RRepoGEO

REPOGEO REPORT · LITE

meta-llama/llama-models

Default branch main · commit 0e0b8c51 · scanned 5/20/2026, 4:21:37 PM

GitHub: 7,606 stars · 1,368 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
22 /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
1 / 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 meta-llama/llama-models, 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
  • highabout#1
    Update repository description to reflect model distribution

    Why:

    CURRENT
    Utilities intended for use with Llama models.
    COPY-PASTE FIX
    Official repository for Meta Llama large language models, providing access to model weights and associated resources.
  • hightopics#2
    Add comprehensive topics for better categorization

    Why:

    CURRENT
    (none)
    COPY-PASTE FIX
    large-language-models, llm, generative-ai, ai-models, deep-learning, machine-learning, meta-ai, foundation-model, model-weights
  • mediumreadme#3
    Add a clear statement about the repository's license to the README

    Why:

    COPY-PASTE FIX
    This repository is licensed under the custom terms found in the LICENSE file. Please review the LICENSE file for full details on usage and distribution.

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 meta-llama/llama-models
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
huggingface/transformers
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. huggingface/transformers · recommended 1×
  2. ggerganov/llama.cpp · recommended 1×
  3. ollama/ollama · recommended 1×
  4. langchain-ai/langchain · recommended 1×
  5. BerriAI/litellm · recommended 1×
  • CATEGORY QUERY
    How can I get started with open-source large language models for generative AI applications?
    you: not recommended
    AI recommended (in order):
    1. Hugging Face Transformers (huggingface/transformers)
    2. Llama.cpp (ggerganov/llama.cpp)
    3. Ollama (ollama/ollama)
    4. LangChain (langchain-ai/langchain)
    5. LiteLLM (BerriAI/litellm)

    AI recommended 5 alternatives but never named meta-llama/llama-models. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Which accessible foundational AI models are available for building custom generative applications?
    you: not recommended
    AI recommended (in order):
    1. OpenAI GPT-4 / GPT-3.5 Turbo
    2. Anthropic Claude
    3. Google Gemini
    4. Meta Llama 3
    5. Mistral AI
    6. Cohere Command

    AI recommended 6 alternatives but never named meta-llama/llama-models. 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 meta-llama/llama-models?
    pass
    AI did not name meta-llama/llama-models — 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 meta-llama/llama-models in production, what risks or prerequisites should they evaluate first?
    pass
    AI named meta-llama/llama-models 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 meta-llama/llama-models solve, and who is the primary audience?
    pass
    AI did not name meta-llama/llama-models — 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?

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  • Brand-free category queries5 vs 2 in Lite
  • Prioritized action items8 vs 3 in Lite