Exoscale vs Runcrate: Pricing, Specs, Strengths & Weaknesses

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

Overview

Attribute

Exoscale

Runcrate

Provider type

Specialist

Founded

2011

2024

Headquarters

Lausanne, Switzerland

Billing model

On-demand (per-minute)

Per-second on-demand

Min commitment

None

Support tier

Basic → Enterprise

Standard

Regions

2 regions

3 regions

Strengths & Best For

Exoscale

Exoscale is a Swiss cloud provider offering A100 and L40S GPU instances with strict Swiss privacy law and GDPR compliance, making it a strong on-demand GPU cloud option for regulated industries requiring Swiss data sovereignty. Per-minute billing with no minimum commitment provides cost-efficient access to GPU compute for AI inference and training workloads in Swiss and EU data centers. A strong choice for financial services, healthcare, and other regulated sectors that need GPU compute within Swiss jurisdiction.

Strengths

Swiss data sovereignty
GDPR + Swiss privacy law
Regulated industry focus
EU/CH data centers

Weaknesses

Very small GPU catalog
Limited to European regions
Not ML-focused — limited AI tooling

Best For

Swiss/EU regulated workloadsGDPR-critical AIFinancial services AI

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Runcrate

Runcrate is a GPU cloud founded in 2024 offering on-demand instances with per-second billing and no minimum commitment — the meter stops the moment you stop the instance. The platform aggregates GPU capacity across eight global regions spanning North America, Europe, and Asia, covering 14 GPU models from RTX A6000 and A100 through H100 and RTX PRO 6000. Full root access via SSH, Docker support, and custom images are included on every instance. An OpenAI-compatible inference API serves open-source models billed per token, and reserved or dedicated capacity is available for teams with monthly volume commitments.

Strengths

Per-second billing — no minimum commitment
OpenAI-compatible inference API
14 GPU models including H100 and RTX PRO 6000
8 global regions across NA, EU, and Asia
Full root SSH access with Docker and custom images
Reserved and dedicated capacity available

Weaknesses

No enterprise SLAs or uptime guarantees
Smaller provider — limited scale vs hyperscalers
No managed platform or containers

Best For

Teams needing flexible per-second GPU billingOpen-source model inference via APIMulti-region GPU workloadsCost-sensitive on-demand training and fine-tuning

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