DeepSeek Education All-in-One is a highly controllable and cost-effective way for schools to use AI models
DeepSeek, a domestically produced AI model, opens a new chapter in smart education.
Core content:
1. The core advantages and technical features of DeepSeek educational all-in-one machine
2. Diversified models to meet the needs of different schools
3. Educational application scenarios and economic value analysis
1. General DeepSeek all-in-one machine
1. Diversified hardware configuration:
-Computing power support: Generally, DeepSeek all-in-one machines use domestic Ascend chips or NVIDIA graphics cards, such as Huawei Ascend 8-card and 16-card solutions. A single machine is often equipped with 8-32 AI chips, with a memory capacity of hundreds of GB and a storage disk that supports TB-level data storage.
-Software ecosystem: Built-in self-developed inference acceleration engine, supports model training, inference and knowledge base management, and is compatible with multiple AI frameworks (such as PyTorch, TensorFlow).
2. Core functions and advantages:
-Full stack independent and controllable: using domestic chips and algorithms, complying with the information and innovation policy, and ensuring data security.
-High performance and flexibility: The measured inference performance reaches the world-class level, supporting flexible deployment of models from full-blooded version to distilled version, and adapting to complex scenarios such as finance, medical care, and government affairs.
-Data privacy protection: Localized deployment ensures that sensitive data does not leave the domain, meeting the high security requirements of industries such as military and medical.
3. Application scenarios and value:
-Industry application: It is widely used in financial anti-fraud, government affairs "one-stop service", energy resource scheduling, intelligent manufacturing and other fields, and achieves deep business integration through secondary development.
- Economic value: The price of a single machine ranges widely (from hundreds of thousands to several million yuan) , with central state-owned enterprises as the main customer group. The market size is expected to exceed 500 billion yuan in 2027.
2. DeepSeek Campus Intelligent Computing Machine
1. Summary of characteristics
1. Diverse models to cover different needs
- 70B (high-end): For group schools, equipped with dual NVIDIA 4090 48G GPUs and 128G memory, supporting ultra-high computing power and large-scale AI tasks.
- 32B (mid-to-high end): suitable for both group and single schools, equipped with dual NVIDIA 4090 24G GPUs, with outstanding cost performance.
- 14B/8B (entry-level): Designed for a single school, it uses AMD/NVIDIA mid-range graphics cards, is lower cost, and is suitable for lightweight AI applications.
2. Core AI Functions
- Built-in well-known knowledge base and educational resource library, supporting the construction of localized dedicated knowledge base.
- Provides AI services such as text dialogue, code generation, document creation, and image generation , supporting multi-style creation.
-Supports open API interface, can quickly connect to external AI applications, and has strong scalability.
3. Flexible and scalable hardware configuration
- Diverse CPU/GPU combinations: Intel Xeon, AMD Ryzen processors with NVIDIA/AMD graphics cards to meet different computing power requirements.
-Differentiated storage solutions: system disk + storage disk combination (512GB to 2TB), supporting massive data storage.
4. Standardized system management
-The entire system supports image management, monitoring alarm, log management, and configuration management to reduce the difficulty of operation and maintenance.
-Provide container environments such as Pytorch/TensorFlow, which are ready to use and suitable for teaching and scientific research scenarios.
5. Service and Support
- 3-year whole machine warranty, remote detection and 7×8 hours technical support to ensure stable operation of the equipment.
- Supports monthly lease (one year minimum) or outright purchase ( 70,000-250,000 ) , flexibly adapting to school budget.
(II) Applicable scenarios
1. Group school AI server (70B/32B)
- Suitable for centralized deployment by education groups, processing cross-campus data collaboration, and large-scale AI model training (such as intelligent teaching analysis and resource library management).
2. Single-school AI server (32B/14B/8B)
-Meet the daily teaching needs of a single school, such as intelligent lesson preparation, student homework grading, and personalized learning recommendations.
