AM29F200BB-70EF: AMD Flash Memory
MPN: AM29F200BB-70EF|By: AMD
Price
Quoted on request
Current pricing within 48 business hours.
In Stockships worldwide
- Condition:
- New (authorized channel)
- Warranty:
- Full manufacturer warranty
Prefer your own inbox? Email us about this part
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 AMD flash Memory, order code AM29F200BB-70EF. Registered, load-reduced and unbuffered modules are not interchangeable, and a board that accepts one will refuse to post on another. 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
- Manufacturer part number
- AM29F200BB-70EF
- Product Type
- Server Memory
- Manufacturer
- AMD
These are the 2 facts we can state about AM29F200BB-70EF without inferring anything. Compatibility beyond this is confirmed per platform, on request, before you order.
Where the AMD AM29F200BB-70EF is deployed
- Sourcing AM29F200BB-70EF 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
- Procurement buying memory kits against a documented configuration
- Virtualisation teams raising host memory to fit more guests per node
- Engineers populating channels correctly on a new or part-filled board
What you get ordering this from us
Ordered by part number
Quoted and supplied against AM29F200BB-70EF 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.
Rank and voltage confirmed
We check rank, voltage and module type against the platform before quoting, which is where most memory orders go wrong.
Questions buyers ask about this part
Is AM29F200BB-70EF genuine and is the warranty intact?
Yes, new and sealed, with the AMD warranty and the firmware update path intact. We do not sell refurbished stock as new, and we do not source grey-market units.
Will AM29F200BB-70EF 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, POs from qualified organisations, net terms on approval, and banded pricing once the quantity is worth banding. Send the number and we will price it properly.
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 AMD.
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.