
NVIDIA A100 8x40GB Baseboard
Price range: 10€ through 100€
Delivery is made within 14-21 days
The prices are presented for both corporate clients and individuals.
Pricing for
The prices are presented for both corporate clients and individuals.
NVIDIA A100 8×40GB Baseboard. Factory 8-GPU SXM baseboard (8×A100 40GB) with NVSwitch for dense AI clusters. Direct import, warranty, careful freight, deployment help.
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Product description
8×NVIDIA A100 40GB SXM GPU Baseboard: Extreme Power for AI and HPC
8×NVIDIA A100 SXM 40GB GPU Baseboard is a high-performance server module that integrates eight NVIDIA A100 GPUs with 40 GB of HBM2 memory each. In total, the system delivers 320 GB of GPU memory and tremendous computing capacity for artificial intelligence, machine learning, and high-performance computing (HPC) workloads.
Built on the Ampere architecture, the module utilizes the SXM4 form factor and interconnects GPUs via NVLink and NVSwitch. With bandwidths of up to 600 GB/s per link, all eight GPUs operate as a unified compute fabric, eliminating bottlenecks typical of PCIe-based systems.
Specifications
- GPU Architecture: NVIDIA Ampere
- Total Memory: 320 GB HBM2
- Memory per GPU: 40 GB HBM2
- Number of GPUs: 8× NVIDIA A100 (SXM4)
- Memory Bandwidth: 1.6 TB/s per GPU
- GPU Interconnect: NVLink with NVSwitch, up to 600 GB/s per link
- Interface: PCIe Gen4
- Form Factor: SXM4 Baseboard
Key Advantages
- Balanced configuration. Compared to the 80 GB version, the 40 GB setup focuses on performance and efficiency for projects that don’t require ultra-large memory volumes.
- High throughput. Each GPU provides 1.6 TB/s memory bandwidth, ensuring rapid data access for large-scale workloads.
- Unified architecture. NVSwitch interconnects all eight GPUs into a single cluster with hundreds of GB/s bandwidth — crucial for LLM and HPC applications.
- Infrastructure efficiency. One baseboard replaces eight discrete GPUs, reducing costs for power, cooling, and integration.
Applications
- Artificial Intelligence and Machine Learning. Training and inference of medium-to-large neural networks.
- High-Performance Computing (HPC) and Big Data. Large-scale analytics, simulation, and modeling tasks.
- Cloud and Data Centers. Scalable GPU clusters for AI and research workloads.
- Generative AI. Designed for multimodal and generative model training where compute density is key.
Why Choose 8×NVIDIA A100 SXM 40GB Baseboard
- Optimal balance of performance and cost — more efficient than eight separate PCIe GPUs.
- NVSwitch/NVLink provide full-mesh interconnect with maximum bandwidth, impossible in PCIe systems.
- 320 GB of HBM2 memory is sufficient for most LLM and HPC workloads without paying for excess capacity.
- OEM baseboard delivers the same architecture as NVIDIA DGX systems at a lower infrastructure cost.
8×NVIDIA A100 SXM 40GB GPU Baseboard is the ideal choice for enterprises and research organizations that need serious compute power without overpaying for maximum configurations. It’s engineered for data centers, scientific institutions, and cloud platforms that demand consistent performance, scalability, and energy efficiency.
Additional information
| Weight | 1,8 kg |
|---|---|
| Dimensions | 26,7 × 11,1 cm |
| Country of manufacture | Taiwan |
| Manufacturer's warranty (years) | 1 |
| Model | NVIDIA A100 |
| Cache L2 (MB) | 40 |
| Process technology (nm) | 4 |
| Memory type | HBM3 |
| Graphics Processing Unit (Chip) | |
| Number of CUDA cores | 16896 |
| Number of Tensor cores | 528 |
| Video memory size (GB) | 40 |
| Memory frequency (MHz) | 14000 |
| Memory bus width (bits) | 5120 |
| Memory Bandwidth (GB/s) | 1555 |
| 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 |
| Length (cm) | 26.7 |
| Width (cm) | 11.1 |
| Weight (kg) | 1.8 |
| Temperature range (°C) | 0–85 |
| NVLink Throughput (GB/s) | 600 |
| Multi-GPU support | Yes (NVSwitch) |
| Virtualization/MIG support | MIG (up to 7 instances) |
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