FluidStack vs Green AI Cloud: GPU Compute Price Comparison
Side-by-side comparison of GPU compute pricing, regions, billing models, and strengths for FluidStack and Green AI Cloud. 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
Green AI Cloud offers H100 and A100 GPU instances powered by 100% renewable energy across European data centers, targeting organizations that need ESG-compliant AI compute for LLM training, fine-tuning, and inference workloads. On-demand billing and a sustainability-first mission make it a responsible choice for enterprises with carbon reduction commitments. A strong option for EU-based AI teams that want verifiably green GPU cloud infrastructure without sacrificing performance.
- 100% renewable energy
- Carbon-neutral compute
- European presence
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.
Green AI Cloud — specialist provider
Green AI Cloud offers H100 and A100 GPU instances powered by 100% renewable energy across European data centers, targeting organizations that need ESG-compliant AI compute for LLM training, fine-tuning, and inference workloads. On-demand billing and a sustainability-first mission make it a responsible choice for enterprises with carbon reduction commitments. A strong option for EU-based AI teams that want verifiably green GPU cloud infrastructure without sacrificing performance.
Billing model comparison
FluidStack uses a On-demand, Spot, Reserved billing model with a minimum commitment of None. Green AI Cloud uses On-demand 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. Green AI Cloud is best suited for: Sustainability-focused teams, ESG-compliant AI, European workloads. Its key strengths are 100% renewable energy, carbon-neutral compute, european presence. 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). Green AI Cloud offers Standard support across 1 region (EU). 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 Green AI Cloud
FluidStack was founded in 2019 and is headquartered in London, UK. Green AI Cloud was founded in 2022 and is headquartered in Europe. FluidStack has 3 years more operational history than Green AI Cloud, 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.