RRepoGEO

REPOGEO REPORT · LITE

TrevorS/voxtral-mini-realtime-rs

Default branch main · commit 2930e95d · scanned 6/11/2026, 2:07:09 PM

GitHub: 792 stars · 50 forks

AI VISIBILITY SCORE
27 /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
1 / 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 TrevorS/voxtral-mini-realtime-rs, 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
    Reposition the README's opening statement to clarify its unique value

    Why:

    CURRENT
    Streaming speech recognition and text-to-speech running natively and in the browser. A pure Rust implementation of Mistral's Voxtral Mini 4B Realtime (ASR) and Voxtral 4B TTS models using the Burn ML framework.
    COPY-PASTE FIX
    **Voxtral Mini 4B Realtime (Rust)** provides a lightweight, real-time, and self-hostable solution for streaming speech recognition (ASR) and text-to-speech (TTS). It's a pure Rust implementation of Mistral's Voxtral Mini 4B models, built with the Burn ML framework for native and browser (WASM) deployment.
  • mediumreadme#2
    Add a dedicated section explaining the project's unique advantages

    Why:

    COPY-PASTE FIX
    ## Why Voxtral Mini Realtime (Rust)?
    
    Unlike cloud-based APIs or generic ML frameworks, Voxtral Mini Realtime (Rust) offers:
    
    - **Full Control & Privacy:** Run models entirely on your infrastructure, without sending data to third-party services.
    - **Real-time Performance:** Optimized for low-latency ASR and TTS, ideal for interactive applications.
    - **Lightweight & Efficient:** Designed for resource-constrained environments, leveraging Rust's performance and Burn ML's efficiency.
    - **Native & Web Deployment:** Seamlessly deploy across desktop, server, and browser (via WASM) targets.
    - **Rust Ecosystem Integration:** Benefit from Rust's safety, speed, and growing ML ecosystem.
  • lowtopics#3
    Add 'edge-computing' and 'embedded' to repository topics

    Why:

    CURRENT
    asr, audio, burn, mistral, q4, rust, speech, tts, voxtral, voxtral-mini-realtime, wasm
    COPY-PASTE FIX
    asr, audio, burn, mistral, q4, rust, speech, tts, voxtral, voxtral-mini-realtime, wasm, edge-computing, embedded

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 TrevorS/voxtral-mini-realtime-rs
Avg rank
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
Azure Cognitive Services Speech
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. Azure Cognitive Services Speech · recommended 2×
  2. alphacep/vosk-api · recommended 1×
  3. mozilla/DeepSpeech · recommended 1×
  4. Google Cloud Speech-to-Text · recommended 1×
  5. Google Cloud Text-to-Speech · recommended 1×
  • CATEGORY QUERY
    How to implement real-time speech recognition and text-to-speech in a Rust application?
    you: not recommended
    AI recommended (in order):
    1. Vosk (alphacep/vosk-api)
    2. DeepSpeech (mozilla/DeepSpeech)
    3. Google Cloud Speech-to-Text
    4. Azure Cognitive Services Speech
    5. Google Cloud Text-to-Speech
    6. Azure Cognitive Services Speech
    7. Amazon Polly
    8. eSpeak NG (espeak-ng/espeak-ng)
    9. Piper (rhasspy/piper)

    AI recommended 9 alternatives but never named TrevorS/voxtral-mini-realtime-rs. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What are options for deploying speech-to-text and text-to-speech models in a browser via WASM?
    you: not recommended
    AI recommended (in order):
    1. Transformers.js (huggingface/transformers.js)
    2. ONNX Runtime Web (microsoft/onnxruntime-web)
    3. Web LLM (MLC LLM) (mlc-ai/mlc-llm)
    4. TensorFlow.js (tensorflow/tfjs)
    5. MediaPipe (Google) (google/mediapipe)
    6. Emscripten (emscripten-core/emscripten)
    7. wasm-pack (rustwasm/wasm-pack)

    AI recommended 7 alternatives but never named TrevorS/voxtral-mini-realtime-rs. 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 TrevorS/voxtral-mini-realtime-rs?
    pass
    AI did not name TrevorS/voxtral-mini-realtime-rs — 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 TrevorS/voxtral-mini-realtime-rs in production, what risks or prerequisites should they evaluate first?
    pass
    AI named TrevorS/voxtral-mini-realtime-rs 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 TrevorS/voxtral-mini-realtime-rs solve, and who is the primary audience?
    pass
    AI did not name TrevorS/voxtral-mini-realtime-rs — 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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TrevorS/voxtral-mini-realtime-rs — 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