Modal is a serverless platform designed for AI and data teams, enabling them to execute CPU, GPU, and data-intensive computations at scale. Key features include:
- Sub-second cold starts: Quickly launch and scale containers.
- Instant autoscaling: Automatically adjust resources based on workload demands.
- Programmable infrastructure: Define infrastructure in code, eliminating YAML or config files.
- Elastic GPU scaling: Access thousands of GPUs across clouds without quotas or reservations.
- Unified observability: Integrated logging and full visibility into functions, containers, and workloads.
Modal supports various use cases, including:
- Inference: Deploy and scale inference for LLMs, audio, and image/video generation.
- Training: Fine-tune open-source models on single or multi-node clusters.
- Sandboxes: Programmatically scale secure, ephemeral environments for running untrusted code.
- Batch processing: Scale to thousands of containers for on-demand batch workloads.
- Notebooks: Collaborate on code and data in real-time with shareable notebooks.
