NVIDIA

NVIDIA DGX Station A100, 4x A100 (160GB)

Modell: DGX Station 4x A100 160GB

The NVIDIA DGX Station 4x A100 is engineered for businesses seeking to leverage AI capabilities. A data center-class AI machine that sits beside a desk: the NVIDIA DGX Station A100 packs four A100 Tensor Core GPUs (160GB total), a 64-core AMD EPYC, and 512GB of RAM into a quiet, air-cooled deskside box that runs on a standard wall outlet, no rack, no data center, no special power. Pre-installed with DGX OS and ready to train. Verified and shipped worldwide DDP by MillionMiner.

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Modell DGX Station 4x A100 160GB
CPU 1x AMD EPYC 7742, 64 cores
GPU 4x NVIDIA A100 Tensor Core GPUs, 160 GB total
Speicher 512 GB DDR4 RAM
Datenspeicherung 7.68 TB NVMe U.2 drive
OS-Speicher 1.92 TB NVMe M.2 drive
Stromversorgung 1500W, 100-240V AC
Abmessungen 26.1 x 10.1 x 20.4 in
Gewicht 91 lbs (43.1 kg)
Vernetzung Dual 10 Gb Ethernet ports
Garantie 2 Years

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Produktdetails

NVIDIA DGX Station A100: The Deskside AI Supercomputer, Who It Is For, and the Secondary-Market Case

This catalog is built from rackmount data center hardware, with one exception: the DGX Station A100 is a deskside machine, and that form factor is the entire point. It exists for the researcher, team, or department that wants real multi-GPU AI compute in their own space, without a data center, a rack, or the infrastructure those demand. What it is. NVIDIA's DGX Station A100 packs four A100 Tensor Core GPUs, 160GB of total GPU memory in this configuration, a 64-core AMD EPYC 7742, and 512GB of DDR4 into a single deskside chassis about the size of a large tower. Crucially, it is built for a normal environment: it runs on a standard wall outlet, not three-phase data center power, and it uses a self-contained refrigerant cooling system that keeps four A100s quiet enough to sit in an office or lab. There is no rack to mount, no raised floor, no special air handling. This is genuinely a data center's worth of AI compute that plugs in like an appliance. Who it is for. The DGX Station was designed as a personal AI supercomputer, and the buyer is specific: an AI or data science team that wants a dedicated machine they fully control, a research group that needs to iterate without queuing for shared cluster time, or a department standing up AI capability without building infrastructure. Its four A100s can be partitioned with MIG into as many as 28 independent GPU instances, so a small team can share one Station as if it were several smaller machines, each developer with isolated resources. It ships pre-installed with DGX OS and NVIDIA's deep-learning frameworks, so it is productive on day one rather than after an integration project. The configuration. Four A100 GPUs at 160GB total, which is the 40GB-per-GPU A100 variant, paired with the 64-core EPYC host and 512GB of RAM. Storage separates roles the way this catalog recommends everywhere: a 7.68TB NVMe U.2 drive for data and a dedicated 1.92TB NVMe M.2 drive for the OS. Dual 10GbE handles networking, a single 1500W supply runs the whole machine from a wall socket, and the unit weighs about 43kg. The secondary-market case. NVIDIA discontinued the DGX Station line, so these are secondary-market units, and that is the realistic way to acquire one now. The framework this catalog applies to its used A100 systems holds: A100 silicon run within spec does not meaningfully degrade, the wear items are fans and the cooling system, and MillionMiner verifies each unit before shipment with condition and the 2-year warranty term confirmed in the quote. For a team that wants A100-class development compute in their own space, a verified DGX Station is both the most convenient form factor and, on the secondary market, an economical one. Shipped worldwide DDP with duties handled, and MillionMiner can advise on rackmount A100 alternatives, including the used Gigabyte G492 A100 server, if a data center deployment turns out to suit better.

NVIDIA DGX Station A100: Data Center Compute, Deskside Form

The DGX Station A100 answers a specific need: serious multi-GPU AI compute for a person or small team that does not have, and does not want, a data center. It is a deskside machine, not a rackmount server. What that means in practice. Four A100 Tensor Core GPUs with 160GB of total GPU memory, a 64-core AMD EPYC 7742, and 512GB of system RAM, the kind of configuration that otherwise lives in a server room, packaged into a chassis that sits beside a desk. It runs on a standard wall outlet rather than data center power, cools itself with a refrigerant-based system quiet enough for an office, and needs no rack, raised floor, or special cooling. Who it is for. AI researchers, data science teams, and departments that want a dedicated development and training machine they control, in their own space, without contending for cluster time or standing up infrastructure. Storage runs a 7.68TB NVMe data drive plus a separate 1.92TB OS drive, networking is dual 10GbE, and it ships pre-installed with DGX OS and NVIDIA's deep-learning frameworks, ready to work on arrival. Because the DGX Station A100 is a discontinued NVIDIA line, units are secondary-market, verified by MillionMiner before shipment. A 2-year warranty term applies as confirmed in the quote. Shipped worldwide DDP.

