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Modal Documentation

Modal provides a serverless cloud for engineers and researchers who want to build compute-intensive applications without thinking about infrastructure.

Run generative AI models, large-scale batch workflows, job queues, and more, all faster than ever before.
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Guide

Everything you need to know to run code on Modal. Dive deep into all of our features and best practices.

Examples

Powerful applications built with Modal. Explore guided starting points for your use case.

Reference

Technical information about the Modal API. Quickly refer to basic descriptions of various programming functionalities.

Playground

Interactive tutorials to learn how to start using Modal. Run serverless cloud functions from your browser.

Featured Examples

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Deploy an OpenAI-compatible LLM service

Run large language models with a drop-in replacement for the OpenAI API.

Custom pet art from Flux with Hugging Face and Gradio

Fine-tune an image generation model on pictures of your pet.

Voice chat with LLMs

Build an interactive voice chat app.

Serve diffusion models

Serve Flux on Modal with a number of optimizations for blazingly fast inference.

Fold proteins with Chai-1

Predict molecular structures from sequences with SotA open source models.

Sandbox a LangGraph agent's code

Run an LLM coding agent that runs its own language models.

RAG Chat with PDFs

Use ColBERT-style, multimodal embeddings with a Vision-Language Model to answer questions about documents.

Fast podcast transcriptions

Build an end-to-end podcast transcription app that leverages dozens of containers for super-fast processing.

Build a protein folding dashboard

Serve a web UI for a protein model with ESM3, Molstar, and Gradio

Deploy a Hacker News Slackbot

Periodically post new Hacker News posts to Slack.

Retrieval-Augmented Generation (RAG) for Q&A

Build a question-answering web endpoint that can cite its sources.

Document OCR job queue

Use Modal as an infinitely scalable job queue that can service async tasks from a web app.

Parallel processing of Parquet files on S3

Analyze data from the Taxi and Limousine Commission of NYC in parallel.