{
  "@context": "https://schema.org",
  "@id": "https://aggr.aymericbeaumet.com/items/qwen-ai/2025-12-08-qwen3-omni-flash-2025-12-01-hear-you-see-you-follow-smarter/#webpage",
  "@type": [
    "WebPage",
    "ArchiveComponent"
  ],
  "articleBody": "![](https://qianwen-res.oss-accelerate-overseas.aliyuncs.com/Qwen3-Omni-Flash-2025-12-01/q3o251201.png#center)\n\n[QWEN CHAT](https://chat.qwenlm.ai) [HUGGING FACE](https://huggingface.co/collections/Qwen/qwen3-omni-68d100a86cd0906843ceccbe) [MODELSCOPE](https://modelscope.cn/collections/Qwen3-Omni-867aef131e7d4f) [DASHSCOPE](https://www.alibabacloud.com/help/en/model-studio/qwen-omni) [GITHUB](https://github.com/QwenLM/Qwen3-Omni) [PAPER](https://github.com/QwenLM/Qwen3-Omni/tree/main/assets/Qwen3_Omni.pdf) [HUGGING FACE DEMO](https://huggingface.co/spaces/Qwen/Qwen3-Omni-Demo) [MODELSCOPE DEMO](https://modelscope.cn/studios/Qwen/Qwen3-Omni-Demo)\n\n**Qwen3-Omni** is a next-generation native multimodal large model capable of seamlessly processing multiple input modalities—including text, images, audio, and video—and generating both text and natural-sounding speech outputs simultaneously via real-time streaming responses. This version introduces multiple enhancements to improve model performance and efficiency.\n\n**Qwen3-Omni-Flash-2025-12-01** is a comprehensively upgraded iteration built upon Qwen3-Omni.\n\nKey highlights of this upgraded version include:\n\n- **Greatly Enhanced Audio-Visual Interaction Experience**: Dramatically improved understanding and execution of audio-visual instructions, effectively resolving the “intelligence drop” issue commonly seen in casual spoken scenarios. Multi-turn audio-visual conversations now achieve significantly higher stability and coherence, enabling more natural and seamless interactions.\n\n- **Strengthened System Prompt Control**: Full customization of system prompts is now supported, enabling precise control over model behavior. Whether it’s persona style (e.g., sweet, cool, anime-inspired), colloquial tone preferences, or output length constraints—every detail can be finely tuned, offering unprecedented command over response characteristics.\n\n- **More Reliable Multilingual Compliance**: Supports text-based interaction in **119 languages**, speech recognition in **19 languages**, and speech synthesis in **10 languages**. Language-following instability from the previous version has been fully addressed, ensuring accurate and consistent performance across diverse linguistic contexts.\n\n- **More Human-Like and Fluent Speech Synthesis**: Eliminates sluggish or robotic speech by significantly enhancing adaptive control over prosody. The model now intelligently adjusts speaking rate, pauses, and intonation based on textual context, delivering expressive, natural-sounding voice output that closely mimics real human speech.\n\n[www.youtube.com](https://www.youtube.com/watch?v=Q4CBTckDAls)\n\n## Performance\n\nOn objective benchmarks, **Qwen3-Omni-Flash-2025-12-01** achieves substantial improvements across all modalities compared to **Qwen3-Omni-Flash**:\n\n- **🧠 Stronger Text Understanding & Generation**:\\\n  Major gains in logical reasoning (**ZebraLogic +5.6**), code generation (**LiveCodeBench-v6 +9.3**, **MultiPL-E +2.7**), and holistic writing quality (**WritingBench +2.2**), enabling more reliable execution of complex, multi-step instructions.