RRepoGEO

REPOGEO REPORT · LITE

openlm-research/open_llama

Default branch main · commit 6e7f73ea · scanned 5/26/2026, 4:47:45 AM

GitHub: 7,525 stars · 407 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 openlm-research/open_llama, 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

2 prioritized changes generated by gemini-2.5-flash. Mark items done after you ship the fix.

OVERALL DIRECTION
  • highreadme#1
    Strengthen the README's opening to highlight core differentiators

    Why:

    CURRENT
    TL;DR: we are releasing our public preview of OpenLLaMA, a permissively licensed open source reproduction of Meta AI’s LLaMA. We are releasing a series of 3B, 7B and 13B models trained on different data mixtures. Our model weights can serve as the drop in replacement of LLaMA in existing implementations.
    COPY-PASTE FIX
    TL;DR: OpenLLaMA offers a permissively licensed, open-source reproduction of Meta AI’s LLaMA, providing a direct, drop-in replacement for LLaMA in existing implementations. We release a series of 3B, 7B, and 13B models trained on diverse data mixtures, making powerful LLMs accessible for commercial and research projects without restrictive licensing.
  • mediumhomepage#2
    Add a homepage URL to the repository metadata

    Why:

    COPY-PASTE FIX
    https://openlm-research.github.io/open_llama/

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 openlm-research/open_llama
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
Llama 3
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. Llama 3 · recommended 1×
  2. Mistral 7B / Mixtral 8x7B · recommended 1×
  3. Gemma · recommended 1×
  4. Falcon · recommended 1×
  5. MPT · recommended 1×
  • CATEGORY QUERY
    Where can I find permissively licensed open source large language models for my projects?
    you: not recommended
    AI recommended (in order):
    1. Llama 3
    2. Mistral 7B / Mixtral 8x7B
    3. Gemma
    4. Falcon
    5. MPT
    6. OpenLLaMA

    AI recommended 6 alternatives but never named openlm-research/open_llama. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Looking for flexible, readily available language models with varying parameter sizes for integration.
    you: not recommended
    AI recommended (in order):
    1. OpenAI GPT-3.5 / GPT-4
    2. Anthropic Claude
    3. Google Gemini
    4. Meta Llama 3
    5. Mistral AI
    6. Cohere
    7. Hugging Face Hub

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

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

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MARKDOWN (README)
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openlm-research/open_llama — 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