NVIDIA GPU-NVTV100 Tesla V100: 16GB HBM2 Graphics Card

The NVIDIA Tesla V100 is a Volta-architecture compute accelerator built around the GV100 GPU, delivering 16GB of HBM2 memory across a 4096-bit memory bus at approximately 900GB/s bandwidth. To put that in context: where GDDR5-based workstation cards of the same era top out around 300–350GB/s, the V100's HBM2 implementation nearly triples available memory bandwidth — a critical factor in transformer model training and large-scale scientific simulation where data movement, not compute, is the bottleneck. The card's Tensor Core units provide up to 112 TFLOPS at FP16 mixed-precision, enabling training runs that would take days on older Pascal-class hardware to complete in hours.

This card is designed for data center insertion — rack servers, blade systems, and GPU compute clusters with managed forced airflow. Its passive cooler is not a compromise; it is an architectural decision optimized for environments where chassis fans move 40–60 CFM directly across expansion slots. Researchers running CUDA-based deep learning frameworks (TensorFlow, PyTorch), financial modeling pipelines, molecular dynamics simulations, and CFD workloads will find the V100 delivers on its spec sheet consistently. It is not appropriate for workstation deployments without a purpose-built GPU workstation chassis, and has no role in any consumer or gaming use case.