Together AI vs FluidStack: GPU Compute Price Comparison
Side-by-side comparison of GPU compute pricing, regions, billing models, and strengths for Together AI and FluidStack. Updated July 2026.
Provider Overview
Strengths & Best For
Together AI provides dedicated H100 and A100 GPU clusters with fast networking, purpose-built for open-source LLM training, fine-tuning, and high-throughput AI inference. On-demand GPU cloud access is paired with a developer-friendly platform that supports popular open models out of the box, reducing time-to-deployment for AI teams. A strong choice for startups and researchers who want managed GPU infrastructure without hyperscaler overhead.
- Inference-optimized
- Open-source LLM support
- Fast networking
- Developer-friendly
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
Live GPU Pricing
Region Coverage
Popular Comparisons
Together AI — specialist provider
Together AI provides dedicated H100 and A100 GPU clusters with fast networking, purpose-built for open-source LLM training, fine-tuning, and high-throughput AI inference. On-demand GPU cloud access is paired with a developer-friendly platform that supports popular open models out of the box, reducing time-to-deployment for AI teams. A strong choice for startups and researchers who want managed GPU infrastructure without hyperscaler overhead.
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.
Billing model comparison
Together AI uses a On-demand, Reserved billing model with a minimum commitment of None. FluidStack uses On-demand, Spot, 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
Together AI is best suited for: LLM inference, Fine-tuning open models, AI startups. Its key strengths are inference-optimized, open-source llm support, fast networking. FluidStack is best suited for: Cost-sensitive training, EU-based teams, Flexible workloads. Its key strengths are competitive pricing, eu/us coverage, spot availability. 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
Together AI offers Community → Enterprise support across 2 regions (US-East, US-West). FluidStack offers Standard → Enterprise support across 4 regions (US-East, US-West, EU-West and 1 more). FluidStack's broader region footprint gives it an advantage for latency-sensitive workloads or teams with data residency requirements in specific geographies.
Provider background: Together AI vs FluidStack
Together AI was founded in 2022 and is headquartered in San Francisco, CA. FluidStack was founded in 2019 and is headquartered in London, UK. FluidStack has 3 years more operational history than Together AI, 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.