IBMpart number
43V5909IBM 43V5909 — GPUs & accelerators
- Title-derived · capacity / module size
- 4GB
- Title-derived · gpu/accelerator
- Nvidia, Tesla
Title-derived fields · unverified
IBM / GPUs & accelerators
Compare the fields actually recorded, preserve complete part-number suffixes and carry your choices into a local RFQ.
IBMpart number
46C9081-NEWIBM 46C9081-NEW — GPUs & accelerators
- Title-derived · capacity / module size
- 785GB
- Title-derived · controller/bus
- PCIE
Title-derived fields · unverified
IBMpart number
46C9082-NEWIBM 46C9082-NEW — GPUs & accelerators
- Title-derived · capacity / module size
- 785GB
- Title-derived · controller/bus
- PCIE
Title-derived fields · unverified
IBMpart number
90Y2451IBM 90Y2451 — GPUs & accelerators
- Title-derived · capacity / module size
- 8GB
- Title-derived · storage/interface
- PCI-E 3.0
- Title-derived · gpu/accelerator
- Nvidia, Quadro
Title-derived fields · unverified
IBMcatalog label
IBM 00P5758-HIGH P — IBM / Matrox Power GXT135P Graphics Adapter 16MB Sdram Pci ( 1 ) One DUAL Link Dvi-I Connection ( 1 ) One VGA ConnectionIBM IBM 00P5758-HIGH P — IBM / Matrox Power GXT135P Graphics Adapter 16MB Sdram Pci ( 1 ) One DUAL Link Dvi-I Connection ( 1 ) One VGA Connection — GPUs & accelerators
- Title-derived · capacity / module size
- 16MB
Title-derived fields · unverified
IBMcatalog label
IBM 0A37598-LOW P — IBM Nvidia Quadro Nvs 295 Graphics Card 256MB 8 Cuda Cores Memory Interface 64 Bit GDDR3 Memory Bandwidth 11.2gb/S PCI-E 2.0 X16 ( 2 ) Two Displayports Mpc 23W Video CardIBM IBM 0A37598-LOW P — IBM Nvidia Quadro Nvs 295 Graphics Card 256MB 8 Cuda Cores Memory Interface 64 Bit GDDR3 Memory Bandwidth 11.2gb/S PCI-E 2.0 X16 ( 2 ) Two Displayports Mpc 23W Video Card — GPUs & accelerators
- Title-derived · capacity / module size
- 256MB
- Title-derived · clock / cores / power
- 23W
- Title-derived · gpu/accelerator
- Nvidia, Quadro
Title-derived fields · unverified
IBMcatalog label
IBM 0A37598-NO BRACKET — IBM Nvidia Quadro Nvs 295 Graphics Card 256MB 8 Cuda Cores Memory Interface 64 Bit GDDR3 Memory Bandwidth 11.2gb/S PCI-E 2.0 X16 ( 2 ) Two Displayports Mpc 23W Video CardIBM IBM 0A37598-NO BRACKET — IBM Nvidia Quadro Nvs 295 Graphics Card 256MB 8 Cuda Cores Memory Interface 64 Bit GDDR3 Memory Bandwidth 11.2gb/S PCI-E 2.0 X16 ( 2 ) Two Displayports Mpc 23W Video Card — GPUs & accelerators
- Title-derived · capacity / module size
- 256MB
- Title-derived · clock / cores / power
- 23W
- Title-derived · gpu/accelerator
- Nvidia, Quadro
Title-derived fields · unverified
IBMcatalog label
IBM 80P4527-HIGH P — IBM / Matrox Power GXT135P Graphics Adapter 16MB Sdram Pci ( 1 ) One DUAL Link Dvi-I Connection ( 1 ) One VGA ConnectionIBM IBM 80P4527-HIGH P — IBM / Matrox Power GXT135P Graphics Adapter 16MB Sdram Pci ( 1 ) One DUAL Link Dvi-I Connection ( 1 ) One VGA Connection — GPUs & accelerators
- Title-derived · capacity / module size
- 16MB
Title-derived fields · unverified
IBMcatalog label
IBM TESLA M1060-IBM — IBM Nvidia Tesla M1060 Computational Accelerator 4GB T10 Processor 240 Cuda Cores Memory Interface 512 Bit PCI-E 2.0 X16 General Purpose Graphics Processing Unit GpgpuIBM IBM TESLA M1060-IBM — IBM Nvidia Tesla M1060 Computational Accelerator 4GB T10 Processor 240 Cuda Cores Memory Interface 512 Bit PCI-E 2.0 X16 General Purpose Graphics Processing Unit Gpgpu — GPUs & accelerators
- Title-derived · capacity / module size
- 4GB
- Title-derived · gpu/accelerator
- TESLA, Nvidia
Title-derived fields · unverified
GPU & AI infrastructure — the next decisions
IBM / GPU & AI infrastructure
GPU & AI infrastructure
Distinguish PCIe cards from integrated accelerator baseboards.
This guide adds the decisions, documents and next steps that support this page.
GPU platforms
Choose the right route
Training
Start with model size, precision, parallelism and dataset movement.
GPU platformsInference
Define request concurrency, latency target and model-memory footprint.
AI systemsGPU expansion
Check slot width, risers, auxiliary power and supported cooling.
GPU checklistDetails that change the configuration
Accelerator architecture
Distinguish PCIe cards from integrated accelerator baseboards.
Fabric & data path
Plan host networking, GPU interconnect and storage access separately.
Rack power & cooling
Request platform power requirements and facility cooling review.
From requirement to handover
- 01
Define AI workload
- 02
Size accelerator memory
- 03
Review fabric & cooling
- 04
Confirm supported BOM
A planning sequence, not a record of completed work.
Explore the relevant catalog
IBM
Recorded catalog identities
Counts show records in the site catalog. They do not represent stock, available quantities or verified compatibility.
Snapshot: 2026-09-15
Compare the buying requirements
| Decision | Record in your brief | Evidence to retain |
|---|---|---|
| Accelerator architecture | Distinguish PCIe cards from integrated accelerator baseboards. | Complete identifier and source revision |
| Fabric & data path | Plan host networking, GPU interconnect and storage access separately. | Platform document or written clarification |
| Rack power & cooling | Request platform power requirements and facility cooling review. | Offered-unit details and agreed scope |
Build your readiness checklist
Your preparation progress
Tick items as you prepare them. This is your personal checklist, not a hardware validation.
Saved in this browser when local storage is available.
A closer look at the hardware
Reference-based generated scenes; actual-unit photos are available only through an explicit unit-specific request. Related models are separate catalog records, not substitutes for the item on this page.
Keep the supporting material together
GPU platforms
Continue the relevant directory or service flow.
Open resourceAI systems
Use the connected tool to develop the requirement.
Open resourceGPU checklist
Retain the supporting reference with your project brief.
Open resourceTurn the brief into the next step
IBM / GPU & AI infrastructure
Keep the requirement specific.
Workload and precision defined · Accelerator model and quantity named · Platform support documents requested · Power and cooling review assigned.