NVIDIA A100 PCIe 80GB — Full Datasheet Specifications
All figures from NVIDIA A100 datasheet (DS-10010-001). Tensor Core TFLOPS with sparsity assumes 2:4 structured sparse format. Note: A100 does not support FP8 — that was introduced with Hopper (H100).
Source: NVIDIA A100 80GB PCIe Datasheet DS-10010-001. All trademarks are the property of NVIDIA Corporation.
A100 vs H100 vs H200 PCIe
H100 FP16 figure includes sparsity. A100 FP16 without sparsity: 312 TFLOPS. Source: NVIDIA datasheets.
A100 PCIe Key Workloads
The A100 Ampere architecture introduced third-generation Tensor Cores supporting TF32 (new in Ampere) and BF16 precision for AI, and introduced MIG — GPU partitioning features that remain commercially relevant for inference infrastructure.
AI Inference (Production)
80GB VRAM handles inference of models up to ~30B parameters at FP16. MIG partitioning enables up to 7 concurrent isolated inference services on one card — ideal for multi-tenant API hosting.
Deep Learning Training
TF32 Tensor Cores deliver 156 TFLOPS for standard precision and 312 TFLOPS with sparsity — accelerating ResNet, BERT, GPT-2 scale models and scientific neural networks.
Multi-Instance GPU (MIG)
A100 introduced MIG — the first GPU to support guaranteed hardware partitioning into independent GPU instances. Seven 10GB instances enable isolated training, inference, or analytics workloads per tenant.
HPC & Scientific Simulation
19.5 TFLOPS FP64 Tensor Core and 80GB memory capacity with NVLink bridge support accelerate computational chemistry, bioinformatics, seismic processing, and CFD simulations.
Cost-Optimised Inference
The A100 PCIe remains relevant for inference where H100 supply is constrained or capital budgets are tighter. Its 80GB VRAM and MIG support provide production-grade multi-workload capability.
RAPIDS GPU Analytics
cuDF, cuML, and RAPIDS Accelerator for Apache Spark use A100's HBM2e bandwidth (1,935 GB/s) to deliver 2–10x throughput improvement for in-memory analytics versus CPU-only clusters.
Compare & Related Products
Need NVIDIA A100 PCIe for AI inference or HPC?
Servnet supplies A100 PCIe 80GB for UK enterprise and research deployments. We advise on upgrade path to H100/H200 PCIe, confirm server compatibility (PCIe 4.0 x16, 300W requirement), and provide current UK availability.

