Alibaba's Qwen team just dropped Qwen3.5-Omni, a native omnimodal model that handles text, image, audio, and video simultaneously. The highlight is "Audio-Visual Vibe Coding," letting you talk to your camera while the AI builds a working website or game in real time. It natively processes up to 10 hours of audio and outperforms Gemini-3.1 Pro in audio tasks.
Alibaba Qwen's central technical leader Junyang Lin just announced he is stepping down from the open-weight project, only a day after releasing the Qwen 3.5 small models. Colleagues called the abrupt exit an immense loss, with one teammate hinting the departure wasn't Lin's choice. The shakeup comes right as China's top open-source model family gains global momentum.
Alibaba's Qwen team just launched the Qwen3.5 Small Model Series, offering four compact sizes from 0.8B to 9B parameters along with base checkpoints. Built with native multimodal architecture and scaled reinforcement learning, the lineup aims to deliver snappy intelligence directly on edge devices and local agents.
Alibaba just dropped its Qwen 3.5 Medium series, featuring four models including Qwen3.5-Flash, 35B-A3B, 122B-A10B, and 27B. The team claims the 35B-A3B model outperforms the previous-generation 235B giant, proving architecture and RL can beat raw parameter scale. The Flash version also brings a default 1M context window and built-in agent tooling.
Alibaba's Qwen team just rolled out Qwen3.5-397B-A17B, the first open-weight model in the Qwen3.5 lineup. Built on a sparse MoE architecture, it carries 397 billion total parameters while activating just 17 billion per token, pushing decoding throughput up to 19x over Qwen3-Max. Why it matters: Developers get Apache 2.0-licensed multimodal agent capabilities without the prohibitive serving costs of dense giants.
Alibaba's Qwen team just launched Qwen-Image-2.0, a major upgrade to its image generation model. It brings native 2K resolution, seamless text rendering without glitchy letters, and handles up to 1K-token prompts for slides and posters. A lighter architecture also cuts inference times while unifying generation and editing.
Alibaba just released Qwen3-Coder-Next, an open-weight model built specifically for coding agents and local developers. It uses agentic training across 800K verifiable tasks and packs an 80B total parameter base into just 3B active params, delivering strong SWE-Bench Pro results while integrating smoothly with tools like Cline.
ByteDance and Alibaba are reportedly prepping next-generation flagship models for release during the February Lunar New Year holiday. ByteDance is lining up Doubao 2.0 alongside major image and video upgrades, while Alibaba is readying Qwen 3.5 with targeted reasoning boosts. With DeepSeek V4 also rumored for mid-February, China's frontier AI race is entering an intense new clash.
Alibaba's Qwen team just dropped Qwen3-Max-Thinking, a new proprietary reasoning model built around advanced test-time scaling and autonomous tool use. Paired with web search, it notched a 49.8 on Humanity's Last Exam, beating both Gemini 3 Pro and GPT-5.2.
Alibaba Qwen just rolled out Qwen Code v0.6.0, introducing experimental Skills to broaden its capabilities alongside new /compress and /summary commands. The update also brings native multi-provider support for Gemini and Anthropic, plus clickable bash outputs inside VS Code. It makes Alibaba's CLI coding assistant much more versatile for everyday development.
Alibaba just rolled out Qwen-Image-Edit-2511, a major upgrade targeting identity drift in group photos and complex scenes. The update sharpens geometric reasoning for design edits and bakes popular community LoRAs right into the model, meaning you no longer need extra fine-tuning for specialized styles.
Alibaba just launched its Qwen3-TTS lineup, introducing VoiceDesign and VoiceClone. VoiceDesign lets users generate custom voices and emotions directly from natural language prompts, while VoiceClone can replicate any voice from just 3 seconds of audio across 10 languages, beating ElevenLabs in word error rate by 15%.
Alibaba's Qwen team just open-sourced Qwen-Image-Layered, a model that natively decomposes flat images into isolated RGBA layers. Users can prompt it to output 3 to 10 distinct layers and drill down recursively for infinite detail. It basically gives creators Photoshop-grade editable layers straight out of the box, skipping manual cutout work.
Alibaba just introduced Wan2.6, a native multimodal model capable of generating 15-second 1080p clips with auto-storyboarded multi-shot narratives. It features native audio-video synchronization with natural lip-sync for multi-speaker dialogues, alongside consistent character casting across scenes. Why it matters: It tackles video AI's toughest bottlenecks—visual consistency and sound sync—in one unified system.
Alibaba Qwen just released Qwen Code v0.5.0, bundling its CLI directly into VSCode alongside a native TypeScript SDK. The update introduces smart session auto-saving and expands model compatibility to OpenAI-compatible reasoning models like DeepSeek V3.2 and Kimi-K2. It makes plugging open reasoning models straight into developer terminals much easier.
Alibaba just released its new flagship model, Qwen3-Max, shipping both a standard Instruct version and a tool-using Thinking variant. The company heavily boosted coding and agentic capabilities, rivaling elite frontier models across tough benchmarks like SWE-Bench and AIME25. It is already live on their chat platform and available through Alibaba Cloud's API.
Alibaba just introduced Qwen3-Omni, a natively end-to-end multimodal model unifying text, images, audio, and video under a single architecture. It boasts a 211ms latency alongside 30-minute audio comprehension, releasing 30B-scale instruct, thinking, and captioner checkpoints for developers.
Alibaba just released Qwen3-Next-80B-A3B, an ultra-sparse MoE model that packs 80B total parameters while only activating 3B per token. It delivers 10x faster inference and 10x cheaper training than Qwen3-32B, with its Thinking variant outperforming Gemini-2.5-Flash-Thinking. Basically, flagship-grade reasoning is now running at lightweight speed.
Alibaba just previewed its first pair of AI-powered glasses at WAIC in Shanghai, taking direct aim at China's heating wearable market. Named after its Quark AI assistant, the company confirmed development is complete and aims for an official launch later this year. Why it matters: Alibaba is no longer just providing software to hardware partners—it wants its own wearable front-end for multimodal intelligence.
Alibaba's Qwen team just scrapped hybrid thinking mode to train Instruct and Thinking models separately for peak quality. Along with the pivot, it rolled out Qwen3-235B-A22B-Instruct-2507 and an FP8 version, promising stronger general capabilities and better performance on agent tasks.
