4X77A93533: Lenovo 96GB TruDDR5 6400MHz RDIMM
MPN: 4X77A93533|By: Lenovo
Starting from
$6,820
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 Lenovo 96GB TruDDR5 6400MHz RDIMM, order code 4X77A93533. Registered, load-reduced and unbuffered modules are not interchangeable, and a board that accepts one will refuse to post on another. This module is RDIMM. Send the server model and we will check it against the supported-DIMM list before you order.
Quotes are itemised down to the accessories, so nothing that is needed to make the part work is left off and discovered later.
Specifications
General
- Manufacturer part number
- 4X77A93533
- Product Type
- Server Memory
- Manufacturer
- Lenovo
Technical specifications
- Capacity
- 96GB
- Module Type
- RDIMM
These are the 4 facts we can state about 4X77A93533 without inferring anything. Compatibility beyond this is confirmed per platform, on request, before you order.
Where the Lenovo 4X77A93533 is deployed
- Swapping out a failed server memory module for 4X77A93533 under change control
- Standardising a host on one module type and speed
- Filling the remaining channels on a part-populated board
Who this part is for
- MSPs matching DIMMs to what a customer already has installed
- Teams retiring mixed-speed memory in favour of one consistent part
- Virtualisation teams raising host memory to fit more guests per node
What you get ordering this from us
Ordered by part number
Quoted and supplied against 4X77A93533 specifically, so what arrives is what your build sheet asks for.
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.
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 4X77A93533 genuine and is the warranty intact?
Yes. It ships new in Lenovo 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 4X77A93533 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 |
| 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 Lenovo.
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.