Qwen Team Releases FlashQLA: a High-Performance Linear Attention Kernel Library That Achieves Up to 3× Speedup on NVIDIA Hopper GPUs

Alibaba’s Qwen Team has released Qwen3.6-27B, the first dense open-weight model in the Qwen3.6 family — and arguably the most capable 27-billion-parameter model available today for coding agents. It brings substantial improvements in agentic coding, a novel Thinking Preservation mechanism, and a hybrid architecture that blends Gated DeltaNet linear attention with traditional self-attention — all […] The post Alibaba Qwen Team Releases Qwen3.6-27B: A Dense Open-Weight Model Outperforming 397B MoE on Agentic Coding Benchmarks appeared first on MarkTechPost.

Qwen Team Open-Sources Qwen3.6-35B-A3B: A Sparse MoE Vision-Language Model with 3B Active Parameters and Agentic Coding Capabilities The post Qwen Team Open-Sources Qwen3.6-35B-A3B: A Sparse MoE Vision-Language Model with 3B Active Parameters and Agentic Coding Capabilities appeared first on MarkTechPost.