[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"tag-gpt-4o":3},{"tag":4,"articles":11},{"id":5,"name":6,"slug":7,"article_count":8,"description_zh":9,"description_en":10},"42dd357a-eb7f-4178-a36d-e2813bcf47e9","GPT-4o","gpt-4o",3,"GPT-4o 是 OpenAI 的多模態模型，常被拿來討論參數規模、延遲、成本與推理品質之間的取捨。這個主題也延伸到語音、影像與 agent 工作流，適合關注模型部署與實際效能的開發者。","GPT-4o is OpenAI’s multimodal model, often discussed in terms of parameter scale, latency, cost, and reasoning quality. This tag also connects to voice, image, and agent workflows, making it relevant for developers evaluating real-world model trade-offs.",[12,21],{"id":13,"slug":14,"title":15,"summary":16,"category":17,"image_url":18,"cover_image":18,"language":19,"created_at":20},"838cb5fd-5651-49fb-9b4c-c2dbde25ca02","claude-opus-45-gpt-parameters-estimate-zh","Claude Opus 4.5 和 GPT 到底多大","GPT-4 常被估到 1.6 兆參數，但 GPT-4o 可能只有 200B 到 300B。Claude Opus 4.5 的真實大小沒公開，重點其實是成本、延遲和效能比。","research","https:\u002F\u002Fxxdpdyhzhpamafnrdkyq.supabase.co\u002Fstorage\u002Fv1\u002Fobject\u002Fpublic\u002Fcovers\u002Finline-1775207388141-adee.png","zh","2026-04-03T09:09:28.833454+00:00",{"id":22,"slug":23,"title":24,"summary":25,"category":26,"image_url":27,"cover_image":27,"language":19,"created_at":28},"e69f860c-dee7-4831-9ebd-c4485a6fb56f","ai-agent-workflows-context-actions-verification-zh","AI Agent 工作流怎麼運作","AI Agent 不是靠一句提示詞就能跑。真正好用的系統靠的是「收集上下文、執行動作、驗證結果、重試」的工作流。","ai-agent","https:\u002F\u002Fxxdpdyhzhpamafnrdkyq.supabase.co\u002Fstorage\u002Fv1\u002Fobject\u002Fpublic\u002Fcovers\u002Finline-1775116338426-p13x.png","2026-04-02T07:03:33.780133+00:00"]