96 GB GDDR7 · 1.8 TB/s · 8× SXM HGX nodes from 20+ vetted providers — ~30% less than hyperscale. Quotes in under 24 hours.
RTX Pro 6000 cloud pricing ranges from $1.80 to $3.20+ per GPU-hour depending on provider and contract type. Blackwell architecture with 96 GB GDDR7 enables inference on 70B+ models–$85/hr per node
| Provider | On-demand $/GPU-hr | RTX Pro 6000 availability | Notes |
|---|---|---|---|
| AWS | ~$3.90 – $10.60 | Wait / limited | 8-GPU nodes only. Egress fees extra. |
| Google Cloud | ~$3.72 (spot) | Preemptible | Spot only. Can be interrupted. |
| Microsoft Azure | ~$6.98 – $13.78 | Limited regions | Most expensive. SLA-backed. |
| CoreWeave | ~$3.50 – $5.00 | Available | Enterprise. Reserved pricing only. |
| Lambda Labs | ~$2.49 – $3.99 | Available | No egress fees. Dev-focused. |
GPUaaS.com — wholesale ↓ UP TO 30% LOWER | ~$2.2 – $2.9 | 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.
Train 70B–Production inference on 70B+ parameter models. 96 GB GDDR7 enables serving large models that previously required datacenter HBM GPUs, at a fraction of the cost.
Generative media workloads — image, video, and 3D generation. 5th gen Tensor Cores and 4th gen RT Cores deliver studio-grade performance for creative AI pipelines.— 40–80% more tokens/sec vs H100.
Full fine-tuning, LoRA, and QLoRA on models that exceed H100 memory. Larger batches, fewer gradient checkpointing hacks, faster convergence per dollar spent.
32k–Fine-tuning 7B–30B models and ML research. Blackwell architecture provides the compute density of datacenter GPUs with the accessibility and pricing of professional workstation hardware.
Pick the region for latency, compliance or sovereignty. We handle the matchmaking — you talk straight to the operator.
GPUaaS wholesale vs. cloud list price. Move the slider to your cluster size.
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Start simple — how many GPUs or nodes and what type — then add as much detail as you like. Inference or training. Model architecture. Precision. Virtualization type. Budgets and timelines.
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When we've found the perfect partner for your project, you'll get quotations for the GPU you need, usually within a few hours.
We'll smooth your ride through the provisioning process, and you can get on with your project.
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GPUaaS.com connects enterprises with vetted GPU providers for large-scale compute at up to 30% lower cost than hyperscalers.
