K4UBE3D4AA-MGCL: Samsung LPDDR4X-4266MHz 1Gx32 (32GB) Memory Chip
MPN: K4UBE3D4AA-MGCL|By: Samsung
Price
Quoted on request
Current pricing within 48 business hours.
In Stockships worldwide
- Condition:
- New (authorized channel)
- Warranty:
- Full manufacturer warranty
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Bulk order? Request volume pricing
Authorized & warrantied
Sourced through authorized distribution, with the full manufacturer warranty.
Compatibility checked
Validated against your server platform before dispatch.
Delivery & lead time
Confirmed with your quote, including expedited freight where available.
Business & public sector
POs, net terms and volume pricing for qualified organizations, government and edu.
Product overview
Part number K4UBE3D4AA-MGCL identifies this Samsung LPDDR4X-4266MHz 1Gx32 (32GB) Memory chip. Population order decides whether you get the full memory bandwidth or a fraction of it, and the rules change between one and two processors. This is a 32GB module. Send the current layout and we will map the slots for you.
Quotes are itemised down to the accessories, so nothing that is needed to make the part work is left off and discovered later.
Specifications
General
- Manufacturer part number
- K4UBE3D4AA-MGCL
- Product Type
- Server Memory
- Manufacturer
- Samsung
Technical specifications
- Capacity
- 32GB
The table below is what the server memory module is documented as, not what we have inferred from the part number. If the figure you need is missing, ask and we will source it from the manufacturer.
Where the Samsung K4UBE3D4AA-MGCL is deployed
- Sourcing K4UBE3D4AA-MGCL against a build sheet that names it explicitly
- Filling the remaining channels on a part-populated board
- Raising host memory to fit more virtual machines per node
Who this part is for
- Virtualisation teams raising host memory to fit more guests per node
- Engineers populating channels correctly on a new or part-filled board
- MSPs matching DIMMs to what a customer already has installed
What you get ordering this from us
Ordered by part number
Quoted and supplied against K4UBE3D4AA-MGCL specifically, so what arrives is what your build sheet asks for.
Answered by a human
A quote comes back with the reasoning attached, including the cases where we think you should buy something else.
Volume pricing
The listed price is per unit; tiered pricing applies at quantity and purchase orders are accepted.
Questions buyers ask about this part
Is K4UBE3D4AA-MGCL genuine and is the warranty intact?
Yes. Supplied new and unopened, so the manufacturer warranty and firmware update path stay supported. No grey-market stock and no refurbished units sold as new.
Will K4UBE3D4AA-MGCL work in my server?
Send the server model and a list of the DIMMs already fitted. Rank, voltage and population order all have to agree, and a module that is electrically compatible can still be unsupported in a given slot. We map the population before you order.
Do you accept purchase orders and quote at volume?
Yes. Purchase orders are accepted from qualified organisations, net terms are available on approval, and tiered pricing applies at quantity. Tell us how many you need.
Compare other Server Memory we stock
| Model | Brand | Key spec | Availability | From |
|---|---|---|---|---|
| SK hynix 32GB DDR5-5600 PC5-44800 ECC Registered CL46 288-Pin RDIMM Server Memory Module | SK hynix | Capacity: 32GB | In Stock | $215 |
| Micron 128GB DDR4-3200 PC4-25600 ECC Load-Reduced CL22 288-Pin LRDIMM Server Memory Module | Micron | Capacity: 128GB | In Stock | $500 |
| Dell Technologies 16GB DDR5-4800 PC5-38400 ECC RDIMM CL40 288-Pin Server Memory Module | Dell Technologies | Capacity: 16GB | In Stock | $95 |
| HPE 16GB DDR5-4800 PC5-38400 ECC RDIMM CL40 288-Pin Server Memory Module | HPE | Capacity: 16GB | In Stock | $95 |
| Lenovo 16GB DDR5-4800 PC5-38400 ECC RDIMM CL40 288-Pin Server Memory Module | Lenovo | Capacity: 16GB | In Stock | $90 |
| Kingston 8GB DDR4-3200 PC4-25600 ECC RDIMM CL22 288-Pin Server Memory Module | Kingston | Capacity: 8GB | In Stock | $35 |
Browse all Server Memory or everything we stock from Samsung.
Specifying a system, not just the part?
Host memory on an AI node is normally sized against accelerator memory, so the model and its working set both fit.