Lightning-AI/LitServe

Health v2 · maintenance only

Adoption not part of the score

3930 stars · 300 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-29, confidence not recorded

LitServe is a Python framework for building custom AI inference servers with full control over batching, routing, streaming, and scaling logic. It wraps FastAPI-based serving with performance optimizations for PyTorch models, LLMs, agents, and RAG pipelines.

Use cases

• serve a pytorch model as a rest api
• deploy an llm inference server
• build a custom model serving endpoint with batching
• host an agent or rag pipeline behind an api
• self-host ai model inference with gpu autoscaling
• replace fastapi-based inference servers with something faster

When to choose

• you need custom inference logic that rigid serving tools like vLLM can't express
• you want to serve multiple models, agents, or non-standard pipelines in Python
• you want batching, streaming, and scaling without writing MLOps glue code

When to avoid

• you only need to serve a single standard LLM with maximum throughput - vLLM may be better
• you need a fully managed serverless platform rather than a self-hosted framework
• your workload is not AI inference at all

Facets

framework · maturity active

llm-inference http-server api-framework machine-learning rag agent-framework chatbot machine-learning deep-learning large-language-models artificial-intelligence web-development backend apis python cloud self-hosted inference-server model-serving fastapi batching streaming rest-api pytorch deployment docker gpu

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markdown · JSON · MCP: product_card(name="Lightning-AI/LitServe")