\n\n- **👂 More Accurate Speech Understanding**:\\\n  Significantly lower word error rate on **Fleurs-zh**, along with a **+3.2** improvement on **VoiceBench**, reflecting enhanced comprehension of spoken language in real-world dialogue scenarios.\n\n- **🎙️ More Natural Speech Synthesis**:\\\n  Higher-quality, human-like voice generation across multiple languages—especially in Chinese and multilingual contexts—with improved prosody, pacing, and pausing that closely mirrors natural human speech.\n\n- **👁️ Deeper Image Understanding**:\\\n  Breakthrough performance on visual reasoning tasks, including **+4.7** on **MMMU**, **+4.8** on **MMMU-Pro**, and **+2.2** on **MathVision\\_full**, demonstrating a stronger ability to “see,” interpret, and reason about complex visual content—from diagrams to mathematical figures.\n\n- **🎬 More Coherent Video Understanding**:\\\n  Steady improvement in video semantic comprehension (**MLVU +1.6**), further strengthened by tighter audio-visual synchronization, laying a solid foundation for seamless real-time video conversations.\n\nWith this upgrade, **Qwen3-Omni-Flash-2025-12-01** truly embodies the vision of **“Hear You. See You. Follow Smarter.”**—delivering an AI interaction experience that is more natural, precise, and vivid than ever before.\n\n![](http://qianwen-res.oss-accelerate.aliyuncs.com/Qwen3-Omni-Flash-2025-12-01/q3o251201_metric.png#center)\n\n## What’s Next\n\nWe are eager to hear your feedback and see the innovative applications you create with Qwen3-Omni. In the near future, we will further advance the model along multiple axes, including multi-speaker ASR, video OCR, audio–video proactive learning, and enhance support for agent-based workflows and function calling.\n\n## Citation\n\nIf you find our model helpful in your research, we’d appreciate a citation!\n\n```bibtex\n@misc{qwen3_omni_20251201,\nauthor = {{Qwen Team, Alibaba}},\ntitle = {{Qwen3-Omni-Flash-2025-12-01：Hear You. See You. Follow Smarter!}},\nyear = {2025},\nurl = {https://qwen.ai/blog?id=qwen3-omni-20251201},\nurldate = {2025-12-05}\n}\n```\n",
  "authors": [
    "QwenTeam"
  ],
  "captured_at": "2026-10-18T23:27:08.867657739+00:00",
  "category": "ai",
  "content_html": "<p><picture class=\"article-picture article-picture-fallback\" style=\"--image-ratio:16 / 9\"><img src=\"https://qianwen-res.oss-accelerate-overseas.aliyuncs.com/Qwen3-Omni-Flash-2025-12-01/q3o251201.png#center\" alt=\"\" loading=\"eager\" decoding=\"async\" fetchpriority=\"high\" referrerpolicy=\"no-referrer\" class=\"progressive-image\"></picture></p>\n<p><a target=\"_blank\" rel=\"noopener noreferrer\" href=\"https://chat.qwenlm.ai\">QWEN CHAT</a> <a target=\"_blank\" rel=\"noopener noreferrer\" href=\"https://huggingface.co/collections/Qwen/qwen3-omni-68d100a86cd0906843ceccbe\">HUGGING FACE</a> <a target=\"_blank\" rel=\"noopener noreferrer\" href=\"https://modelscope.cn/collections/Qwen3-Omni-867aef131e7d4f\">MODELSCOPE</a> <a target=\"_blank\" rel=\"noopener noreferrer\" href=\"https://www.alibabacloud.com/help/en/model-studio/qwen-omni\">DASHSCOPE</a> <a target=\"_blank\" rel=\"noopener noreferrer\" href=\"https://github.com/QwenLM/Qwen3-Omni\">GITHUB</a> <a target=\"_blank\" rel=\"noopener noreferrer\" href=\"https://github.com/QwenLM/Qwen3-Omni/tree/main/assets/Qwen3_Omni.pdf\">PAPER</a> <a target=\"_blank\" rel=\"noopener noreferrer\" href=\"https://huggingface.co/spaces/Qwen/Qwen3-Omni-Demo\">HUGGING FACE DEMO</a> <a target=\"_blank\" rel=\"noopener noreferrer\" href=\"https://modelscope.cn/studios/Qwen/Qwen3-Omni-Demo\">MODELSCOPE DEMO</a></p>\n<p><strong>Qwen3-Omni</strong> is a next-generation native multimodal large model capable of seamlessly processing multiple input modalities—including text, images, audio, and video—and generating both text and natural-sounding speech outputs simultaneously via real-time streaming responses. This version introduces multiple enhancements to improve model performance and efficiency.