RRepoGEO

REPOGEO REPORT · LITE

jjang-ai/mlxstudio

Default branch main · commit 543754ab · scanned 6/5/2026, 9:46:58 AM

GitHub: 768 stars · 49 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 jjang-ai/mlxstudio, 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
    Add a clear introductory sentence to the README

    Why:

    COPY-PASTE FIX
    MLX Studio is a unified native macOS desktop application that brings local LLMs, image generation, and coding assistance together on Apple Silicon, powered by Swift and Metal. (Place this sentence immediately after the H3 and badges, before the vMLX v2 paragraph.)
  • highlicense#2
    Add a LICENSE file to the repository

    Why:

    COPY-PASTE FIX
    Create a `LICENSE` file in the repository root with the chosen license text (e.g., MIT, Apache-2.0, GPL-3.0).
  • mediumabout#3
    Refine the GitHub repository description

    Why:

    CURRENT
    MLX Studio - Home of JANG_Q - Image Gen/Edit + Chat/Code All in one - + OpenClaw (Anthropic API)
    COPY-PASTE FIX
    MLX Studio: The native macOS desktop app for local AI. Run LLMs, generate/edit images, and get coding assistance, all powered by Apple Silicon.

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 jjang-ai/mlxstudio
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/ollama · recommended 2×
  3. jan-ai/jan · recommended 2×
  4. DiffusionBee · recommended 2×
  5. mudler/LocalAI · recommended 1×
  • CATEGORY QUERY
    What are the best macOS desktop applications for running local LLMs on Apple Silicon?
    you: not recommended
    AI recommended (in order):
    1. LM Studio
    2. Ollama (ollama/ollama)
    3. Jan (jan-ai/jan)
    4. LocalAI (mudler/LocalAI)
    5. GPT4All (nomic-ai/gpt4all)
    6. whisper.cpp (ggerganov/whisper.cpp)
    7. Stable Diffusion
    8. DiffusionBee
    9. Draw Things

    AI recommended 9 alternatives but never named jjang-ai/mlxstudio. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Seeking a unified macOS AI platform for local LLMs, image generation, and coding assistance.
    you: not recommended
    AI recommended (in order):
    1. LM Studio
    2. Ollama (ollama/ollama)
    3. InvokeAI (invoke-ai/InvokeAI)
    4. Jan (jan-ai/jan)
    5. LocalAI (go-skynet/LocalAI)
    6. DiffusionBee
    7. RunDiffusion
    8. Mochi Diffusion (godly-devotion/MochiDiffusion)
    9. Code Llama

    AI recommended 9 alternatives but never named jjang-ai/mlxstudio. 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 jjang-ai/mlxstudio?
    pass
    AI did not name jjang-ai/mlxstudio — 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 jjang-ai/mlxstudio in production, what risks or prerequisites should they evaluate first?
    pass
    AI named jjang-ai/mlxstudio 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 jjang-ai/mlxstudio solve, and who is the primary audience?
    pass
    AI named jjang-ai/mlxstudio 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 jjang-ai/mlxstudio. It auto-updates whenever the report is rescanned and links back to the latest report — easy public proof that you care about AI discoverability.

RepoGEO badge previewLive preview
MARKDOWN (README)
[![RepoGEO](https://repogeo.com/badge/jjang-ai/mlxstudio.svg)](https://repogeo.com/en/r/jjang-ai/mlxstudio)
HTML
<a href="https://repogeo.com/en/r/jjang-ai/mlxstudio"><img src="https://repogeo.com/badge/jjang-ai/mlxstudio.svg" alt="RepoGEO" /></a>
Pro

Subscribe to Pro for deep diagnoses

jjang-ai/mlxstudio — 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