Provider Overview
Strengths & Best For
Runcrate is a Berlin-based GPU cloud marketplace aggregating bare-metal and VM instances across 21 GPU types and 11 global regions, with some of the lowest starting prices for on-demand GPU rental available anywhere. The marketplace model gives teams access to H100, A100, and a wide range of other GPU SKUs through a single platform, with flexible spot and on-demand billing. A cost-effective option for EU-based teams needing broad GPU variety and multi-region flexibility.
- 21 GPU types
- 11 global regions
- Very competitive pricing
- Bare metal + VM options
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
Runcrate — marketplace provider
Runcrate is a Berlin-based GPU cloud marketplace aggregating bare-metal and VM instances across 21 GPU types and 11 global regions, with some of the lowest starting prices for on-demand GPU rental available anywhere. The marketplace model gives teams access to H100, A100, and a wide range of other GPU SKUs through a single platform, with flexible spot and on-demand billing. A cost-effective option for EU-based teams needing broad GPU variety and multi-region flexibility.
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
Runcrate uses a On-demand, Spot 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
Runcrate is best suited for: Cost-sensitive teams, Multi-region deployments, Wide GPU variety needs. Its key strengths are 21 gpu types, 11 global regions, very competitive pricing. Beam is best suited for: Serverless AI inference, Batch processing, Python-first teams. Its key strengths are serverless model, auto-scaling, simple sdk. Marketplace providers aggregate GPU supply from multiple sources, often offering the lowest spot rates but with more variable availability and less predictable performance compared to dedicated providers.
Support tiers and region coverage
Runcrate offers Community → Standard support across 4 regions (EU-Central, US, APAC and 1 more). Beam offers Standard support across 1 region (US). Runcrate's broader region footprint gives it an advantage for latency-sensitive workloads or teams with data residency requirements in specific geographies.
Provider background: Runcrate vs Beam
Runcrate was founded in 2024 and is headquartered in Berlin, Germany. Beam was founded in 2022 and is headquartered in New York, NY. Beam has 2 years more operational history than Runcrate, 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.