RRepoGEO

REPOGEO REPORT · LITE

bilibili/Index-1.9B

Default branch main · commit 57c81280 · scanned 6/27/2026, 5:47:42 PM

GitHub: 1,019 stars · 50 forks

Scan history for this repo

Score trend below includes all ready runs (older left, newer right; scroll horizontally if needed). The table is collapsed by default—expand for newest-first rows, 10 per page.

Score trend (left → right: older → newer)

2 ready scans. Expand the table below for newest-first rows (10 per page, paginated).

AI VISIBILITY SCORE
28 /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
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 bilibili/Index-1.9B, 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
  • highreadme#1
    Reposition the README H1 to highlight core differentiators

    Why:

    CURRENT
    <h1>Index-1.9B</h1>
    COPY-PASTE FIX
    <h1>Index-1.9B: Compact Multilingual LLM (Chinese & English) with Long Context & GGUF Support</h1>
  • mediumtopics#2
    Add specific topics to improve categorization

    Why:

    CURRENT
    llm, nlp
    COPY-PASTE FIX
    llm, nlp, multilingual-llm, chinese-llm, english-llm, compact-llm, long-context, gguf, ollama, local-llm
  • mediumhomepage#3
    Add the Hugging Face Space link to the repository homepage field

    Why:

    COPY-PASTE FIX
    https://huggingface.co/spaces/IndexTeam/Index-1.9B

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 bilibili/Index-1.9B
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
mBERT (Multilingual BERT)
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. mBERT (Multilingual BERT) · recommended 1×
  2. XLM-R (Cross-lingual Language Model RoBERTa) · recommended 1×
  3. mT5 (Multilingual T5) · recommended 1×
  4. MiniCPM · recommended 1×
  5. BLOOMZ & BLOOMZ-MT · recommended 1×
  • CATEGORY QUERY
    What are some efficient, compact LLMs suitable for multilingual text processing, especially Chinese and English?
    you: not recommended
    AI recommended (in order):
    1. mBERT (Multilingual BERT)
    2. XLM-R (Cross-lingual Language Model RoBERTa)
    3. mT5 (Multilingual T5)
    4. MiniCPM
    5. BLOOMZ & BLOOMZ-MT
    6. DistilBERT (multilingual versions)

    AI recommended 6 alternatives but never named bilibili/Index-1.9B. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    How can I find a small LLM with long context support for local deployment using GGUF?
    you: not recommended
    AI recommended (in order):
    1. Mistral 7B Instruct v0.2
    2. OpenHermes 2.5 Mistral 7B
    3. Zephyr 7B Beta
    4. TinyLlama 1.1B Chat
    5. Phi-2
    6. Llama-2 7B Chat

    AI recommended 6 alternatives but never named bilibili/Index-1.9B. 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 bilibili/Index-1.9B?
    pass
    AI did not name bilibili/Index-1.9B — 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?

  • If a team adopts bilibili/Index-1.9B in production, what risks or prerequisites should they evaluate first?
    pass
    AI named bilibili/Index-1.9B 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 bilibili/Index-1.9B solve, and who is the primary audience?
    pass
    AI named bilibili/Index-1.9B explicitly

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

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bilibili/Index-1.9B — 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