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IBM 7915H3J x3650 M4 Intel Xeon E5 V2 10-Core 2.20GHz 25MB Cache CPU 8GB RAM Rack Server System
- Processor: Intel Xeon E5 V2 10-Core 2.20GHz
- Cache: 25MB
- Memory: 8GB RAM
- Form Factor: Rack Server
- Model: x3650 M4
- Manufacturer: IBM
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Product Overview
The IBM 7915H3J x3650 M4 is a versatile rack server designed for demanding enterprise workloads. It features a powerful Intel Xeon E5 V2 10-Core processor and 8GB of RAM, providing robust performance for virtualization, databases, and general-purpose computing.
Technical Information
| Processor Type | Intel Xeon E5 V2 |
| Number of Cores | 10 |
| Processor Clock Speed | 2.20GHz |
| Cache | 25MB |
Additional Specifications
| Memory Size | 8GB RAM |
| Form Factor | Rack Server |
| Model | x3650 M4 |
| SKU | 7915H3J |
Product Description
The IBM System x3650 M4 is a 2U rack server engineered for performance, reliability, and efficiency. It is equipped with a powerful Intel Xeon E5 V2 processor, offering a significant boost in processing power for complex applications and virtualized environments. The server's architecture is optimized for high-density computing, making it an ideal choice for data centers seeking to maximize performance within a limited footprint. With 8GB of RAM, the x3650 M4 can handle a variety of memory-intensive tasks, ensuring smooth operation for applications such as databases, web servers, and virtualization platforms. The server supports a flexible configuration of hard drives and network interfaces, allowing for customization to meet specific business needs. Its robust design includes features for enhanced data protection and system availability, crucial for mission-critical operations. The IBM 7915H3J model specifically highlights its 10-core Intel Xeon E5 V2 processor running at 2.20GHz with a 25MB cache, paired with 8GB of RAM. This configuration provides a strong foundation for a wide range of enterprise workloads, delivering the performance and scalability required by modern IT infrastructures. The x3650 M4 is built for ease of management and maintenance, further reducing operational costs and complexity.
