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Nexus A100 PCIe 40GB 8-GPU MIG Inference Server

Eight A100 40GB GPUs partitioned with MIG for dense multi-tenant inference.

Full manufacturer warrantyAuthorized channel48-hour quote

We help you choose, configure, and deliver the right system — no obligation.

Nexus A100 PCIe 40GB 8-GPU MIG Inference Server — Nexus Compute enterprise hardware
Nexus A100 PCIe 40GB 8-GPU MIG Inference Server hardware detail 1
Nexus A100 PCIe 40GB 8-GPU MIG Inference Server hardware detail 2
Nexus A100 PCIe 40GB 8-GPU MIG Inference Server hardware detail 3

Configuration at a Glance

GPU / Accelerator8x NVIDIA A100 PCIe 40GB HBM2
GPU PartitioningMIG up to 7 instances/GPU (56 total)
CPUDual AMD EPYC 7543 (32-core)
Memory512GB–1TB DDR4-3200 ECC

Tailored per engagement. Full technical overview below.

Configuration Options

Core specifications for this system. Every component is configurable to your workload — request a quote for a tailored build.

GPU / Accelerator

8x NVIDIA A100 PCIe 40GB HBM2

Processor

Dual AMD EPYC 7543 (32-core)

Memory

512GB–1TB DDR4-3200 ECC

Storage

Hot-swap NVMe array (configurable)

Overview

This high-density node packs eight A100 40GB PCIe accelerators, each partitionable into up to seven MIG instances for isolated, predictable inference tenancy. Nexus Compute specifies, configures, and warranty-backs the system through authorized channels for cost-efficient serving at scale.

Who This Solution Is For

Platform teams serving many concurrent inference tenants
SaaS providers offering isolated GPU slices
Enterprises maximizing utilization across mixed models
Operators optimizing cost-per-request at volume

Business Benefits

Up to 56 isolated instances

MIG partitions eight GPUs into as many as 56 hardware-isolated instances for guaranteed quality of service.

High utilization economics

Right-sized GPU slices keep small and medium models from stranding expensive accelerator capacity.

Predictable tenant isolation

Each MIG instance has dedicated memory and compute, preventing noisy-neighbor interference between workloads.

Typical Business Use Cases

1

Multi-tenant LLM and vision model serving

2

Mixed-model inference with QoS guarantees

3

Internal AI platform GPU-as-a-service

4

High-concurrency embedding and ranking endpoints

Industry Applications

SaaS & SoftwareAI & Machine LearningFinancial ServicesTelecom

Technical Overview

A dual-socket 4U platform hosting eight NVIDIA A100 40GB PCIe Gen4 GPUs, each supporting Multi-Instance GPU partitioning into up to seven instances. PCIe switch topology and dual 100GbE serve high-concurrency inference traffic.

GPU / Accelerator8x NVIDIA A100 PCIe 40GB HBM2
GPU PartitioningMIG up to 7 instances/GPU (56 total)
CPUDual AMD EPYC 7543 (32-core)
Memory512GB–1TB DDR4-3200 ECC
StorageHot-swap NVMe array (configurable)
Networking / FabricDual 100GbE load-balanced
Form Factor4U rackmount
Power4x redundant 2200W PSUs
Warranty3-year warranty with advanced replacement

Specifications are indicative and configured to each engagement. Request a quote for a configuration tailored to your requirements.

Warranty, Support & Fulfillment

Every system ships from an authorized channel, configured and tested, with the documentation enterprise buyers need — backed by warranty and a dedicated account team.

Enterprise Warranty

Full manufacturer warranty with optional on-site, next-business-day support and extended coverage.

Authorized Channel

Sourced through Tier-1 distribution and OEM partners — never grey market. Asset & warranty records included.

Lead Time & Deployment

48-hour quotes, then configured, burn-in tested, and delivered on a committed schedule.

Nationwide Fulfillment

Coordinated logistics, rack-and-stack, and delivery wherever your infrastructure lives.

Frequently Asked Questions

What is MIG and why does it help inference?

Multi-Instance GPU splits each A100 into hardware-isolated partitions, so many small models run concurrently with guaranteed memory and compute instead of contending for one GPU.

Is 40GB enough for serving?

For most inference and partitioned serving, 40GB per GPU is ample; choose our 80GB configurations when single-model context or batch sizes exceed that envelope.

How many concurrent workloads can it host?

Up to 56 isolated MIG instances across the eight GPUs, with the exact partitioning profile tuned to your model mix during specification.

Hardware Assistance

Configure the Nexus A100 PCIe 40GB 8-GPU MIG Inference Server with Nexus Compute

Tell us your requirements and a hardware specialist will help you specify, configure, and quote the right system — typically within two business days. No obligation.