Exeton Quasar 640X 8x A100 AI Server (640GB NVLink)

Model: Quasar 640X

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A complete, fully specified 8-GPU training node: eight NVIDIA A100 80GB GPUs linked by NVLink for 640GB of combined GPU memory, dual Intel Xeon Platinum 8358 processors, 1TB of ECC memory, enterprise NVMe storage, and a 200G InfiniBand fabric NIC, all decided in one correctly proportioned build. Sourced, tested, and shipped worldwide DDP by MillionMiner.

Full Specifications

Model Quasar 640X
Power Supply 4x 3000W high-efficiency
CPU Dual Intel Xeon Platinum 8358
Memory 1TB (32x 32GB DDR4 ECC REG)
SSD 2x 960GB Enterprise, 1x 7.68TB U.2 NVMe SSD
GPU 8x NVIDIA A100 (80GB VRAM, NVLink)
Network Dual 10 Gigabit Ethernet, 1x 200G InfiniBand NIC
Warranty 3 years replacement parts

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Get a Quote for the Exeton Quasar 640X 8x A100 AI Server (640GB NVLink)

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Product Details

Exeton Quasar 640X 8x A100 AI Server: Component-by-Component Configuration Logic, Training Capability, and Where It Sits Against DGX and Configurable Platforms

There are three ways to buy an eight-GPU A100 node, and MillionMiner's catalog carries all of them honestly. The NVIDIA DGX A100 is the sealed appliance: NVIDIA's software stack and single-vendor support, at appliance economics. The Supermicro AS-4124GO-NART+ is the configurable platform: you specify the host yourself. The Exeton Quasar 640X is the third way, the decided build: a complete, fixed configuration where an integrator has already made every host decision, and the spec sheet shows they made them well. For teams that want to evaluate one quote, approve one line item, and deploy one known-good machine, this is the shortest path to 640GB of NVLinked A100 compute. The GPU complex. Eight NVIDIA A100 80GB GPUs connect through NVLink, pooling 640GB of HBM2e GPU memory across the node. In practical terms that supports full fine-tuning of models in the 30B to 70B parameter class using parallelism across the GPUs, training of smaller models at very large batch sizes, and simultaneous inference serving of multiple 70B-class models. Each A100 also partitions into up to seven MIG instances, so the node can present as many as 56 hardware-isolated GPU slices for multi-tenant inference, which lets one machine train overnight and serve dozens of isolated workloads through the day. The A100 remains the most production-proven AI accelerator in existence, with first-class support across current CUDA releases, PyTorch, TensorFlow, JAX, TensorRT, Triton, and vLLM. The host, component by component, and why each default is correct. Dual Intel Xeon Platinum 8358 processors deliver 64 cores and 128 threads on Intel's Ice Lake server platform with PCIe Gen 4 and eight-channel memory, the throughput needed to preprocess and feed eight accelerators without becoming the bottleneck. System memory is 1TB of DDR4 ECC across 32 modules: the working rule for a training node is system memory at or above total GPU memory, and 1TB over a 640GB GPU pool clears it with margin. Storage is split by function, two 960GB enterprise SSDs for the operating system and a 7.68TB U.2 NVMe drive for datasets, so checkpoint writes and dataset reads never fight the boot volume. Networking carries both of a node's lives: dual 10 Gigabit Ethernet handles management, monitoring, and general traffic, while the included 200G InfiniBand NIC provides the compute fabric port that turns a single server into a cluster member the day you add a second node. Power is four 3000W high-efficiency supplies, the redundant envelope this class of machine requires. Who buys this configuration. Teams standardized on Intel hosts who want fleet consistency. Research groups and companies that need DGX-class A100 capability but whose procurement favors a complete fixed quote over either an appliance premium or a configuration exercise. Inference operators who value the 56-instance MIG density. And buyers extending into multi-node training who want the InfiniBand fabric port included from day one rather than discovered as a missing line item later. On the brand question, answered plainly. Exeton is a specialist integrator rather than a tier-one server marque, and the spec sheet is where that shows up as an advantage: the configuration choices are the ones an experienced AI infrastructure engineer would have made, at integrator rather than appliance economics. The silicon inside is standard NVIDIA and Intel. Every unit MillionMiner supplies is sourced and tested before shipment, backed by three years of replacement parts coverage, and delivered worldwide DDP with duties and customs handled. Deployment guidance and hosting in MillionMiner's own data centers are available for teams that prefer not to provision power and cooling on-site. Share your workload through the quote form and a specialist confirms fit within one business day.

Exeton Quasar 640X: Every Component an 8-GPU Node Needs, Already Chosen Correctly

Most teams buying their first 8-GPU server discover the GPUs were the easy part. The hard part is the forty smaller decisions around them: how much system memory, which storage layout, what networking, what power redundancy. Get any of them wrong and eight expensive accelerators sit idle waiting on the host. The Quasar 640X exists for buyers who want those decisions made by someone who has built these nodes before. Walk through the spec sheet and each choice holds up. System memory is 1TB across 32 ECC modules, comfortably above the 640GB of GPU memory, which is the working rule for keeping data loading ahead of eight A100s. Storage splits the way a training node should: two 960GB enterprise SSDs handle the operating system, and a separate 7.68TB U.2 NVMe drive carries datasets, so training I/O never contends with the boot path. Networking covers both jobs a node has: dual 10 Gigabit Ethernet for management and general traffic, and a 200G InfiniBand NIC for the compute fabric, which means multi-node clustering is a cable away rather than a retrofit. Four 3000W high-efficiency power supplies provide the envelope eight A100-class GPUs and dual server CPUs demand, with redundancy built in. The compute itself: eight NVIDIA A100 80GB GPUs with NVLink interconnect, the most production-proven accelerator generation ever deployed, behind dual Intel Xeon Platinum 8358 processors with 64 cores and 128 threads on a PCIe Gen 4 platform. Three years of replacement parts coverage backs the hardware. MillionMiner sources and tests every unit, then ships worldwide DDP with customs handled.

