FDFM2: Dell 1GB DDR3 1333MHz ECC 240-Pin UDIMM Memory
MPN: FDFM2|By: Dell
Starting from
$80
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
This is the Dell 1GB DDR3 1333MHz ECC 240-Pin UDIMM Memory, order code FDFM2. 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.
Ask for the datasheet and firmware notes with the quote; we would rather you check our claim than take it.
Specifications
General
- Manufacturer part number
- FDFM2
- Product Type
- Server Memory
- Manufacturer
- Dell
Technical specifications
- Capacity
- 1GB
- Memory Type
- DDR3
- Module Type
- ECC
Published specifications for FDFM2. 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 FDFM2 is deployed
- Swapping out a failed server memory module for FDFM2 under change control
- 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
- Engineers populating channels correctly on a new or part-filled board
What you get ordering this from us
Ordered by part number
The order is placed against FDFM2, not against a description of it, so there is no room for a substitution you did not agree to.
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.
Compatibility checked
We confirm the part is supported on your platform before it ships, rather than leaving the check to you.
Questions buyers ask about this part
Is FDFM2 genuine and is the warranty intact?
Yes, new and sealed, with the Dell warranty and the firmware update path intact. We do not sell refurbished stock as new, and we do not source grey-market units.
Will FDFM2 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 |
| 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.