24 GB GDDR6 · 300 GB/s · PCIe Gen4 x16, single-slot, 72W. 4–8 cards per 2U server, from 20+ vetted providers, ~30% less than hyperscale. Quotes in under 24 hours.
L4 cloud pricing ranges from $0.35 to $0.70+ per GPU-hour depending on provider and contract type. AWS on-demand L4 rates start at $0.80/hr (g6e.xlarge). GPUaaS.com wholesale pricing saves up to 30%. Pricing data last reviewed: May 2026.–$85/hr per node
| Provider | On-demand $/GPU-hr | L4 availability | Notes |
|---|---|---|---|
| AWS | ~$0.70 – $0.80 | On-demand | 8-GPU nodes only. Egress fees extra. |
| Google Cloud | ~$0.55 | On-demand | Widely available |
| Microsoft Azure | ~$0.65 – $0.70 | Multiple regions | Most expensive. SLA-backed. |
| CoreWeave | ~$0.44 – $0.55 | Available | Enterprise. Reserved pricing only. |
| Lambda Labs | ~$0.40 – $0.50 | Available | No egress fees. Dev-focused. |
GPUaaS.com , wholesale ↓ UP TO 30% LOWER | ~$0.34 – $0.45 | 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 70B–Small model inference at the lowest price point. 24 GB GDDR6 handles 7B models and video AI workloads at under $0.50/hr per GPU.
Video AI and computer vision. Ada Lovelace architecture with hardware video encode/decode excels at real-time video processing and analytics at scale.
Deploy cost-efficient inference for 7B–13B quantized models. 24 GB GDDR6 at 72W per card enables high-density deployments.
32k–Cost-sensitive ML workloads and edge deployment preparation. L4 is ideal for teams running high volumes of small inference requests where cost per query is the primary metric.
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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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GPUaaS.com connects enterprises with vetted GPU providers for large-scale compute at up to 30% lower cost than hyperscalers.
