Modal: High-performance AI infrastructure

# Modal llms.txt > Modal is a platform for running Python code in the cloud with minimal > configuration, especially for serving AI models and high-performance batch > processing. It supports fast prototyping, serverless APIs, scheduled jobs, > GPU inference, distributed volumes, and sandboxes. Important notes: - Modal's primitives are embedded in Python and tailored for AI/GPU use cases, but they can be used for general-purpose cloud compute. - Modal is a serverless platform, meaning you are only billed for resources used and can spin up containers on demand in seconds. You can sign up for free at [https://modal.com] and get $30/month of credits. ## Guide - [Introduction](https://modal.com/docs/guide) - Custom container images - [Defining Images](https://modal.com/docs/guide/images.md) - [Using existing container images](https://modal.com/docs/guide/existing-images.md) - [Fast pull from registry](https://modal.com/docs/guide/fast-pull-from-registry.md) - GPUs and other resources - [GPU acceleration](https://modal.com/docs/guide/gpu.md) - [Using CUDA on Modal](https://modal.com/docs/guide/cuda.md) - [Configuring CPU, memory, and disk](https://modal.com/docs/guide/resources.md) - Scaling out - [Scaling out](https://modal.com/docs/guide/scale.md) - [Input concurrency](https://modal.com/docs/guide/concurrent-inputs.md) - [Batch processing](https://modal.com/docs/guide/batch-processing.md) - [Job queues](https://modal.com/docs/guide/job-queue.md) - [Dynamic batching](https://modal.com/docs/guide/dynamic-batching.md) - [Multi-node clusters (beta)](https://modal.com/docs/guide/multi-node-training.md) - Deployment - [Apps, Functions, and entrypoints](https://modal.com/docs/guide/apps.md) - [Managing deployments](https://modal.com/docs/guide/managing-deployments.md) - [Invoking deployed functions](https://modal.com/docs/guide/trigger-deployed-functions.md) - [Continuous deployment](https://modal.com/docs/guide/continuous-deployment.