RRepoGEO

REPOGEO REPORT · LITE

QwenLM/Qwen-Image

Default branch main · commit 6b5e1f5c · scanned 5/14/2026, 12:17:59 PM

GitHub: 7,885 stars · 492 forks

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 QwenLM/Qwen-Image, 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

2 prioritized changes generated by gemini-2.5-flash. Mark items done after you ship the fix.

OVERALL DIRECTION
  • highreadme#1
    Reposition the core value proposition at the top of the README

    Why:

    CURRENT
    <p align="center">
    
<p> 
<p align="center">&nbsp&nbsp💜 <a href="https://chat.qwen.ai/">Qwen Chat</a>&nbsp&nbsp |
           &nbsp&nbsp🤗 <a href="https://huggingface.co/Qwen/Qwen-Image">HuggingFace(T2I)</a>&nbsp&nbsp |
           &nbsp&nbsp🤗 <a href="https://huggingface.co/Qwen/Qwen-Image-Edit-2511">HuggingFace(Edit)</a>&nbsp&nbsp | &nbsp&nbsp🤖 <a href="https://modelscope.cn/models/Qwen/Qwen-Image">ModelScope-T2I</a>&nbsp&nbsp | &nbsp&nbsp🤖 <a href="https://modelscope.cn/models/Qwen/Qwen-Image-Edit-2511">ModelScope-Edit</a>&nbsp&nbsp| &nbsp&nbsp 📑 <a href="https://arxiv.org/abs/2508.02324">Tech Report</a> &nbsp&nbsp | &nbsp&nbsp 📑 <a href="https://qwenlm.github.io/blog/qwen-image/">Blog(T2I)</a> &nbsp&nbsp | &nbsp&nbsp 📑 <a href="https://qwenlm.github.io/blog/qwen-image-edit-2511/">Blog(Edit)</a> &nbsp&nbsp 
<br>
🖥️ <a href="https://huggingface.co/spaces/Qwen/Qwen-Image">T2I Demo</a>&nbsp&nbsp | 🖥️ <a href="https://huggingface.co/spaces/Qwen/Qwen-Image-Edit-2511">Edit Demo</a>&nbsp&nbsp | &nbsp&nbsp💬 <a href="https://github.com/QwenLM/Qwen-Image/blob/main/assets/wechat.png">WeChat (微信)</a>&nbsp&nbsp | &nbsp&nbsp🫨 <a href="https://discord.gg/CV4E9rpNSD">Discord</a>&nbsp&nbsp
</p>

<p align="center">
    
<p>

## Introduction
We are thrilled to release **Qwen-Image**, a 20B MMDiT image foundation model that achieves significant advances in **complex text rendering** and **precise image editing**. Experiments show strong general capabilities in both
    COPY-PASTE FIX
    Qwen-Image is a powerful 20B MMDiT image foundation model, excelling in high-quality image generation with complex text rendering and precise image editing capabilities.

<p align="center">
    
<p> 
<p align="center">&nbsp&nbsp💜 <a href="https://chat.qwen.ai/">Qwen Chat</a>&nbsp&nbsp |
           &nbsp&nbsp🤗 <a href="https://huggingface.co/Qwen/Qwen-Image">HuggingFace(T2I)</a>&nbsp&nbsp |
           &nbsp&nbsp🤗 <a href="https://huggingface.co/Qwen/Qwen-Image-Edit-2511">HuggingFace(Edit)</a>&nbsp&nbsp | &nbsp&nbsp🤖 <a href="https://modelscope.cn/models/Qwen/Qwen-Image">ModelScope-T2I</a>&nbsp&nbsp | &nbsp&nbsp🤖 <a href="https://modelscope.cn/models/Qwen/Qwen-Image-Edit-2511">ModelScope-Edit</a>&nbsp&nbsp| &nbsp&nbsp 📑 <a href="https://arxiv.org/abs/2508.02324">Tech Report</a> &nbsp&nbsp | &nbsp&nbsp 📑 <a href="https://qwenlm.github.io/blog/qwen-image/">Blog(T2I)</a> &nbsp&nbsp | &nbsp&nbsp 📑 <a href="https://qwenlm.github.io/blog/qwen-image-edit-2511/">Blog(Edit)</a> &nbsp&nbsp 
<br>
🖥️ <a href="https://huggingface.co/spaces/Qwen/Qwen-Image">T2I Demo</a>&nbsp&nbsp | 🖥️ <a href="https://huggingface.co/spaces/Qwen/Qwen-Image-Edit-2511">Edit Demo</a>&nbsp&nbsp | &nbsp&nbsp💬 <a href="https://github.com/QwenLM/Qwen-Image/blob/main/assets/wechat.png">WeChat (微信)</a>&nbsp&nbsp | &nbsp&nbsp🫨 <a href="https://discord.gg/CV4E9rpNSD">Discord</a>&nbsp&nbsp
</p>

<p align="center">
    
<p>

## Introduction
We are thrilled to release **Qwen-Image**, a 20B MMDiT image foundation model that achieves significant advances in **complex text rendering** and **precise image editing**. Experiments show strong general capabilities in both
  • mediumhomepage#2
    Add a homepage URL to the repository's About section

    Why:

    COPY-PASTE FIX
    https://huggingface.co/Qwen/Qwen-Image

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 QwenLM/Qwen-Image
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
DALL-E 3
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. DALL-E 3 · recommended 2×
  2. ChatGPT Plus · recommended 2×
  3. Microsoft Copilot · recommended 2×
  4. Adobe Firefly · recommended 2×
  5. Midjourney · recommended 1×
  • CATEGORY QUERY
    What AI models can generate high-quality images with accurate text rendering capabilities?
    you: not recommended
    AI recommended (in order):
    1. Midjourney
    2. DALL-E 3
    3. ChatGPT Plus
    4. Microsoft Copilot
    5. Stable Diffusion XL
    6. ControlNet
    7. Adobe Firefly
    8. Adobe Creative Cloud
    9. Ideogram
    10. DeepFloyd IF

    AI recommended 10 alternatives but never named QwenLM/Qwen-Image. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Seeking a powerful foundation model for precise image editing and manipulation from text prompts.
    you: not recommended
    AI recommended (in order):
    1. DALL-E 3
    2. ChatGPT Plus
    3. Microsoft Copilot
    4. Midjourney v6
    5. Stable Diffusion XL (SDXL)
    6. ControlNet (lllyasviel/ControlNet)
    7. Automatic1111 (AUTOMATIC1111/stable-diffusion-webui)
    8. ComfyUI (comfyanonymous/ComfyUI)
    9. Adobe Firefly
    10. Photoshop
    11. Imagen 2
    12. Google Cloud Vertex AI
    13. Leonardo.Ai

    AI recommended 13 alternatives but never named QwenLM/Qwen-Image. 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 QwenLM/Qwen-Image?
    pass
    AI did not name QwenLM/Qwen-Image — 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 QwenLM/Qwen-Image in production, what risks or prerequisites should they evaluate first?
    pass
    AI named QwenLM/Qwen-Image 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 QwenLM/Qwen-Image solve, and who is the primary audience?
    pass
    AI named QwenLM/Qwen-Image explicitly

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

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QwenLM/Qwen-Image — 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