ASUS ROG GL703VM-EE138T RAM upgrade specifications

ASUS GL703VM-EE138T ASUS GL703VM-EE138T ASUS GL703VM-EE138T ASUS GL703VM-EE138T ASUS GL703VM-EE138T

ASUS ROG Strix GL703VM-EE138T laptop RAM upgrade specifications: Compatible with DDR4-SDRAM memory modules. Equipped with 2x SO-DIMM slots supporting maximum capacity of 32 GB total RAM. Memory operates at 2400 MHz frequency. Upgrades utilize SO-DIMM form factor modules. Specifications define compatible memory configurations for this gaming laptop model.

Memory Upgrade Specifications

SpecificationValue
Memory slots2x SO-DIMM
Form factorSO-DIMM
Memory typeDDR4-SDRAM
Frequency2400 MHz
Maximum RAM32 GB
Voltage1.2V
Number of pins260-pin
InterfacePC4
PC Speed RatingPC4-2400 (PC4-19200)
Bandwidth19.2 GB/s
Laptop Release date11 February 2019

Additional Notes

  • The ASUS ROG Strix GL703VM-EE138T contains 2 memory slots configured as SO-DIMM, which restricts upgrade capacity to a maximum of 32 GB total across both slots when using matched pairs of 16 GB modules.
  • DDR4-2400 MHz represents the native supported frequency; higher-speed DDR4 modules (2666 MHz, 2933 MHz, 3200 MHz) may function but will downclock to 2400 MHz specification, providing no performance benefit while consuming additional cost.
  • SO-DIMM form factor requires laptop-specific memory modules rather than full-size DIMM sticks, eliminating compatibility with desktop RAM and necessitating sourcing from laptop-compatible product lines.
  • Populating both SO-DIMM slots simultaneously may generate thermal constraints in the compact chassis design typical of gaming ultrabooks; single-slot configurations or asymmetrical capacity pairings (8 GB + 16 GB) produce lower heat density if thermal throttling occurs during sustained workloads.
  • The 32 GB ceiling indicates no BIOS-level support for 64 GB configurations, making future capacity expansion beyond this threshold impossible without hardware modification outside manufacturer warranty scope.
  • Memory speed of 2400 MHz on a 6th or 7th generation Intel platform may present latency constraints when paired with discrete GPU workloads, as the memory bandwidth ceiling becomes a secondary bottleneck during data-intensive gaming or rendering operations.