NVIDIA A100 SXM4 80GB HBM2e

The NVIDIA A100 SXM4 80GB HBM2e is a flagship data center GPU built on NVIDIA's Ampere architecture, delivering transformational compute performance for the most demanding AI training, inference, and high-performance computing workloads. Manufactured with TSMC 7nm process technology, the A100 SXM4 integrates 6,912 CUDA cores, 432 third-generation Tensor Cores, and 80GB of HBM2e memory operating at 2TB/s memory bandwidth — setting a new benchmark for throughput in enterprise and hyperscale environments. The SXM4 form factor enables NVLink 3.0 connectivity, supporting multi-GPU configurations with up to 600GB/s bidirectional bandwidth per GPU when deployed in NVLink-connected systems such as the NVIDIA DGX A100.

At the core of the A100's AI acceleration capability are its third-generation Tensor Cores, which support a full range of precisions including TF32, FP64, FP32, FP16, BF16, and INT8, enabling flexible deployment across mixed-precision training and high-throughput inference pipelines. The A100 also introduces Multi-Instance GPU (MIG) technology, which allows a single A100 to be partitioned into up to seven independent GPU instances — each with dedicated compute, memory, and bandwidth resources — dramatically improving utilization and workload isolation in shared enterprise and cloud infrastructure.

Designed for integration into NVLink- and NVSwitch-based server platforms, the A100 SXM4 80GB is the compute foundation behind leading AI supercomputing systems and enterprise AI factories worldwide. Its support for NVMe GPUDirect, GPUDirect RDMA, and PCIe Gen4 (via host platform) ensures low-latency, high-bandwidth data paths critical to large-scale deep learning model training, genomics pipelines, financial simulations, and scientific research. Organizations across UAE, GCC, EMEA, and APAC rely on this GPU to accelerate their most compute-intensive digital transformation initiatives.

Ideal for

• Large-scale deep learning model training including transformer-based LLMs and vision models requiring high memory capacity and FP64/TF32/BF16 mixed-precision compute
• High-throughput AI inference serving for enterprise production environments, leveraging MIG partitioning to run multiple isolated inference workloads concurrently on a single GPU
• High-performance computing (HPC) simulations in computational fluid dynamics, molecular dynamics, climate modeling, and finite element analysis using FP64 double-precision performance
• Genomics and life sciences workloads including genome sequencing, drug discovery, and protein structure prediction pipelines requiring massive parallel compute throughput
• Financial services quantitative modeling, Monte Carlo simulations, and real-time risk analytics demanding high memory bandwidth and numerical precision
• Multi-tenant GPU virtualization in enterprise data centers, using MIG to allocate dedicated GPU partitions to separate teams, departments, or containerized workloads

Technical specifications

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