RRepoGEO

REPOGEO REPORT · LITE

deepseek-ai/DeepSeek-LLM

Default branch main · commit 6712a86b · scanned 5/19/2026, 5:42:35 PM

GitHub: 6,920 stars · 1,082 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
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 deepseek-ai/DeepSeek-LLM, 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 relevant topics to the repository

    Why:

    COPY-PASTE FIX
    large-language-model, llm, deep-learning, natural-language-processing, nlp, ai, machine-learning, open-source-llm, chinese-english-llm, code-generation, reasoning, math-llm
  • mediumreadme#2
    Strengthen the README's opening statement to highlight key differentiators

    Why:

    CURRENT
    The README currently starts with badges and links before the '1. Introduction' section.
    COPY-PASTE FIX
    Add the following sentence right after the initial badges/links and before '1. Introduction':

DeepSeek LLM is a powerful, open-source large language model, excelling in both English and Chinese, with strong capabilities in reasoning, coding, and mathematics, designed for researchers and developers.
  • lowreadme#3
    Clarify the dual license structure in the README

    Why:

    CURRENT
    The README contains links to 'LICENSE-CODE' and 'LICENSE-MODEL' under a div, and a link to '#8-license'.
    COPY-PASTE FIX
    In the '8. License' section, add or clarify with a sentence like: 'The repository's code is licensed under MIT. Please refer to LICENSE-CODE for code-specific terms and LICENSE-MODEL for terms governing the use of the trained models.'

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 deepseek-ai/DeepSeek-LLM
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
GPT-4
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. GPT-4 · recommended 2×
  2. Gemini 1.5 Pro · recommended 2×
  3. Claude 3 Opus · recommended 1×
  4. Llama 3 (8B and 70B) · recommended 1×
  5. Mistral Large · recommended 1×
  • CATEGORY QUERY
    What are some powerful pre-trained large language models for general AI applications?
    you: not recommended
    AI recommended (in order):
    1. GPT-4
    2. Claude 3 Opus
    3. Gemini 1.5 Pro
    4. Llama 3 (8B and 70B)
    5. Mistral Large

    AI recommended 5 alternatives but never named deepseek-ai/DeepSeek-LLM. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Which large language models excel at processing both English and Chinese text?
    you: not recommended
    AI recommended (in order):
    1. GPT-4
    2. Claude 3 Opus / Sonnet
    3. ERNIE 4.0
    4. LLaMA 3
    5. Gemini 1.5 Pro
    6. GLM-4

    AI recommended 6 alternatives but never named deepseek-ai/DeepSeek-LLM. 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 deepseek-ai/DeepSeek-LLM?
    pass
    AI named deepseek-ai/DeepSeek-LLM explicitly

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

  • If a team adopts deepseek-ai/DeepSeek-LLM in production, what risks or prerequisites should they evaluate first?
    pass
    AI named deepseek-ai/DeepSeek-LLM 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 deepseek-ai/DeepSeek-LLM solve, and who is the primary audience?
    pass
    AI named deepseek-ai/DeepSeek-LLM explicitly

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

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deepseek-ai/DeepSeek-LLM — 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