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NVIDIA DGX Station A100: The AI Supercomputer for Your Office

Every other machine in this catalog needs a rack and a data center. This one needs a wall outlet. The NVIDIA DGX Station A100 puts four A100 Tensor Core GPUs (160GB total), a 64-core AMD EPYC 7742, and 512GB of RAM into a quiet, air-cooled deskside chassis built to sit next to a desk in an office or lab. It draws from a standard power socket, cools without data center air handling, and runs quietly enough to share a room. Pre-installed with DGX OS and NVIDIA's deep-learning stack, it is a personal or small-team AI development machine that arrives ready to train. Verified and shipped worldwide DDP by MillionMiner.

Plugs Into a Wall Outlet

Four A100 GPUs, 64-core EPYC, 512GB RAM, in a quiet air-cooled deskside box. No rack, no data center, no special power. Office and lab ready.

A Personal AI Supercomputer

160GB of A100 compute for a researcher or small team. MIG partitions the four GPUs into as many as 28 instances, so a team shares one Station.

Ready on Day One

Pre-installed with DGX OS and NVIDIA's deep-learning frameworks. Verified secondary-market unit, productive on arrival, not after an integration project.

Häufig gestellte Fragen

Häufig gestellte Fragen

It is a deskside machine, not a rackmount server. The DGX Station A100 is built to sit beside a desk in an office or lab: it runs on a standard wall outlet, cools itself quietly without data center air handling, and needs no rack. Every other AI machine in this catalog is data center hardware; this is the one you can put in a normal room and use like an appliance.

A person, team, or department that wants real multi-GPU AI compute they control, without building infrastructure. AI researchers iterating without queuing for cluster time, data science teams wanting a dedicated training machine, and departments standing up AI capability in their own space. It was designed as a personal AI supercomputer, and that is exactly the role it fills.

A standard wall outlet. The single 1500W supply runs on ordinary 100 to 240V AC, and the machine uses a self-contained refrigerant cooling system quiet enough for an office, so there is no rack, raised floor, three-phase power, or special air handling required. That ordinary-environment design is the whole reason the DGX Station exists.

Four A100 Tensor Core GPUs at 160GB total, a 64-core AMD EPYC 7742, and 512GB of DDR4 RAM. Storage is a 7.68TB NVMe U.2 data drive plus a separate 1.92TB NVMe M.2 OS drive, networking is dual 10GbE, and the whole machine runs from a single 1500W supply. It weighs about 43kg and ships pre-installed with DGX OS.

160GB total across four GPUs is the 40GB-per-GPU A100 configuration. The DGX Station A100 was offered in both 40GB and 80GB versions, and this is the 40GB one. The exact memory configuration of your unit is confirmed in the quote, and MillionMiner can advise if your workload needs the larger per-GPU memory.

Yes, and it was designed for it. The A100's Multi-Instance GPU feature partitions the four GPUs into as many as 28 independent instances, each with isolated memory and compute, so several developers can work on one Station simultaneously as if it were multiple smaller machines. For a small team, that sharing is a large part of the value.

Secondary-market. NVIDIA discontinued the DGX Station line, so these are pre-owned units, which is the realistic way to acquire one now. MillionMiner verifies each unit before shipment and confirms its condition and the 2-year warranty term in the quote, the same secondary-market discipline applied across the catalog's A100 inventory.

For most development and training work, yes. The A100 remains a highly capable Tensor Core GPU, and four of them with 160GB is substantial compute for model development, fine-tuning, and inference. For a team that wants a controlled, in-house machine rather than cloud time or a data center deployment, it is a strong and economical choice on the secondary market.

Yes. It ships pre-installed with DGX OS and NVIDIA's deep-learning frameworks and tools, so it is productive on arrival rather than after a setup project. Plug it into a wall outlet and a network connection, and it is ready to train, which is part of why the DGX Station suits teams without dedicated infrastructure staff.

Submit your requirements through the quote form. A MillionMiner specialist confirms the unit's configuration and memory variant, its condition and warranty, and delivery. Each Station is verified before shipment and shipped worldwide DDP with duties handled, and MillionMiner can advise on rackmount A100 alternatives if a data center deployment suits your situation better.