</p>\n<p><strong>Qwen3-Omni-Flash-2025-12-01</strong> is a comprehensively upgraded iteration built upon Qwen3-Omni.</p>\n<p>Key highlights of this upgraded version include:</p>\n<ul>\n<li>\n<p><strong>Greatly Enhanced Audio-Visual Interaction Experience</strong>: Dramatically improved understanding and execution of audio-visual instructions, effectively resolving the “intelligence drop” issue commonly seen in casual spoken scenarios. Multi-turn audio-visual conversations now achieve significantly higher stability and coherence, enabling more natural and seamless interactions.</p>\n</li>\n<li>\n<p><strong>Strengthened System Prompt Control</strong>: Full customization of system prompts is now supported, enabling precise control over model behavior. Whether it’s persona style (e.g., sweet, cool, anime-inspired), colloquial tone preferences, or output length constraints—every detail can be finely tuned, offering unprecedented command over response characteristics.</p>\n</li>\n<li>\n<p><strong>More Reliable Multilingual Compliance</strong>: Supports text-based interaction in <strong>119 languages</strong>, speech recognition in <strong>19 languages</strong>, and speech synthesis in <strong>10 languages</strong>. Language-following instability from the previous version has been fully addressed, ensuring accurate and consistent performance across diverse linguistic contexts.</p>\n</li>\n<li>\n<p><strong>More Human-Like and Fluent Speech Synthesis</strong>: Eliminates sluggish or robotic speech by significantly enhancing adaptive control over prosody. The model now intelligently adjusts speaking rate, pauses, and intonation based on textual context, delivering expressive, natural-sounding voice output that closely mimics real human speech.</p>\n</li>\n</ul>\n<p><a target=\"_blank\" rel=\"noopener noreferrer\" href=\"https://www.youtube.com/watch?v=Q4CBTckDAls\">www.youtube.com</a></p>\n<h2>Performance</h2>\n<p>On objective benchmarks, <strong>Qwen3-Omni-Flash-2025-12-01</strong> achieves substantial improvements across all modalities compared to <strong>Qwen3-Omni-Flash</strong>:</p>\n<ul>\n<li>\n<p><strong>🧠 Stronger Text Understanding &amp; Generation</strong>:<br />\nMajor gains in logical reasoning (<strong>ZebraLogic +5.6</strong>), code generation (<strong>LiveCodeBench-v6 +9.3</strong>, <strong>MultiPL-E +2.7</strong>), and holistic writing quality (<strong>WritingBench +2.2</strong>), enabling more reliable execution of complex, multi-step instructions.</p>\n</li>\n<li>\n<p><strong>👂 More Accurate Speech Understanding</strong>:<br />\nSignificantly lower word error rate on <strong>Fleurs-zh</strong>, along with a <strong>+3.2</strong> improvement on <strong>VoiceBench</strong>, reflecting enhanced comprehension of spoken language in real-world dialogue scenarios.</p>\n</li>\n<li>\n<p><strong>🎙️ More Natural Speech Synthesis</strong>:<br />\nHigher-quality, human-like voice generation across multiple languages—especially in Chinese and multilingual contexts—with improved prosody, pacing, and pausing that closely mirrors natural human speech.