RRepoGEO

REPOGEO REPORT · LITE

facebookresearch/MetaCLIP

Default branch main · commit f47f7841 · scanned 6/19/2026, 4:06:45 PM

GitHub: 1,840 stars · 77 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
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 facebookresearch/MetaCLIP, 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 the repository

    Why:

    COPY-PASTE FIX
    ["vision-language-models", "multilingual-ai", "clip", "large-scale-models", "computer-vision", "natural-language-processing", "deep-learning", "ai-research", "multimodal-ai"]
  • highhomepage#2
    Set the repository homepage URL

    Why:

    COPY-PASTE FIX
    https://arxiv.org/abs/2507.22062
  • mediumreadme#3
    Clarify the project's license in the README

    Why:

    COPY-PASTE FIX
    Add a section or line in the README, e.g., "License: This project is licensed under [describe the actual license(s) found in the LICENSE file, e.g., a custom research license or a combination of licenses]. Please refer to the LICENSE file for full details."

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 facebookresearch/MetaCLIP
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 1 of 2 queries
COMPETITOR LEADERBOARD
  1. GPT-4o · recommended 1×
  2. Gemini 1.5 Pro · recommended 1×
  3. Claude 3 Opus/Sonnet · recommended 1×
  4. CoCa (Contrastive Captioners) · recommended 1×
  5. BLIP-2 (Bootstrapping Language-Image Pre-training with Frozen Image Encoders and Large Language Models) · recommended 1×
  • CATEGORY QUERY
    Seeking a vision-language model offering strong multilingual performance without compromising English accuracy.
    you: not recommended
    AI recommended (in order):
    1. GPT-4o
    2. Gemini 1.5 Pro
    3. Claude 3 Opus/Sonnet
    4. CoCa (Contrastive Captioners)
    5. BLIP-2 (Bootstrapping Language-Image Pre-training with Frozen Image Encoders and Large Language Models)
    6. OpenCLIP (OpenAI CLIP)

    AI recommended 6 alternatives but never named facebookresearch/MetaCLIP. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What are the best options for training large-scale multimodal models on diverse worldwide datasets?
    you: not recommended
    AI recommended (in order):
    1. Google Cloud Vertex AI
    2. AWS SageMaker
    3. Microsoft Azure Machine Learning
    4. PyTorch FSDP
    5. NVIDIA NeMo Framework (NVIDIA/NeMo)
    6. Hugging Face Accelerate (huggingface/accelerate)
    7. DeepSpeed (microsoft/DeepSpeed)
    8. FairScale (facebookresearch/fairscale)

    AI recommended 8 alternatives but never named facebookresearch/MetaCLIP. 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 facebookresearch/MetaCLIP?
    pass
    AI named facebookresearch/MetaCLIP explicitly

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

  • If a team adopts facebookresearch/MetaCLIP in production, what risks or prerequisites should they evaluate first?
    pass
    AI named facebookresearch/MetaCLIP 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 facebookresearch/MetaCLIP solve, and who is the primary audience?
    pass
    AI named facebookresearch/MetaCLIP 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 facebookresearch/MetaCLIP. It auto-updates whenever the report is rescanned and links back to the latest report — easy public proof that you care about AI discoverability.

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MARKDOWN (README)
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facebookresearch/MetaCLIP — 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