Modal vs Latitude.sh: GPU Compute Price Comparison
Side-by-side comparison of GPU compute pricing, regions, billing models, and strengths for Modal and Latitude.sh. 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
Latitude.sh provides bare-metal H100, A100, and RTX 4090 servers with no virtualization overhead across US, EU, and Brazil data centers, delivering dedicated hardware performance for latency-sensitive AI inference and distributed training. On-demand and reserved billing options are available with predictable pricing and no noisy-neighbor effects. A top choice for teams that need bare-metal GPU performance with global reach including LATAM coverage.
- Bare-metal performance
- No virtualization overhead
- Brazil region
- Predictable pricing
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.
Latitude.sh — bare-metal provider
Latitude.sh provides bare-metal H100, A100, and RTX 4090 servers with no virtualization overhead across US, EU, and Brazil data centers, delivering dedicated hardware performance for latency-sensitive AI inference and distributed training. On-demand and reserved billing options are available with predictable pricing and no noisy-neighbor effects. A top choice for teams that need bare-metal GPU performance with global reach including LATAM coverage.
Billing model comparison
Modal uses a Per-second serverless billing model with a minimum commitment of None. Latitude.sh 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. Latitude.sh is best suited for: Performance-critical workloads, Latency-sensitive inference, LATAM teams. Its key strengths are bare-metal performance, no virtualization overhead, brazil region. 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). Latitude.sh offers Standard → Enterprise support across 3 regions (US-East, EU-West, BR-South). Latitude.sh'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 Latitude.sh
Modal was founded in 2021 and is headquartered in New York, NY. Latitude.sh was founded in 2020 and is headquartered in São Paulo, Brazil. Latitude.sh has 1 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.