</p>\n</li>\n<li>\n<p><strong>👁️ Deeper Image Understanding</strong>:<br />\nBreakthrough performance on visual reasoning tasks, including <strong>+4.7</strong> on <strong>MMMU</strong>, <strong>+4.8</strong> on <strong>MMMU-Pro</strong>, and <strong>+2.2</strong> on <strong>MathVision_full</strong>, demonstrating a stronger ability to “see,” interpret, and reason about complex visual content—from diagrams to mathematical figures.</p>\n</li>\n<li>\n<p><strong>🎬 More Coherent Video Understanding</strong>:<br />\nSteady improvement in video semantic comprehension (<strong>MLVU +1.6</strong>), further strengthened by tighter audio-visual synchronization, laying a solid foundation for seamless real-time video conversations.</p>\n</li>\n</ul>\n<p>With this upgrade, <strong>Qwen3-Omni-Flash-2025-12-01</strong> truly embodies the vision of <strong>“Hear You. See You. Follow Smarter.”</strong>—delivering an AI interaction experience that is more natural, precise, and vivid than ever before.</p>\n<p><picture class=\"article-picture article-picture-fallback\" style=\"--image-ratio:16 / 9\"><img src=\"http://qianwen-res.oss-accelerate.aliyuncs.com/Qwen3-Omni-Flash-2025-12-01/q3o251201_metric.png#center\" alt=\"\" loading=\"lazy\" decoding=\"async\" fetchpriority=\"low\" referrerpolicy=\"no-referrer\" class=\"progressive-image\"></picture></p>\n<h2>What’s Next</h2>\n<p>We are eager to hear your feedback and see the innovative applications you create with Qwen3-Omni. In the near future, we will further advance the model along multiple axes, including multi-speaker ASR, video OCR, audio–video proactive learning, and enhance support for agent-based workflows and function calling.</p>\n<h2>Citation</h2>\n<p>If you find our model helpful in your research, we’d appreciate a citation!</p>\n<pre><code class=\"language-bibtex\"><span class=\"code-snippet\" data-language=\"Bibtex\"><span class=\"syntax-text syntax-bibtex\"><span class=\"syntax-meta syntax-entry syntax-braces syntax-bibtex\"><span class=\"syntax-keyword syntax-other syntax-entry-type syntax-bibtex\"><span class=\"syntax-punctuation syntax-definition syntax-keyword syntax-bibtex\">@</span>misc</span><span class=\"syntax-punctuation syntax-section syntax-entry syntax-begin syntax-bibtex\">{</span><span class=\"syntax-entity syntax-name syntax-type syntax-entry-key syntax-bibtex\">qwen3_omni_20251201</span>,\n<span class=\"syntax-meta syntax-key-assignment syntax-bibtex\"><span class=\"syntax-string syntax-unquoted syntax-key syntax-bibtex\">author</span> <span class=\"syntax-punctuation syntax-separator syntax-key-value syntax-bibtex\">=</span> <span class=\"syntax-string syntax-quoted syntax-other syntax-braces syntax-bibtex\"><span class=\"syntax-punctuation syntax-definition syntax-string syntax-begin syntax-bibtex\">{</span><span class=\"syntax-punctuation syntax-definition syntax-group syntax-begin syntax-bibtex\">{</span>Qwen Team, Alibaba<span class=\"syntax-punctuation syntax-definition syntax-group syntax-end syntax-bibtex\">}</span><span class=\"syntax-punctuation syntax-definition syntax-string syntax-end syntax-bibtex\">}</span></span></span>,\n<span class=\"syntax-meta syntax-key-assignment syntax-bibtex\"><span class=\"syntax-string syntax-unquoted syntax-key syntax-bibtex\">title</span> <span class=\"syntax-punctuation syntax-separator syntax-key-value syntax-bibtex\">=</span> <span class=\"syntax-string syntax-quoted syntax-other syntax-braces syntax-bibtex\"><span class=\"syntax-punctuation syntax-definition syntax-string syntax-begin syntax-bibtex\">{</span><span class=\"syntax-punctuation syntax-definition syntax-group syntax-begin syntax-bibtex\">{</span>Qwen3-Omni-Flash-2025-12-01：Hear You. See You. Follow Smarter!