48 GB GDDR6 · 864 GB/s · 8× SXM HGX nodes from 20+ vetted providers — ~30% less than hyperscale. Quotes in under 24 hours.
L40S cloud pricing ranges from $0.95 to $1.60+ per GPU-hour depending on provider and contract type. L40S delivers the best cost-per-token for inference workloads at $15–$85/hr per node
| Provider | On-demand $/GPU-hr | L40S 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–Multi-modal inference across image, video, and text workloads. 48 GB GDDR6 handles concurrent model serving for production AI applications at the lowest cost per token.
Fine-tune 7B–30B parameter models efficiently. Ada Lovelace architecture with 4th gen Tensor Cores delivers strong training throughput without datacenter GPU pricing.— 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–Image and video generation at scale. Stable Diffusion, SDXL, and video AI pipelines run natively on L40S with full CUDA and Tensor Core support.
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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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 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.
