RRepoGEO

REPOGEO REPORT · LITE

antirez/voxtral.c

Default branch main · commit 134d366c · scanned 5/27/2026, 4:43:30 PM

GitHub: 1,666 stars · 118 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 antirez/voxtral.c, 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

2 prioritized changes generated by gemini-2.5-flash. Mark items done after you ship the fix.

OVERALL DIRECTION
  • highreadme#1
    Reposition the README H1 to explicitly state 'speech-to-text'

    Why:

    CURRENT
    # Voxtral Realtime 4B Pure C Implementation
    COPY-PASTE FIX
    # Voxtral Realtime 4B Speech-to-Text: Pure C Implementation
  • mediumreadme#2
    Clarify the README's first paragraph to emphasize speech-to-text

    Why:

    CURRENT
    This is a C implementation of the inference pipeline for the Mistral AI's Voxtral Realtime 4B model. It has zero external dependencies beyond the C standard library. The MPS inference is decently fast, while the BLAS acceleration is usable but slow (it continuously convert the bf16 weights to fp32).
    COPY-PASTE FIX
    This project provides a pure C, zero-dependency implementation of the Mistral AI's Voxtral Realtime 4B **speech-to-text** model inference pipeline. It enables efficient, real-time audio transcription with minimal external requirements. The MPS inference is decently fast, while the BLAS acceleration is usable but slow (it continuously convert the bf16 weights to fp32).

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 antirez/voxtral.c
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
Vosk
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. Vosk · recommended 1×
  2. Picovoice Rhino Speech-to-Text Engine · recommended 1×
  3. Mozilla DeepSpeech · recommended 1×
  4. Pocketsphinx · recommended 1×
  5. TensorFlow Lite · recommended 1×
  • CATEGORY QUERY
    What are the best pure C libraries for real-time speech-to-text on embedded systems?
    you: not recommended
    AI recommended (in order):
    1. Vosk
    2. Picovoice Rhino Speech-to-Text Engine
    3. Mozilla DeepSpeech
    4. Pocketsphinx
    5. TensorFlow Lite
    6. Edge Impulse

    AI recommended 6 alternatives but never named antirez/voxtral.c. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    How to implement efficient streaming audio transcription with minimal external dependencies?
    you: not recommended
    AI recommended (in order):
    1. Whisper (openai/whisper)
    2. VOSK (alphacep/vosk-api)
    3. Mozilla DeepSpeech (mozilla/DeepSpeech)
    4. Picovoice Rhino/Cheetah
    5. CMU Sphinx (cmusphinx/pocketsphinx)

    AI recommended 5 alternatives but never named antirez/voxtral.c. 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 antirez/voxtral.c?
    pass
    AI named antirez/voxtral.c explicitly

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

  • If a team adopts antirez/voxtral.c in production, what risks or prerequisites should they evaluate first?
    pass
    AI named antirez/voxtral.c 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 antirez/voxtral.c solve, and who is the primary audience?
    pass
    AI named antirez/voxtral.c 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 antirez/voxtral.c. 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/antirez/voxtral.c.svg)](https://repogeo.com/en/r/antirez/voxtral.c)
HTML
<a href="https://repogeo.com/en/r/antirez/voxtral.c"><img src="https://repogeo.com/badge/antirez/voxtral.c.svg" alt="RepoGEO" /></a>
Pro

Subscribe to Pro for deep diagnoses

antirez/voxtral.c — 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
antirez/voxtral.c — RepoGEO report