RRepoGEO

REPOGEO REPORT · LITE

kapi2800/qwen3-tts-apple-silicon

Default branch main · commit f74e52ee · scanned 6/13/2026, 4:02:58 AM

GitHub: 505 stars · 66 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 kapi2800/qwen3-tts-apple-silicon, 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
    Refine the 'About' description for stronger positioning

    Why:

    CURRENT
    Run Qwen3-TTS text-to-speech locally on Mac (M1/M2/M3/M4). Voice cloning, voice design, custom voices. 100% offline using MLX.
    COPY-PASTE FIX
    The ultimate local Qwen3-TTS text-to-speech solution for Mac (M1/M2/M3/M4). Enjoy voice cloning, voice design, and custom voices, 100% offline with MLX.
  • highlicense#2
    Add a LICENSE file to the repository

    Why:

    COPY-PASTE FIX
    Create a LICENSE file in the repository root with a standard open-source license (e.g., MIT, Apache-2.0, GPL-3.0) that accurately reflects your intentions for the project.
  • mediumreadme#3
    Add an explicit differentiator to the README introduction

    Why:

    COPY-PASTE FIX
    Add this sentence after the first paragraph in the README: "Unlike cloud services or general-purpose frameworks, this project is purpose-built for optimal local performance on Apple Silicon, ensuring privacy and efficiency."

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 kapi2800/qwen3-tts-apple-silicon
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
ElevenLabs
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. ElevenLabs · recommended 2×
  2. coqui-ai/TTS · recommended 1×
  3. MycroftAI/mimic3 · recommended 1×
  4. mozilla/TTS · recommended 1×
  5. collabora/WhisperSpeech · recommended 1×
  • CATEGORY QUERY
    Looking for a local text-to-speech solution with voice cloning for Apple Silicon.
    you: not recommended
    AI recommended (in order):
    1. ElevenLabs
    2. Coqui TTS (coqui-ai/TTS)
    3. Mycroft Mimic 3 (MycroftAI/mimic3)
    4. Mozilla TTS (mozilla/TTS)
    5. WhisperSpeech (collabora/WhisperSpeech)

    AI recommended 5 alternatives but never named kapi2800/qwen3-tts-apple-silicon. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What are the best offline AI voice generation tools available for macOS?
    you: not recommended
    AI recommended (in order):
    1. Whisper Desktop
    2. ElevenLabs
    3. Coqui TTS
    4. Rhasspy
    5. macOS Built-in Text-to-Speech
    6. Tacotron 2 / WaveNet

    AI recommended 6 alternatives but never named kapi2800/qwen3-tts-apple-silicon. 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 kapi2800/qwen3-tts-apple-silicon?
    pass
    AI named kapi2800/qwen3-tts-apple-silicon explicitly

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

  • If a team adopts kapi2800/qwen3-tts-apple-silicon in production, what risks or prerequisites should they evaluate first?
    pass
    AI named kapi2800/qwen3-tts-apple-silicon 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 kapi2800/qwen3-tts-apple-silicon solve, and who is the primary audience?
    pass
    AI did not name kapi2800/qwen3-tts-apple-silicon — 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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kapi2800/qwen3-tts-apple-silicon — 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