modal-serverless-gpu
Modal Serverless GPU
Comprehensive guide to running ML workloads on Modal's serverless GPU cloud platform.
When to use Modal
Use Modal when:
- Running GPU-intensive ML workloads without managing infrastructure
- Deploying ML models as auto-scaling APIs
- Running batch processing jobs (training, inference, data processing)
- Need pay-per-second GPU pricing without idle costs
- Prototyping ML applications quickly
- Running scheduled jobs (cron-like workloads)
Key features:
- Serverless GPUs: T4, L4, A10G, L40S, A100, H100, H200, B200 on-demand
- Python-native: Define infrastructure in Python code, no YAML
- Auto-scaling: Scale to zero, scale to 100+ GPUs instantly
- Sub-second cold starts: Rust-based infrastructure for fast container launches
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