Qwen

🚀 Qwen3-VL Tech report is now out on arXiv! From pretraining to post-training, architecture to infra, data to evaluation — we’ve packed in the details for anyone building on vision-language models. 🔥 3 models >1M downloads in just over a month 🏆 Qwen3-VL-8B leads with 2M+ downloads 📚 Built on the shoulders of Qwen2.5-VL (2800+ citations in <10 months!) Check out the paper for insights, baselines, and future directions. Let’s keep pushing VLMs forward — together. https://lnkd.in/gV-kPFTf

🏆 We are incredibly honored to announce that our paper, "Gated Attention for Large Language Models: Non-linearity, Sparsity, and Attention-Sink-Free" has received the NeurIPS 2025 Best Paper Award! A huge congratulations to our dedicated research team for pushing the boundaries of AI. Read more: https://lnkd.in/gziShEec

🚀 Qwen Code v0.2.1 is here! We shipped 8 versions（v0.1.0->v0.2.1） in just 17 days with major improvements: What's New: 🌐 Free Web Search: Support for multiple providers. Qwen OAuth users get 2000 free searches per day! ��� Smarter Code Editing: New fuzzy matching pipeline reduces errors and saves tokens—fewer retries needed. ⚙️More Control: Fine-tune AI behavior with temperature, top_p, and max tokens settings. 💻 Better IDE Integration: Enhanced Zed IDE support with todo and task management tools. 📝 Cleaner Output: Tool responses now use plain text instead of complex JSON—easier for AI to understand. 🔍 Improved Search: Better file filtering (respects `.gitignore`), smarter search tools, and standardized naming. ⚡ Faster Performance: Multi-stage normalization pipeline for zero-overhead matching, better Unicode handling, and optimized output limits. 🐛 Bug Fixes: Fixed token limits for multiple models, improved cross-platform support (macOS & Windows), and better stability. Try it now—smoother, more reliable AI coding! 🔗 https://lnkd.in/gfWKUJvq   📝 https://lnkd.in/gu-ypWVJ

🚀 Qwen DeepResearch 2511 is LIVE! 🚀 We've just dropped a major upgrade, making your research deeper, faster, and smarter! 🔗：  https://lnkd.in/gEz2fX7f APP:   https://qwen.ai/download ✨ Dual Mode Selection: Normal Mode: Efficient & versatile for most needs! Advanced Mode: Go deeper! Devotes extra time for a more thorough analysis. 🧠 📄 File Uploads Enabled: Now you can easily upload your documents or images for the AI to analyze! ⚡️ Boosted Search Power: Drastically improved search efficiency & depth. Read and process more web info in less time! 📊 Precise Report Control: Command the report format—word count, paragraphs, & content! Get comprehensive reports with enhanced citation reliability. 🧑💻 All-New UX: Our new decoupled architecture delivers a smoother, more responsive user experience!

We’ve released an early preview of Qwen3-Max-Thinking—an intermediate checkpoint still in training. Even at this stage, when augmented with tool use and scaled test-time compute, it achieves 100% on challenging reasoning benchmarks like AIME 2025 and HMMT. You can try the current version in Qwen Chat and Alibaba Cloud API—more to come as training continues. Qwen Chat: https://lnkd.in/g9bCkR6f Alibaba Cloud API （enable_thinking=True）: https://lnkd.in/gvM86jgD

🎉 Qwen3-VL is now available on llama.cpp!  Run this powerful vision-language model directly on your personal devices—fully supported on CPU, CUDA, Metal, Vulkan, and other backends.  We’ve also released GGUF weights for all variants—from 2B up to 235B. Download and enjoy! 🚀 🤗 Hugging Face: https://lnkd.in/gQW5igpj ��� ModelScope: https://lnkd.in/gB9yeXyx 📌 PR: https://lnkd.in/gxkkNURw

Introducing Qwen3-VL-2B and Qwen3-VL-32B! From edge to cloud, these dense powerhouses deliver ultimate performance per GPU memory, packing the full capabilities of Qwen3-VL into compact and scalable forms. 🔥 Qwen3-VL-32B outperforms GPT-5 mini & Claude 4 Sonnet across STEM, VQA, OCR, video understanding, agent tasks, and more. 💡 It matches models up to 235B (even beating them on OSWorld!) with only 32B parameters. ⚡️ FP8 versions available for ultra-efficient deployment. 🔧 Also releasing Instruct & Thinking variants for flexible use cases. Try it now: https://lnkd.in/gkiW3quP Hugging Face:https://lnkd.in/g6E4ssgE ModelScope:https://lnkd.in/gB9yeXyx  API - instruct: https://lnkd.in/gEPtvybZ API - thinking: https://lnkd.in/gP7FcQhF Cookbook: https://lnkd.in/gRwFiYy2

Qwen Deep Research just got a major upgrade. ⚡️ It now creates not only the report, but also a live webpage 🌐 and a podcast 🎙️ - Powered by Qwen3-Coder, Qwen-Image, and Qwen3-TTS. Your insights, now visual and audible. ✨ 👉 https://lnkd.in/gEz2fX7f

Excited to announce the launch of Qwen3-VL-Flash on Alibaba Cloud Model Studio! 🚀 A powerful new vision-language model that combines reasoning and non-reasoning modes, outperforming open-source Qwen3-VL-30B-A3B and Qwen2.5-72B with faster response, stronger capabilities, and the lower cost! 📸 Supports ultra-long context (up to 256K tokens) – perfect for long videos & documents 🧠 Enhanced image/video understanding with 2D/3D localization and spatial awareness 🌍 Advanced OCR, multilingual recognition, agent control & real-world applications 🚨 Significantly improved security perception and real-environment visual intelligence API： https://lnkd.in/gB6BqMpq

We're open-sourcing several core components from the Qwen3Guard Technical Report, now available for research and community use: 🔹 Qwen3-4B-SafeRL: A safety-aligned model fine-tuned via reinforcement learning using feedback from Qwen3Guard-Gen-4B. → Achieves significant safety improvement on WildJailbreak (64.7 → 98.1) without compromising general task performance. 🔹 Qwen3GuardTest: A benchmark for evaluating Guard models, covering: (1) Safety classification of intermediate reasoning/thinking content (2) Moderation of streaming/token-by-token outputs 🔗 Hugging Face: https://lnkd.in/ehin3j-c 🤖 ModelScope: https://lnkd.in/ey8RPp6G 📊 Dataset: https://lnkd.in/ewY3gqaD 💻 Code & Details: https://lnkd.in/gaiU8xFH