Thalassa Cloud vs Beam: GPU Compute Price Comparison
Side-by-side comparison of GPU compute pricing, regions, billing models, and strengths for Thalassa Cloud and Beam. Updated July 2026.
Provider Overview
Strengths & Best For
Thalassa Cloud is a European GPU cloud offering H100 and A100 instances from Mediterranean data centers with competitive on-demand pricing and GDPR-compliant EU data residency for AI training and inference workloads. Flexible billing and European infrastructure make it accessible for Southern European AI teams that need local GPU compute without routing data through Northern European or US providers. A cost-effective European GPU cloud for teams in Greece and the broader Mediterranean region.
- European presence
- Competitive pricing
- GDPR compliant
Beam is a serverless GPU platform that lets developers deploy AI models and run H100, A100, and T4 compute jobs with automatic scaling and per-second pay-per-use billing — no infrastructure management required. A Python-native SDK and fast cold starts make it easy to build and ship LLM inference APIs, batch ML pipelines, and AI model serving endpoints quickly. A strong choice for Python-first teams that want serverless GPU infrastructure with predictable, usage-based pricing.
- Serverless model
- Auto-scaling
- Simple SDK
- Fast cold starts
Live GPU Pricing
Region Coverage
Popular Comparisons
Thalassa Cloud — specialist provider
Thalassa Cloud is a European GPU cloud offering H100 and A100 instances from Mediterranean data centers with competitive on-demand pricing and GDPR-compliant EU data residency for AI training and inference workloads. Flexible billing and European infrastructure make it accessible for Southern European AI teams that need local GPU compute without routing data through Northern European or US providers. A cost-effective European GPU cloud for teams in Greece and the broader Mediterranean region.
Beam — specialist provider
Beam is a serverless GPU platform that lets developers deploy AI models and run H100, A100, and T4 compute jobs with automatic scaling and per-second pay-per-use billing — no infrastructure management required. A Python-native SDK and fast cold starts make it easy to build and ship LLM inference APIs, batch ML pipelines, and AI model serving endpoints quickly. A strong choice for Python-first teams that want serverless GPU infrastructure with predictable, usage-based pricing.
Billing model comparison
Thalassa Cloud uses a On-demand billing model with a minimum commitment of None. Beam uses Per-second usage 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
Thalassa Cloud is best suited for: European AI teams, Cost-sensitive workloads, GDPR compliance. Its key strengths are european presence, competitive pricing, gdpr compliant. Beam is best suited for: Serverless AI inference, Batch processing, Python-first teams. Its key strengths are serverless model, auto-scaling, simple sdk. 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
Thalassa Cloud offers Standard support across 2 regions (GR, EU). Beam offers Standard support across 1 region (US). Thalassa Cloud's broader region footprint gives it an advantage for latency-sensitive workloads or teams with data residency requirements in specific geographies.
Provider background: Thalassa Cloud vs Beam
Thalassa Cloud was founded in 2022 and is headquartered in Greece. Beam was founded in 2022 and is headquartered in New York, NY. Both providers were founded in the same year — evaluate them on current pricing, region coverage, and support tier rather than operational history. 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.