Provider Overview
Strengths & Best For
Koyeb is a serverless GPU platform for deploying AI inference endpoints without managing infrastructure, with automatic scaling to zero and pay-per-use billing across EU and US regions. Git-based deployment and a simple dashboard make it easy to ship LLM inference APIs and AI model serving endpoints in minutes. A strong choice for teams that want zero-ops GPU inference with automatic scaling and no idle compute costs.
- Serverless — no infrastructure management
- Automatic scaling to zero
- EU and US regions
- Git-based deployment
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
Koyeb — specialist provider
Koyeb is a serverless GPU platform for deploying AI inference endpoints without managing infrastructure, with automatic scaling to zero and pay-per-use billing across EU and US regions. Git-based deployment and a simple dashboard make it easy to ship LLM inference APIs and AI model serving endpoints in minutes. A strong choice for teams that want zero-ops GPU inference with automatic scaling and no idle compute costs.
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
Koyeb uses a Pay-per-use (serverless) 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
Koyeb is best suited for: Inference API deployments, Serverless AI apps, Teams wanting zero-ops GPU. Its key strengths are serverless — no infrastructure management, automatic scaling to zero, eu and us regions. 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
Koyeb offers Community → Standard support across 2 regions (EU, US). Beam offers Standard support across 1 region (US). Koyeb's broader region footprint gives it an advantage for latency-sensitive workloads or teams with data residency requirements in specific geographies.
Provider background: Koyeb vs Beam
Koyeb was founded in 2021 and is headquartered in Paris, France. Beam was founded in 2022 and is headquartered in New York, NY. Koyeb has 1 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.