<span class=\"syntax-punctuation syntax-definition syntax-group syntax-end syntax-bibtex\">}</span><span class=\"syntax-punctuation syntax-definition syntax-string syntax-end syntax-bibtex\">}</span></span></span>,\n<span class=\"syntax-meta syntax-key-assignment syntax-bibtex\"><span class=\"syntax-string syntax-unquoted syntax-key syntax-bibtex\">year</span> <span class=\"syntax-punctuation syntax-separator syntax-key-value syntax-bibtex\">=</span> <span class=\"syntax-string syntax-quoted syntax-other syntax-braces syntax-bibtex\"><span class=\"syntax-punctuation syntax-definition syntax-string syntax-begin syntax-bibtex\">{</span>2025<span class=\"syntax-punctuation syntax-definition syntax-string syntax-end syntax-bibtex\">}</span></span></span>,\n<span class=\"syntax-meta syntax-key-assignment syntax-bibtex\"><span class=\"syntax-string syntax-unquoted syntax-key syntax-bibtex\">url</span> <span class=\"syntax-punctuation syntax-separator syntax-key-value syntax-bibtex\">=</span> <span class=\"syntax-string syntax-quoted syntax-other syntax-braces syntax-bibtex\"><span class=\"syntax-punctuation syntax-definition syntax-string syntax-begin syntax-bibtex\">{</span>https://qwen.ai/blog?id=qwen3-omni-20251201<span class=\"syntax-punctuation syntax-definition syntax-string syntax-end syntax-bibtex\">}</span></span></span>,\n<span class=\"syntax-meta syntax-key-assignment syntax-bibtex\"><span class=\"syntax-string syntax-unquoted syntax-key syntax-bibtex\">urldate</span> <span class=\"syntax-punctuation syntax-separator syntax-key-value syntax-bibtex\">=</span> <span class=\"syntax-string syntax-quoted syntax-other syntax-braces syntax-bibtex\"><span class=\"syntax-punctuation syntax-definition syntax-string syntax-begin syntax-bibtex\">{</span>2025-12-05<span class=\"syntax-punctuation syntax-definition syntax-string syntax-end syntax-bibtex\">}</span></span>\n</span><span class=\"syntax-punctuation syntax-section syntax-entry syntax-end syntax-bibtex\">}</span></span>\n</span></span></code></pre>\n",
  "content_markdown": "![](https://qianwen-res.oss-accelerate-overseas.aliyuncs.com/Qwen3-Omni-Flash-2025-12-01/q3o251201.png#center)\n\n[QWEN CHAT](https://chat.qwenlm.ai) [HUGGING FACE](https://huggingface.co/collections/Qwen/qwen3-omni-68d100a86cd0906843ceccbe) [MODELSCOPE](https://modelscope.cn/collections/Qwen3-Omni-867aef131e7d4f) [DASHSCOPE](https://www.alibabacloud.com/help/en/model-studio/qwen-omni) [GITHUB](https://github.com/QwenLM/Qwen3-Omni) [PAPER](https://github.com/QwenLM/Qwen3-Omni/tree/main/assets/Qwen3_Omni.pdf) [HUGGING FACE DEMO](https://huggingface.co/spaces/Qwen/Qwen3-Omni-Demo) [MODELSCOPE DEMO](https://modelscope.cn/studios/Qwen/Qwen3-Omni-Demo)\n\n**Qwen3-Omni** is a next-generation native multimodal large model capable of seamlessly processing multiple input modalities—including text, images, audio, and video—and generating both text and natural-sounding speech outputs simultaneously via real-time streaming responses. This version introduces multiple enhancements to improve model performance and efficiency.\n\n**Qwen3-Omni-Flash-2025-12-01** is a comprehensively upgraded iteration built upon Qwen3-Omni.