# lm-sys/RouteLLM

A framework for serving and evaluating LLM routers - save LLM costs without compromising quality

Repository: https://github.com/lm-sys/RouteLLM
Canonical: https://ross.abutalabs.com/products/routellm
Language: Python
License: Apache-2.0
License Family: permissive
Last push: 2024-08-10T19:10:15+00:00

## Health v2 (maintenance only)
Score: 24/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 0, release rhythm 35, longevity 58
- inputs: {"age_days": 822, "days_push": 753, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 5408, forks 425 (observed 2026-08-28T04:09:17.661332+00:00)

## What it is
RouteLLM is a Python framework for serving and evaluating LLM routers that route queries between strong and weak models to cut costs. It provides an OpenAI-compatible client and server, pre-trained routers, and benchmarking tools.

## Use cases
- reduce LLM API costs by routing simple queries to cheaper models
- serve an OpenAI-compatible endpoint that routes between GPT-4 and a smaller model
- benchmark and compare different LLM routing strategies
- calibrate cost/quality tradeoff thresholds for model routing
- route requests to local models instead of paid APIs

## When to choose
- you pay for a strong LLM like GPT-4 but many queries could be handled by a cheaper model
- you want an OpenAI drop-in replacement with intelligent model routing
- you need to evaluate or research routing algorithms across benchmarks

## When to avoid
- all your queries genuinely require top-tier model quality with no cost flexibility
- you use a single self-hosted model with no alternative to route to
- you need non-LLM request routing or generic API gateway features

## Facets
- artifact type: framework
- maturity: active
- function: llm-inference, api-framework, benchmarking, http-server
- domain: large-language-models, machine-learning, developer-tools, apis
- platform: python, cloud
- tags: llm-routing, cost-optimization, openai-compatible, model-routing, inference-optimization, docker

## Member repositories
- lm-sys/RouteLLM (main) score 24

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:09:17.661332+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-29T17:57:46.768182+00:00, confidence not recorded.
  - readme: https://github.com/lm-sys/RouteLLM (fetched 2026-08-28T04:09:17.661332+00:00, sha de8f28bf92e3)
  - registry_pypi: https://pypi.org/pypi/routellm/json (fetched 2026-08-29T08:52:22.564981+00:00, sha 73aab407b3b9)
- Data as of 2026-08-30T08:39:29.467469+00:00.