3290736-A: Hitachi Vsp Cache Flash Memory For G200 Storage
MPN: 3290736-A|By: Hitachi
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
3290736-A is a Hitachi vsp cache flash Memory for G200 storage. Population order decides whether you get the full memory bandwidth or a fraction of it, and the rules change between one and two processors. Send the current layout and we will map the slots for you.
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
- 3290736-A
- Product Type
- Server Memory
- Manufacturer
- Hitachi
Compatibility & compliance
- Compatible Platform
- G200 Storage
The table below is what the server memory module is documented as, not what we have inferred from the part number. If the figure you need is missing, ask and we will source it from the manufacturer.
Where the Hitachi 3290736-A is deployed
- Sourcing 3290736-A against a build sheet that names it explicitly
- Filling the remaining channels on a part-populated board
- Replacing a DIMM flagged by correctable-error logging
Who this part is for
- Teams retiring mixed-speed memory in favour of one consistent part
- Virtualisation teams raising host memory to fit more guests per node
- MSPs matching DIMMs to what a customer already has installed
What you get ordering this from us
Ordered by part number
3290736-A is what is quoted and 3290736-A is what ships; where an alternate code is genuinely the same part we name it rather than swap it silently.
Answered by a human
A quote comes back with the reasoning attached, including the cases where we think you should buy something else.
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 3290736-A genuine and is the warranty intact?
Yes. It ships new in Hitachi 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 3290736-A 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 Hitachi.
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.