NVIDIA A100 8x80GB Baseboard (A100-8x80GB-Baseboard)

P/N: A100-8x80GB-Baseboard

84 805  (inc. VAT (Spain))

  • EU Delivery time is made within 3-7 days

  • Warranty 2 year

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NVIDIA A100 8×80GB Baseboard. with fast EU delivery and worldwide shipping. Includes official warranty.

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Technical Specifications Product

Weight 10,00 kg
Dimensions 26,7 × 11,1 × 17 cm
Country of manufacture

Taiwan

Manufacturer's warranty (years)

1

Model

NVIDIA A100

Cache L2 (MB)

40

Process technology (nm)

4

Memory type

HBM2e

Graphics Processing Unit (Chip)

Number of CUDA cores

6912

Number of Tensor cores

432

Video memory size (GB)

80

Memory frequency (MHz)

16000

Memory bus width (bits)

5120

Memory Bandwidth (GB/s)

2039

Connection interface (PCIe)

PCIe 5.0 x16

FP16 performance (TFLOPS)

312

FP32 performance (TFLOPS)

156

FP64 performance (TFLOPS)

9.7

Cooling type

Passive (server module)

Number of occupied slots (pcs)

8

Temperature range (°C)

0–85

Multi-GPU support

Yes (NVSwitch)

Virtualization/MIG support

MIG (up to 7 instances)

Architecture

Ampere

Product description

8×NVIDIA A100 80GB SXM GPU Baseboard: Ultimate Power for AI and HPC

8×NVIDIA A100 SXM 80GB GPU Baseboard is a high-density compute module that integrates eight NVIDIA A100 GPUs with 80 GB of HBM2e memory each — providing a total of 640 GB of ultra-fast memory and immense computational throughput for artificial intelligence, data analytics, and high-performance computing (HPC) workloads.

Unlike traditional PCIe configurations, GPUs within this baseboard are interconnected via NVLink and NVSwitch, enabling direct high-bandwidth communication between all eight accelerators. This design allows them to operate as a unified system, eliminating PCIe bottlenecks and maximizing parallel efficiency for the most demanding AI and scientific applications.

Specifications

  • Total GPU Memory: 640 GB HBM2e
  • Memory per GPU: 80 GB HBM2e
  • GPU Count: 8× NVIDIA A100 (SXM4 form factor)
  • Memory Bandwidth: up to 2 TB/s per GPU
  • GPU Interconnect: NVLink with NVSwitch — up to 600 GB/s per link
  • Architecture: NVIDIA Ampere
  • Interface: PCIe Gen4 (integration-ready baseboard)
  • Cooling: Passive, optimized for rack-mounted servers

Key Advantages

  • Unified GPU architecture. NVSwitch connects all GPUs into a single compute matrix — essential for LLM training and generative AI workloads.
  • Extreme performance and reliability. Up to 2 TB/s memory bandwidth and hundreds of GB/s inter-GPU throughput ensure consistent scalability.
  • Infrastructure efficiency. Shared power and cooling systems reduce total energy consumption and simplify deployment.
  • Seamless scalability. Multiple baseboards can be interconnected to form full AI clusters for large-scale model training or HPC tasks.

Applications

  • Large Language Models (LLMs). Training and inference of GPT, DeepSeek, Qwen, Mistral, and other advanced architectures.
  • HPC Simulations. Molecular modeling, energy research, CFD, and climate simulation workloads.
  • Data Centers. High-density GPU racks and cloud compute environments.
  • Generative AI. Training multimodal and complex generative systems with high data throughput.

Why Choose 8×NVIDIA A100 80GB SXM Baseboard

  • Eight A100 GPUs in one module — delivering supercomputer-class performance.
  • Higher efficiency and bandwidth compared to eight separate PCIe GPUs, thanks to NVLink/NVSwitch.
  • Reduced setup time and operational overhead for heavy AI and HPC workloads.
  • OEM baseboard offers DGX-class architecture at a lower infrastructure cost.

8×NVIDIA A100 SXM 80GB GPU Baseboard is a foundational building block for modern data centers and AI clusters. It provides unmatched performance, scalability, and efficiency — an ideal solution for enterprises and research institutions advancing large-scale AI, simulation, and scientific computing projects.

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Product Berchmark

Overview and Analysis of the NVIDIA A100 8x80GB Baseboard

The NVIDIA A100 8x80GB Baseboard is a high-performance data center solution focused on the most resource-intensive tasks in artificial intelligence, data analytics, and high-performance computing (HPC). This model represents a key infrastructure element for training neural networks and scientific simulation, offering a balance between massive video memory capacity and high bandwidth.

A key advantage of this configuration is the use of HBM2e memory with record-breaking bandwidth, allowing for efficient work with massive models. Unlike standard PCIe versions, the Baseboard implementation (typically in the SXM form factor) features an expanded 400W thermal envelope, ensuring higher clock speeds and stable performance during sustained workloads. Support for double-precision (FP64) computing makes it indispensable for engineering calculations where maximum precision is required.


Comparative Table of Technical Specifications

The table presents a comparison of the NVIDIA A100 8x80GB Baseboard with nine closest competitors, including the latest flagships of the H100 and H200 series, as well as professional solutions from the L40 and RTX lines.

