48 GB GDDR6 · 960 GB/s · 8× SXM HGX nodes from 20+ vetted providers — ~30% less than hyperscale. Quotes in under 24 hours.
RTX 6000 Ada cloud pricing ranges from $0.85 to $1.40+ per GPU-hour depending on provider and contract type. The Ada offers a mid-market sweet spot for inference and visual AI workloads–$85/hr per node
| Provider | On-demand $/GPU-hr | RTX 6000 Ada 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 for 7B–30B models. 48 GB GDDR6 ECC memory handles concurrent model serving for visual AI, NLP, and multi-modal workloads at excellent cost efficiency.
Visual AI and computer vision workloads. Ada Lovelace architecture with 4th gen RT Cores excels at real-time rendering, 3D generation, and image processing 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 mid-size models at a fraction of datacenter GPU cost. The RTX 6000 Ada bridges the gap between consumer GPUs and enterprise HBM hardware for teams scaling their ML operations.
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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GPUaaS.com connects enterprises with vetted GPU providers for large-scale compute at up to 30% lower cost than hyperscalers.
