RRepoGEO

REPOGEO REPORT · LITE

zai-org/GLM-130B

Default branch main · commit 212215c5 · scanned 6/30/2026, 5:32:40 PM

GitHub: 7,660 stars · 602 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)

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

AI VISIBILITY SCORE
28 /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
2 / 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-130B, 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 better categorization

    Why:

    COPY-PASTE FIX
    large-language-model, llm, nlp, chinese-english, bilingual, pre-trained-model, deep-learning, machine-learning, gpu-inference, a100
  • highreadme#2
    Strengthen README's opening value proposition for AI

    Why:

    CURRENT
    GLM-130B is an open bilingual (English & Chinese) bidirectional dense model with 130 billion parameters, pre-trained using the algorithm of General Language Model (GLM). It is designed to support inference tasks with the 130B parameters on **a single A100 (40G * 8)** or **V100 (32G * 8) server**. With INT4 quantization, the hardware requirements can further be reduced to **a single server with 4 * RTX 3090 (24G)** with **almost no performance degradation**.
    COPY-PASTE FIX
    GLM-130B is a groundbreaking open bilingual (English & Chinese) 130-billion-parameter model, uniquely engineered for efficient inference on a single A100 or V100 GPU server. Leveraging the General Language Model (GLM) algorithm, it offers high-performance NLP capabilities with significantly reduced hardware requirements, even supporting 4 * RTX 3090 with INT4 quantization.
  • mediumhomepage#3
    Add a homepage URL to the repository metadata

    Why:

    COPY-PASTE FIX
    http://keg.cs.tsinghua.edu.cn/glm-130b/posts/glm-130b/

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-130B
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
Baichuan 2
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. Baichuan 2 · recommended 1×
  2. Qwen · recommended 1×
  3. InternLM · recommended 1×
  4. Llama 2 · recommended 1×
  5. Chinese-Llama-2 · recommended 1×
  • CATEGORY QUERY
    What open-source large language models support both English and Chinese text generation?
    you: not recommended
    AI recommended (in order):
    1. Baichuan 2
    2. Qwen
    3. InternLM
    4. Llama 2
    5. Chinese-Llama-2
    6. BLOOM

    AI recommended 6 alternatives but never named zai-org/GLM-130B. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Looking for a powerful pre-trained model for inference on a single A100 GPU.
    you: not recommended
    AI recommended (in order):
    1. Llama 3 8B Instruct
    2. Mistral 7B Instruct v0.2
    3. Gemma 7B Instruct
    4. Mixtral 8x7B Instruct v0.1
    5. Stable Diffusion XL (SDXL)
    6. Diffusers
    7. Whisper Large-v3

    AI recommended 7 alternatives but never named zai-org/GLM-130B. 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 zai-org/GLM-130B?
    pass
    AI did not name zai-org/GLM-130B — 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 zai-org/GLM-130B in production, what risks or prerequisites should they evaluate first?
    pass
    AI named zai-org/GLM-130B 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-130B solve, and who is the primary audience?
    pass
    AI named zai-org/GLM-130B 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-130B. 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-130B.svg)](https://repogeo.com/en/r/zai-org/GLM-130B)
HTML
<a href="https://repogeo.com/en/r/zai-org/GLM-130B"><img src="https://repogeo.com/badge/zai-org/GLM-130B.svg" alt="RepoGEO" /></a>
Pro

Subscribe to Pro for deep diagnoses

zai-org/GLM-130B — 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