LitServe
A Python framework for building custom AI inference APIs with batching, streaming, multiple models and control over request handling.
About LitServe
Serving a custom model pipeline requires coordinating model loading, concurrent requests and output streaming.
Who it’s for
- ML engineers exposing custom inference pipelines
- Developers serving models, agents and RAG workflows
When to consider it
Consider LitServe when you need to define inference logic in Python and control batching and streaming for your own API.
Tradeoffs & limitations
- Apache-2.0 licensed and requires Python 3.10 or newer. You implement the model-loading and prediction logic and run the server locally or on hosting infrastructure.
SOTA overview · Documentation-based assessment · Sources & review method
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Sources & review method
Documentation-based assessment · Oct 30, 2026 · Prepared with AI assistance; not a hands-on benchmark.
Checked by SOTA · AI-assisted documentation review. Selection advice is our assessment; verify current requirements for your deployment.
Import history & original evidence
LitServe official repository
A Python framework for building custom AI inference APIs with batching, streaming, multiple models and control over request handling.
Based on official pages and announcements checked on 2026-10-30. No hands-on test, performance benchmark or popularity ranking is claimed.