RRepoGEO

REPOGEO REPORT · LITE

deepseek-ai/DeepSeek-MoE

Default branch main · commit 66edeee5 · scanned 5/19/2026, 12:18:30 AM

GitHub: 1,933 stars · 308 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
56 /100
Needs work
Category recall
1 / 2
Avg rank #3.0 when recommended
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-MoE, 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 improve categorization

    Why:

    CURRENT
    (none)
    COPY-PASTE FIX
    mixture-of-experts, moe, large-language-models, llm, deep-learning, ai, machine-learning, efficient-ai, scalable-ai, deepseek
  • mediumreadme#2
    Add a concise, high-level summary statement at the top of the README

    Why:

    CURRENT
    The current README starts with a series of centered links and then '## 1. Introduction'.
    COPY-PASTE FIX
    Add the following line right after the 'Paper Link' paragraph and before '## 1. Introduction':

DeepSeekMoE 16B is an innovative Mixture-of-Experts (MoE) language model designed for efficient, scalable AI, offering comparable performance to larger models with significantly reduced computational cost.
  • lowhomepage#3
    Add a homepage URL to the repository metadata

    Why:

    CURRENT
    (none)
    COPY-PASTE FIX
    https://www.deepseek.com/

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
1 / 2
50% of queries surface deepseek-ai/DeepSeek-MoE
Avg rank
#3.0
Lower is better. #1 = top recommendation.
Share of voice
8%
Of all named tools, what % are you?
Top rival
Switch Transformers
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. Switch Transformers · recommended 1×
  2. GShard · recommended 1×
  3. MoE-BERT · recommended 1×
  4. DeepSpeed-MoE · recommended 1×
  5. Megatron-LM · recommended 1×
  • CATEGORY QUERY
    How can I find an efficient Mixture-of-Experts architecture for building scalable language models?
    you: not recommended
    AI recommended (in order):
    1. Switch Transformers
    2. GShard
    3. MoE-BERT
    4. DeepSpeed-MoE
    5. Megatron-LM
    6. Fairseq
    7. Tutel

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

    Show full AI answer
  • CATEGORY QUERY
    What are powerful open-source large language models utilizing expert specialization for enhanced capabilities?
    you: #3
    AI recommended (in order):
    1. Mixtral 8x7B
    2. Dolphin-Mixtral
    3. DeepSeek-MoE ← you
    4. Qwen1.5-MoE
    5. OpenChat 3.5
    6. Hugging Face Transformers
    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-MoE?
    pass
    AI did not name deepseek-ai/DeepSeek-MoE — 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-MoE in production, what risks or prerequisites should they evaluate first?
    pass
    AI named deepseek-ai/DeepSeek-MoE 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-MoE solve, and who is the primary audience?
    pass
    AI named deepseek-ai/DeepSeek-MoE 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-MoE — 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