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MODAL
High-performance serverless AI infrastructure developers love
Apache-2.0
ABOUT
AI teams waste significant time and money managing GPU infrastructure — provisioning instances, configuring Docker containers, handling autoscaling, and paying for idle compute. Modal eliminates all of that by providing a serverless platform where you write Python functions, annotate them with @app.function, and Modal handles deployment, scaling, and billing down to the second. Cold starts in under a second and automatic scale-to-zero mean you never pay for idle GPUs.
INSTALL
pip install modalINTEGRATION GUIDE
1. Deploy and scale LLM inference endpoints with automatic scale-to-zero when not in use
2. Run ephemeral GPU workloads like model fine-tuning or batch inference without provisioning servers
3. Execute massively parallel batch inference jobs across thousands of containers simultaneously
4. Serve diffusion models and image/video generation with request-based autoscaling
5. Launch ephemeral cloud notebooks and sandboxes for collaborative ML development
TAGS
serverlessgpuinferencetrainingbatch-processingcloudinfrastructurepythonautoscaling