726722-S21: HPE 32GB DDR4 2133MHz ECC RDIMM Memory Module
MPN: 726722-S21|By: HPE
Starting from
$235
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 HPE 32GB DDR4 2133MHz ECC RDIMM Memory Module, order code 726722-S21. Memory is the part most often ordered wrong, because rank, voltage and population rules differ per platform and per slot. This module is DDR4. Give us the server model and the DIMMs already fitted and we will confirm the configuration is supported.
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
- 726722-S21
- Product Type
- Server Memory
- Manufacturer
- HPE
Technical specifications
- Capacity
- 32GB
- Memory Type
- DDR4
- Module Type
- ECC
Specifications for 726722-S21 as published by HPE. Where a value is absent it is because we could not verify it, not because it does not exist. Ask and we will check.
Where the HPE 726722-S21 is deployed
- Sourcing 726722-S21 against a build sheet that names it explicitly
- Replacing a DIMM flagged by correctable-error logging
- Standardising a host on one module type and speed
Who this part is for
- Engineers populating channels correctly on a new or part-filled board
- MSPs matching DIMMs to what a customer already has installed
- Procurement buying memory kits against a documented configuration
What you get ordering this from us
Ordered by part number
Quoted and supplied against 726722-S21 specifically, so what arrives is what your build sheet asks for.
Volume pricing
The listed price is per unit; tiered pricing applies at quantity and purchase orders are accepted.
Population mapped for you
Send the current DIMM layout and we return the slot map with the quote, so the modules go in the right order.
Questions buyers ask about this part
Is 726722-S21 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 726722-S21 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 |
| 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 HPE.
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.