\n\nKey highlights of this upgraded version include:\n\n- **Greatly Enhanced Audio-Visual Interaction Experience**: Dramatically improved understanding and execution of audio-visual instructions, effectively resolving the “intelligence drop” issue commonly seen in casual spoken scenarios. Multi-turn audio-visual conversations now achieve significantly higher stability and coherence, enabling more natural and seamless interactions.\n\n- **Strengthened System Prompt Control**: Full customization of system prompts is now supported, enabling precise control over model behavior. Whether it’s persona style (e.g., sweet, cool, anime-inspired), colloquial tone preferences, or output length constraints—every detail can be finely tuned, offering unprecedented command over response characteristics.\n\n- **More Reliable Multilingual Compliance**: Supports text-based interaction in **119 languages**, speech recognition in **19 languages**, and speech synthesis in **10 languages**. Language-following instability from the previous version has been fully addressed, ensuring accurate and consistent performance across diverse linguistic contexts.\n\n- **More Human-Like and Fluent Speech Synthesis**: Eliminates sluggish or robotic speech by significantly enhancing adaptive control over prosody. The model now intelligently adjusts speaking rate, pauses, and intonation based on textual context, delivering expressive, natural-sounding voice output that closely mimics real human speech.\n\n[www.youtube.com](https://www.youtube.com/watch?v=Q4CBTckDAls)\n\n## Performance\n\nOn objective benchmarks, **Qwen3-Omni-Flash-2025-12-01** achieves substantial improvements across all modalities compared to **Qwen3-Omni-Flash**:\n\n- **🧠 Stronger Text Understanding & Generation**:\\\n  Major gains in logical reasoning (**ZebraLogic +5.6**), code generation (**LiveCodeBench-v6 +9.3**, **MultiPL-E +2.7**), and holistic writing quality (**WritingBench +2.2**), enabling more reliable execution of complex, multi-step instructions.\n\n- **👂 More Accurate Speech Understanding**:\\\n  Significantly lower word error rate on **Fleurs-zh**, along with a **+3.2** improvement on **VoiceBench**, reflecting enhanced comprehension of spoken language in real-world dialogue scenarios.\n\n- **🎙️ More Natural Speech Synthesis**:\\\n  Higher-quality, human-like voice generation across multiple languages—especially in Chinese and multilingual contexts—with improved prosody, pacing, and pausing that closely mirrors natural human speech.\n\n- **👁️ Deeper Image Understanding**:\\\n  Breakthrough performance on visual reasoning tasks, including **+4.7** on **MMMU**, **+4.8** on **MMMU-Pro**, and **+2.2** on **MathVision\\_full**, demonstrating a stronger ability to “see,” interpret, and reason about complex visual content—from diagrams to mathematical figures.\n\n- **🎬 More Coherent Video Understanding**:\\\n  Steady improvement in video semantic comprehension (**MLVU +1.6**), further strengthened by tighter audio-visual synchronization, laying a solid foundation for seamless real-time video conversations.\n\nWith this upgrade, **Qwen3-Omni-Flash-2025-12-01** truly embodies the vision of **“Hear You. See You. Follow Smarter.”**—delivering an AI interaction experience that is more natural, precise, and vivid than ever before.