RRepoGEO

REPOGEO REPORT · LITE

QwenLM/Qwen2.5-Omni

Default branch main · commit d8a31ca5 · scanned 5/17/2026, 4:52:44 AM

GitHub: 4,000 stars · 325 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
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 QwenLM/Qwen2.5-Omni, 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 to improve categorization

    Why:

    COPY-PASTE FIX
    multimodal-ai, large-language-model, llm, vision-language-model, vlm, audio-language-model, alm, real-time-speech-synthesis, end-to-end-model, qwen
  • highreadme#2
    Reposition the core description to the top of the README

    Why:

    CURRENT
    We release **Qwen2.5-Omni**, the new flagship end-to-end multimodal model in the Qwen series. Designed for comprehensive multimodal perception, it seamlessly processes diverse inputs including text, images, audio, and video, while delivering real-time streaming responses through both text generation and natural speech synthesis. Let's click the video below for more
    COPY-PASTE FIX
    # Qwen2.5-Omni

Qwen2.5-Omni is the new flagship end-to-end multimodal model in the Qwen series. Designed for comprehensive multimodal perception, it seamlessly processes diverse inputs including text, images, audio, and video, while delivering real-time streaming responses through both text generation and natural speech synthesis.

<p align="left">
        <a href="README_CN.md">中文</a> &nbsp｜ &nbsp English&nbsp&nbsp
</p>
<br>

<p align="center">
    
<p>

<p align="center">
        💜 <a href="https://chat.qwenlm.ai/"><b>Qwen Chat</b></a>&nbsp&nbsp | &nbsp&nbsp🤗 <a href="https://huggingface.co/collections/Qwen/qwen25-omni-67de1e5f0f9464dc6314b36e">Hugging Face</a>&nbsp&nbsp | &nbsp&nbsp🤖 <a href="https://modelscope.cn/collections/Qwen25-Omni-a2505ce0d5514e">ModelScope</a>&nbsp&nbsp | &nbsp&nbsp📑 <a href="https://qwenlm.github.io/blog/qwen2.5-omni/">Blog</a>&nbsp&nbsp | &nbsp&nbsp📚 <a href="https://github.com/QwenLM/Qwen2.5-Omni/tree/main/cookbooks">Cookbooks</a>&nbsp&nbsp | &nbsp&nbsp📑 <a href="https://arxiv.org/abs/2503.20215">Paper</a>&nbsp&nbsp
<br>
🖥️ <a href="https://huggingface.co/spaces/Qwen/Qwen2.5-Omni-7B-Demo ">Demo</a>&nbsp&nbsp | &nbsp&nbsp💬 <a href="https://github.com/QwenLM/Qwen/blob/main/assets/wechat.png">WeChat (微信)</a>&nbsp&nbsp | &nbsp&nbsp🫨 <a href="https://discord.gg/CV4E9rpNSD">Discord</a>&nbsp&nbsp | &nbsp&nbsp📑 <a href="https://help.aliyun.com/zh/model-studio/user-guide/qwen-omni">API</a>

</p>
  • mediumhomepage#3
    Add a homepage URL to the repository metadata

    Why:

    COPY-PASTE FIX
    https://qwenlm.github.io/blog/qwen2.5-omni/

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/Qwen2.5-Omni
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
Azure AI Services
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. Azure AI Services · recommended 2×
  2. Azure AI Vision · recommended 2×
  3. Whisper · recommended 2×
  4. Hugging Face Transformers · recommended 2×
  5. Google Gemini · recommended 1×
  • CATEGORY QUERY
    What AI model can process text, images, video, and audio for real-time responses?
    you: not recommended
    AI recommended (in order):
    1. Google Gemini
    2. OpenAI GPT-4o
    3. Azure AI Services
    4. Azure OpenAI Service
    5. Azure AI Vision
    6. Azure AI Speech
    7. Azure AI Language
    8. Meta Llama 3
    9. Meta's Segment Anything Model (SAM)
    10. Whisper
    11. Hugging Face Transformers
    12. BLIP-2
    13. LLaVA
    14. Whisper
    15. Llama 3
    16. Mistral
    17. ImageBind

    AI recommended 17 alternatives but never named QwenLM/Qwen2.5-Omni. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Seeking a single AI solution for integrated multimodal understanding and real-time speech synthesis.
    you: not recommended
    AI recommended (in order):
    1. Google Cloud AI Platform
    2. Vertex AI
    3. Google Cloud Text-to-Speech
    4. Azure AI Services
    5. Azure Cognitive Services
    6. Azure Text to Speech
    7. AWS AI Services
    8. Amazon Rekognition
    9. Amazon Comprehend
    10. Amazon Polly
    11. Hugging Face Transformers
    12. Tacotron 2
    13. FastSpeech 2
    14. HiFi-GAN
    15. WaveGlow
    16. ElevenLabs
    17. Google Cloud Vision AI
    18. Azure AI Vision

    AI recommended 18 alternatives but never named QwenLM/Qwen2.5-Omni. 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/Qwen2.5-Omni?
    pass
    AI named QwenLM/Qwen2.5-Omni explicitly

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

  • If a team adopts QwenLM/Qwen2.5-Omni in production, what risks or prerequisites should they evaluate first?
    pass
    AI named QwenLM/Qwen2.5-Omni 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/Qwen2.5-Omni solve, and who is the primary audience?
    pass
    AI named QwenLM/Qwen2.5-Omni explicitly

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

Embed your GEO score

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QwenLM/Qwen2.5-Omni — 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