RRepoGEO

REPOGEO REPORT · LITE

deepseek-ai/DeepSeek-Math-V2

Default branch main · commit 665c8407 · scanned 5/28/2026, 2:32:38 PM

GitHub: 1,589 stars · 147 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 deepseek-ai/DeepSeek-Math-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

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

OVERALL DIRECTION
  • highabout#1
    Add a concise repository description

    Why:

    COPY-PASTE FIX
    DeepSeekMath-V2 is a Mixture-of-Experts (MoE) large language model specifically designed and optimized for advanced mathematical reasoning and verifiable problem-solving.
  • mediumreadme#2
    Strengthen the README's opening statement for immediate positioning

    Why:

    CURRENT
    Large language models have made significant progress in mathematical reasoning, which serves as an important testbed for AI and could impact scientific research if further advanced. By scaling reasoning with reinforcement learning that rewards correct final answers, LLMs have improved from poor performance to saturating quantitative reasoning competitions like AIME and HMMT in one year. However, this approach faces fundamental limitations. Pursuing higher final answer accuracy doesn't address a key issue: correct answers don't guarantee correct reasoning. Moreover, many mathematical tasks like theorem proving require rigorous step-by-step derivation rather than numerical answers, making final answer rewards inapplicable. To push the limits of deep reasoning, we believe it is necessary to verify the comprehensiveness and rigor of mathematical reasoning. Self-verification is particularly important for scalin
    COPY-PASTE FIX
    DeepSeekMath-V2 is a state-of-the-art Mixture-of-Experts (MoE) large language model specifically engineered for advanced mathematical reasoning and self-verifiable problem-solving. Unlike traditional approaches focused solely on final answer accuracy, DeepSeekMath-V2 emphasizes comprehensive and rigorous step-by-step derivation, crucial for complex tasks like theorem proving and ensuring the correctness of reasoning itself.

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-Math-V2
Avg rank
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
Wolfram Alpha
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. Wolfram Alpha · recommended 2×
  2. GPT-4 · recommended 1×
  3. Claude 3 Opus · recommended 1×
  4. AlphaGeometry · recommended 1×
  5. Minerva by Google · recommended 1×
  • CATEGORY QUERY
    Which AI models excel at complex mathematical reasoning and solution verification?
    you: not recommended
    AI recommended (in order):
    1. GPT-4
    2. Claude 3 Opus
    3. AlphaGeometry
    4. Minerva by Google
    5. Llama 3
    6. Wolfram Alpha

    AI recommended 6 alternatives but never named deepseek-ai/DeepSeek-Math-V2. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Need an advanced language model for robust mathematical problem-solving with verifiable steps.
    you: not recommended
    AI recommended (in order):
    1. OpenAI GPT-4
    2. Google Gemini Advanced
    3. Anthropic Claude 3 Opus
    4. Wolfram Alpha
    5. Meta Llama 3

    AI recommended 5 alternatives but never named deepseek-ai/DeepSeek-Math-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
    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 deepseek-ai/DeepSeek-Math-V2?
    pass
    AI did not name deepseek-ai/DeepSeek-Math-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-Math-V2 in production, what risks or prerequisites should they evaluate first?
    pass
    AI named deepseek-ai/DeepSeek-Math-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-Math-V2 solve, and who is the primary audience?
    pass
    AI named deepseek-ai/DeepSeek-Math-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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  • Brand-free category queries5 vs 2 in Lite
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