RRepoGEO

REPOGEO REPORT · LITE

Zyphra/Zonos

Default branch main · commit bc40d98e · scanned 5/30/2026, 6:58:01 AM

GitHub: 7,212 stars · 810 forks

AI VISIBILITY SCORE
35 /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
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 Zyphra/Zonos, 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 disambiguation statement in the README's introduction

    Why:

    CURRENT
    Zonos-v0.1 is a leading open-weight text-to-speech model trained on more than 200k hours of varied multilingual speech...
    COPY-PASTE FIX
    This repository contains Zyphra's Zonos-v0.1, an open-weight text-to-speech model, and is distinct from any e-commerce or web analytics services. Zonos-v0.1 is a leading open-weight text-to-speech model trained on more than 200k hours of varied multilingual speech...
  • hightopics#2
    Add specific topics for text-to-speech and AI models

    Why:

    COPY-PASTE FIX
    text-to-speech, tts, voice-synthesis, speech-synthesis, voice-cloning, ai-model, deep-learning, multilingual, open-source
  • mediumreadme#3
    Highlight core capabilities as a bulleted list in the README's introduction

    Why:

    CURRENT
    Our model enables highly natural speech generation from text prompts when given a speaker embedding or audio prefix, and can accurately perform speech cloning when given a reference clip spanning just a few seconds. The conditioning setup also allows for fine control over speaking rate, pitch variation, audio quality, and emotions such as happiness, fear, sadness, and anger. The model outputs speech natively at 44kHz.
    COPY-PASTE FIX
    Our model enables highly natural speech generation from text prompts when given a speaker embedding or audio prefix, and can accurately perform speech cloning when given a reference clip spanning just a few seconds. The conditioning setup also allows for fine control over speaking rate, pitch variation, audio quality, and emotions such as happiness, fear, sadness, and anger. The model outputs speech natively at 44kHz.
    
    Key Capabilities:
    *   Highly natural speech generation from text prompts
    *   Accurate speech cloning from short reference clips
    *   Fine control over speaking rate, pitch, audio quality, and emotions (happiness, fear, sadness, anger)
    *   Multilingual support from 200k+ hours of varied speech data
    *   Open-weight model for full transparency and customizability

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 Zyphra/Zonos
Avg rank
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
VITS
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. VITS · recommended 1×
  2. Coqui TTS · recommended 1×
  3. ESPnet · recommended 1×
  4. FastSpeech2 · recommended 1×
  5. HiFi-GAN · recommended 1×
  • CATEGORY QUERY
    What open-source text-to-speech models offer highly natural, expressive voice generation?
    you: not recommended
    AI recommended (in order):
    1. VITS
    2. Coqui TTS
    3. ESPnet
    4. FastSpeech2
    5. HiFi-GAN
    6. Parallel WaveGAN
    7. Tacotron2
    8. WaveGlow

    AI recommended 8 alternatives but never named Zyphra/Zonos. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    How can I implement realistic voice cloning with controllable emotions from text prompts?
    you: not recommended
    AI recommended (in order):
    1. ElevenLabs
    2. Resemble.ai
    3. Play.ht
    4. Coqui TTS (coqui-ai/TTS)
    5. Meta Voicebox
    6. Google Cloud Text-to-Speech
    7. Microsoft Azure AI Speech

    AI recommended 7 alternatives but never named Zyphra/Zonos. 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 Zyphra/Zonos?
    pass
    AI named Zyphra/Zonos explicitly

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

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

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

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Zyphra/Zonos — 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