Provider Overview
Strengths & Best For
Modal is a serverless GPU cloud that lets Python developers run H100, A100, and T4 workloads with a simple decorator-based API and zero infrastructure management — cold starts measured in seconds. Per-second billing means you only pay for actual compute time, making it highly cost-efficient for bursty AI inference, LLM serving, and batch ML jobs. The go-to on-demand GPU cloud for ML engineers who want to ship fast without touching DevOps.
- Zero infra management
- Instant cold starts
- Python-native API
- Per-second billing
Velokey provides H100, A100, and RTX GPU cloud instances with low-latency provisioning and competitive on-demand pricing for AI and ML workloads, making it easy to spin up GPU compute quickly for training runs and inference experiments. Fast provisioning and straightforward billing lower the barrier to entry for AI startups and developers who need quick access to professional NVIDIA hardware. A practical on-demand GPU cloud for teams that value speed of provisioning and transparent pricing.
- Fast provisioning
- Competitive pricing
- Low latency
Live GPU Pricing
Region Coverage
Popular Comparisons
Modal — specialist provider
Modal is a serverless GPU cloud that lets Python developers run H100, A100, and T4 workloads with a simple decorator-based API and zero infrastructure management — cold starts measured in seconds. Per-second billing means you only pay for actual compute time, making it highly cost-efficient for bursty AI inference, LLM serving, and batch ML jobs. The go-to on-demand GPU cloud for ML engineers who want to ship fast without touching DevOps.
Velokey — specialist provider
Velokey provides H100, A100, and RTX GPU cloud instances with low-latency provisioning and competitive on-demand pricing for AI and ML workloads, making it easy to spin up GPU compute quickly for training runs and inference experiments. Fast provisioning and straightforward billing lower the barrier to entry for AI startups and developers who need quick access to professional NVIDIA hardware. A practical on-demand GPU cloud for teams that value speed of provisioning and transparent pricing.
Billing model comparison
Modal uses a Per-second serverless billing model with a minimum commitment of None. Velokey uses On-demand 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
Modal is best suited for: ML engineers, Serverless inference, Rapid prototyping, Python-first teams. Its key strengths are zero infra management, instant cold starts, python-native api. Velokey is best suited for: Quick experiments, Inference workloads, AI startups. Its key strengths are fast provisioning, competitive pricing, low latency. 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
Modal offers Community → Enterprise support across 2 regions (US-East, US-West). Velokey offers Standard support across 1 region (US). Modal's broader region footprint gives it an advantage for latency-sensitive workloads or teams with data residency requirements in specific geographies.
Provider background: Modal vs Velokey
Modal was founded in 2021 and is headquartered in New York, NY. Velokey was founded in 2023 and is headquartered in United States. Modal has 2 years more operational history than Velokey, 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.