NVIDIA A100 GPU: Models, Costs, and Use Cases for AI and HPC
- server-parts.eu server-parts.eu
- Mar 23
- 3 min read
Updated: Mar 25
The NVIDIA A100 GPU is a powerful solution for AI workloads, data science, and high-performance computing (HPC). Built on NVIDIA's Ampere architecture, the NVIDIA A100 is designed to handle demanding tasks like deep learning, data analytics, and complex simulations.
NVIDIA A100 GPUs: Save Up to 80%
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With multiple models available, it's crucial to understand the differences and choose the right option for your use case. This article provides technical details, specifications, and use cases to help you make an informed decision.
What is the NVIDIA A100 GPU?
The NVIDIA A100 is an enterprise-grade GPU built on the Ampere architecture, succeeding the NVIDIA V100. It is designed for large-scale AI model training, HPC workloads, and inference tasks. The NVIDIA A100 offers strong performance improvements with key features like:
MIG (Multi-Instance GPU) technology for improved efficiency.
HBM2e memory for high bandwidth data processing.
Tensor Cores (3rd Gen) for faster AI model training.
FP64 precision for accurate scientific computing.
NVLink support in SXM4 models for extreme scalability in multi-GPU setups.
NVIDIA A100 GPU Models, Specifications & Prices
NVIDIA A100 PCIe 40GB is the entry-level model with 40GB of HBM2 memory and a bandwidth of 1.55TB/s. It’s an ideal choice for smaller-scale AI training, inference tasks, and data analytics. With 250W power consumption, it’s energy-efficient and fits most PCIe-based servers.
NVIDIA A100 PCIe 80GB offers the same core specifications but doubles the memory size to 80GB HBM2e, improving bandwidth to 2TB/s. This model is perfect for large-scale data analytics, deep learning frameworks, and handling massive datasets. At 300W, it requires slightly more power than the 40GB model.
NVIDIA A100 SXM4 40GB uses the NVLink interface for maximum scalability in GPU clusters. With 400W power consumption, it’s designed for demanding AI training and scientific workloads in multi-GPU environments. This model is ideal for data centers that require high-performance networking capabilities.
NVIDIA A100 SXM4 80GB is the highest-end model, combining 80GB of HBM2e memory with NVLink support for up to 600GB/s bandwidth. This model is the best option for the largest AI workloads, HPC clusters, and enterprise data centers with heavy computational requirements.
Feature | A100 40GB PCIe | A100 80GB PCIe | A100 40GB SXM4 | A100 80GB SXM4 |
GPU Architecture | Ampere (GA100) | Ampere (GA100) | Ampere (GA100) | Ampere (GA100) |
Memory Size | 40GB HBM2 | 80GB HBM2e | 40GB HBM2 | 80GB HBM2e |
Memory Bandwidth | 1.55 TB/s | 2.0 TB/s | 1.6 TB/s | 2.0 TB/s |
Memory Bus Width | 5120-bit | 5120-bit | 5120-bit | 5120-bit |
CUDA Cores | 6912 | 6912 | 6912 | 6912 |
Tensor Cores | 432 | 432 | 432 | 432 |
FP64 Performance | 9.7 TFLOPS | 9.7 TFLOPS | 9.7 TFLOPS | 9.7 TFLOPS |
FP32 Performance | 19.5 TFLOPS | 19.5 TFLOPS | 19.5 TFLOPS | 19.5 TFLOPS |
TF32 Performance | 156 TFLOPS | 156 TFLOPS | 156 TFLOPS | 156 TFLOPS |
INT8 Performance | 624 TOPS | 624 TOPS | 624 TOPS | 624 TOPS |
Power Consumption | 250W | 300W | 400W | 400W |
MIG Support | Yes (7 instances) | Yes (7 instances) | Yes (7 instances) | Yes (7 instances) |
NVLink Support | No | No | Yes (600GB/s) | Yes (600GB/s) |
Server Compatibility | Standard PCIe Servers | Standard PCIe Servers | DGX A100, HPE Apollo | DGX A100, HPE Apollo |
Choosing the Right NVIDIA A100 GPU Model
For Flexible Server Integration:
The NVIDIA A100 PCIe 40GB or A100 PCIe 80GB GPUs are ideal choices for organizations that need GPUs that can slot into existing PCIe-based servers. They offer excellent performance for AI inference, data analytics, and smaller-scale training without requiring additional infrastructure changes. The PCIe models are best suited for environments where ease of installation and compatibility with mainstream servers like Dell PowerEdge, HPE ProLiant, and Lenovo ThinkSystem is a priority.
For Large Language Models and Deep Learning:
If you’re handling massive datasets, complex AI models like GPT-3, or need improved throughput for large neural networks, the NVIDIA A100 80GB PCIe or A100 80GB SXM4 GPU is the optimal choice. The 80GB memory capacity ensures smooth data handling without memory bottlenecks, and its high bandwidth accelerates model training significantly.
For Multi-GPU Clusters and HPC Setups:
The NVIDIA A100 SXM4 40GB or A100 SXM4 80GB GPUs are designed for high-performance computing environments that demand scalability. SXM4 models support NVLink technology, which provides up to 600GB/s bandwidth for fast GPU-to-GPU communication — ideal for multi-node AI training, simulations, and scientific calculations in data centers.
For Virtualization in Data Centers:
The NVIDIA A100 PCIe and SXM4 GPU models both support MIG (Multi-Instance GPU) technology, which allows you to partition one A100 GPU into up to 7 independent GPU instances. This feature enables efficient multi-user environments, making the NVIDIA A100 ideal for businesses running multiple concurrent AI workloads or virtual desktop infrastructures (VDI).
NVIDIA A100 GPUs: Save Up to 80%
✔️ Fast Shipping, Large Inventory, No Upfront Payment Required.
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