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GPUaaS vs Hyperstack: Pricing, Specs, Strengths & Weaknesses

Side-by-side comparison of GPU compute pricing, regions, billing models, and strengths for GPUaaS and Hyperstack. Rates sourced from public APIs — verify current availability and billing terms before purchasing.

Overview

Provider type
Specialist
Specialist
Founded
2022
2022
Headquarters
Europe
London, UK
Billing model
On-demand
On-demand (per-minute), Reserved, Spot VMs
Min commitment
None
None
Support tier
Standard
Standard → Enterprise
Regions
1 regions
3 regions

Strengths & Best For

GPUaaS

GPUaaS delivers H100 and A100 GPU compute as a fully managed service, enabling European AI teams to access high-performance GPU infrastructure without any infrastructure overhead or operational complexity. On-demand billing and a managed service model make it easy to scale AI training and inference workloads without dedicated DevOps resources. A strong choice for European AI teams that want managed GPU-as-a-service with EU data residency and minimal operational burden.

Strengths
  • Managed service
  • Simple onboarding
  • European presence
Weaknesses
  • Small provider — limited GPU catalog
  • Fewer regions than larger providers
  • Less mature ecosystem vs CoreWeave
Best For
Teams avoiding infrastructureEuropean AI workloadsManaged inference
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GPUaaS Rating

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Hyperstack

Hyperstack (by NexGen Cloud) is a full-stack AI cloud offering NVIDIA GB200 NVL72, GB300 NVL72, HGX B200, HGX B300, H200 SXM, H100 SXM, H100 NVLink, H100 PCIe, A100 SXM, A100, L40, RTX A6000, RTX A4000, and RTX Pro 6000 SE instances with per-minute billing. Reservation and spot VMs available. 100% renewable energy. Managed Kubernetes, object storage, Terraform, Go/Python SDKs, LLM Inference Toolkit.

Strengths
  • B300, B200, H200 — competitive Blackwell and Hopper pricing
  • A4000 — cheapest enterprise GPU for light workloads
  • Per-minute billing — pay only for what you use
  • 100% renewable energy across all data centers
  • Wide GPU catalog: 13 SKUs from A4000 to GB300 NVL72
  • Managed Kubernetes, Terraform, Go/Python SDKs, LLM Inference Toolkit
Weaknesses
  • Smaller provider — limited scale vs CoreWeave or hyperscalers
  • Fewer regions than major cloud providers
  • B300 on-demand not yet available (reserved private clusters only as of Sept 2026)
Best For
Enterprise AI teams wanting latest Blackwell hardwareEU/NA teams needing renewable-energy GPU computeTeams wanting managed Kubernetes with GPU VMsCost-sensitive teams using reservation discounts
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Key differences

GPUaaS

GPU as a Service

Hyperstack

B300, B200, H200, H100 — per-minute billing, 100% renewable energy

AttributeGPUaaSHyperstack
Provider typespecialistspecialist
Billing modelOn-demandOn-demand (per-minute), Reserved, Spot VMs
Min commitmentNoneNone
Regions1 (EU)3 (EU-West, EU-Central, US-East)
Support tierStandardStandard → Enterprise
Best forTeams avoiding infrastructure, European AI workloadsEnterprise AI teams wanting latest Blackwell hardware, EU/NA teams needing renewable-energy GPU compute
Founded / HQ2022 · Europe2022 · London, UK