2026年初开源LLM架构综述：十大模型对比
原标题：A Dream of Spring for Open-Weight LLMs: 10 Architectures from Jan-Feb 2026
AI 摘要
本文回顾了2026年1月至2月期间发布的10个开源权重LLM，重点比较了它们的架构异同。主要发布包括Arcee AI的Trinity Large、Moonshot AI的Kimi K2.5、StepFun Step 3.5 Flash、Qwen3-Coder-Next、z.AI的GLM-5、MiniMax M2.5、Nanbeige 4.1 3B、Qwen 3.5、Ant Group的Ling 2.5和Ring 2.5，以及Cohere的Tiny Aya。文章详细分析了Trinity Large的架构特点，如交替局部/全局注意力、QK-Norm、门控注意力等，并指出Kimi K2.5作为1万亿参数的多模态模型，在发布时达到了领先专有模型的性能水平。
正文节选
A Dream of Spring for Open-Weight LLMs: 10 Architectures from Jan-Feb 2026 A Round Up And Comparison of 10 Open-Weight LLM Releases in Spring 2026 If you have struggled a bit to keep up with open-weight model releases this month, this article should catch you up on the main themes. In this article, I will walk you through the ten main releases in chronological order, with a focus on the architecture similarities and differences: - Arcee AI’s Trinity Large (Jan 27, 2026) - Moonshot AI’s Kimi K2.5