M393T3253FZ0-CCC: Samsung 256MB RDIMM 240-Pin Memory Module
MPN: M393T3253FZ0-CCC|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
M393T3253FZ0-CCC is a Samsung 256MB RDIMM 240-Pin Memory Module. 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.
Send a photo or a dump of the current DIMM layout and we will map the population for you before you order.
Specifications
General
- Manufacturer part number
- M393T3253FZ0-CCC
- Product Type
- Server Memory
- Manufacturer
- Samsung
Technical specifications
- Capacity
- 256MB
- Module Type
- RDIMM
Published specifications for M393T3253FZ0-CCC. 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 Samsung M393T3253FZ0-CCC is deployed
- Swapping out a failed server memory module for M393T3253FZ0-CCC under change control
- Raising host memory to fit more virtual machines per node
- Filling the remaining channels on a part-populated board
Who this part is for
- Virtualisation teams raising host memory to fit more guests per node
- Procurement buying memory kits against a documented configuration
- MSPs matching DIMMs to what a customer already has installed
What you get ordering this from us
Ordered by part number
The order is placed against M393T3253FZ0-CCC, not against a description of it, so there is no room for a substitution you did not agree to.
Rank and voltage confirmed
We check rank, voltage and module type against the platform before quoting, which is where most memory orders go wrong.
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 M393T3253FZ0-CCC 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 M393T3253FZ0-CCC 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
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|---|---|---|---|---|
| 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.
