MSI Gaming GF63 Thin 10SCSR-1244FR RAM upgrade specifications

MSI GF63 Thin 10SCSR-1244FR MSI GF63 Thin 10SCSR-1244FR MSI GF63 Thin 10SCSR-1244FR MSI GF63 Thin 10SCSR-1244FR MSI GF63 Thin 10SCSR-1244FR

The MSI GF63 Thin 10SCSR-1244FR gaming laptop features DDR4-SDRAM memory upgrade specifications with two SO-DIMM slots supporting maximum capacity of 64 GB. The memory operates at 2666 MHz frequency. Compatible RAM upgrades utilize the SO-DIMM form factor. Specifications indicate the GF series gaming model accommodates dual-channel memory configuration for enhanced performance. Current memory slots accept standard DDR4 modules, enabling users to upgrade from factory-installed capacity up to the 64 GB maximum supported by the MSI GF63 Thin platform.

Memory Upgrade Specifications

SpecificationValue
Memory slots2x SO-DIMM
Form factorSO-DIMM
Memory typeDDR4-SDRAM
Frequency2666 MHz
Maximum RAM64 GB
Voltage1.2V
Number of pins260-pin
InterfacePC4
PC Speed RatingPC4-2666 (PC4-21328)
Bandwidth21.3 GB/s
Laptop Release date07 February 2021

Additional Notes

  • Dual channel architecture requires matching memory modules to reach peak data transfer rates and prevent memory controller latency.
  • The processor architecture in the MSI GF63 Thin 10SCSR-1244FR acts as a hardware ceiling for memory speed even if modules with higher rated frequencies are installed.
  • Reaching the 64 GB capacity necessitates the replacement of both factory modules since no vacant slots exist for expansion.
  • Internal access for memory replacement involves the removal of the bottom chassis cover which typically requires breaking a factory seal.
  • Integrated graphics performance scales directly with total available system memory and the presence of two active memory channels.
  • High density 32 GB sticks must adhere to the 260 pin physical standard to ensure signal integrity and proper seating within the socket.
  • Power consumption increases slightly when utilizing both available slots but provides the necessary bandwidth for modern gaming workloads.