YY90K: Dell 2GB DDR3 1600MHz ECC 240-Pin UDIMM Memory
MPN: YY90K|By: Dell
Starting from
$275
Indicative. Final pricing is confirmed with your quote.
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
Dell lists YY90K as a 2GB DDR3 1600MHz ECC 240-Pin UDIMM Memory. Registered, load-reduced and unbuffered modules are not interchangeable, and a board that accepts one will refuse to post on another. This module is ECC. Send the server model and we will check it against the supported-DIMM list before you order.
Quote requests are answered within 48 business hours, with availability confirmed before you raise a purchase order rather than after.
Specifications
General
- Manufacturer part number
- YY90K
- Product Type
- Server Memory
- Manufacturer
- Dell
Technical specifications
- Capacity
- 2GB
- Memory Type
- DDR3
- Module Type
- ECC
These are the 5 facts we can state about YY90K without inferring anything. Compatibility beyond this is confirmed per platform, on request, before you order.
Where the Dell YY90K is deployed
- Like-for-like replacement of YY90K in an existing system
- Standardising a host on one module type and speed
- Replacing a DIMM flagged by correctable-error logging
Who this part is for
- Engineers populating channels correctly on a new or part-filled board
- Teams retiring mixed-speed memory in favour of one consistent part
- Procurement buying memory kits against a documented configuration
What you get ordering this from us
Ordered by part number
Quoted and supplied against YY90K specifically, so what arrives is what your build sheet asks for.
Compatibility checked
We confirm the part is supported on your platform before it ships, rather than leaving the check to you.
Answered by a human
A quote comes back with the reasoning attached, including the cases where we think you should buy something else.
Questions buyers ask about this part
Is YY90K genuine and is the warranty intact?
Yes. It ships new in Dell packaging, which is what keeps the warranty and the firmware entitlement valid. Anything we cannot supply that way we tell you about before you order.
Will YY90K 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. We quote against a purchase order and hold the price for the quote period, with tiered rates at quantity. Net terms are available once the account is approved.
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 |
| Samsung 16GB DDR4-3200 PC4-25600 ECC Registered CL22 288-Pin RDIMM Server Memory Module | Samsung | Capacity: 16GB | In Stock | $55 |
| 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 |
Browse all Server Memory or everything we stock from Dell.
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.