80 GB HBM2e · 3.35 TB/s · 8× SXM HGX nodes from 20+ vetted providers — ~30% less than hyperscale. Quotes in under 24 hours.
A100 cloud pricing ranges from $1.20 to $3.50+ per GPU-hour depending on provider and contract type. Hyperscalers bundle A100 in 8-GPU HGX nodes at $30–$85/hr per node
| Provider | On-demand $/GPU-hr | A100 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–Train models up to 70B parameters on a single 8-GPU node. 80 GB per GPU enables full model sharding without cross-node overhead on most production LLM workloads.
Serve production LLM traffic at scale. 3.35 TB/s bandwidth sustains high token throughput for inference workloads up to 30B parameters.— 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–Large context windows fit comfortably in HBM2e. Vector search, retrieval pipelines, and scientific computing workloads run without memory-pressure fallbacks.
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.
