Name: CSA1-N8 AI Server
Brand: Firefly Store
Availability: OutOfStock

CSA1-N8 AI Server

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CSA1-N8 AI Server

CSA1-N8 features built-in distributed computing nodes with 8 computing platforms, each capable of delivering up to 32 TOPS of computing power. It supports the private deployment of mainstream AI large models and multiple deep learning frameworks. Equipped with two 10-gigabit Ethernet ports and a gigabit Ethernet port, it also supports expandable 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 traditional network architectures (CNN, RNN, LSTM) and mainstream deep learning frameworks (TensorFlow, PyTorch, PaddlePaddle, ONNX), with additional capabilities for custom operator development and Docker containerization.

Video AI Processing Capability

Capable of AI processing for 256 concurrent video streams, featuring robust multi-tasking performance. Actual throughput depends on the core board and AI model, enabling diverse applications in 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.

256 TOPS Computing Power NPU

CSA1-N8 features eight distributed computing nodes, configurable with either Sophon BM1684X or BM1684 chips. Each node delivers up to 32 TOPS or 17.6 TOPS of computing power, respectively. The number of nodes is also customizable (up to eight), providing robust computational support for AI and deep learning applications.

Application Scenarios

Widely applicable to edge computing, private deployment of large models, smart transportation, Intelligent security, smart healthcare, smart industry and other products and fields.

Edge Computing

Private Deployment of Large Models

Smart Transportation

Smart Healthcare

Intelligent Security

Smart Industry

Interfaces

Specifications

		CSA1-N8S1684X	CSA1-N8S1684
Technical Specifications	Server form	1U rack-mounted computing power server
	Architecture	ARM architecture
	Number of nodes	8 distributed computing nodes + 1 control node
	Compute nodes	Octa-core 64-bit processor BM1684X, up to 2.3GHz	Octa-core 64-bit processor BM1684, up to 2.3GHz
	Control nodes	Octa-core 64-bit processor RK3588S, main frequency up to 2.4GHz, the highest computing power is 6TOPS
	AI computing power	256TOPS (32T × 8, INT8)	140.8TOPS (17.6T × 8, INT8)
	Fan module	6 high-speed cooling fans
Basic Specifications	Video encoding	H.264: 3×4K@25fps, 12×1080P@25fps	H.264: 2×1080P@25fps
	Video decoding	H.264: 8×4K@25fps, 32×1080P@25fps	H.264: 32×1080P@30fps
	RAM	16GB LPDDR4 × 8 (Number of Compute Nodes)	12GB LPDDR4/LPDDR4X × 8 (12GB/16GB Optional)
	Storage	64GB eMMC × 8 (64GB/128GB Optional)	32GB eMMC × 8 (32GB/256GB Optional)
	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 consumption	Normal: 300W, Max: 430W	Normal: 170W, Max: 350W
	Dimension	490.0mm × 417.3mm × 44.4mm
	Environment	Operating Temperature: 0ºC ~ 42ºC, Storage Temperature: -40ºC ~ 60ºC, Operating Humidity: 20% ~ 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: 6.7kg, total weight with packaging: 8.9kg
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	BM1684X: 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.
	AI Painting	BM1684X: 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
Interface Specifications	Internet	2 × 10G Ethernet (SFP+), 2 × Gigabit Ethernet (RJ45, 1 management network port, 1 ordinary network port)
	Video output	1 × HDMI2.0 (Maximum resolution 1080P, main processor core board display)
	USB	2 × USB3.0 HOST, 1 × Type-C (USB3.0 OTG, processor core board debugging)
	Other interfaces	1 × SIM Card, 2 × 4G antenna