RRepoGEO

REPOGEO REPORT · LITE

microsoft/Magma

Default branch main · commit e3737803 · scanned 5/27/2026, 12:26:58 AM

GitHub: 1,927 stars · 160 forks

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 microsoft/Magma, 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 for multimodal AI agents and foundation models

    Why:

    COPY-PASTE FIX
    multimodal-ai, ai-agents, foundation-model, large-multimodal-model, lmm, computer-vision, nlp, cvpr-2025, microsoft-research
  • highreadme#2
    Add a direct, one-sentence summary to the README's opening

    Why:

    COPY-PASTE FIX
    Insert this sentence directly after the `<h2>` tag: "Magma is a pioneering foundation model designed to empower the development and evaluation of advanced multimodal AI agents."
  • mediumhomepage#3
    Populate the repository homepage URL

    Why:

    COPY-PASTE FIX
    https://microsoft.github.io/Magma/

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 microsoft/Magma
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
GPT-4o
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. GPT-4o · recommended 2×
  2. Gemini 1.5 Pro · recommended 2×
  3. Llama 3 · recommended 2×
  4. Claude 3 Opus · recommended 1×
  5. LLaVA-VL/LLaVA · recommended 1×
  • CATEGORY QUERY
    Looking for a foundation model to build multimodal AI agents.
    you: not recommended
    AI recommended (in order):
    1. GPT-4o
    2. Gemini 1.5 Pro
    3. Claude 3 Opus
    4. Llama 3
    5. LLaVA (LLaVA-VL/LLaVA)
    6. Fuyu-8B
    7. CogVLM (THUDM/CogVLM)

    AI recommended 7 alternatives but never named microsoft/Magma. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What are the best models for creating AI agents that understand multiple data types?
    you: not recommended
    AI recommended (in order):
    1. GPT-4o
    2. Google Gemini
    3. Gemini 1.5 Pro
    4. Claude 3
    5. Llama 3
    6. LLaVA (Large Language and Vision Assistant)
    7. CLIP (Contrastive Language-Image Pre-training)
    8. GPT-3.5
    9. Llama 2
    10. BLIP-2 (Bootstrapping Language-Image Pre-training with Frozen Latents)
    11. FlanT5
    12. OPT

    AI recommended 12 alternatives but never named microsoft/Magma. 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 microsoft/Magma?
    pass
    AI named microsoft/Magma explicitly

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

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

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

Embed your GEO score

Drop this badge into the README of microsoft/Magma. It auto-updates whenever the report is rescanned and links back to the latest report — easy public proof that you care about AI discoverability.

RepoGEO badge previewLive preview
MARKDOWN (README)
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HTML
<a href="https://repogeo.com/en/r/microsoft/Magma"><img src="https://repogeo.com/badge/microsoft/Magma.svg" alt="RepoGEO" /></a>
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microsoft/Magma — 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