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Qwen 3.8-Max: Alibaba's 2.4T-Parameter Model Sets New Bar in Autonomous Coding and Real-World Work
Alibaba's Qwen 3.8-Max, a 2.4T-parameter MoE model, demonstrates unprecedented autonomy in coding and work tasks, from building a...
Qwen3.5-Max-Preview Debuts on Arena with Strong Preliminary Results
Alibaba's Qwen team has released the preview of Qwen3.5-Max on the Arena platform, showcasing impressive performance in early eval...
Qwen-Image-Edit-2511: Enhanced Consistency and LoRA Integration
Alibaba's Qwen team releases an improved image editing model with better character consistency, multi-person group photo fusion, b...
Alibaba’s Qwen3-TTS Introduces Voice Cloning and Voice Design Models
Qwen3-TTS family expands with two new models: Qwen3-TTS-VD-Flash for voice design via natural language instructions and Qwen3-TTS-...
Qwen-Image-Layered: Decomposing Images into Editable RGBA Layers
Alibaba's Qwen introduces a model that decomposes images into multiple RGBA layers, enabling independent manipulation of each laye...
SAPO: Alibaba's New RL Method Promises Stable and Performant LLM Training
Alibaba's Qwen team introduces Soft Adaptive Policy Optimization (SAPO), a reinforcement learning method that replaces hard clippi...
Qwen DeepResearch 2511: Making Deep Research as Easy as a Thought
Alibaba's Qwen unveils DeepResearch 2511, a research assistant that minimizes the friction between inspiration and validation, fea...