The Nvidia A100 GPU is a broad-purpose accelerator for enterprise data centres that need proven performance across AI training, inference and HPC. Its Multi-Instance GPU support helps shared environments keep utilisation high while delivering consistent results across mixed workloads.
Guide price: Price range: £5,995.00 through £9,995.00 Ex. VAT
Mixed AI, analytics and simulation workloads are putting more pressure on shared GPU estates to stay productive without creating another layer of platform sprawl.
The Nvidia A100 GPU is built for AI training and HPC environments that also need to carry inference and analytics workloads in established data-centre clusters. With 80 GB of GPU memory, it gives platform teams room for larger models and data sets on a single accelerator class.
Its NVLink 3.0 interconnect, with 600 GB/s bi-dir bandwidth, supports fast GPU-to-GPU communication where jobs are distributed across nodes. That makes it a practical fit for mixed accelerated infrastructure that depends on mature software support and consistent utilisation.
With 312 TFLOPS of BF16 / FP16 performance, the platform helps keep throughput strong across training and HPC pipelines. It also suits shared environments where a proven Ampere-class GPU is preferred over a rapid refresh to newer generations.
Our team can help you assess the Nvidia A100 GPU for your clustered workloads and deployment plans.
It is a straightforward choice when you need one accelerator platform to support day-to-day operational demands.
The Nvidia A100 GPU is a data center accelerator for AI and high-performance computing environments, providing a platform for compute-intensive workloads that need scalable throughput and tightly integrated interconnect architecture.
Tensor Core Compute
The platform is designed to accelerate AI training and inference workloads, with BF16 and FP16 performance reaching 312 TFLOPS.
Large GPU Memory Pool
80 GB of GPU memory supports larger model and data working sets within a single accelerator context.
Data Center Workload Alignment
The A100 GPU is positioned for demanding enterprise and research workloads that benefit from high-throughput parallel compute.
Interconnect-Ready Architecture
NVLink 3.0 provides up to 600 GB/s bi-directional bandwidth to support tightly coupled GPU scaling.
Multi-GPU Communication
NVLink-based connectivity helps maintain efficient data exchange between GPUs for distributed compute execution.
Parallel Processing Model
The architecture supports workload partitioning across accelerated compute resources to improve utilization in high-demand environments.
Platform-Level Throughput
High performance and interconnect bandwidth work together to sustain compute-heavy application pipelines.
When AI or HPC workloads require a balanced accelerator platform, our team can help match Nvidia A100 deployments to model size, throughput targets, and scaling requirements.
The Nvidia A100 GPU is a mature data-centre accelerator for shared AI, analytics and HPC workloads where teams need high utilisation, proven software support and flexible partitioning across many users and job types.
In central infrastructure teams, the A100 often sits in pooled GPU servers serving analytics, inference and simulation jobs. Its mix of maturity and partitioning helps operators keep expensive capacity busy without dedicating whole cards to every request.
Broadcast and post-production environments use the A100 when rendering-adjacent AI, media analytics and video processing must share one stable GPU estate. It avoids disruptive platform changes while supporting mixed creative and operational workloads.
Healthcare research teams deploy the A100 across imaging, genomics and biomedical AI projects that change frequently and involve several departments. Partitioning supports shared access, while the established platform reduces uncertainty for regulated research operations.
In finance, the A100 fits estates running pricing, fraud detection, forecasting and data science together. Teams value a proven accelerator that supports broad workload variety and strong utilisation without forcing a rapid move to the newest generation.
Software teams use the A100 for AI and HPC development, integration testing and reproducible builds that must run across large installed Ampere estates. It gives platform teams a familiar GPU class to standardise around.
Our team can help design and deploy Nvidia A100 GPU environments for shared data-centre infrastructure, media pipelines, healthcare research, finance and development clusters, with practical advice on sizing, partitioning and operational fit.
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Below you’ll find alternative models, suitable software and services that pair with this solution – helping you to avoid compatibility issues, reduce support overhead and deploy with confidence.
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