RRepoGEO

REPOGEO REPORT · LITE

THUDM/GLM

Default branch main · commit 4f61ed72 · scanned 5/26/2026, 12:58:05 AM

GitHub: 3,501 stars · 352 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 THUDM/GLM, 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 relevant topics for language models and NLP

    Why:

    COPY-PASTE FIX
    large-language-model, llm, nlp, natural-language-processing, deep-learning, pretraining, autoregressive-model, blank-filling, chinese-llm
  • highreadme#2
    Reposition the README H1 to clearly state GLM is an open-source pretrained model

    Why:

    CURRENT
    # GLM

GLM is a General Language Model pretrained with an autoregressive blank-filling objective and can be finetuned on various natural language understanding and generation tasks.
    COPY-PASTE FIX
    # GLM

GLM is an open-source General Language Model (GLM) that provides pretrained models, developed using an autoregressive blank-filling objective, and designed for finetuning on various natural language understanding and generation tasks.
  • mediumreadme#3
    Add a sentence highlighting GLM's strength in Chinese language tasks

    Why:

    COPY-PASTE FIX
    Building on the GLM framework, models like ChatGLM-6B demonstrate strong performance, particularly optimized for Chinese QA and dialogue.

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 THUDM/GLM
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
Llama 3
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. Llama 3 · recommended 1×
  2. Mistral 7B · recommended 1×
  3. Mixtral 8x7B · recommended 1×
  4. Gemma · recommended 1×
  5. Falcon · recommended 1×
  • CATEGORY QUERY
    What are good open-source general language models for natural language understanding and generation?
    you: not recommended
    AI recommended (in order):
    1. Llama 3
    2. Mistral 7B
    3. Mixtral 8x7B
    4. Gemma
    5. Falcon
    6. LLaMA 2
    7. OpenHermes 2.5
    8. OpenHermes 2.5 Mistral 7B
    9. Zephyr 7B Beta

    AI recommended 9 alternatives but never named THUDM/GLM. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    How to pretrain a language model using an autoregressive blank-filling objective?
    you: not recommended
    AI recommended (in order):
    1. Hugging Face Transformers
    2. PyTorch
    3. TensorFlow
    4. Keras
    5. JAX
    6. Flax
    7. DeepSpeed
    8. Fairseq

    AI recommended 8 alternatives but never named THUDM/GLM. 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 THUDM/GLM?
    pass
    AI named THUDM/GLM explicitly

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

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

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

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THUDM/GLM — 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