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Micron MTC10F1084S1RC80BH1 16GB DDR5 RDIMM Memory
Original price was: ₹699,999.00.₹599,999.00Current price is: ₹599,999.00.
Micron MTC10F1084S1RC80BH1 16GB DDR5 RDIMM Memory delivers high-speed 8000 MT/s performance, ECC error protection, and enterprise-class reliability. Designed for servers, virtualization, cloud computing, and data center applications, it provides stable and efficient operation for demanding workloads.
Micron MTC10F1084S1RC80BH1 16GB DDR5 RDIMM Memory
Features
- 16GB DDR5 server memory designed for enterprise and data center environments.
- 8000 MT/s transfer speed provides fast data movement between memory and processor.
- ECC protection automatically detects and corrects memory errors for better reliability.
- RDIMM design improves signal integrity and system stability in multi-DIMM server configurations.
- 1.1V low-power operation helps reduce power consumption and heat generation.
- Single-rank architecture offers efficient performance for mainstream server workloads.
- Supports continuous 24/7 operation in business-critical systems.
- Built for virtualization, cloud services, databases, and AI applications.
- Operating temperature up to 95°C ensures reliable performance in demanding server environments.
Specifications
| Manufacturer | Micron |
| Part Number | MTC10F1084S1RC80BH1 |
| Memory Capacity | 16GB |
| Memory Type | DDR5 SDRAM |
| Module Type | RDIMM (Registered DIMM) |
| Form Factor | 288-Pin DIMM |
| Data Transfer Rate | 8000 MT/s |
| Memory Clock Speed | 4000 MHz |
| Rank Configuration | Single Rank (1Rx8) |
| Data Width | x80 (72-bit + ECC) |
| Error Correction | ECC (Error Correcting Code) |
| Voltage | 1.1V |
| Operating Temperature | 0°C to +95°C |
| Memory Organization | 2Gb x80 |
| Package Type | VFBGA |
| Signal Processing | Registered (Buffered) |
| Memory Technology | DRAM |
| Server Compatibility | DDR5 Server Platforms |
| Power Management | On-Module PMIC |
| Reliability Features | ECC, On-Die ECC, Registered Buffering |
| Application | Enterprise Servers, Data Centers, Cloud Computing, Virtualization, AI Workloads |
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