A high-ranking Hacker News thread highlighted a two-sided Qwen story: rapid model quality gains and potential organizational instability. As Qwen 3.5 expands across model sizes, reported leadership departures raise questions about roadmap continuity in the open-weight LLM ecosystem.
A widely-shared r/LocalLLaMA comparison of Qwen's smallest models across three generations (score: 681) reveals extraordinary efficiency gains. The Qwen 3.5 9B now outperforms the previous-generation 80B on several benchmarks, while the 2B handles video understanding better than many 7B models.
Alibaba Qwen team released the Qwen 3.5 small model series (0.8B to 9B). Models run in-browser via WebGPU and show dramatic benchmark improvements over previous generations.
Alibaba released the Qwen3.5 small model series (0.8B, 4B, 9B). The 9B model achieves performance comparable to GPT-oss 20B–120B, making high-quality local inference accessible to users with modest GPU hardware.
Alibaba's Qwen team has released Qwen 3.5 Small, a new small dense model in their flagship open-source series. The announcement topped r/LocalLLaMA with over 1,000 upvotes, reflecting the local AI community's enthusiasm for capable small models.
Users on r/LocalLLaMA have spotted Qwen3.5 model names appearing in Alibaba's official Qwen chat interface, signaling an imminent release of the next generation of Alibaba's open-source LLM series.
Alibaba launched Qwen3.5, a 397B-parameter open-weight multimodal model supporting 201 languages. The company claims it outperforms GPT-5.2, Claude Opus 4.5, and Gemini 3 on benchmarks, while costing 60% less than its predecessor.
Alibaba launched Qwen 3.5 on February 16 under Apache 2.0, featuring 397B parameters with a sparse MoE architecture (17B active), 256K context, and native multimodal capabilities matching leading US proprietary models on key benchmarks.