RRepoGEO

REPOGEO REPORT · LITE

Langboat/Mengzi3

Default branch main · commit 81370f5b · scanned 5/13/2026, 10:12:33 AM

GitHub: 1,369 stars · 16 forks

AI VISIBILITY SCORE
23 /100
Critical
Category recall
0 / 2
Not recommended in any query
Rule findings
1 pass · 0 warn · 1 fail
Objective metadata checks
AI knows your name
2 / 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 Langboat/Mengzi3, 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

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

OVERALL DIRECTION
  • highabout#1
    Add a concise description to the About section

    Why:

    COPY-PASTE FIX
    Mengzi3 is a series of powerful open-source large language models (8B/13B parameters) specifically optimized for advanced Chinese natural language processing applications.
  • mediumhomepage#2
    Add a homepage URL to the repository's About section

    Why:

    COPY-PASTE FIX
    https://www.langboat.com/portal/mengzi-gpt

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 Langboat/Mengzi3
Avg rank
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
Llama 2 13B
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. Llama 2 13B · recommended 1×
  2. Mistral 7B Instruct v0.2 · recommended 1×
  3. Nous Hermes 2 - Mistral 7B DPO · recommended 1×
  4. OpenHermes 2.5 Mistral 7B · recommended 1×
  5. Vicuna-13B v1.5 · recommended 1×
  • CATEGORY QUERY
    What are some powerful open-source large language models around 8 to 13 billion parameters?
    you: not recommended
    AI recommended (in order):
    1. Llama 2 13B
    2. Mistral 7B Instruct v0.2
    3. Nous Hermes 2 - Mistral 7B DPO
    4. OpenHermes 2.5 Mistral 7B
    5. Vicuna-13B v1.5

    AI recommended 5 alternatives but never named Langboat/Mengzi3. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Seeking robust open-source large language models for advanced Chinese natural language processing applications.
    you: not recommended
    AI recommended (in order):
    1. Qwen
    2. Baichuan
    3. ChatGLM
    4. InternLM
    5. Pangu-Σ
    6. MOSS

    AI recommended 6 alternatives but never named Langboat/Mengzi3. This is the gap to close.

    Show full AI answer

Objective checks

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

  • Metadata completeness
    fail

    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 Langboat/Mengzi3?
    pass
    AI named Langboat/Mengzi3 explicitly

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

  • If a team adopts Langboat/Mengzi3 in production, what risks or prerequisites should they evaluate first?
    pass
    AI named Langboat/Mengzi3 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 Langboat/Mengzi3 solve, and who is the primary audience?
    pass
    AI did not name Langboat/Mengzi3 — likely talking about a different project

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

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Langboat/Mengzi3 — 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