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.
The r/LocalLLaMA community is buzzing over Qwen 3.5-35B-A3B, which users report outperforms GPT-OSS-120B while being only one-third the size, making it an excellent local daily driver for development tasks.
A high-engagement r/LocalLLaMA thread reports strong early results for Qwen3.5-35B-A3B in local agentic coding workflows. The original poster cites 100+ tokens/sec on a single RTX 3090 setup, while comments show mixed reproducibility and emphasize tooling, quantization, and prompt pipeline differences.
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.
Qwen3's TTS model encodes voices into 1024-dimensional vectors, enabling gender swapping, pitch adjustment, voice mixing, and semantic voice search through vector math — now available as a standalone lightweight encoder on HuggingFace.
A high-scoring r/LocalLLaMA thread surfaced Qwen3.5-397B-A17B, an open-weight multimodal model card on Hugging Face that lists 397B total parameters with 17B activated and up to about 1M-token extended context.
A high-signal r/LocalLLaMA thread tracked the merge of llama.cpp PR #19375 and highlighted practical throughput gains for Qwen3Next models. Both PR benchmarks and community tests suggest meaningful t/s improvements from graph-level copy reduction.