RRepoGEO

REPOGEO REPORT · LITE

ulab-uiuc/LLMRouter

Default branch main · commit c65a32b1 · scanned 5/24/2026, 8:37:57 PM

GitHub: 1,852 stars · 177 forks

AI VISIBILITY SCORE
35 /100
Critical
Category recall
0 / 2
Not recommended in any query
Rule findings
1 pass · 1 warn · 0 fail
Objective metadata checks
AI knows your name
3 / 3
Direct prompts that named your repo
HOW TO READ THIS REPORT

Action plan is what to do next — copy-pasteable changes prioritized by impact. Category visibility is the real GEO test: when a user asks an AI a brand-free question that should surface ulab-uiuc/LLMRouter, does the AI actually recommend you — or your competitors? Objective checks verify the metadata signals AI engines weight first. Self-mention check detects whether AI even knows you exist by name.

Action plan — copy-paste fixes

3 prioritized changes generated by gemini-2.5-flash. Mark items done after you ship the fix.

OVERALL DIRECTION
  • hightopics#1
    Add specific topics to improve categorization

    Why:

    COPY-PASTE FIX
    llm-routing, llm-orchestration, model-routing, dynamic-routing, llm-inference-optimization, multi-llm, ai-router, machine-learning, python
  • highreadme#2
    Strengthen README's opening to highlight unique differentiation

    Why:

    CURRENT
    LLMRouter is an intelligent routing system designed to optimize LLM inference by dynamically selecting the most suitable model for each query.
    COPY-PASTE FIX
    LLMRouter is an intelligent routing system designed to optimize LLM inference by dynamically selecting the most suitable model for each query. Unlike general LLM frameworks, LLMRouter focuses on adaptive learning and multi-objective optimization, balancing latency, accuracy, and cost through advanced routing models rather than static rules.
  • mediumabout#3
    Expand the repository description

    Why:

    CURRENT
    LLMRouter: An Open-Source Library for LLM Routing
    COPY-PASTE FIX
    LLMRouter is an open-source library for intelligent LLM routing, designed to optimize LLM inference by dynamically selecting the most suitable model for each query. It offers adaptive learning and multi-objective optimization to balance latency, accuracy, and cost, primarily for developers and organizations managing multi-LLM deployments.

Category GEO backends resolved for this scan: google/gemini-2.5-flash, deepseek/deepseek-v4-flash

Category visibility — the real GEO test

Brand-free queries asked to google/gemini-2.5-flash. Did AI recommend you, or someone else?

Same questions for every model — switch tabs to compare answers and rankings.

Recall
0 / 2
0% of queries surface ulab-uiuc/LLMRouter
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
LangChain
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. LangChain · recommended 2×
  2. LlamaIndex · recommended 1×
  3. OpenAI Function Calling · recommended 1×
  4. scikit-learn · recommended 1×
  5. Hugging Face Transformers · recommended 1×
  • CATEGORY QUERY
    How to intelligently route user queries to the most suitable large language model?
    you: not recommended
    AI recommended (in order):
    1. LangChain
    2. LlamaIndex
    3. OpenAI Function Calling
    4. scikit-learn
    5. Hugging Face Transformers
    6. Microsoft Guidance
    7. Guardrails AI

    AI recommended 7 alternatives but never named ulab-uiuc/LLMRouter. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What open-source libraries offer dynamic LLM routing to optimize inference and costs?
    you: not recommended
    AI recommended (in order):
    1. LiteLLM
    2. LangChain
    3. Haystack
    4. OpenRouter.ai
    5. VLLM

    AI recommended 5 alternatives but never named ulab-uiuc/LLMRouter. This is the gap to close.

    Show full AI answer

Objective checks

Rule-based audits of metadata signals AI engines weight most.

  • Metadata completeness
    warn

    Suggestion:

  • README presence
    pass

Self-mention check

Does AI even know your repo exists when asked about it directly?

  • Compared to common alternatives in this category, what is the core differentiator of ulab-uiuc/LLMRouter?
    pass
    AI named ulab-uiuc/LLMRouter explicitly

    AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?

  • If a team adopts ulab-uiuc/LLMRouter in production, what risks or prerequisites should they evaluate first?
    pass
    AI named ulab-uiuc/LLMRouter explicitly

    AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?

  • In one sentence, what problem does the repo ulab-uiuc/LLMRouter solve, and who is the primary audience?
    pass
    AI named ulab-uiuc/LLMRouter explicitly

    AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?

Embed your GEO score

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MARKDOWN (README)
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ulab-uiuc/LLMRouter — Lite scans stay free; this card itemizes Pro deep limits vs Lite.

  • Deep reports10 / month
  • Brand-free category queries5 vs 2 in Lite
  • Prioritized action items8 vs 3 in Lite