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ScalewayvsSpheron

Scaleway vs Spheron: Pricing, Specs, Strengths & Weaknesses

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

Overview

Attribute
Scaleway
Spheron
Provider type
Specialist
Marketplace
Founded
2015
2022
Headquarters
Paris, France
United States
Billing model
On-demand, Reserved
On-demand (per-minute), Spot, Reserved
Min commitment
None
20-minute minimum runtime
Support tier
Basic → Enterprise
Community → Standard
Regions
3 regions
3 regions

Strengths & Best For

Scaleway

Scaleway is a French cloud provider offering H100 SXM and PCIe GPU instances alongside a full cloud platform — managed Kubernetes (Kapsule), object storage, managed databases, serverless functions, and private networking — all within EU data centers. In 2025–2026 Scaleway launched H100 PCIe instances at competitive EU pricing, expanded its managed Kubernetes GPU node pools to support multi-GPU workloads natively, and introduced a GPU-optimized bare-metal tier for latency-sensitive inference. As a subsidiary of Iliad Group (one of France's largest telecoms), Scaleway has the financial backing and network infrastructure to compete seriously in the EU GPU market. A strong choice for European teams that want GPU compute and a full cloud stack from a single EU-sovereign provider, avoiding US hyperscaler data residency concerns entirely.

Strengths
  • Full EU-sovereign cloud stack — GPU, Kubernetes, storage, databases in one platform
  • H100 SXM and PCIe at competitive European pricing
  • Managed Kubernetes with native GPU node pool support
  • Backed by Iliad Group — strong financial stability and network infrastructure
  • GPU-optimized bare-metal tier for low-latency inference
Weaknesses
  • GPU catalog narrower than AWS, GCP, or Azure
  • Primarily EU regions — limited options for US or APAC deployments
  • ML ecosystem tooling less mature than hyperscalers
Best For
EU-based teams needing GPU + full cloud stack from one EU-sovereign providerOrganizations avoiding US hyperscaler data residency concernsTeams running GPU training alongside managed Kubernetes workloadsFrench and European enterprises with strict data sovereignty requirements
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Spheron

Spheron is a GPU marketplace sourcing from certified data center partners globally. GPU catalog: B300 Blackwell, B200 Blackwell, H200, H100, MI300X, GH200, A100, RTX PRO 6000, RTX 5090, L40S, RTX 4090 — on-demand and spot. GB200 and GB300 available to reserve. NVIDIA R100 Rubin (288 GB HBM4) pre-order. Per-minute billing, 20-minute minimum. Accepts USDT/USDC.

Strengths
  • B300, H100, RTX 4090 — competitive live pricing
  • Spot pricing available on H200, H100, A100
  • MI300X — AMD high-VRAM option
  • NVIDIA R100 Rubin pre-order available
  • Per-minute billing, 20-minute minimum, no contracts
  • Accepts USDT and USDC crypto payments
Weaknesses
  • Marketplace model — hardware consistency varies by partner
  • 20-minute minimum runtime (not per-second)
  • No enterprise SLAs
Best For
Cost-sensitive AI workloads needing multi-provider flexibilityTeams wanting vetted marketplace GPU accessSpot-tolerant batch training and inferenceCrypto-native teams
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Live GPU Pricing

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Region Coverage

Scaleway — 3 regions
EU-West (Paris)EU-West (Amsterdam)EU-Central (Warsaw)
Spheron — 3 regions
USEUAPAC

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Provider pages

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Key differences

Scaleway

European GPU cloud — H100, managed Kubernetes, and full cloud stack with EU sovereignty

Spheron

B300, H100, B200, H200 — per-minute billing, 20-min minimum

AttributeScalewaySpheron
Provider typespecialistmarketplace
Billing modelOn-demand, ReservedOn-demand (per-minute), Spot, Reserved
Min commitmentNone20-minute minimum runtime
Regions3 (EU-West (Paris), EU-West (Amsterdam), EU-Central (Warsaw))3 (US, EU, APAC)
Support tierBasic → EnterpriseCommunity → Standard
Best forEU-based teams needing GPU + full cloud stack from one EU-sovereign provider, Organizations avoiding US hyperscaler data residency concernsCost-sensitive AI workloads needing multi-provider flexibility, Teams wanting vetted marketplace GPU access
Founded / HQ2015 · Paris, France2022 · United States