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Exeton Quasar 640X: The Fully Decided 8x A100 Build

The Quasar 640X is an 8x A100 server where every configuration decision has already been made, and made correctly. Eight NVIDIA A100 80GB GPUs connect over NVLink for 640GB of combined GPU memory. The host carries dual Intel Xeon Platinum 8358 processors with 64 cores, 1TB of DDR4 ECC memory, mirrored enterprise boot SSDs plus a 7.68TB U.2 NVMe dataset drive, dual 10GbE for operations, and a 200G InfiniBand NIC for compute fabric. Four 3000W high-efficiency power supplies carry the load with redundancy. One complete node, nothing left to specify, quoted and shipped worldwide DDP by MillionMiner.

640GB of A100, Zero Decisions Left

Eight NVIDIA A100 80GB GPUs with NVLink in one complete, fixed configuration. Every host component already specified, and specified correctly.

A Host Built to the Sizing Rules

1TB ECC memory above the 640GB GPU pool, mirrored enterprise boot SSDs, and a separate 7.68TB NVMe dataset drive. The GPUs never wait on the host.

Cluster-Ready Out of the Box

A 200G InfiniBand fabric NIC ships in the base build alongside dual 10GbE. Adding a second node is a cable, not a retrofit.

FAQ

Frequently Asked Questions

Exeton is a specialist AI server integrator rather than a tier-one marque like Supermicro or NVIDIA. The components inside are standard: NVIDIA A100 GPUs, Intel Xeon Platinum processors, enterprise SSDs. What the integrator contributes is the configuration, and the spec sheet shows experienced judgment throughout. Every unit MillionMiner supplies is sourced and tested before shipment, carries three years of replacement parts coverage, and is supported by MillionMiner directly, so the brand on the chassis does not change who stands behind your hardware.

Fixed, and that is the point of this product. The Quasar 640X is the complete, decided build for buyers who want one quote and one known-good machine. If you need a different CPU platform, memory capacity, or storage layout, the Supermicro AS-4124GO-NART+ in this catalog is the configurable 8x A100 path, and MillionMiner quotes both.

Both deliver eight A100 80GB GPUs with NVLink and 640GB of combined GPU memory. The DGX adds NVIDIA's full software stack, Base Command, NGC certified containers, and single-vendor support, at appliance economics. The Quasar delivers the same class of GPU compute in a complete fixed build at integrator economics, with you running standard open tooling on top. Certainty-led enterprise buyers tend toward the DGX; value-led teams comfortable with the standard CUDA ecosystem tend here.

The Supermicro is a configurable platform where you specify CPUs, memory, storage, and networking yourself, on an AMD EPYC host. The Quasar is a fixed Intel Xeon build where those decisions are already made, including 1TB of memory and a 200G InfiniBand NIC in the base spec. Choose the Supermicro to tailor the host; choose the Quasar to skip the configuration exercise entirely.

Because the working rule for an 8-GPU training node is system memory at or above total GPU memory. Data loading, preprocessing, and augmentation for eight A100s need host-side headroom, and an undersized host starves the accelerators you actually paid for. With 640GB of GPU memory in the node, 1TB of ECC system memory clears the rule with margin, which is exactly why this configuration was chosen.

Separation of duties. Two 960GB enterprise SSDs carry the operating system, and a dedicated 7.68TB U.2 NVMe drive carries datasets and checkpoints. Training jobs read datasets and write checkpoints constantly; keeping that I/O off the boot volume prevents contention and keeps both the OS and the training pipeline responsive. It is the layout an experienced operator would have specified anyway.

Yes, and the base build anticipates it. The included 200G InfiniBand NIC provides the compute fabric port for GPU-to-GPU communication across nodes, while the dual 10 Gigabit Ethernet handles management traffic. Scaling from one node to several is an interconnect and switch exercise rather than a hardware retrofit, and MillionMiner advises on fabric design during configuration.

Full fine-tuning of models in the 30B to 70B class with parallelism across the eight GPUs, training of smaller models at very large batch sizes, and simultaneous serving of multiple 70B-class inference workloads. Using MIG, the node partitions into up to 56 hardware-isolated GPU instances, each suited to serving models in the 7B to 13B class, which makes one server a complete multi-tenant inference platform.

This is a data center machine. Four 3000W high-efficiency power supplies define the envelope, and an eight-GPU A100 node draws several kilowatts under sustained training load with high-volume front-to-back airflow required. MillionMiner confirms the exact power and cooling plan for your site during configuration, and hosting in MillionMiner's own facilities is available if you prefer not to provision infrastructure.

Submit your workload and deployment details through the quote form, and a MillionMiner specialist replies with a complete quote covering the system, three-year replacement parts coverage, and delivery. Every unit is tested before shipment and delivered worldwide DDP with duties and customs handled. Rack integration guidance and hosted deployment are both available.