RRepoGEO

REPOGEO REPORT · LITE

qnguyen3/chat-with-mlx

Default branch main · commit 1b799c0b · scanned 6/20/2026, 10:57:28 PM

GitHub: 1,595 stars · 128 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
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 qnguyen3/chat-with-mlx, 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 descriptive topics to the repository

    Why:

    COPY-PASTE FIX
    llm, mlx, apple-silicon, local-llm, chat-ui, generative-ai, machine-learning, python
  • highreadme#2
    Update README's opening to explicitly state "LLM Chat UI"

    Why:

    CURRENT
    An all-in-one Chat Playground using Apple MLX on Apple Silicon Macs.
    COPY-PASTE FIX
    An all-in-one **LLM Chat UI** for Apple Silicon Macs, powered by the MLX Framework.
  • mediumreadme#3
    Add a sentence highlighting the MLX/Apple Silicon differentiator in the README intro

    Why:

    COPY-PASTE FIX
    Leveraging Apple's MLX framework, it provides an optimized and native experience for running open-source LLMs directly on your Apple Silicon Mac.

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 qnguyen3/chat-with-mlx
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
LM Studio
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. LM Studio · recommended 2×
  2. Ollama · recommended 2×
  3. Jan · recommended 2×
  4. LocalAI · recommended 2×
  5. GPT4All · recommended 2×
  • CATEGORY QUERY
    What are good local LLM chat interfaces for Apple Silicon Macs?
    you: not recommended
    AI recommended (in order):
    1. LM Studio
    2. Ollama
    3. Chatbot UI
    4. MacWhisper
    5. Jan
    6. LocalAI
    7. Open WebUI
    8. GPT4All
    9. Pinokio

    AI recommended 9 alternatives but never named qnguyen3/chat-with-mlx. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    How can I easily run and chat with open-source language models on my Mac?
    you: not recommended
    AI recommended (in order):
    1. LM Studio
    2. Ollama
    3. Jan
    4. GPT4All
    5. LocalAI
    6. text-generation-webui (oobabooga)
    7. Hugging Face Transformers
    8. llama-cpp-python
    9. ctransformers

    AI recommended 9 alternatives but never named qnguyen3/chat-with-mlx. 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 qnguyen3/chat-with-mlx?
    pass
    AI did not name qnguyen3/chat-with-mlx — 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 qnguyen3/chat-with-mlx in production, what risks or prerequisites should they evaluate first?
    pass
    AI named qnguyen3/chat-with-mlx 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 qnguyen3/chat-with-mlx solve, and who is the primary audience?
    pass
    AI named qnguyen3/chat-with-mlx explicitly

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

Embed your GEO score

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MARKDOWN (README)
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qnguyen3/chat-with-mlx — 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