RRepoGEO

REPOGEO REPORT · LITE

baichuan-inc/Baichuan-13B

Default branch main · commit 21017d59 · scanned 6/29/2026, 8:28:09 PM

GitHub: 2,932 stars · 231 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
33 /100
Critical
Category recall
0 / 2
Not recommended in any query
Rule findings
2 pass · 0 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 baichuan-inc/Baichuan-13B, 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
    Elevate core value proposition to the top of the README

    Why:

    CURRENT
    The current README places the "介绍" (Introduction) section after update information and the table of contents.
    COPY-PASTE FIX
    Move the key positioning statement from the "介绍" section to immediately below the main title and links. For example, add this sentence (or its English equivalent in README_EN.md) right after the initial links: "Baichuan-13B 是百川智能开发的开源可商用130亿参数大规模语言模型，在中文和英文benchmark上均取得同尺寸最佳效果，提供预训练和对齐版本。"
  • mediumabout#2
    Enhance the repository description

    Why:

    CURRENT
    A 13B large language model developed by Baichuan Intelligent Technology
    COPY-PASTE FIX
    An open-source, commercially available 13-billion parameter large language model by Baichuan Intelligent Technology, excelling in both Chinese and English benchmarks for general NLP and chat applications.
  • lowreadme#3
    Add an explicit comparison section in the README

    Why:

    COPY-PASTE FIX
    Add a new section to the README, e.g., "与同类模型对比" (Comparison with Similar Models) or "Why Baichuan-13B?", that explicitly highlights its advantages over key open-source 13B models (like Llama 2 13B, Vicuna-13B) in terms of data size, performance on Chinese/English benchmarks, and commercial license.

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 baichuan-inc/Baichuan-13B
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. Vicuna-13B · recommended 1×
  3. GPT-4 · recommended 1×
  4. Claude 3 Opus / Sonnet · recommended 1×
  5. ERNIE Bot · recommended 1×
  • CATEGORY QUERY
    What are the best open-source 13-billion parameter language models for general NLP tasks?
    you: not recommended
    AI recommended (in order):
    1. Llama 2 13B
    2. Vicuna-13B

    AI recommended 2 alternatives but never named baichuan-inc/Baichuan-13B. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Which large language models offer strong performance for both Chinese and English commercial applications?
    you: not recommended
    AI recommended (in order):
    1. GPT-4
    2. Claude 3 Opus / Sonnet
    3. ERNIE Bot
    4. Google Gemini 1.5 Pro
    5. Llama 3 (70B Instruct)
    6. Mistral Large

    AI recommended 6 alternatives but never named baichuan-inc/Baichuan-13B. This is the gap to close.

    Show full AI answer

Objective checks

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

  • Metadata completeness
    pass

  • 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 baichuan-inc/Baichuan-13B?
    pass
    AI did not name baichuan-inc/Baichuan-13B — 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 baichuan-inc/Baichuan-13B in production, what risks or prerequisites should they evaluate first?
    pass
    AI named baichuan-inc/Baichuan-13B 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 baichuan-inc/Baichuan-13B solve, and who is the primary audience?
    pass
    AI named baichuan-inc/Baichuan-13B 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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baichuan-inc/Baichuan-13B — 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