RRepoGEO

REPOGEO REPORT · LITE

zai-org/GLM-TTS

Default branch main · commit 4b944f4b · scanned 5/16/2026, 1:23:30 PM

GitHub: 1,000 stars · 127 forks

AI VISIBILITY SCORE
33 /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
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 zai-org/GLM-TTS, 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
    Explicitly state 'open-source project' in the README's Model Introduction

    Why:

    CURRENT
    GLM-TTS is a high-quality text-to-speech (TTS) synthesis system based on large language models, supporting zero-shot voice cloning and streaming inference.
    COPY-PASTE FIX
    GLM-TTS is an open-source project providing a high-quality text-to-speech (TTS) synthesis system based on large language models, supporting zero-shot voice cloning and streaming inference.
  • mediumtopics#2
    Add 'open-source' and 'ai-model' to repository topics

    Why:

    CURRENT
    edge-computing, llm, tts
    COPY-PASTE FIX
    open-source, llm, tts, ai-model, speech-synthesis
  • mediumabout#3
    Refine repository description to clarify audience and project type

    Why:

    CURRENT
    GLM-TTS: Controllable & Emotion-Expressive Zero-shot TTS with Multi-Reward Reinforcement Learning
    COPY-PASTE FIX
    GLM-TTS is an open-source project for AI researchers and developers, offering a controllable & emotion-expressive zero-shot TTS system with Multi-Reward Reinforcement Learning.

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 zai-org/GLM-TTS
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. Google Cloud Text-to-Speech · recommended 2×
  3. Azure AI Speech · recommended 2×
  4. Resemble.ai · recommended 2×
  5. Play.ht · recommended 2×
  • CATEGORY QUERY
    How can I generate expressive, emotional speech with zero-shot voice cloning capabilities?
    you: not recommended
    AI recommended (in order):
    1. ElevenLabs
    2. Meta Voicebox
    3. Google Cloud Text-to-Speech
    4. Azure AI Speech
    5. Resemble.ai
    6. Play.ht
    7. Descript

    AI recommended 7 alternatives but never named zai-org/GLM-TTS. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What are good LLM-powered text-to-speech systems for controllable, high-quality audio generation?
    you: not recommended
    AI recommended (in order):
    1. ElevenLabs
    2. Google Cloud Text-to-Speech
    3. Azure AI Speech
    4. AWS Polly
    5. Play.ht
    6. Resemble.ai

    AI recommended 6 alternatives but never named zai-org/GLM-TTS. 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 zai-org/GLM-TTS?
    pass
    AI named zai-org/GLM-TTS explicitly

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

  • If a team adopts zai-org/GLM-TTS in production, what risks or prerequisites should they evaluate first?
    pass
    AI named zai-org/GLM-TTS 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 zai-org/GLM-TTS solve, and who is the primary audience?
    pass
    AI did not name zai-org/GLM-TTS — 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?

Embed your GEO score

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MARKDOWN (README)
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zai-org/GLM-TTS — Lite scans stay free; this card itemizes Pro deep limits vs Lite.

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  • Brand-free category queries5 vs 2 in Lite
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