80 GB HBM2e · 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. AWS on-demand A100 rates start at $3.67/hr (p4d.24xlarge). GPUaaS.com wholesale pricing saves up to 30%. Pricing data last reviewed: May 2026.–$85/hr per node
| Provider | On-demand $/GPU-hr | A100 availability | Notes |
|---|---|---|---|
| AWS | ~$3.40 – $3.67 | On-demand | 8-GPU nodes only. Egress fees extra. |
| Google Cloud | ~$2.48 | On-demand | Widely available |
| Microsoft Azure | ~$3.00 – $3.40 | Multiple regions | Most expensive. SLA-backed. |
| CoreWeave | ~$1.64 – $2.06 | Available | Enterprise. Reserved pricing only. |
| Lambda Labs | ~$1.29 – $1.49 | Available | No egress fees. Dev-focused. |
GPUaaS.com , wholesale ↓ UP TO 30% LOWER | ~$1.10 – $1.27 | In stock | No platform fee. 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 models up to 70B parameters on multi-node A100 clusters. 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.
Full fine-tuning on models up to 70B parameters. 80 GB HBM2e per GPU with NVLink 3.0 for efficient multi-GPU parallelism.
Serve 32k–128k context windows for RAG pipelines. 80 GB HBM2e supports retrieval-augmented generation 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.
Tell us the essentials. We'll line up real quotes from our vetted wholesale partners, and you contract directly with the operator.
No need to crawl through GPU marketplaces. The world's best wholesale GPU providers are right here.
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.
Get the best GPU deals →We do the legwork, and find providers with capacity that fits your need. Our network includes:
When we've found the perfect match for your project, you'll get a quotation 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.
