Description
The Cisco UCS C885A M8 CPU Sled (C885A-M8-CC-SLD15) is a high-performance compute module designed for Cisco’s flagship UCS C885A M8 platform. Powered by the AMD EPYC 9575F processor and equipped with 96GB of ultra-fast DDR5-6400 memory, this CPU sled delivers exceptional processing throughput and memory bandwidth for modern AI, HPC, and large-scale data workloads.
Integrated NVIDIA ConnectX-7 (CX-7) networking ensures ultra-low-latency, high-bandwidth connectivity across GPU-dense clusters, while the B3220 SuperNIC support enables optimized east-west and north-south traffic for accelerated training and inference environments. Engineered for scalability, reliability, and performance, this sled is ideal for enterprises building next-generation AI infrastructure on Cisco UCS.
| Specification | Details |
|---|---|
| SKU | C885A-M8-CC-SLD15 |
| Product Type | CPU Sled |
| Platform Compatibility | Cisco UCS C885A M8 |
| Processor | AMD EPYC 9575F |
| CPU Architecture | 5th Gen AMD EPYC |
| Installed Memory | 96GB DDR5 |
| Memory Speed | 6400 MT/s |
| Memory Type | DDR5 RDIMM |
| Networking | NVIDIA ConnectX-7 (CX-7) |
| SuperNIC Support | B3220 |
| Use Case | AI Training, AI Inference, HPC, Data Analytics |
| Form Factor | UCS C885A M8 CPU Sled |
| Installation | Hot-swappable within UCS C885A M8 chassis |
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Return Policy (Short Summary)
We offer a 30-day return window for most unopened, factory-sealed items.
Returns must be authorized before shipping back and must include all original packaging and accessories. Opened or used items are not returnable unless defective.
Some products—such as custom orders, special-order items, audio gear, software, and LED video walls—are non-returnable. Non-defective returns may be subject to a 20–30% restocking fee, and customers are responsible for return shipping costs.
For damaged or incorrect items, please contact us immediately.
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This product is rarely deployed alone. It’s typically part of a fully integrated AV system. AVENDOR designs, integrates, and supports end-to-end environments—from single rooms to enterprise-wide deployments.
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