Provider Overview
Strengths & Best For
Verda (formerly DataCrunch) is a Finnish GPU cloud offering 13 GPU types including H100, A100, RTX A6000, and V100 instances with competitive on-demand pricing and enterprise-grade infrastructure for AI and ML workloads. On-demand and reserved billing options are available from Finnish data centers, providing EU data residency for Nordic and European teams with GDPR requirements. A reliable European GPU cloud for cost-sensitive AI training and inference with broad hardware variety.
- Finnish infrastructure
- Competitive V100/A100 pricing
- 13 GPU types
- Enterprise-grade
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
Verda — specialist provider
Verda (formerly DataCrunch) is a Finnish GPU cloud offering 13 GPU types including H100, A100, RTX A6000, and V100 instances with competitive on-demand pricing and enterprise-grade infrastructure for AI and ML workloads. On-demand and reserved billing options are available from Finnish data centers, providing EU data residency for Nordic and European teams with GDPR requirements. A reliable European GPU cloud for cost-sensitive AI training and inference with broad hardware variety.
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
Verda uses a On-demand, Reserved 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
Verda is best suited for: EU AI teams, Cost-sensitive training, Nordic data residency. Its key strengths are finnish infrastructure, competitive v100/a100 pricing, 13 gpu types. 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
Verda offers Standard → Enterprise support across 2 regions (EU-North, EU-West). Beam offers Standard support across 1 region (US). Verda's broader region footprint gives it an advantage for latency-sensitive workloads or teams with data residency requirements in specific geographies.
Provider background: Verda vs Beam
Verda was founded in 2020 and is headquartered in Helsinki, Finland. Beam was founded in 2022 and is headquartered in New York, NY. Verda has 2 years more operational history than Beam, 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.