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16GB G.Skill 2666MHz DDR4 SO-DIMM Laptop Memory CL18 1.2V PC4-21300 Ripjaws 2x8G
US $38.61
ApproximatelyS$ 49.19
Condition:
New
A brand-new, unused, unopened, undamaged item in its original packaging (where packaging is applicable). Packaging should be the same as what is found in a retail store, unless the item was packaged by the manufacturer in non-retail packaging, such as an unprinted box or plastic bag. See the seller's listing for full details.
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Shipping:
Free Standard Shipping.
Located in: Charlotte, North Carolina, United States
Delivery:
Estimated between Fri, 11 Jul and Thu, 17 Jul to 94104
Returns:
30 days return. Seller pays for return shipping.
Coverage:
Read item description or contact seller for details. See all detailsSee all details on coverage
(Not eligible for eBay purchase protection programmes)
Shop with confidence
Seller assumes all responsibility for this listing.
eBay item number:335872984574
Item specifics
- Condition
- Brand
- G.Skill
- MPN
- F4-2666C18D-16GRS
- Unit Quantity
- 1
- Unit Type
- Unit
- Total Capacity
- 16 GB
- Number of Modules
- 2
- Form Factor
- SO-DIMM
- Type
- DDR4 SO-DIMM
- UPC
- Does not apply
Item description from the seller
Seller feedback (27,314)
- t***t (1186)- Feedback left by buyer.Past monthVerified purchaseDecent shipping on first order. Ordered a second minutes after this and shipping was delayed over a week
- c***l (30)- Feedback left by buyer.Past monthVerified purchaseItem new in original packaging as advertised. Works great for jellyfin hardware acceleration in a proxmox container. Strikes a good balance between power consumption and graphics computing capacity
- e***u (196)- Feedback left by buyer.Past monthVerified purchaseA++ thanks!
Seller feedback (27,314)
- t***t (1186)- Feedback left by buyer.Past monthVerified purchaseDecent shipping on first order. Ordered a second minutes after this and shipping was delayed over a week
- c***l (30)- Feedback left by buyer.Past monthVerified purchaseItem new in original packaging as advertised. Works great for jellyfin hardware acceleration in a proxmox container. Strikes a good balance between power consumption and graphics computing capacity
- e***u (196)- Feedback left by buyer.Past monthVerified purchaseA++ thanks!