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RouteLLM
A framework for serving and evaluating LLM routers - save LLM costs without compromising quality
Best fitUsers who want source-backed project understanding before installing it.
Check whether this project matches your task before installing it.
What it can doPortable AI capability assetReview the portable capability path.
Before continuingVerify in a sandboxDo not treat a preview pack as a proven local install.
GitHub snapshot5.0k stars394 forks · 7 contributors
Doramagic.ai Last verification date: 2026-07-24 Verification method: source evidence, semantic profile, public page gate, and static build acceptance.
Publication status · 2026-07-24
What is RouteLLM?
- A framework for serving and evaluating LLM routers - save LLM costs without compromising quality
- Best fit: Users who want source-backed project understanding before installing it.
- Not for: Not for users who want to skip sandbox verification or cannot accept configuration, permission, or maintenance overhead.
- Capability added to an AI workflow: Portable AI capability asset
- First safe verification step: Verify the smallest path in an isolated environment and keep a rollback path.
- Verification state: source, Quick Start, and sandbox install checks are recorded as passed.
- Top risk: May increase setup, validation, or first-run risk for the user.
- Evidence base: https://github.com/lm-sys/RouteLLM, https://github.com/lm-sys/RouteLLM#readme, Human Manual, Pitfall Log
01
Quick decision
Use this section to decide whether the project is worth a deeper read.A framework for serving and evaluating LLM routers - save LLM costs without compromising quality
5.0k stars · 394 forks
02
What it can do
Translate the upstream project into concrete capabilities the user can judge before installing.Overview & System Architecture
Related topics: Router Implementations & Algorithms, Deployment, Configuration & Threshold Calibration
Source: https://github.com/lm-sys/RouteLLM / Human Manual
Router Implementations & Algorithms
Related topics: Overview & System Architecture, Deployment, Configuration & Threshold Calibration, Extensibility, Training & Custom Integrations
Source: https://github.com/lm-sys/RouteLLM / Human Manual
Deployment, Configuration & Threshold Calibration
Related topics: Overview & System Architecture, Router Implementations & Algorithms
Source: https://github.com/lm-sys/RouteLLM / Human Manual
Extensibility, Training & Custom Integrations
Related topics: Router Implementations & Algorithms, Deployment, Configuration & Threshold Calibration
Source: https://github.com/lm-sys/RouteLLM / Human Manual
Doramagic Pitfall Log
Source-linked risks stay visible on the manual page so the preview does not read like a recommendation.
Source: Doramagic discovery, validation, and Project Pack records
Sources: https://github.com/lm-sys/RouteLLM, Human Manual, Project Pack evidence, and downstream validation signals.
03
Community Discussion Evidence
Project-level external discussion stays visible on the detail page, not only inside the manual.Community Discussion Evidence
8 source-linked itemsReview these external discussions before using RouteLLM with real data or production workflows. They are review inputs, not standalone proof that the project is production-ready.
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01
Add AgentWeb business data integration
github / github_issue
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02
litellm.drop_params error when running the openapi server
github / github_issue
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03
How can I use the different embedding model for mf router
github / github_issue
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04
What is the .npy file for query embedding in mf router training.
github / github_issue
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05
Can BERT router source code (esp. for training) be added to the repo?
github / github_issue
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06
Following demo it doesn't work
github / github_issue
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07
Try to run 2 Ollam
github / github_issue
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08
Capability evidence risk requires verification
GitHub / issue
04
How to start
Only source-backed commands are shown here. Verify them in an isolated environment first.Try the prompt first
Test the workflow without installing the upstream project.
previewRead the Human Manual
Understand inputs, outputs, limits, and failure modes.
manualTake context to your AI host
Use the compiled assets in your preferred AI environment.
contextRun sandbox verification
Confirm install commands and rollback before using a primary environment.
verifypip install routellmOfficial start command · https://github.com/lm-sys/RouteLLM#readme · verified: yes
05
Human Manual
The English page must expose the real manual, not a short placeholder.8+ sections · Human Manual
RouteLLM Manual
A framework for serving and evaluating LLM routers - save LLM costs without compromising quality
Open the full manual- https://github.com/lm-sys/RouteLLM Project Manual
- Table of Contents
- Overview & System Architecture
- Related Pages
- Purpose and Scope
- High-Level Architecture
- Core Components
- Controller
Overview & System Architecture
Related topics: Router Implementations & Algorithms, Deployment, Configuration & Threshold Calibration
Source: https://github.com/lm-sys/RouteLLM / Human Manual
Router Implementations & Algorithms
Related topics: Overview & System Architecture, Deployment, Configuration & Threshold Calibration, Extensibility, Training & Custom Integrations
Source: https://github.com/lm-sys/RouteLLM / Human Manual
Deployment, Configuration & Threshold Calibration
Related topics: Overview & System Architecture, Router Implementations & Algorithms
Source: https://github.com/lm-sys/RouteLLM / Human Manual
Extensibility, Training & Custom Integrations
Related topics: Router Implementations & Algorithms, Deployment, Configuration & Threshold Calibration
Source: https://github.com/lm-sys/RouteLLM / Human Manual
Doramagic Pitfall Log
Source-linked risks stay visible on the manual page so the preview does not read like a recommendation.
Source: Doramagic discovery, validation, and Project Pack records
06
AI Context Pack and portable assets
After deciding to continue, take the project context into your own AI host.Complete pack plus user-owned assets
These files are planning and verification assets for Claude Code, Codex, Gemini, Cursor, ChatGPT, and other AI hosts.
07
Preflight checks
Treat this page as a planning asset, not proof that your local environment is ready.- The manual is generated from source-linked project files and Doramagic validation signals.
- Community evidence warnings stay visible instead of being converted into marketing claims.
- This English page is indexable because the locale quality gate passed and explicit English index approval is enabled.
- Use the upstream repository as the final authority for installation commands, license, and version-specific behavior.
08
Pitfall Log and verification risks
Doramagic surfaces high-risk items before users treat a candidate capability as verified.Configuration risk requires verification
May increase setup, validation, or first-run risk for the user.
Installation risk requires verification
May increase setup, validation, or first-run risk for the user.
Configuration risk requires verification
May increase setup, validation, or first-run risk for the user.
Capability evidence risk requires verification
May increase setup, validation, or first-run risk for the user.
Runtime risk requires verification
May increase setup, validation, or first-run risk for the user.
Maintenance risk requires verification
May increase setup, validation, or first-run risk for the user.
Security or permission risk requires verification
May increase setup, validation, or first-run risk for the user.
Security or permission risk requires verification
May increase setup, validation, or first-run risk for the user.