RRepoGEO

REPOGEO REPORT · LITE

huggingface/distil-whisper

Default branch main · commit cc96130f · scanned 6/25/2026, 10:52:59 AM

GitHub: 4,086 stars · 352 forks

Scan history for this repo

Score trend below includes all ready runs (older left, newer right; scroll horizontally if needed). The table is collapsed by default—expand for newest-first rows, 10 per page.

Score trend (left → right: older → newer)

3 ready scans. Expand the table below for newest-first rows (10 per page, paginated).

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 huggingface/distil-whisper, 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
  • hightopics#1
    Add specific topics for efficiency and deployment

    Why:

    CURRENT
    audio, speech-recognition, whisper
    COPY-PASTE FIX
    audio, speech-recognition, whisper, real-time, edge-ai, resource-efficient, inference-optimization
  • mediumhomepage#2
    Populate the 'homepage' field in the repository settings

    Why:

    COPY-PASTE FIX
    https://huggingface.co/collections/distil-whisper/distil-whisper-models-65411987e6727569748d2eb6
  • lowreadme#3
    Enhance the README's opening to explicitly state target deployment scenarios

    Why:

    CURRENT
    Distil-Whisper is a distilled version of Whisper for English speech recognition that is **6 times faster**, 49% smaller, and performs **within 1% word error rate (WER)** on out-of-distribution evaluation sets:
    COPY-PASTE FIX
    Distil-Whisper is a distilled version of Whisper for English speech recognition, offering **6 times faster** inference and a 49% smaller footprint while maintaining **within 1% word error rate (WER)**. This makes it ideal for **real-time, edge, and resource-constrained deployments** where efficiency is critical:

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 huggingface/distil-whisper
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
Google Cloud Speech-to-Text
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. Google Cloud Speech-to-Text · recommended 2×
  2. AssemblyAI · recommended 2×
  3. openai/whisper · recommended 1×
  4. Amazon Transcribe · recommended 1×
  5. OpenAI Whisper · recommended 1×
  • CATEGORY QUERY
    Looking for a highly efficient speech-to-text model for real-time applications.
    you: not recommended
    AI recommended (in order):
    1. OpenAI Whisper (openai/whisper)
    2. Google Cloud Speech-to-Text
    3. AssemblyAI
    4. Amazon Transcribe

    AI recommended 4 alternatives but never named huggingface/distil-whisper. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Need a fast and accurate English audio transcription solution with a smaller footprint.
    you: not recommended
    AI recommended (in order):
    1. OpenAI Whisper
    2. Mozilla DeepSpeech
    3. Picovoice Rhino Speech-to-Text
    4. Google Cloud Speech-to-Text
    5. AssemblyAI

    AI recommended 5 alternatives but never named huggingface/distil-whisper. 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 huggingface/distil-whisper?
    pass
    AI named huggingface/distil-whisper explicitly

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

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

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

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huggingface/distil-whisper — RepoGEO report