RRepoGEO

REPOGEO REPORT · LITE

guinmoon/LLMFarm

Default branch main · commit ee6d251a · scanned 6/30/2026, 12:06:52 PM

GitHub: 2,048 stars · 171 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
40 /100
Critical
Category recall
0 / 2
Not recommended in any query
Rule findings
2 pass · 0 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 guinmoon/LLMFarm, 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 the README's opening to emphasize its role as a user-friendly local LLM application

    Why:

    CURRENT
    LLMFarm is an iOS and MacOS app to work with large language models (LLM).
    COPY-PASTE FIX
    LLMFarm is a user-friendly, cross-platform application (GUI) for iOS and macOS, designed to run and interact with large language models (LLMs) locally and offline.
  • mediumtopics#2
    Expand the repository topics to include broader category terms

    Why:

    CURRENT
    ai, ggml, gpt-2, gptneox, ios, llama, macos, rwkv, starcoder, swift
    COPY-PASTE FIX
    ai, ggml, gpt-2, gptneox, ios, llama, macos, rwkv, starcoder, swift, local-llm, llm-inference, desktop-app, ai-chat-client, offline-ai
  • lowabout#3
    Refine the repository description to highlight its application nature

    Why:

    CURRENT
    llama and other large language models on iOS and MacOS offline using GGML library.
    COPY-PASTE FIX
    Run llama and other large language models as a user-friendly application on iOS and MacOS, enabling offline inference using the GGML library.

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 guinmoon/LLMFarm
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
Ollama
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. Ollama · recommended 1×
  2. LM Studio · recommended 1×
  3. Jan · recommended 1×
  4. MLC LLM · recommended 1×
  5. llama.cpp · recommended 1×
  • CATEGORY QUERY
    How can I run large language models locally on my iPhone or Mac?
    you: not recommended
    AI recommended (in order):
    1. Ollama
    2. LM Studio
    3. Jan
    4. MLC LLM
    5. llama.cpp
    6. LocalAI

    AI recommended 6 alternatives but never named guinmoon/LLMFarm. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What tools enable offline inference for various AI models on macOS and iOS?
    you: not recommended
    AI recommended (in order):
    1. Core ML
    2. TensorFlow Lite
    3. ONNX Runtime
    4. PyTorch Mobile
    5. MLX
    6. OpenVINO

    AI recommended 6 alternatives but never named guinmoon/LLMFarm. This is the gap to close.

    Show full AI answer

Objective checks

Rule-based audits of metadata signals AI engines weight most.

  • Metadata completeness
    pass

  • 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 guinmoon/LLMFarm?
    pass
    AI named guinmoon/LLMFarm explicitly

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

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

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

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guinmoon/LLMFarm — 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