-Support the construction of a school-based knowledge base for on-campus resource sharing and question-and-answer services.
3. Educational innovation and scientific research
- Develop customized educational applications (such as AI teaching assistants and virtual laboratories) through API docking.
-Support RAG dialogue service, create an intelligent question-and-answer system, and improve the efficiency of teacher-student interaction .
4. Low-cost trial of AI (8B)
- Suitable for schools with limited budgets and used for lightweight AI applications (such as simple image and text generation, basic data analysis).
(III) Reference for price and model
(IV) Reference Configuration
Zhihui DeepSeek Campus Intelligent Computing Machine-70B | |||
Applicable scenarios | Group School AI Server | ||
Technical highlights | Equipped with ultra-high computing power, full-stack intelligent computing, built-in well-known knowledge base, and educational resource library, the intelligent computing application is ready to use out of the box and can be customized on demand | ||
Large Model | Windows/Ubuntu-RAGFlow+Deepseek-R1:70b | ||
Technical Parameters | name | model | quantity |
Motherboard | GIGABYTE MU72-SU0 | 1 | |
CPU | Intel Xeon 6330 28C56T 2.0GHz | 1 | |
Memory | Server Memory RECC DDR4 32G 3200MHz | 4 | |
System disk | Yangtze Memory 512GB | 1 | |
Storage disk | 2TB M2 NVMe | 1 | |
GPU | 4090 48G | 2 | |
Chassis | Customized chassis | 1 | |
heat sink | Air Cooling Radiator | 1 | |
power supply | Great Wall 1650W | 1 | |
System management functions | Image Management | Supports the management of public images and user private images, and supports the creation and access of container environments such as Pytorch/Tensorflow/Vscode/Jupyter. | |
Monitoring alarm | Supports real-time monitoring of various indicators; supports resource monitoring of each process on each GPU card; supports customization of various alarm rules, supports configuration of multiple mainstream alarm notification methods, and supports historical query of alarm records. | ||
Log Management | Supports the collection and archiving of system logs /container logs, and supports log retrieval. | ||
Configuration Management | Supports specification configuration and system configuration, including various resource node specifications, system logo, system name, billing configuration, monitoring alarm and other functions. | ||
Large model service function | Model Management | Built-in 15+ large models, including deepseek/qwen/llama/phi/stablediffusion and other large models, supports self-built large models, model disclosure, and version management. | |
Dataset Management | Built-in 5+ data sets, including ms-bench, alpaca, gpt4all, cot, medical, CodeAlpaca and other data sets, supports self-built data sets, and supports version management. | ||
AI Services | Built-in well-known knowledge base and educational resource library Support users to build dedicated knowledge base based on local resources Support online text dialogue, code generation, and manuscript creation Support online image generation to assist in the creation of images of different styles and contents Support the creation of dedicated knowledge base and RAG-based dialogue services Support open API interface for quick docking of various AI applications | ||
After-sales | 3-year machine warranty, remote machine detection capability, 7*8 hours technical support | ||
Certification | Includes: NVIDIA certified global NPN supplier | ||
Zhihui DeepSeek Campus Intelligent Computing Machine-32B | |||
Applicable scenarios | Group school /single school AI server | ||
Technical highlights | Extremely cost-effective, built-in well-known knowledge base, educational resource library, intelligent computing applications are ready to use and can be customized on demand | ||
Large Model | Windows/Ubuntu-RAGFlow+Deepseek-R1:32b | ||
Technical Parameters | name | model | quantity |
Motherboard | GIGABYTE MU72-SU0 | 1 | |
CPU | Intel Xeon 6330 28C56T 2.0GHz | 1 | |
Memory | Server Memory RECC DDR4 32G 3200MHz | 2 | |
System disk | Yangtze Memory 512GB | 1 | |
Storage disk | 2TB M2 NVMe | 1 | |
GPU | Nvidia 4090 24G | 2 | |
Chassis | Customized chassis | 1 | |
heat sink | Air Cooling Radiator | 1 | |
power supply | Great Wall 1650W | 1 | |
System management functions | Image Management | Supports the management of public images and user private images, and supports the creation and access of container environments such as Pytorch/Tensorflow/Vscode/Jupyter. | |
