PT4JW: Dell 2GB DDR3 1333MHz ECC 240-Pin UDIMM Memory
MPN: PT4JW|By: Dell
Starting from
$140
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
Part number PT4JW identifies this Dell 2GB DDR3 1333MHz ECC 240-Pin UDIMM Memory. A channel runs at the speed of its slowest module, so a faster part fitted alongside an older one buys nothing. Tell us what is already installed and we will keep the channel consistent.
Tell us the deadline you are working to and we will say whether it is achievable before you commit to it internally.
Specifications
General
- Manufacturer part number
- PT4JW
- Product Type
- Server Memory
- Manufacturer
- Dell
Technical specifications
- Capacity
- 2GB
- Memory Type
- DDR3
- Module Type
- ECC
Published specifications for PT4JW. Anything not listed here we will confirm against the manufacturer's documentation before quoting, because we would rather answer the question than let you assume.
Where the Dell PT4JW is deployed
- Sourcing PT4JW against a build sheet that names it explicitly
- Raising host memory to fit more virtual machines per node
- Standardising a host on one module type and speed
Who this part is for
- MSPs matching DIMMs to what a customer already has installed
- Procurement buying memory kits against a documented configuration
- Teams retiring mixed-speed memory in favour of one consistent part
What you get ordering this from us
Ordered by part number
PT4JW is what is quoted and PT4JW is what ships; where an alternate code is genuinely the same part we name it rather than swap it silently.
No substitutions without asking
If we cannot supply the exact code we tell you what we can supply and why, rather than shipping an equivalent and letting you find out.
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 PT4JW 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 PT4JW 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.