Model VRAM (GB) Memory Type Bandwidth (GB/s)* CUDA Cores Tensor Cores FP16 (TFLOPS) FP32 (TFLOPS) FP64 (TFLOPS) Tensor Perf (TFLOPS) Interface TDP (W)
NVIDIA A100 8x80GB Baseboard 80** HBM2e 2039 6912 432 312 156 9.7 624 PCIe 5.0 x16 400
NVIDIA H100 80GB 80 HBM2e 2039 14592 432 1979 989 49 3958 PCIe 5.0 x16 350
NVIDIA H200 141GB 141 HBM3e 4800 14592 432 1979 989 49 3958 PCIe 5.0 x16 600
NVIDIA H100 NVL 94GB 94 HBM3 3900 14592 432 1513 756 30 3026 PCIe 5.0 x16 400
NVIDIA H100 96GB 94 HBM3 3900 16896 432 1979 989 49 3958 PCIe 5.0 x16 400
NVIDIA A100 80GB 80 HBM2e 1935 6912 432 312 156 9.7 624 PCIe 4.0 x16 300
NVIDIA RTX Pro 6000 Blackwell 96GB 96 GDDR7 ECC 1792 24064 752 110.1 55.1 1.9 220.2 PCIe 5.0 x16 600
NVIDIA L40S 48GB 48 GDDR6 ECC 864 18176 568 733 366 PCIe 4.0 x16 350
NVIDIA RTX 6000 Ada 48GB 48 GDDR6 ECC 960 18176 568 91.1 1457 PCIe 4.0 x16 300
NVIDIA A40 48GB 48 GDDR6 695.8 10752 336 37.4 37.4 0.5 PCIe 4.0 x16 300

*Bandwidth — Memory Bandwidth. Values “-” indicate data is unavailable.
**Memory volume per single GPU within the Baseboard is indicated. Total system memory volume is 640 GB.


Analysis of the Strengths of the NVIDIA A100 8x80GB Baseboard

Technical data analysis confirms that the NVIDIA A100 8x80GB Baseboard retains its position as one of the most balanced solutions in the segment, distinguished by the following characteristics:

  • Memory Subsystem Superiority: The use of HBM2e memory with a bandwidth of 2039 GB/s gives the card a significant advantage over models based on GDDR6/GDDR7 memory (L40S, RTX 6000 Ada, A40). This is a critically important parameter for tasks where the bottleneck is data transfer speed rather than pure computational power. The bandwidth figure is identical to the newer H100 80GB, highlighting the relevance of the memory architecture.
  • Scalable Memory Subsystem (640 GB Total VRAM): Unlike single cards with 40, 48, or 80 GB of memory, the Baseboard provides a cumulative capacity of 640 GB (8×80 GB). This allows for loading entire massive neural network models into memory that physically do not fit on competitive solutions such as the L40S or RTX 6000 Ada.
  • FP64 Computational Power: Compared to RTX and L40 series cards, which virtually lack effective double-precision (FP64) support, the A100 provides performance at the level of 9.7 TFLOPS. This makes it the unparalleled choice for scientific simulation (CFD, CAE) among cards of its generation, surpassing even the newest workstations (RTX Pro 6000 Blackwell) in this specific scenario by nearly 5 times.
  • Efficient Baseboard Form Factor: A higher TDP (400 W) compared to the standard A100 PCIe version (300 W) allows for maintaining maximum frequencies for extended periods without throttling. This yields a real performance gain in round-the-clock computations typical for data centers compared to power-limited PCIe adapters.

Conclusion

The NVIDIA A100 8x80GB Baseboard remains a benchmark of reliability and performance for deep learning infrastructure and scientific calculations. Despite the release of newer generations, the combination of a massive 80 GB memory buffer, high HBM2e bandwidth, and full FP64 support makes this card the preferred choice for tasks requiring maximum stability and speed when working with large datasets, where it confidently outperforms many alternative consumer and professional-class solutions.

Product FAQ

The NVIDIA A100 8x80GB Baseboard is an SXM form factor solution designed for installation in specialized server platforms (HGX). Unlike PCIe versions, this layout provides higher power consumption limits (400W TDP), which allows for maintaining maximum GPU performance for extended periods without clock speed reduction (throttling).

Each graphics processor in the configuration is equipped with 80 GB of high-speed HBM2e memory. This is double the capacity compared to the first A100 version (40 GB), which is critical for loading massive neural networks and working with large datasets (Big Data).

The memory bandwidth is 2039 GB/s. This is one of the highest figures in the industry, allowing the GPU to instantly access data for calculations, eliminating bottlenecks when training complex AI models and preventing compute core idleness.

Yes, thanks to Multi-Instance GPU (MIG) technology, each physical A100 80GB accelerator can be partitioned into 7 isolated instances. This allows for simultaneously serving multiple users or running different tasks (for example, inference of smaller models) with guaranteed memory and cache resource allocation.

The NVIDIA A100 8x80GB Baseboard is ideally suited for the most resource-intensive calculations: Deep Learning, High-Performance Computing (HPC), scientific simulation (weather, genomics, physics), and big data analysis. High performance in FP64 (9.7 TFLOPS) makes it the standard for engineering calculations.

Given the high heat dissipation level (400W TDP per GPU), the Baseboard solution requires installation in server chassis with a powerful airflow system or the use of liquid cooling systems. The passive heatsinks on the modules are designed for external airflow from server fans.

Despite the release of the new generation, the A100 remains the “gold standard” in terms of the availability-to-performance ratio. A huge base of optimized software and libraries makes it the most stable and predictable solution for deploying existing AI pipelines.

The accelerator is equipped with 432 third-generation Tensor Cores, providing peak performance of up to 624 TFLOPS (using sparsity). This ensures colossal acceleration of matrix calculations, which lie at the foundation of modern artificial intelligence.

Yes, the Baseboard (SXM) form factor is specifically designed for maximum NVLink technology efficiency. This allows combining all GPUs on the board into a single computing cluster with massive data exchange speeds between them, which is unattainable for standard PCIe cards.

Payment & Shipping methods

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Additional Notes

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