Modal vs Cirrascale: GPU Compute Price Comparison
Side-by-side comparison of GPU compute pricing, regions, billing models, and strengths for Modal and Cirrascale. Updated July 2026.
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
Cirrascale Cloud Services provides enterprise-grade AI infrastructure featuring H100 NVL, H100 SXM5, and H200 GPU clusters with InfiniBand networking for high-throughput distributed LLM training and large-scale AI workloads. Dedicated cluster deployments and reserved configurations give enterprises full control over their GPU infrastructure without shared-tenancy concerns. A specialist provider for AI labs and enterprises that need dedicated H100 or H200 cluster capacity at scale.
- H100/H200 cluster focus
- InfiniBand networking
- Dedicated deployments
- Enterprise SLAs
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.
Cirrascale — specialist provider
Cirrascale Cloud Services provides enterprise-grade AI infrastructure featuring H100 NVL, H100 SXM5, and H200 GPU clusters with InfiniBand networking for high-throughput distributed LLM training and large-scale AI workloads. Dedicated cluster deployments and reserved configurations give enterprises full control over their GPU infrastructure without shared-tenancy concerns. A specialist provider for AI labs and enterprises that need dedicated H100 or H200 cluster capacity at scale.
Billing model comparison
Modal uses a Per-second serverless billing model with a minimum commitment of None. Cirrascale uses On-demand, Reserved 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. Cirrascale is best suited for: Large-scale AI training, Enterprise LLM workloads, Dedicated cluster users. Its key strengths are h100/h200 cluster focus, infiniband networking, dedicated deployments. 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). Cirrascale offers Standard → Enterprise 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 Cirrascale
Modal was founded in 2021 and is headquartered in New York, NY. Cirrascale was founded in 2009 and is headquartered in San Diego, CA. Cirrascale has 12 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.