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资讯
只聚合标题、AI 摘要与原文链接。列表按发布时间倒序；同源同主题的重复报道会被折叠成簇。
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Qwen3Guard: Real-time Safety for Your Token Stream
来源摘要 Tech Report GitHub Hugging Face ModelScope DISCORD Introduction We are excited to introduce Qwen3Guard, the first safety guardrail model in the Qwen family. Built upon the powerful Qwen3 foundation models and fine-tuned specifically for safety classificatoin, Qwen3Guard ensures r…
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Qwen-Image-Edit: Image Editing with Higher Quality and Efficiency
来源摘要 QWEN CHAT GITHUB HUGGING FACE MODELSCOPE DISCORD We are excited to introduce Qwen-Image-Edit, the image editing version of Qwen-Image. Built upon our 20B Qwen-Image model, Qwen-Image-Edit successfully extends Qwen-Image’s unique text rendering capabilities to image editing tasks,…
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Qwen-Image: Crafting with Native Text Rendering
来源摘要 GITHUB HUGGING FACE MODELSCOPE DEMO DISCORD 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. To try the latest model, feel free to visit Qwen Chat and choose “Image Ge…
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Qwen-MT: Where Speed Meets Smart Translation
来源摘要 DEMO API DISCORD Introduction Here we introduce the latest update of Qwen-MT (qwen-mt-turbo) via Qwen API. This update builds upon the powerful Qwen3, leveraging trillions multilingual and translation tokens to comprehensively enhance the model’s multilingual understanding and tr…
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Qwen3-Coder: Agentic Coding in the World
来源摘要 GITHUB HUGGING FACE MODELSCOPE DISCORD Today, we’re announcing Qwen3-Coder, our most agentic code model to date. Qwen3-Coder is available in multiple sizes, but we’re excited to introduce its most powerful variant first: Qwen3-Coder-480B-A35B-Instruct — a 480B-parameter Mixture-o…
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Time to Speak Some Dialects, Qwen-TTS!
来源摘要 API DISCORD Introduction Here we introduce the latest update of Qwen-TTS (qwen-tts-latest or qwen-tts-2025-05-22) through Qwen API . Trained on a large-scale dataset encompassing over millions of hours of speech, Qwen-TTS achieves human-level naturalness and expressiveness. Notab…
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Qwen VLo: From "Understanding" the World to "Depicting" It
来源摘要 QWEN CHAT DISCORD Introduction The evolution of multimodal large models is continually pushing the boundaries of what we believe technology can achieve. From the initial QwenVL to the latest Qwen2.5 VL, we have made progress in enhancing the model’s ability to understand image co…
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Qwen3 Embedding: Advancing Text Embedding and Reranking Through Foundation Models
来源摘要 GITHUB HUGGING FACE MODELSCOPE DISCORD We release Qwen3 Embedding series, a new proprietary model of the Qwen model family. These models are specifically designed for text embedding, retrieval, and reranking tasks, built on the Qwen3 foundation model. Leveraging Qwen3’s robust mu…
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Qwen3: Think Deeper, Act Faster
来源摘要 QWEN CHAT GitHub Hugging Face ModelScope Kaggle DEMO DISCORD Introduction Today, we are excited to announce the release of Qwen3, the latest addition to the Qwen family of large language models. Our flagship model, Qwen3-235B-A22B, achieves competitive results in benchmark evalua…
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QVQ-Max: Think with Evidence
来源摘要 QWEN CHAT GITHUB HUGGING FACE MODELSCOPE DISCORD Introduction Last December, we launched QVQ-72B-Preview as an exploratory model, but it had many issues. Today, we are officially releasing the first version of QVQ-Max, our visual reasoning model. This model can not only “understa…
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Qwen2.5 Omni: See, Hear, Talk, Write, Do It All!
来源摘要 QWEN CHAT HUGGING FACE MODELSCOPE DASHSCOPE GITHUB PAPER DEMO DISCORD 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,…
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Qwen2.5-VL-32B: Smarter and Lighter
来源摘要 QWEN CHAT GITHUB HUGGING FACE MODELSCOPE DISCORD Introduction At the end of January this year, we launched the Qwen2.5-VL series of models, which received widespread attention and positive feedback from the community. Building on the Qwen2.5-VL series, we continued to optimize th…
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QwQ-32B: Embracing the Power of Reinforcement Learning
来源摘要 QWEN CHAT Hugging Face ModelScope DEMO DISCORD Scaling Reinforcement Learning (RL) has the potential to enhance model performance beyond conventional pretraining and post-training methods. Recent studies have demonstrated that RL can significantly improve the reasoning capabiliti…
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<think>...</think> QwQ-Max-Preview
来源摘要 QWEN CHAT DISCORD This is a blog created by QwQ-Max-Preview. We hope you enjoy it! Introduction Okay, the user wants me to create a title and introduction for their blog announcing the release of QwQ-Max-Preview. Let me start by understanding the key points they mentioned. First,…
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Qwen2.5-Max: Exploring the Intelligence of Large-scale MoE Model
来源摘要 QWEN CHAT API DEMO DISCORD It is widely recognized that continuously scaling both data size and model size can lead to significant improvements in model intelligence. However, the research and industry community has limited experience in effectively scaling extremely large models…
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Qwen2.5-1M: Deploy Your Own Qwen with Context Length up to 1M Tokens
来源摘要 Tech Report HuggingFace ModelScope Qwen Chat HuggingFace Demo ModelScope Demo DISCORD Introduction Two months after upgrading Qwen2.5-Turbo to support context length up to one million tokens, we are back with the open-source Qwen2.5-1M models and the corresponding inference frame…
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Qwen2.5 VL! Qwen2.5 VL! Qwen2.5 VL!
来源摘要 QWEN CHAT GITHUB HUGGING FACE MODELSCOPE DISCORD We release Qwen2.5-VL, the new flagship vision-language model of Qwen and also a significant leap from the previous Qwen2-VL. To try the latest model, feel free to visit Qwen Chat and choose Qwen2.5-VL-72B-Instruct. Also, we open b…
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Global-batch load balance almost free lunch to improve your MoE LLM training
来源摘要 GITHUB HUGGING FACE MODELSCOPE DISCORD Background The Mixture-of-Experts (MoEs) architecture has become a popular model-parameter-scale-up technique. Typically, one MoE layer consists of a router (often parameterized as one single Linear layer) and a group of experts (for transfo…
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Towards Effective Process Supervision in Mathematical Reasoning
来源摘要 GITHUB HUGGING FACE MODELSCOPE DISCORD Introduction In recent years, Large Language Models (LLMs) have made remarkable advances in mathematical reasoning, yet they can make mistakes, such as miscalculations or logical errors, leading to wrong conclusions. Moreover, even when achi…