\n\n![](http://qianwen-res.oss-accelerate.aliyuncs.com/Qwen3-Omni-Flash-2025-12-01/q3o251201_metric.png#center)\n\n## What’s Next\n\nWe are eager to hear your feedback and see the innovative applications you create with Qwen3-Omni. In the near future, we will further advance the model along multiple axes, including multi-speaker ASR, video OCR, audio–video proactive learning, and enhance support for agent-based workflows and function calling.\n\n## Citation\n\nIf you find our model helpful in your research, we’d appreciate a citation!\n\n```bibtex\n@misc{qwen3_omni_20251201,\nauthor = {{Qwen Team, Alibaba}},\ntitle = {{Qwen3-Omni-Flash-2025-12-01：Hear You. See You. Follow Smarter!}},\nyear = {2025},\nurl = {https://qwen.ai/blog?id=qwen3-omni-20251201},\nurldate = {2025-12-05}\n}\n```\n",
  "dateCreated": "2026-10-18T23:27:08.867657739+00:00",
  "date_created": "2025-12-08T21:00:00+00:00",
  "date_modified": null,
  "date_published": "2025-12-08T21:00:00+00:00",
  "description": "QWEN CHAT HUGGING FACE MODELSCOPE DASHSCOPE GITHUB PAPER HUGGING FACE DEMO MODELSCOPE DEMO Qwen3-Omni is a next-generation native multimodal large model capable of seamlessly processing multiple input modalities—including text, images,…",
  "external_url": "https://qwen.ai/blog?id=qwen3-omni-flash-20251201",
  "git": {
    "commit": "ebb0941c5c06a2ab2377342d607535262a3e969e",
    "path": "items/qwen-ai/2025/12/2025-12-08-qwen3-omni-flash-2025-12-01-hear-you-see-you-follow-smarter.md",
    "permalink": "https://github.com/aymericbeaumet/aggr-instance/blob/ebb0941c5c06a2ab2377342d607535262a3e969e/items/qwen-ai/2025/12/2025-12-08-qwen3-omni-flash-2025-12-01-hear-you-see-you-follow-smarter.md"
  },
  "id": "urn:aggr:item:7d1e0094fcefedb85af24d893a043c3fef1653a6",
  "isBasedOn": {
    "@id": "https://qwen.ai/blog?id=qwen3-omni-flash-20251201"
  },
  "mainEntity": {
    "@id": "https://qwen.ai/blog?id=qwen3-omni-flash-20251201",
    "@type": "CreativeWork",
    "archivedAt": {
      "@id": "https://aggr.aymericbeaumet.com/items/qwen-ai/2025-12-08-qwen3-omni-flash-2025-12-01-hear-you-see-you-follow-smarter/#webpage"
    },
    "author": [
      {
        "@type": "Person",
        "name": "QwenTeam"
      }
    ],
    "datePublished": "2025-12-08T21:00:00+00:00",
    "headline": "Qwen3-Omni-Flash-2025-12-01：Hear You. See You. Follow Smarter!",
    "image": {
      "@type": "ImageObject",
      "caption": null,
      "height": 90,
      "url": "https://img.alicdn.com/imgextra/i1/O1CN01CBLbrb1NJx0kSCqbk_!!6000000001550-2-tps-1590-954.png",
      "width": 160
    },
    "timeRequired": "PT3M",
    "url": "https://qwen.ai/blog?id=qwen3-omni-flash-20251201",
    "wordCount": 581
  },
  "name": "Archived snapshot: Qwen3-Omni-Flash-2025-12-01：Hear You. See You. Follow Smarter!",
  "preview": {
    "alt": null,
    "color": null,
    "height": 90,
    "placeholder": {
      "data_url": "data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAAEAAAABCAQAAAC1HAwCAAAAC0lEQVR42mNk+A8AAQUBAScY42YAAAAASUVORK5CYII=",
      "hash": ""
    },
    "url": "https://img.alicdn.com/imgextra/i1/O1CN01CBLbrb1NJx0kSCqbk_!!6000000001550-2-tps-1590-954.png",
    "width": 160
  },
  "reading_minutes": 3,
  "replicated_at": null,
  "source": "qwen-ai",
  "source_name": "Qwen",
  "summary": null,
  "tags": [
    "release"
  ],
  "temporalCoverage": "2026-10-18T23:27:08.867657739+00:00",
  "title": "Qwen3-Omni-Flash-2025-12-01：Hear You. See You. Follow Smarter!",
  "url": "https://aggr.aymericbeaumet.com/items/qwen-ai/2025-12-08-qwen3-omni-flash-2025-12-01-hear-you-see-you-follow-smarter/",
  "word_count": 581
}