart cities, smart healthcare, smart industry, and intelligent security.

Edge Computing

Private Deployment of Large Models

Smart City

Smart Healthcare

Smart Industry

Intelligent Security

Interfaces

Specifications

CSB1-N10S1684X
Technical Specifications	Server form	1U rack-mounted computing power server
	Architecture	ARM architecture
	Number of nodes	10 distributed computing nodes + 1 control node
	Compute nodes	Octa-core 64-bit processor BM1684X, main frequency up to 2.3GHz
	Control nodes	Octa-core 64-bit processor RK3588, main frequency up to 2.4GHz, the highest computing power is 6TOPS
	AI computing power	320TOPS (32T × 10, INT8)
	Fan module	6 high-speed cooling fans
Basic Specifications	Video encoding	H.264: 3×4K@25fps, 12×1080P@25fps
	Video decoding	H.264: 8×4K@25fps, 32×1080P@25fps 1×8K@25fps
	RAM	8GB LPDDR4 × 10 (8/12/16GB)
	Storage	32GB eMMC × 10 (32/64/128GB)
	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)
	Dimension	494.0mm × 440.5mm × 44.4mm
	Environment	Operating Temperature: 0ºC ~ 45ºC, 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: 8.1kg, total weight with packaging: 10.3kg
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	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
	Vision large models	BM1684X: Support the privatization deployment of large visual models such as ViT, Grounding DINO, SAM, etc. Jetson Orin NX: Supports the privatization deployment of large vision models such as EfficientVIT, NanoOWL, NanoSAM, SAM, TAM, etc.
	AI Painting	BM1684X/Jetson Orin NX: Support the private deployment of Flux, Stable Diffusion, and Stable Diffusion XL image generation models
	Deep learning	All models: Support traditional network architectures such as CNN, RNN, LSTM, and support various deep learning frameworks such as TensorFlow, PyTorch, PaddlePaddle, ONNX, and Caffe. Support custom operator development and Docker containerization management technology Jetson Orin NX: Supports Ollama local large model deployment framework and ComfyUI graphical deployment framework
Interface Specifications	Internet	2 × 10G Ethernet (SFP+), 2 × Gigabit Ethernet (RJ45), 1 × Gigabit Ethernet (RJ45, MGMT is used as BMC management network)
	Console	1 × Console (RJ45, BMC debug serial port, baud rate 115200)
	Video output	1 × VGA (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)