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B200 on Azure: Pricing, Specs & How to Rent

Deploybase · March 24, 2026 · GPU Pricing

Contents

B200 Azure Pricing Introduction

Azure B200 pricing: $5.50-$7.50/hr. Limited availability. Scarce compared to H100 or A100.

Available in US East and West Europe only. Call Azure sales to reserve capacity. No spot instances yet. Reserved instances drop 30-40% off but require multi-month commitments.

B200 GPU Technical Specifications

B200: ~9,000 TFLOPS FP8 dense (~9 PFLOPS). 192GB HBM3e. 8.0 TB/s memory bandwidth. Handles 1M+ token contexts, trillion-parameter models.

TF32 performance: 2.2 PFLOPS sparse (1.1 PFLOPS dense). Next-gen Transformer Engine. 1,000W TDP (needs production cooling).

B200 instances on Azure combine eight GPUs per node with NVLink 5.0 interconnect at 1.8 TB/s per GPU between GPUs. This architecture matches NVIDIA's own DGX SuperPOD specifications, delivering consistent performance across distributed training jobs.

Compare B200 specifications against H100 alternatives for performance-per-dollar analysis or H200 as interim solutions.

How to Rent B200 on Azure

Not pay-as-you-go. Call Azure sales. They ask what you're building, then negotiate custom deals.

Provisioning: 2-6 weeks from first call. Upfront commitment + monthly usage fees.

Once provisioned, deployment follows standard Azure Resource Manager workflows. Teams select the specialized ND96XS_A100_v4-equivalent tier adapted for B200, configure networking, and launch training environments. Cluster orchestration uses Kubernetes or Azure Batch for distributed workloads.

Azure provides dedicated technical support for B200 deployments, including optimization consulting, troubleshooting, and performance tuning.

Competitive B200 Provider Analysis

CoreWeave's B200 pricing of $68.80 per hour for eight-GPU clusters scales to $8.60 per GPU, approximately 15% higher than Azure's typical B200 rates. CoreWeave prioritizes immediate availability with no multi-week sales cycles.

RunPod's B200 pricing sits at $5.98 per hour for single GPUs, undercutting Azure and CoreWeave significantly. However, RunPod's B200 availability remains extremely limited, with spot instances appearing sporadically.

Lambda Labs offers B200 SXM at $6.08/hour as of March 2026, with supply limited to production customers.

For cost-sensitive teams, RunPod's rates justify switching if capacity becomes available. For guaranteed access and production support, Azure remains the reliable choice despite premium pricing.

Explore RunPod GPU pricing for budget alternatives or CoreWeave pricing for immediate availability.

B200 Use Cases on Azure

Training trillion-parameter language models requires B200's extreme throughput. Distributed training across eight B200 GPUs achieves 1.2+ TB/s aggregate memory bandwidth, enabling 16K-token batch sizes and reducing training time from months to weeks.

Inference on long-context models benefits from B200's 192GB memory. Deploying models with 1M-token context windows becomes practical without sequence splitting or advanced memory optimization techniques.

Real-time research environments processing massive datasets use B200's performance. Computer vision, generative modeling, and multimodal research accelerates significantly.

Financial modeling and risk simulation at extreme scale justifies B200 investment. Quantitative trading firms and risk management teams use B200 for Monte Carlo simulations involving billions of parameters.

Advantages and Limitations

Azure's production infrastructure provides compliance certifications (FedRAMP, HIPAA) unavailable from smaller providers. Teams handling government contracts or healthcare data benefit from Azure's attestations and audit trails.

Limited availability represents the primary constraint. B200 capacity remains restricted compared to H100 commoditization. Teams cannot elastically scale from 1 to 100 B200 GPUs within days.

B200 pricing premiums are substantial. Per-unit costs approximately double H100 rates. ROI analysis must account for training time reductions offsetting hardware premiums.

Long sales cycles create friction. Teams planning workloads benefit from early capacity reservations, but reactive scaling becomes impossible.

FAQ

Is B200 on Azure worth the cost over H100? For trillion-parameter model training, B200's time-to-completion advantages reduce total hardware costs despite per-hour premiums. For smaller models (under 100B parameters), H100 delivers better cost-per-FLOP ratios.

How long does B200 deployment take on Azure? Sales qualification takes 1-2 weeks. Capacity provisioning takes an additional 1-4 weeks. Total lead time from first inquiry to GPU access ranges 2-6 weeks. Plan accordingly for time-sensitive projects.

Can I mix B200 and H100 in Azure training jobs? Azure instance families segregate GPU types. Single deployments cannot mix B200 and H100. Distributed training can federate across separate B200 and H100 clusters if loss synchronization overhead remains acceptable.

What's the difference between B200 and H100 for inference? B200's 192GB memory handles longer context windows than H100's 80GB. B200's 8 TB/s memory bandwidth supports higher request concurrency. For models under 70B parameters with short context, H100 suffices. For long-context or very large models, B200 becomes necessary.

Are B200 spot instances available on Azure? No. B200 remains a reserved-capacity-only offering as of March 2026. Spot instances may appear as supply stabilizes in 2027.

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