Last week, I spent three hours trying to debug a 40,000-line Python repository. I needed an AI that could actually hold the entire codebase in its working memory without hallucinating function signatures or forgetting the file structure from two prompts ago. If you're shopping for a high-context LLM in mid-2026, you've probably narrowed your list down to the same two models I did: Google's Gemini 3.1 Pro Preview and Zhipu AI's GLM-5.2 (max).
# Google Gemini 高效工作流：与 AI 协作的最佳实践 上周我遇到了一个棘手的问题：我需要将一份长达 80 页的技术架构文档拆解成 15 个独立的微服务设计书，每个都要包含接口定义、数据模型和部署方案。如果按传统方式，这至少得熬三个通宵。 于是我决定彻底改变工作方式，把 Gemini 当作真正的协作搭档，而不是简单的问答机器。经过几周的摸索和踩坑，我总结出了一套与 Gemini
# Gemini Omni 隐藏功能揭秘：你可能不知道的用法 上周我在剪一支产品宣传片，拍了段手部特写展示新品，但画面实在太单调。我想让手里的产品悬浮起来，周围环绕一些动态粒子，但我的 After Effects 技术仅限于加个字幕。找外包？预算不够。自己硬啃 AE？时间不允许。 就在我准备放弃特效妥协交片时，我注意到了 Google 刚推出的 Gemini Omni Flash。官方说法是"
Last month, I was building a customer support dashboard that needed to process incoming support tickets, categorize them, extract key information, and draft responses. I started with a heavier model,
