Provider Overview
Strengths & Best For
CoreWeave is a purpose-built GPU cloud offering H100 SXM5, H200, and A100 clusters with InfiniBand and NVLink interconnects for large-scale AI training and LLM fine-tuning. On-demand and reserved H100 instances are available across US East, US West, and EU regions, with some of the highest GPU density and lowest latency networking of any specialist cloud. A top choice for AI labs and enterprises running multi-node distributed training at scale.
- Highest GPU density
- InfiniBand networking
- Kubernetes-native
- Fast provisioning
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
Live GPU Pricing
Region Coverage
Popular Comparisons
CoreWeave — specialist provider
CoreWeave is a purpose-built GPU cloud offering H100 SXM5, H200, and A100 clusters with InfiniBand and NVLink interconnects for large-scale AI training and LLM fine-tuning. On-demand and reserved H100 instances are available across US East, US West, and EU regions, with some of the highest GPU density and lowest latency networking of any specialist cloud. A top choice for AI labs and enterprises running multi-node distributed training at scale.
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.
Billing model comparison
CoreWeave uses a On-demand, Reserved billing model with a minimum commitment of None. Modal uses Per-second serverless 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
CoreWeave is best suited for: Large-scale AI training, LLM fine-tuning, High-throughput inference. Its key strengths are highest gpu density, infiniband networking, kubernetes-native. 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. 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
CoreWeave offers Standard → Enterprise support across 3 regions (US-East, US-West, EU-West). Modal offers Community → Enterprise support across 2 regions (US-East, US-West). CoreWeave's broader region footprint gives it an advantage for latency-sensitive workloads or teams with data residency requirements in specific geographies.
Provider background: CoreWeave vs Modal
CoreWeave was founded in 2017 and is headquartered in Roseland, NJ. Modal was founded in 2021 and is headquartered in New York, NY. CoreWeave has 4 years more operational history than Modal, 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.