The Nvidia B200 GPU delivers flagship acceleration for AI training and inference at scale in data centre environments. Built on Blackwell architecture with MIG support, it helps service providers run frontier-model workloads with higher throughput and greater efficiency.
Guide price: Price range: £29,995.00 through £34,995.00 Ex. VAT
As AI workloads scale, infrastructure teams need more throughput, lower latency between jobs, and a platform that can keep pace with dense training and inference demand without adding unnecessary complexity.
The Nvidia B200 GPU is built for Blackwell-era AI infrastructure, where production systems need headroom for frontier-model training, large-scale inference, and reasoning-heavy workloads. It fits refresh cycles that are moving beyond Hopper-class deployments and into higher-density AI factories.
With 180 GB of GPU memory, 4500 TFLOPS BF16/FP16 performance, and NVLink 5.0 at 1.8 TB/s bi-dir, it supports the data movement and compute intensity that modern AI pipelines place on shared infrastructure. MIG support also helps teams partition capacity more cleanly across mixed production demands.
That combination helps organisations train and serve larger models more efficiently, improve utilisation of accelerated infrastructure, and reduce pressure on surrounding systems. It gives platform teams a practical path to sustain faster experiment cycles and more responsive model services.
Our team can help you assess the Nvidia B200 GPU for your AI platform roadmap and align it with your production requirements.
The Nvidia B200 GPU is a datacenter acceleration platform for large-scale AI and HPC deployments, designed to deliver high-throughput compute within modern accelerator-based infrastructure.
Massive Tensor Throughput
The platform delivers BF16 and FP16 acceleration at up to 4500 TFLOPS for training and inference workloads that benefit from high parallel compute density.
Large On-Device Memory
180 GB of GPU memory supports data-intensive model execution and helps keep active workloads resident on the accelerator.
High-Bandwidth Accelerator Design
The architecture is built for sustained data movement between GPU resources and surrounding platform components to support compute-heavy processing.
Scale-Up Performance Fabric
NVLink 5.0 provides 1.8 TB/s bi-directional interconnect bandwidth for tightly coupled multi-GPU operation.
Multi-GPU Cohesion
NVLink-based connectivity enables closely coordinated GPU-to-GPU communication for platform designs that require shared acceleration resources.
Capacity for Large Workloads
The 180 GB memory footprint supports larger model states and working sets within a single accelerator deployment.
Datacenter Integration
The B200 GPU fits into enterprise accelerator environments where compute resources are provisioned as part of a broader AI infrastructure stack.
When AI training demand outgrows conventional compute, our team can help align Nvidia B200 GPU deployment choices with your architecture, performance targets, and scaling strategy.
The Nvidia B200 GPU is a Blackwell-era accelerator for AI-heavy environments that need more training and inference throughput from each deployed system. It fits organisations refreshing current-generation GPU infrastructure for larger model work, faster iteration, and tighter operational efficiency.
Large data centres moving beyond Hopper-era constraints use the B200 when frontier training and high-volume inference start to bottleneck delivery. It gives platform teams more headroom per node and helps reduce the number of cycles needed to serve demanding AI estates.
Media and entertainment teams running generative video and content-creation workloads need higher throughput to keep turnaround times acceptable. The B200 supports heavier creative GPU use, making it a practical choice when earlier generations struggle to sustain output at scale.
Healthcare organisations building multimodal or domain-specific AI pipelines often face growing compute demand as model size and inference volume increase. The B200 suits in-house research and clinical AI platforms that need stronger efficiency for advanced biomedical workloads.
Finance teams serving large models, simulation jobs and AI-driven analysis need faster answers without inflating infrastructure overhead. The B200 is a credible deployment choice where performance and utilisation both matter to trading support, risk workflows and internal copilots.
Software development teams standardising on current-generation hardware use the B200 to train, test and tune more ambitious models. It helps engineering groups shorten experiment cycles and build against the Blackwell performance envelope expected in later deployments.
Our team can help design and deploy Nvidia B200 GPU environments for data centres, media production, healthcare AI, financial modelling and ML engineering platforms, with support tailored to performance, scaling and operational planning.
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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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