RRepoGEO

REPOGEO REPORT · LITE

zai-org/GLM-ASR

Default branch main · commit a324aa59 · scanned 6/9/2026, 6:38:02 PM

GitHub: 809 stars · 76 forks

AI VISIBILITY SCORE
40 /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
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 zai-org/GLM-ASR, 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
  • highabout#1
    Update repository description to highlight unique strengths

    Why:

    CURRENT
    GLM-ASR-Nano: A robust, open-source speech recognition model with 1.5B parameters
    COPY-PASTE FIX
    GLM-ASR-Nano: A robust, open-source speech recognition model (1.5B params) excelling in diverse dialects and quiet speech scenarios, outperforming Whisper V3.
  • hightopics#2
    Add specific topics for dialect and quiet speech recognition

    Why:

    CURRENT
    asr, edge, llm, voice
    COPY-PASTE FIX
    asr, speech-to-text, dialect-recognition, quiet-speech, low-volume-audio, whisper-alternative, mandarin, cantonese, llm-asr
  • mediumreadme#3
    Add a concise, benefit-driven sentence to the top of the README

    Why:

    COPY-PASTE FIX
    Add this line right after `# GLM-ASR` and before the community links: "GLM-ASR-Nano is a 1.5B parameter open-source ASR model designed for real-world complexity, excelling in diverse dialects and quiet speech, and outperforming OpenAI Whisper V3."

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-ASR
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
openai/whisper
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. openai/whisper · recommended 1×
  2. mozilla/DeepSpeech · recommended 1×
  3. pytorch/fairseq · recommended 1×
  4. espnet/espnet · recommended 1×
  5. kaldi-asr/kaldi · recommended 1×
  • CATEGORY QUERY
    What are robust open-source speech recognition models that handle diverse dialects?
    you: not recommended
    AI recommended (in order):
    1. Whisper (openai/whisper)
    2. Mozilla DeepSpeech (mozilla/DeepSpeech)
    3. Wav2Vec 2.0 (pytorch/fairseq)
    4. ESPnet (espnet/espnet)
    5. Kaldi (kaldi-asr/kaldi)

    AI recommended 5 alternatives but never named zai-org/GLM-ASR. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Seeking an accurate speech-to-text model for quiet audio and various language dialects.
    you: not recommended
    AI recommended (in order):
    1. Whisper
    2. Google Cloud Speech-to-Text
    3. Amazon Transcribe
    4. Azure Cognitive Services Speech
    5. AssemblyAI

    AI recommended 5 alternatives but never named zai-org/GLM-ASR. 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-ASR?
    pass
    AI named zai-org/GLM-ASR 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-ASR in production, what risks or prerequisites should they evaluate first?
    pass
    AI named zai-org/GLM-ASR 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-ASR solve, and who is the primary audience?
    pass
    AI named zai-org/GLM-ASR 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 zai-org/GLM-ASR. 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/zai-org/GLM-ASR.svg)](https://repogeo.com/en/r/zai-org/GLM-ASR)
HTML
<a href="https://repogeo.com/en/r/zai-org/GLM-ASR"><img src="https://repogeo.com/badge/zai-org/GLM-ASR.svg" alt="RepoGEO" /></a>
Pro

Subscribe to Pro for deep diagnoses

zai-org/GLM-ASR — 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