192 GB HBM3e/GPU · NVLink 5.0 · 72 B200 GPUs per NVL72 rack from 20+ vetted providers — ~30% less than hyperscale. Quotes in under 24 hours.
GB200 NVL pricing ranges from $10.00 to $18.00+ per GPU-hour depending on provider and contract type. Hyperscaler NVL rack rates start at $18.00+/hr per GPU on-demand. GPUaaS.com wholesale pricing saves up to 30%. Pricing data last reviewed: May 2026.–$85/hr per node
| Provider | On-demand $/GPU-hr | GB200 NVL availability | Notes |
|---|---|---|---|
| AWS | ~$14.24 – $18.00+ | Contract only | 8-GPU nodes only. Egress fees extra. |
| Google Cloud | ~$12.00+ | Contract only | NVL72 racks. Contract required. |
| Microsoft Azure | ~$16.00 – $20.00+ | Contract only | Most expensive. SLA-backed. |
| CoreWeave | ~$10.00 – $14.00 | Available | Enterprise. Reserved pricing only. |
| Lambda Labs | ~$8.50 – $12.00 | Available | No egress fees. Dev-focused. |
GPUaaS.com — wholesale ↓ UP TO 30% LOWER | ~$7.20 – $10.00 | In stock | Free matchmaking. Flexible commitment. |
Prices indicative as of May 2026. Hyperscaler rates from public pricing pages. Wholesale rates via GPUaaS.com vary by configuration and commitment term.
Trillion-parameter model training across 72 GPUs with unified NVLink 5 fabric. The NVL72 rack architecture connects 72 Blackwell GPUs over NVLink 5.0 as a single unified memory domain — no multi-node communication overhead.
Real-time inference on the largest production models. GB200 delivers the highest throughput per rack of any available GPU system for serving 200B+ parameter models at production scale.GB200 NVL72 delivers ~30x H100 throughput per NVIDIA.
Full fine-tuning, LoRA, and QLoRA on models that exceed H100 memory. Larger batches, fewer gradient checkpointing hacks, faster convergence per dollar spent.
32k–Agentic AI and multi-modal foundation models. The unified memory architecture handles mixture-of-experts, multi-modal, and chain-of-thought workloads without memory fragmentation across nodes.
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GPUaaS.com connects enterprises with vetted GPU providers for large-scale compute at up to 30% lower cost than hyperscalers.
