Modal

Modal provides a serverless environment for running Python functions and applications with on‑demand CPU, GPU, and data‑intensive compute. Users define their code and hardware requirements directly in Python, eliminating separate configuration files, and the platform launches containers in seconds with sub‑second cold starts. Elastic scaling lets workloads expand to thousands of GPUs across multiple clouds and shrink back to zero when idle, while a unified observability layer offers integrated logging and visibility for every function and container.

The service targets AI and data teams that need to deploy inference, training, batch processing, or interactive notebooks without managing underlying infrastructure. It supports a range of workloads such as large language model inference, speech transcription, image and video generation, and fine‑tuning of open‑source models, offering secure, ephemeral sandboxes for untrusted code and collaborative, for real‑time development.

Modal’s architecture includes a globally distributed storage layer optimized for high‑throughput, low‑latency data access, and first‑party integrations for cloud storage, MLOps tools, and telemetry services. The platform’s multi‑cloud capacity pool provides intelligent scheduling of compute resources, enabling developers to focus on application logic while the system handles performance, scaling, and resource provisioning.