RRepoGEO

REPOGEO REPORT · LITE

deepseek-ai/DeepSeek-V2

Default branch main · commit ec98ee3c · scanned 6/25/2026, 10:37:31 AM

GitHub: 5,015 stars · 544 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)

3 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 deepseek-ai/DeepSeek-V2, 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 the repository

    Why:

    CURRENT
    (none)
    COPY-PASTE FIX
    large-language-model, llm, mixture-of-experts, moe, deep-learning, generative-ai, ai-model, deepseek-v2
  • highhomepage#2
    Set the repository homepage URL

    Why:

    CURRENT
    (none)
    COPY-PASTE FIX
    https://www.deepseek.com/
  • mediumreadme#3
    Clarify the licensing terms in the README

    Why:

    COPY-PASTE FIX
    DeepSeek-V2 is released under a dual licensing model. The code in this repository is licensed under the [MIT License](https://github.com/deepseek-ai/DeepSeek-V2/blob/main/LICENSE-CODE), while the DeepSeek-V2 model weights are licensed under the [DeepSeek-V2 Model License](https://github.com/deepseek-ai/DeepSeek-V2/blob/main/LICENSE-MODEL).

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-V2
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
GPT-3.5 Turbo
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. GPT-3.5 Turbo · recommended 1×
  2. meta-llama/llama3 · recommended 1×
  3. mistralai/Mistral-7B-v0.1 · recommended 1×
  4. mistralai/Mixtral-8x7B-v0.1 · recommended 1×
  5. Google Gemini 1.5 Flash · recommended 1×
  • CATEGORY QUERY
    What are some efficient and cost-effective large language models for general-purpose applications?
    you: not recommended
    AI recommended (in order):
    1. GPT-3.5 Turbo
    2. Llama 3 (meta-llama/llama3)
    3. Mistral 7B Instruct (mistralai/Mistral-7B-v0.1)
    4. Mixtral 8x7B Instruct (mistralai/Mixtral-8x7B-v0.1)
    5. Google Gemini 1.5 Flash
    6. Cohere Command R
    7. Cohere Command R+

    AI recommended 7 alternatives but never named deepseek-ai/DeepSeek-V2. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Which mixture-of-experts language models offer strong performance for custom deployments?
    you: not recommended
    AI recommended (in order):
    1. Mixtral 8x7B
    2. Qwen1.5-MoE
    3. DeepSeek-MoE
    4. GPT-4
    5. LLaMA 3

    AI recommended 5 alternatives but never named deepseek-ai/DeepSeek-V2. 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-V2?
    pass
    AI did not name deepseek-ai/DeepSeek-V2 — 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 deepseek-ai/DeepSeek-V2 in production, what risks or prerequisites should they evaluate first?
    pass
    AI named deepseek-ai/DeepSeek-V2 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-V2 solve, and who is the primary audience?
    pass
    AI named deepseek-ai/DeepSeek-V2 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-V2 — 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