24 GB GDDR6X · 1.01 TB/s · 8× SXM HGX nodes from 20+ vetted providers — ~30% less than hyperscale. Quotes in under 24 hours.
RTX 4090 cloud pricing ranges from $0.60 to $1.00+ per GPU-hour depending on provider and contract type. The most cost-effective GPU for small model inference and ML development–$85/hr per node
| Provider | On-demand $/GPU-hr | RTX 4090 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–Inference for 7B–13B parameter models at the lowest price point. 24 GB GDDR6X handles Llama 2 7B, Mistral 7B, and similar models efficiently for production serving.
ML development and experimentation. RTX 4090 provides datacenter-class performance for prototyping, testing, and iteration at consumer 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–Cost-sensitive production inference and fine-tuning small models. Ideal for startups and research labs that need GPU compute without datacenter GPU budgets.
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.
