Modal

What is Modal?

Modal is a high-performance serverless platform designed for AI and data teams, enabling you to bring your own code and run CPU, GPU, and data-intensive compute at scale. Built from the ground up for heavy AI workloads, Modal offers super-fast autoscaling and containers that boot instantly, routing workloads across clouds and regions in real time. With Modal, you can get the GPUs you need in seconds without commitments or capacity planning, and scale to zero between requests while bursting to handle demand.

Key features include composable primitives that specify everything from logic to hardware in one place, integrated logging and full visibility into every function, sandbox, and container, and observability tools to build robust, production-ready applications. Modal supports a wide range of use cases, including deploying and scaling inference for LLMs, audio, image/video generation, fine-tuning open-source models on single or multi-node clusters, and programmatically scaling secure, ephemeral environments for running untrusted code.

Technical highlights include sub-10ms overhead latency from anywhere with globally distributed compute, out-of-the-box support for token streaming, WebRTC, and WebSocket, and access to up to 128 B200s with 3200 Gbps Infiniband networking, gang-scheduled with a single line of code. Modal handles everything from single-GPU fine-tuning to parallel hyperparameter sweeps to multi-node runs in a single code file, supporting any framework and any hardware configuration. Whether you need to run evals, embeddings, re-ranking, or dataset generation at scale, Modal provides thousands of GPUs fully parallel with no job orchestration to manage. From the proxy layer to the GPU scheduler, every part of Modal's stack is optimized for how inference workloads actually behave, making it the ideal platform for AI and data teams seeking high-performance, serverless infrastructure.

Use Cases

Key Features

serverless platform instant container boot super fast autoscaling GPU access on demand composable primitives integrated logging observability tools global compute distribution token streaming support scale to zero

Who is it for?

AI teams, data teams, ML engineers, data scientists, DevOps engineers, platform teams, researchers

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