RRepoGEO

REPOGEO REPORT · LITE

JIA-Lab-research/MGM

Default branch main · commit 769820cb · scanned 5/9/2026, 10:03:06 PM

GitHub: 3,325 stars · 275 forks

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 JIA-Lab-research/MGM, 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
    Reposition README's opening paragraph to clarify purpose and category

    Why:

    CURRENT
    The framework supports a series of dense and MoE Large Language Models (LLMs) from 2B to 34B with image understanding, reasoning, and generation simultaneously. We build this repo based on LLaVA.
    COPY-PASTE FIX
    Mini-Gemini is a comprehensive framework for developing and researching multi-modal Large Language Models (LLMs). It enables advanced image understanding, reasoning, and text generation by supporting a series of dense and MoE LLMs from 2B to 34B. Built upon LLaVA, Mini-Gemini provides a robust foundation for exploring the potential of multi-modality in AI.
  • mediumhomepage#2
    Add project homepage to GitHub repository's 'About' section

    Why:

    COPY-PASTE FIX
    https://mini-gemini.github.io/
  • lowtopics#3
    Add more specific topics to improve categorization

    Why:

    CURRENT
    generation, large-language-models, vision-language-model
    COPY-PASTE FIX
    generation, large-language-models, vision-language-model, multimodal-ai, image-to-text, llm-framework

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 JIA-Lab-research/MGM
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
Hugging Face Transformers
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. Hugging Face Transformers · recommended 2×
  2. ViT-GPT2 · recommended 1×
  3. BLIP · recommended 1×
  4. PyTorch · recommended 1×
  5. torchvision · recommended 1×
  • CATEGORY QUERY
    How can I build an AI model that understands images and generates text descriptions?
    you: not recommended
    AI recommended (in order):
    1. Hugging Face Transformers
    2. ViT-GPT2
    3. BLIP
    4. PyTorch
    5. torchvision
    6. torchaudio
    7. ResNet
    8. EfficientNet
    9. Swin Transformer
    10. TensorFlow
    11. Keras
    12. InceptionV3
    13. Xception
    14. OpenCV
    15. fast.ai

    AI recommended 15 alternatives but never named JIA-Lab-research/MGM. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What frameworks enable multi-modal large language models for image reasoning and content generation?
    you: not recommended
    AI recommended (in order):
    1. OpenAI's GPT-4V (Vision)
    2. Google's Gemini (Pro/Ultra)
    3. LlamaIndex
    4. LangChain
    5. LLaVA (Large Language and Vision Assistant)
    6. Hugging Face Transformers
    7. Microsoft's Florence-2

    AI recommended 7 alternatives but never named JIA-Lab-research/MGM. 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 JIA-Lab-research/MGM?
    pass
    AI did not name JIA-Lab-research/MGM — 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 JIA-Lab-research/MGM in production, what risks or prerequisites should they evaluate first?
    pass
    AI named JIA-Lab-research/MGM 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 JIA-Lab-research/MGM solve, and who is the primary audience?
    pass
    AI named JIA-Lab-research/MGM 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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JIA-Lab-research/MGM — 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