RRepoGEO

REPOGEO REPORT · LITE

zai-org/CogVLM

Default branch main · commit f7283b2c · scanned 5/17/2026, 9:47:23 AM

GitHub: 6,743 stars · 454 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
59 /100
Needs work
Category recall
1 / 2
Avg rank #2.0 when recommended
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/CogVLM, 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
    Strengthen README's opening statement for benchmark performance

    Why:

    CURRENT
    # CogVLM & CogAgent

📗 [中文版README](./README_zh.md)
    COPY-PASTE FIX
    # CogVLM & CogAgent

**CogVLM and CogAgent are state-of-the-art open visual language models, achieving top performance across numerous cross-modal understanding benchmarks and offering advanced high-resolution image processing capabilities.**

📗 [中文版README](./README_zh.md)
  • mediumtopics#2
    Add 'high-resolution-vlm' topic

    Why:

    CURRENT
    cross-modality, language-model, multi-modal, pretrained-models, visual-language-models
    COPY-PASTE FIX
    cross-modality, language-model, multi-modal, pretrained-models, visual-language-models, high-resolution-vlm
  • lowhomepage#3
    Add a homepage URL to the repository About section

    Why:

    COPY-PASTE FIX
    https://arxiv.org/abs/2311.03079

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
1 / 2
50% of queries surface zai-org/CogVLM
Avg rank
#2.0
Lower is better. #1 = top recommendation.
Share of voice
8%
Of all named tools, what % are you?
Top rival
LLaVA
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. LLaVA · recommended 1×
  2. MiniGPT-4 · recommended 1×
  3. InstructBLIP · recommended 1×
  4. Qwen-VL · recommended 1×
  5. Fuyu-8B · recommended 1×
  • CATEGORY QUERY
    What are the best open-source visual language models for image understanding and multi-turn dialogue?
    you: #2
    AI recommended (in order):
    1. LLaVA
    2. CogVLM ← you
    3. MiniGPT-4
    4. InstructBLIP
    5. Qwen-VL
    6. Fuyu-8B
    Show full AI answer
  • CATEGORY QUERY
    Looking for a powerful pretrained multi-modal model to improve cross-modal understanding benchmarks.
    you: not recommended
    AI recommended (in order):
    1. GPT-4o
    2. Gemini
    3. LLaVA (haotian-liu/LLaVA)
    4. CLIP (openai/CLIP)
    5. BLIP-2 (salesforce/BLIP)
    6. Flamingo (deepmind/flamingo)

    AI recommended 6 alternatives but never named zai-org/CogVLM. 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/CogVLM?
    pass
    AI did not name zai-org/CogVLM — 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/CogVLM in production, what risks or prerequisites should they evaluate first?
    pass
    AI named zai-org/CogVLM 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/CogVLM solve, and who is the primary audience?
    pass
    AI named zai-org/CogVLM explicitly

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

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zai-org/CogVLM — 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