Gigabyte NVIDIA A100 PCIe 40GB GPU

The Gigabyte NVIDIA A100 PCIe 40GB GPU (MPN: 900-21020-0010-000) is built on NVIDIA's Ampere architecture, delivering a generational leap in compute density for enterprise datacenter environments. The A100 features 6,912 CUDA cores, 432 Tensor Cores (third-generation), and 40GB of HBM2e memory with 1,555 GB/s of memory bandwidth, providing exceptional throughput for the most demanding AI training, inference, and high-performance computing workloads. The PCIe 4.0 form factor enables broad compatibility with existing server infrastructure without requiring NVLink-based switch fabrics, making it a practical choice for organizations scaling GPU capacity within standard rack deployments.

At the heart of the A100's capability is NVIDIA's Multi-Instance GPU (MIG) technology, which allows a single physical GPU to be partitioned into as many as seven isolated GPU instances, each with dedicated compute resources, memory, and memory bandwidth. This enables fine-grained resource allocation for mixed workloads — simultaneously running large-model training jobs alongside real-time inference services — without cross-workload interference. The A100 also supports third-generation NVLink (on SXM variants) and, in this PCIe configuration, integrates cleanly into multi-GPU topologies via standard PCIe switching for scale-out deployments.

Targeted at AI researchers, cloud service operators, financial analytics platforms, genomics pipelines, and scientific simulation environments, the Gigabyte A100 PCIe 40GB is positioned as a cornerstone accelerator for organizations that require sustained, reproducible FP64, FP32, FP16, BF16, TF32, and INT8 compute performance. Its 250W TDP, passive cooling design, and PCIe 4.0 x16 interface make it compatible with hyperscale and enterprise server platforms from leading brands, and its support for NVIDIA's mature CUDA ecosystem ensures access to optimized libraries including cuDNN, cuBLAS, TensorRT, and RAPIDS.

Ideal for

• Large-scale deep learning model training across computer vision, natural language processing, and multimodal AI frameworks such as PyTorch and TensorFlow
• High-throughput AI inference serving for enterprise applications requiring low-latency responses at scale, leveraging TensorRT optimization and INT8/FP16 precision modes
• High-performance computing simulations in computational fluid dynamics, molecular dynamics, and climate modeling requiring FP64 double-precision throughput
• Multi-tenant GPU virtualization using NVIDIA MIG to partition a single A100 into up to seven isolated instances for cloud and enterprise shared-infrastructure deployments
• Genomics and life sciences data processing pipelines, including genome sequencing analysis and drug discovery workflows accelerated via RAPIDS and CUDA libraries
• Financial services quantitative analytics and real-time risk modeling workloads that demand high memory bandwidth and deterministic double-precision compute performance

Technical specifications

Available from Omnixon Global. Submit an RFQ and our team will confirm configuration and availability for your order.