FluidStack vs Gcore: GPU Compute Price Comparison
Side-by-side comparison of GPU compute pricing, regions, billing models, and strengths for FluidStack and Gcore. 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
Gcore is a global GPU cloud and CDN provider offering H100, A100, L40S, and L4 instances across 40+ points of presence worldwide, with ultra-low latency networking and built-in DDoS protection for edge AI inference workloads. On-demand and reserved billing options are available, making it a versatile GPU cloud for teams that need both compute and network performance at a global scale. A top choice for latency-sensitive AI inference applications that need to serve users across multiple continents.
- 40+ global PoPs
- Ultra-low latency
- DDoS protection
- Edge AI inference
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.
Gcore — specialist provider
Gcore is a global GPU cloud and CDN provider offering H100, A100, L40S, and L4 instances across 40+ points of presence worldwide, with ultra-low latency networking and built-in DDoS protection for edge AI inference workloads. On-demand and reserved billing options are available, making it a versatile GPU cloud for teams that need both compute and network performance at a global scale. A top choice for latency-sensitive AI inference applications that need to serve users across multiple continents.
Billing model comparison
FluidStack uses a On-demand, Spot, Reserved billing model with a minimum commitment of None. Gcore 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. Gcore is best suited for: Global inference deployment, Latency-sensitive AI apps, Teams needing edge compute. Its key strengths are 40+ global pops, ultra-low latency, ddos protection. 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). Gcore offers Standard → Enterprise support across 5 regions (EU, US, APAC and 2 more). Gcore'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 Gcore
FluidStack was founded in 2019 and is headquartered in London, UK. Gcore was founded in 2014 and is headquartered in Luxembourg. Gcore has 5 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.