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Cisco

Cisco HCI-GPU-A100-80M6 | Data center GPU | 80GB HBM2e | PCIe 4.0 x16 | Passive cooling | 300W TDP | Dual-slot FHFL

SKU:HCI-GPU-A100-80M6

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Description

High-density accelerator engineered for AI/ML, HPC, and advanced analytics. 80GB of HBM2e memory delivers extreme bandwidth, while Multi-Instance GPU (MIG) enables secure partitioning for multi-tenant and mixed workloads. Passive cooling design requires robust server airflow and enterprise chassis integration. PCIe 4.0 x16 connectivity ensures high throughput in modern servers.

Features

- 80GB HBM2e for extreme memory bandwidth
- MIG for secure multi-tenant partitioning
- PCIe 4.0 x16 for high host bandwidth
- Passive, data center-optimized thermal design
- Enterprise-ready for AI/ML, HPC, and analytics

Warranty

All products sold by XS Network Tech include a 12-month warranty on both new and used items. Our in-house technical team thoroughly tests used hardware prior to sale to ensure enterprise-grade reliability.

All technical data should be verified on the manufacturer data sheets.

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FAQs

Technical Specifications

FAQs

Q: Will this work in my server?
A: Requires an available PCIe x16 slot, adequate chassis airflow for passive cooling, and power budget for a 300W accelerator. Consult your server’s compatibility matrix.

Q: Does it support partitioning for multiple workloads?
A: Yes. It supports Multi-Instance GPU (MIG) and is compatible with virtual GPU workflows when paired with the appropriate software licensing.

Q: Is additional software required for virtualization?
A: Yes, vGPU features require a separate software license, not included.

Q: What cables or connectors are needed?
A: It may require auxiliary GPU power depending on the server platform. Use only the power cabling specified by your server vendor.

Technical Specifications

- Memory: 80GB HBM2e, ECC
- Interface: PCIe Gen4 x16
- Cooling: Passive (requires strong chassis airflow)
- Thermal Design Power: 300W
- Form factor: Full-height, full-length (FHFL), dual-slot
- Virtualization: MIG/vGPU partitioning capable
- Use cases: AI/ML training and inference, HPC, data analytics
- Power: Auxiliary power required (per server platform guidance)

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