[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"tag-glm-5":3},{"tag":4,"articles":11,"peer_article_count":8},{"id":5,"name":6,"slug":7,"article_count":8,"description_zh":9,"description_en":10},"d79e91f0-2882-4696-ae41-cf7f4c3163b8","GLM-5","glm-5",4,"GLM-5 是 Z.AI 的旗艦大型語言模型，主打程式碼生成、代理式工作流與長上下文推理。它在 SWE-bench、Terminal Bench 等基準的表現，讓開源模型在實務開發與自架部署上更值得比較。","GLM-5 is Z.AI’s flagship large language model, built for coding, agent workflows, and long-context reasoning. Its results on SWE-bench and Terminal Bench make it a relevant benchmark when comparing open models for real development and self-hosted deployment.",[12,21,29,37],{"id":13,"slug":14,"title":15,"summary":16,"category":17,"image_url":18,"cover_image":18,"language":19,"created_at":20},"020c80c8-c92f-4f7b-a175-0cb29bd1b8c7","glm-5-kill-vibe-coding-agent-engineering-en","GLM-5 Is Right to Kill Vibe Coding and Push Agent Engineering","GLM-5 is a useful signal that AI development must move from vibe coding to agent engineering.","ai-agent","https:\u002F\u002Fxxdpdyhzhpamafnrdkyq.supabase.co\u002Fstorage\u002Fv1\u002Fobject\u002Fpublic\u002Fcovers\u002Finline-1782223372408-840t.png","en","2026-06-23T14:02:24.351865+00:00",{"id":22,"slug":23,"title":24,"summary":25,"category":26,"image_url":27,"cover_image":27,"language":19,"created_at":28},"96d5d6ba-05e8-47cb-a87b-01e6ef03e840","coding-plan-pro-integration-guide-en","Coding Plan Pro 接入完整指南","本指南演示如何配置 Coding Plan Pro 套餐并验证可用模型。","tools","https:\u002F\u002Fxxdpdyhzhpamafnrdkyq.supabase.co\u002Fstorage\u002Fv1\u002Fobject\u002Fpublic\u002Fcovers\u002Finline-1781630272181-s6hg.png","2026-06-16T17:17:24.543206+00:00",{"id":30,"slug":31,"title":32,"summary":33,"category":34,"image_url":35,"cover_image":35,"language":19,"created_at":36},"91fe9555-c2db-4489-babe-df23943ec39b","glm-5-zai-flagship-coding-agents-en","GLM-5: Z.AI's new flagship for coding and agents","GLM-5 posts 77.8 on SWE-bench Verified and 56.2 on Terminal Bench 2.0, putting Z.AI in direct competition with top coding models.","model-release","https:\u002F\u002Fxxdpdyhzhpamafnrdkyq.supabase.co\u002Fstorage\u002Fv1\u002Fobject\u002Fpublic\u002Fcovers\u002Finline-1775135076803-ig5q.png","2026-04-02T13:03:42.827978+00:00",{"id":38,"slug":39,"title":40,"summary":41,"category":34,"image_url":42,"cover_image":42,"language":19,"created_at":43},"424af64f-8d0b-4cd5-b58b-f37ee073bfa1","open-source-llm-comparison-2026-en","Open Source LLMs in 2026: Who Leads?","Qwen 3.5, GLM-5, DeepSeek R1, and Llama 4 now push open models into serious production territory, with licensing still deciding deployments.","https:\u002F\u002Fxxdpdyhzhpamafnrdkyq.supabase.co\u002Fstorage\u002Fv1\u002Fobject\u002Fpublic\u002Fcovers\u002Finline-1775131810853-8ewo.png","2026-04-02T12:09:40.211772+00:00"]