Monitoring alarm | Supports real-time monitoring of various indicators; supports resource monitoring of each process on each GPU card; supports customization of various alarm rules, supports configuration of multiple mainstream alarm notification methods, and supports historical query of alarm records. | ||
Log Management | Supports the collection and archiving of system logs /container logs, and supports log retrieval. | ||
Configuration Management | Supports specification configuration and system configuration, including various resource node specifications, system logo, system name, billing configuration, monitoring alarm and other functions. | ||
Large model service function | Model Management | Built-in 5+ large models, including deepseek/qwen/llama/phi/stablediffusion and other large models, supports self-built large models, model disclosure, and version management. | |
Dataset Management | Built-in 5+ data sets, including ms-bench, alpaca, gpt4all, cot, medical, CodeAlpaca and other data sets, supports self-built data sets, and supports version management. | ||
AI Services | Built-in well-known knowledge base and educational resource library Support users to build dedicated knowledge base based on local resources Support online text dialogue, code generation, and manuscript creation Support online image generation to assist in the creation of images of different styles and contents Support the creation of dedicated knowledge base and RAG-based dialogue services Support open API interface for quick docking of various AI applications | ||
After-sales | 3-year machine warranty, remote machine detection capability, 7*8 hours technical support | ||
Certification | Includes: NVIDIA certified global NPN supplier | ||
Zhihui DeepSeek Campus Intelligent Computing Machine-14B | |||
Applicable scenarios | Single-school AI server | ||
Technical highlights | Super cost-effective, built-in well-known knowledge base, educational resource library, intelligent computing applications are ready to use and can be customized on demand | ||
Large Model | Windows/Ubuntu-RAGFlow+Deepseek-R1:14b | ||
Technical Parameters | name | model | quantity |
Motherboard | MSI B840 | 1 | |
CPU | AMD Ryzen 5 9600X | 1 | |
Memory | 16G DDR5 | 2 | |
System disk | Yangtze Memory 512GB | 1 | |
Storage disk | Yangtze Memory 2TB SSD | 1 | |
GPU | AMD RADEON RX7900 XTX 24G | 1 | |
Chassis | Customized chassis | 1 | |
heat sink | Air Cooling Radiator | 1 | |
power supply | Antec NE850 850W | 1 | |
System management functions | Image Management | Supports the management of public images and user private images, and supports the creation and access of container environments such as Pytorch/Tensorflow/Vscode/Jupyter. | |
Monitoring alarm | Supports real-time monitoring of various indicators; supports resource monitoring of each process on each GPU card; supports customization of various alarm rules, supports configuration of multiple mainstream alarm notification methods, and supports historical query of alarm records. | ||
Log Management | Supports the collection and archiving of system logs /container logs, and supports log retrieval. | ||
Configuration Management | Supports specification configuration and system configuration, including various resource node specifications, system logo, system name, billing configuration, monitoring alarm and other functions. | ||
Large model service function | Model Management | Built-in 5+ large models, including deepseek/qwen/llama/phi/stablediffusion and other mainstream large models, supports self-built large models, model disclosure, and version management. | |
Dataset Management | Built-in 5+ data sets, including ms-bench, alpaca, gpt4all, cot, medical, CodeAlpaca and other data sets, supports self-built data sets, and supports version management. | ||
AI Services | Built-in well-known knowledge base and educational resource library Support users to build dedicated knowledge base based on local resources Support online text dialogue, code generation, and manuscript creation Support online image generation to assist in the creation of images of different styles and contents Support the creation of dedicated knowledge base and RAG-based dialogue services Support open API interface for quick docking of various AI applications | ||
After-sales | 3-year machine warranty, remote machine detection capability, 7*8 hours technical support | ||
