Build

AI Studio Notebooks GPU VMs ComfyUI

Train

Interactive training Experiment logging Training clusters PyTorch Lightning

Inference

Model APIs Dedicated models Deploy custom models Managed inference

GPUs Security Docs Pricing

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LitServe

Platform

Lightning AIDevelop, train and deploy on Lightning AI Python SDKProgrammatic access to the Lightning AI platform CLIAccess the Lightning AI platform from the command line

Open Source Libraries

PyTorch LightningFinetune and pretrain AI models. Focus on science, not engineering.Lightning FabricScale foundation models to 1000s of GPUs with expert-level control TorchMetrics90+ PyTorch metrics, optimized for distributed training ThunderCompiler for PyTorch: Make PyTorch models faster!LitLoggerExperiment tracking built into Lightning AI LitDataStream and process datasets at scale LitServeEasily serve AI models — Lightning fast LitAILLM router and minimal agent framework in one LitGPT20+ high-performance LLMs with recipes to pretrain, finetune and deploy at scale.

Home Install Quick start Speed up serving by 200x Benchmarks Advantages Migrate from FastAPI to LitServe FAQ Examples

Async and concurrency Authentication Autoscaling Batching Callbacks, middleware Deploy on cloud Dockerization Full control GPU inference Health check Hosting methods Logging and monitoring Model Context Protocol (MCP) servers Multiple API endpoints on one port Multiple models one server OpenAI spec OpenAI embedding Request, response format Serve LLMs Streaming Variable precision

LitAPI LitServer

Logging and Debugging ML API testing with pytest Programmatic shutdown Types of parallelism Use external APIs

Docs/LitServe/API reference

API reference

LitAPI
LitServer

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