FluidStack vs Cirrascale: GPU Compute Price Comparison
Side-by-side comparison of GPU compute pricing, regions, billing models, and strengths for FluidStack and Cirrascale. Updated July 2026.
Provider Overview
Strengths & Best For
FluidStack aggregates H100, A100, and consumer GPU capacity from data centers across the US and EU, offering competitive bulk pricing and flexible contracts for AI training and LLM fine-tuning workloads. Spot GPU rental is available alongside on-demand and reserved options, making it a cost-effective choice for teams with variable compute needs. A strong pick for EU-based teams wanting broad GPU availability without committing to a single provider.
- Competitive pricing
- EU/US coverage
- Spot availability
- Flexible contracts
Cirrascale Cloud Services provides enterprise-grade AI infrastructure featuring H100 NVL, H100 SXM5, and H200 GPU clusters with InfiniBand networking for high-throughput distributed LLM training and large-scale AI workloads. Dedicated cluster deployments and reserved configurations give enterprises full control over their GPU infrastructure without shared-tenancy concerns. A specialist provider for AI labs and enterprises that need dedicated H100 or H200 cluster capacity at scale.
- H100/H200 cluster focus
- InfiniBand networking
- Dedicated deployments
- Enterprise SLAs
Live GPU Pricing
Region Coverage
Popular Comparisons
FluidStack — specialist provider
FluidStack aggregates H100, A100, and consumer GPU capacity from data centers across the US and EU, offering competitive bulk pricing and flexible contracts for AI training and LLM fine-tuning workloads. Spot GPU rental is available alongside on-demand and reserved options, making it a cost-effective choice for teams with variable compute needs. A strong pick for EU-based teams wanting broad GPU availability without committing to a single provider.
Cirrascale — specialist provider
Cirrascale Cloud Services provides enterprise-grade AI infrastructure featuring H100 NVL, H100 SXM5, and H200 GPU clusters with InfiniBand networking for high-throughput distributed LLM training and large-scale AI workloads. Dedicated cluster deployments and reserved configurations give enterprises full control over their GPU infrastructure without shared-tenancy concerns. A specialist provider for AI labs and enterprises that need dedicated H100 or H200 cluster capacity at scale.
Billing model comparison
FluidStack uses a On-demand, Spot, Reserved billing model with a minimum commitment of None. Cirrascale uses On-demand, Reserved billing with a None minimum. Both providers offer flexible billing options — compare the live pricing table above to find the best rate for your specific GPU model and workload duration.
Which workloads each provider suits best
FluidStack is best suited for: Cost-sensitive training, EU-based teams, Flexible workloads. Its key strengths are competitive pricing, eu/us coverage, spot availability. Cirrascale is best suited for: Large-scale AI training, Enterprise LLM workloads, Dedicated cluster users. Its key strengths are h100/h200 cluster focus, infiniband networking, dedicated deployments. Both providers target similar workload profiles — the live pricing table above is the most reliable way to determine which offers better value for your specific GPU model and region requirements.
Support tiers and region coverage
FluidStack offers Standard → Enterprise support across 4 regions (US-East, US-West, EU-West and 1 more). Cirrascale offers Standard → Enterprise support across 1 region (US). FluidStack's broader region footprint gives it an advantage for latency-sensitive workloads or teams with data residency requirements in specific geographies.
Provider background: FluidStack vs Cirrascale
FluidStack was founded in 2019 and is headquartered in London, UK. Cirrascale was founded in 2009 and is headquartered in San Diego, CA. Cirrascale has 10 years more operational history than FluidStack, which may matter for teams evaluating provider stability and long-term contract risk. Use the live pricing table above to compare current on-demand and spot rates for specific GPU models, and the region map to verify coverage in your target geography.