Zhihui DeepSeek Campus Intelligent Computing Machine-8B | |||
Applicable scenarios | Single-school AI server | ||
Technical highlights | Super cost-effective, built-in well-known knowledge base, educational resource library, intelligent computing applications are ready to use and can be customized on demand | ||
Large Model | Windows/Ubuntu-RAGFlow+Deepseek-R1:8b | ||
Technical Parameters | name | model | quantity |
Motherboard | MSI B840 | 1 | |
CPU | AMD Ryzen 5 9600X | 1 | |
Memory | 16G DDR5 | 2 | |
System disk | Yangtze Memory 512GB | 1 | |
Storage disk | Yangtze Memory 1TB SSD | 1 | |
GPU | Nvidia 4060ti 16G | 1 | |
Chassis | Customized chassis | 1 | |
heat sink | Air Cooling Radiator | 1 | |
power supply | Antec NE850 850W | 1 | |
System management functions | Image Management | Supports the management of public images and user private images, and supports the creation and access of container environments such as Pytorch/Tensorflow/Vscode/Jupyter. | |
Monitoring alarm | Supports real-time monitoring of various indicators; supports resource monitoring of each process on each GPU card; supports customization of various alarm rules, supports configuration of multiple mainstream alarm notification methods, and supports historical query of alarm records. | ||
Log Management | Supports the collection and archiving of system logs /container logs, and supports log retrieval. | ||
Configuration Management | Supports specification configuration and system configuration, including various resource node specifications, system logo, system name, billing configuration, monitoring alarm and other functions. | ||
Large model service function | Model Management | Built-in 5+ large models, including deepseek/qwen/llama/phi/stablediffusion and other large models, supports self-built large models, model disclosure, and version management. | |
Dataset Management | Built-in 5+ data sets, including ms-bench, alpaca, gpt4all, cot, medical, CodeAlpaca and other data sets, supports self-built data sets, and supports version management. | ||
AI Services | Built-in well-known knowledge base and educational resource library Support users to build dedicated knowledge base based on local resources Support online text dialogue, code generation, and manuscript creation Support online image generation to assist in the creation of images of different styles and contents Support the creation of dedicated knowledge base and RAG-based dialogue services Support open API interface for quick docking of various AI applications | ||
After-sales | 3-year machine warranty, remote machine detection capability, 7*8 hours technical support | ||
3. Comparison between DeepSeek Campus Intelligent Computing Machine and General DeepSeek All-in - One Machine
1. Hardware specifications:
- The campus version is mainly low-end configuration, such as the 70B model equipped with dual NVIDIA 4090 48G GPU (128G memory), priced at 70,000-250,000 yuan ; while the general DeepSeek all-in-one machine (such as China Telecom's "Xiran") uses the Ascend 32 card solution, priced at millions of yuan .
-Computing power adaptation: The campus version focuses on lightweight AI tasks (such as text generation and image creation), while the general DeepSeek all-in-one machine is aimed at large-scale training and reasoning.
2. Scenario-specific:
-Campus Edition: Built-in educational resource library and teaching management functions (such as intelligent lesson preparation and homework grading), and supports API docking for educational applications.
-General version: covers a wider range of industries, such as personalized medical services and financial anti-fraud, and functional modules require secondary development.
3. Pricing and deployment model:
- The campus version provides buyout and monthly lease (one-year minimum) models to reduce the school's initial investment costs; the general version mostly adopts a buyout system, which is suitable for central state-owned enterprises with sufficient budgets.
4. Core advantages of DeepSeek campus intelligent computing machine in campus scenarios
1. Deep adaptation of educational scenarios:
2. Low cost and high cost performance:
3. Out-of-the-box AI services:
4. Data security and localization:
5. Prediction of the development trend of campus intelligent computing machines
1. Technology popularization:
2. Deepening of functional scenarios:
3. Ecological expansion and standardization:
4. Policy-driven popularization:
