[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"article-microsoft-new-coding-model-build-2026-zh":3,"article-related-microsoft-new-coding-model-build-2026-zh":32,"series-model-release-31a11fa6-07fe-42c6-a2e5-93760fc776a8":85},{"id":4,"slug":5,"title":6,"content":7,"summary":8,"source":9,"source_url":10,"author":11,"image_url":12,"cover_image":12,"category":13,"language":14,"translated_content":11,"related_article_id":15,"keywords":16,"key_takeaways":24,"views":28,"created_at":29,"published_at":30,"topic_cluster_id":31},"31a11fa6-07fe-42c6-a2e5-93760fc776a8","microsoft-new-coding-model-build-2026-zh","微軟將在 Build 發表新寫碼模型","\u003Cp data-speakable=\"summary\">微軟預計在 Build 發表自家寫碼模型，想把 \u003Ca href=\"\u002Ftag\u002Fgithub-copilot\">GitHub Copilot\u003C\u002Fa> 更深塞進開發流程。\u003C\u002Fp>\u003Cp>這件事不小。Build 是微軟的\u003Ca href=\"\u002Fnews\u002Fgithub-esc-merch-dev-culture-summer-gear-zh\">開發者\u003C\u002Fa>大秀。地點在舊金山，時間是下週，Reuters 先報了這個消息。對開發者來說，重點不是發表會多熱鬧，而是這個模型會不會真的進到日常寫碼流程。\u003C\u002Fp>\u003Cp>講白了，微軟想把 \u003Ca href=\"\u002Ftag\u002Fcopilot\">Copilot\u003C\u002Fa> 變成更黏的工具。不是只有補幾行程式碼。它要碰的是編輯器、Repo、審查流程，還有企業內部的工作流。這種改動，影響的不是一個 demo，而是一整條產品線。\u003C\u002Fp>\u003Ctable>\u003Cthead>\u003Ctr>\u003Cth>項目\u003C\u002Fth>\u003Cth>內容\u003C\u002Fth>\u003C\u002Ftr>\u003C\u002Fthead>\u003Ctbody>\u003Ctr>\u003Ctd>活動\u003C\u002Ftd>\u003Ctd>\u003Ca href=\"https:\u002F\u002Fbuild.microsoft.com\u002F\" target=\"_blank\" rel=\"noopener\">Microsoft Build\u003C\u002Fa>\u003C\u002Ftd>\u003C\u002Ftr>\u003Ctr>\u003Ctd>時間\u003C\u002Ftd>\u003Ctd>下週，2026 年 5 月\u003C\u002Ftd>\u003C\u002Ftr>\u003Ctr>\u003Ctd>地點\u003C\u002Ftd>\u003Ctd>舊金山\u003C\u002Ftd>\u003C\u002Ftr>\u003Ctr>\u003Ctd>產品焦點\u003C\u002Ftd>\u003Ctd>自家 AI 模型，包含寫碼模型\u003C\u002Ftd>\u003C\u002Ftr>\u003Ctr>\u003Ctd>目標\u003C\u002Ftd>\u003Ctd>拉高 \u003Ca href=\"https:\u002F\u002Fgithub.com\u002Ffeatures\u002Fcopilot\" target=\"_blank\" rel=\"noopener\">GitHub Copilot\u003C\u002Fa> 使用率\u003C\u002Ftd>\u003C\u002Ftr>\u003C\u002Ftbody>\u003C\u002Ftable>\u003Ch2>微軟為什麼急著自己做模型\u003C\u002Fh2>\u003Cp>先講結論。微軟不是只想做一個更會寫程式的 LLM。它想要的是控制權。模型放在自己手上，速度、成本、延遲、更新節奏，都比較好管。這對一家把雲端和開發工具綁很緊的公司，很重要。\u003C\u002Fp>\n\u003Cfigure class=\"my-6\">\u003Cimg src=\"https:\u002F\u002Fxxdpdyhzhpamafnrdkyq.supabase.co\u002Fstorage\u002Fv1\u002Fobject\u002Fpublic\u002Fcovers\u002Finline-1780077779088-nupb.png\" alt=\"微軟將在 Build 發表新寫碼模型\" class=\"rounded-xl w-full\" loading=\"lazy\" \u002F>\u003C\u002Ffigure>\n\u003Cp>如果模型是外部供應商提供，微軟就得看別人臉色。今天 API 價格變了，明天能力調整了，後天支援範圍縮了，產品節奏就會卡住。自家模型至少能讓它少受一層掣肘。\u003C\u002Fp>\u003Cp>另外，Copilot 早就不是單純的自動補字工具。現在大家期待的是懂 Repo、懂上下文、懂測試、懂重構。你可能會想問，這跟一般聊天機器人差在哪。差很多。寫碼工具要少胡說，還要能接住\u003Ca href=\"\u002Fnews\u002F5-github-explore-picks-for-builders-zh\">專案\u003C\u002Fa>脈絡。\u003C\u002Fp>\u003Cul>\u003Cli>微軟能自己決定模型上線節奏\u003C\u002Fli>\u003Cli>Copilot 可和 GitHub、VS Code 更緊密整合\u003C\u002Fli>\u003Cli>微軟能少依賴外部模型供應商\u003C\u002Fli>\u003Cli>企業客戶比較容易接受同一套工具鏈\u003C\u002Fli>\u003C\u002Ful>\u003Ch2>Build 不是秀場，是產品發令台\u003C\u002Fh2>\u003Cp>\u003Ca href=\"https:\u002F\u002Fbuild.microsoft.com\u002F\" target=\"_blank\" rel=\"noopener\">Build\u003C\u002Fa> 一向是微軟對開發者講故事的地方。它不是只拿來放簡報。很多功能、API、Azure 工具，都是先在這裡定調，再慢慢落地到產品裡。\u003C\u002Fp>\u003Cp>這次如果真的端出寫碼模型，意思很直接。微軟想把 AI 從泛用話題，拉回到可賣、可用、可整合的軟體工具。這種說法很務實，也很微軟。它不想只談模型參數，它想談怎麼收錢。\u003C\u002Fp>\u003Cp>對台灣開發者來說，這種變化會很有感。因為很多團隊本來就用 \u003Ca href=\"https:\u002F\u002Fcode.visualstudio.com\u002F\" target=\"_blank\" rel=\"noopener\">Visual Studio Code\u003C\u002Fa>、GitHub、Azure。只要 Copilot 更深地塞進這些工具，團隊導入的門檻就會更低。\u003C\u002Fp>\u003Cblockquote>\u003Cp>“AI is the defining technology of our time,” \u003Ca href=\"\u002Ftag\u002Fmicrosoft\">Microsoft\u003C\u002Fa> CEO Satya Nadella said at the company’s Build conference in 2023.\u003C\u002Fp>\u003C\u002Fblockquote>\u003Cp>這句話很直白。微軟早就把 AI 當主軸，不是附加功能。從 Windows 到 Azure，再到 GitHub，它都在把 AI 往核心產品線裡塞。這次的寫碼模型，只是這條路上的新一步。\u003C\u002Fp>\u003Ch2>競爭對手也不是吃素的\u003C\u002Fh2>\u003Cp>這個市場現在很擠。\u003Ca href=\"https:\u002F\u002Fopenai.com\u002F\" target=\"_blank\" rel=\"noopener\">OpenAI\u003C\u002Fa>、\u003Ca href=\"https:\u002F\u002Fwww.anthropic.com\u002F\" target=\"_blank\" rel=\"noopener\">Anthropic\u003C\u002Fa>、Google 都在打寫碼和 agent 工作流。大家都知道，開發者是高價值客群。誰能黏住開發者，誰就比較容易黏住企業預算。\u003C\u002Fp>\n\u003Cfigure class=\"my-6\">\u003Cimg src=\"https:\u002F\u002Fxxdpdyhzhpamafnrdkyq.supabase.co\u002Fstorage\u002Fv1\u002Fobject\u002Fpublic\u002Fcovers\u002Finline-1780077772974-pmt3.png\" alt=\"微軟將在 Build 發表新寫碼模型\" class=\"rounded-xl w-full\" loading=\"lazy\" \u002F>\u003C\u002Ffigure>\n\u003Cp>但真正的差別，不是誰的模型名字比較響。開發者在意的是幾件事。第一，能不能看懂整個專案。第二，能不能記住上下文。第三，會不會亂改、亂補、亂生 bug。這三件事，比單一 \u003Ca href=\"\u002Ftag\u002Fbenchmark\">benchmark\u003C\u002Fa> 還實際。\u003C\u002Fp>\u003Cp>所以微軟這次如果只是講模型很大、分數很高，老實說不夠。大家已經看太多這種話術了。真正有用的是，它能不能在真實 Repo 裡少出錯，能不能讓 \u003Ca href=\"\u002Ftag\u002Fcode-review\">code review\u003C\u002Fa> 省時間。\u003C\u002Fp>\u003Cul>\u003Cli>\u003Ca href=\"https:\u002F\u002Fopenai.com\u002Findex\u002Fintroducing-codex\u002F\" target=\"_blank\" rel=\"noopener\">OpenAI Codex\u003C\u002Fa> 早期定義了寫碼生成工具\u003C\u002Fli>\u003Cli>\u003Ca href=\"https:\u002F\u002Fwww.anthropic.com\u002Fnews\u002Fclaude-3-7-sonnet\" target=\"_blank\" rel=\"noopener\">Anthropic Claude 3.7 Sonnet\u003C\u002Fa> 在推理型寫碼任務表現不錯\u003C\u002Fli>\u003Cli>\u003Ca href=\"https:\u002F\u002Fblog.google\u002Ftechnology\u002Fdevelopers\u002Fgemini-code-assist\u002F\" target=\"_blank\" rel=\"noopener\">Google Gemini Code Assist\u003C\u002Fa> 直接卡進開發流程\u003C\u002Fli>\u003Cli>\u003Ca href=\"https:\u002F\u002Fgithub.com\u002Ffeatures\u002Fcopilot\" target=\"_blank\" rel=\"noopener\">GitHub Copilot\u003C\u002Fa> 目前是微軟最重要的入口之一\u003C\u002Fli>\u003C\u002Ful>\u003Ch2>真正的考題是交付，不是口號\u003C\u002Fh2>\u003Cp>如果微軟真的在 Build 公布新模型，接下來要看的不是新聞稿，而是上線速度。它多久能進 \u003Ca href=\"https:\u002F\u002Fcode.visualstudio.com\u002F\" target=\"_blank\" rel=\"noopener\">VS Code\u003C\u002Fa>？多久能進 GitHub Copilot？企業版\u003Ca href=\"\u002Fnews\u002Fjapan-classifying-ethereum-financial-product-zh\">什麼\u003C\u002Fa>時候能用？這些才是開發者會在意的點。\u003C\u002Fp>\u003Cp>還有一個很現實的問題。它到底能不能省時間。很多 AI 工具看起來很帥，但一進真實專案就開始掉鏈子。上下文太短、補碼太飄、測試沒過，最後還是人自己收尾。這種工具，大家用一兩次就會嫌煩。\u003C\u002Fp>\u003Cp>所以我覺得，微軟這次如果要贏，不是靠一句大話。它要拿出實測、benchmarks、和真實工作流的整合細節。沒有這些，發表會再大也只是聲量。\u003C\u002Fp>\u003Ch2>這件事放在 2026 年的脈絡裡看\u003C\u002Fh2>\u003Cp>2026 年的 AI 工具市場，已經不是誰先喊出模型名字誰就贏。現在比的是整合能力。模型只是底層。上面還有 IDE、Repo、權限、企業治理、成本控制。誰把這些串好，誰就比較容易進企業。\u003C\u002Fp>\u003Cp>微軟的優勢很明顯。它手上有 GitHub、Azure、VS Code，還有一大票企業客戶。這種組合很難複製。問題是，優勢不等於結果。開發者很現實，工具不好用就換。再大的公司也一樣。\u003C\u002Fp>\u003Cp>所以這次 Build 的看點，不是微軟會不會講 AI。它一定會講。真正要看的是，它能不能把寫碼模型變成一個真的能用、能買、能部署的產品。那才是開發者會記住的地方。\u003C\u002Fp>\u003Ch2>接下來我會盯這三件事\u003C\u002Fh2>\u003Cp>第一，模型是自研到什麼程度。第二，Copilot 的功能會不會直接升級。第三，微軟有沒有把價格講清楚。這三件事，比任何形容詞都重要。\u003C\u002Fp>\u003Cp>如果你是開發者，我建議直接看 Build 的實機展示。別只看新聞標題。看它怎麼處理真實程式碼，怎麼接上下文，怎麼跟 GitHub 和 VS Code 串起來。這些細節，才會決定它到底是新玩具，還是你每天都會開的工具。\u003C\u002Fp>","微軟預計在 Build 發表自家寫碼模型，想把 GitHub Copilot 更深塞進開發流程，也會直接對上 OpenAI、Anthropic 和 Google。","www.reuters.com","https:\u002F\u002Fwww.reuters.com\u002Fbusiness\u002Fmicrosoft-release-new-coding-model-next-week-information-reports-2026-05-28\u002F",null,"https:\u002F\u002Fxxdpdyhzhpamafnrdkyq.supabase.co\u002Fstorage\u002Fv1\u002Fobject\u002Fpublic\u002Fcovers\u002Finline-1780077779088-nupb.png","model-release","zh","6374fd69-c30e-426a-9c44-52a96cbc92cb",[17,18,19,20,21,22,23],"Microsoft","Build","GitHub Copilot","AI coding model","Visual Studio Code","開發者工具","LLM",[25,26,27],"微軟想用自家寫碼模型，讓 Copilot 更深進入開發流程。","真正的重點是整合、成本、延遲，不是單一 benchmark。","Build 之後要看模型多久能進 VS Code 和 GitHub。",4,"2026-05-29T18:02:30.242356+00:00","2026-05-29T18:02:30.214+00:00","0ccb5d2e-69f1-4354-a3e0-cb370221cd95",{"tags":33,"relatedLang":44,"relatedPosts":48},[34,36,38,40,42],{"name":17,"slug":35},"microsoft",{"name":21,"slug":37},"visual-studio-code",{"name":19,"slug":39},"github-copilot",{"name":18,"slug":41},"build",{"name":20,"slug":43},"ai-coding-model",{"id":15,"slug":45,"title":46,"language":47},"microsoft-new-coding-model-build-2026-en","Microsoft set to unveil a new coding model at Build","en",[49,55,61,67,73,79],{"id":50,"slug":51,"title":52,"cover_image":53,"image_url":53,"created_at":54,"category":13},"466021f3-b8a4-4ecb-ad64-8070beaf9cbc","gemini-1-5-pro-002-flash-002-2-0-flash-update-zh","Gemini 1.5 與 2.0 Flash 更新上線","https:\u002F\u002Fxxdpdyhzhpamafnrdkyq.supabase.co\u002Fstorage\u002Fv1\u002Fobject\u002Fpublic\u002Fcovers\u002Finline-1780999389960-97qh.png","2026-06-09T10:02:27.849751+00:00",{"id":56,"slug":57,"title":58,"cover_image":59,"image_url":59,"created_at":60,"category":13},"66ce4542-3c93-4a0c-ab52-5e6f90a36212","minimax-m3-kai-fang-quan-zhong-xie-cheng-shi-reng-neng-ying-zh","MiniMax M3 證明開放權重在寫程式上仍能贏","https:\u002F\u002Fxxdpdyhzhpamafnrdkyq.supabase.co\u002Fstorage\u002Fv1\u002Fobject\u002Fpublic\u002Fcovers\u002Finline-1780968786191-lele.png","2026-06-09T01:32:30.829528+00:00",{"id":62,"slug":63,"title":64,"cover_image":65,"image_url":65,"created_at":66,"category":13},"948a7dc4-b172-42f9-9bef-abcbbffaca18","gemini-35-flash-pricing-benchmarks-zh","Gemini 3.5 Flash 價格與長上下文解析","https:\u002F\u002Fxxdpdyhzhpamafnrdkyq.supabase.co\u002Fstorage\u002Fv1\u002Fobject\u002Fpublic\u002Fcovers\u002Finline-1780840978961-6b9n.png","2026-06-07T14:02:29.835438+00:00",{"id":68,"slug":69,"title":70,"cover_image":71,"image_url":71,"created_at":72,"category":13},"5507f140-5223-4f68-ade6-30d9e5457638","gemma-4-12b-specs-benchmarks-run-locally-zh","怎麼做 Gemma 4 12B 本地部署","https:\u002F\u002Fxxdpdyhzhpamafnrdkyq.supabase.co\u002Fstorage\u002Fv1\u002Fobject\u002Fpublic\u002Fcovers\u002Finline-1780777971165-4bit.png","2026-06-06T20:32:24.857611+00:00",{"id":74,"slug":75,"title":76,"cover_image":77,"image_url":77,"created_at":78,"category":13},"ef42a437-8b06-4ff5-a135-ece7662c01f4","best-kimi-models-2026-k2-5-vs-k2-thinking-zh","2026 最佳 Kimi 模型：K2.5 對 K2 Thinking","https:\u002F\u002Fxxdpdyhzhpamafnrdkyq.supabase.co\u002Fstorage\u002Fv1\u002Fobject\u002Fpublic\u002Fcovers\u002Finline-1780770790333-x3lk.png","2026-06-06T18:32:39.410186+00:00",{"id":80,"slug":81,"title":82,"cover_image":83,"image_url":83,"created_at":84,"category":13},"fd2ad557-5c09-4758-964d-cda1c3c87a4c","kimi-k2-6-open-source-coding-agent-swarm-zh","Kimi K2.6 開源加上 Agent Swarm","https:\u002F\u002Fxxdpdyhzhpamafnrdkyq.supabase.co\u002Fstorage\u002Fv1\u002Fobject\u002Fpublic\u002Fcovers\u002Finline-1780761795960-0zg9.png","2026-06-06T16:02:21.702099+00:00",[86,91,96,101,106,111,116,121,126,131],{"id":87,"slug":88,"title":89,"created_at":90},"58b64033-7eb6-49b9-9aab-01cf8ae1b2f2","nvidia-rubin-six-chips-one-ai-supercomputer-zh","NVIDIA Rubin 把六顆晶片塞進 AI 機櫃","2026-03-26T07:18:45.861277+00:00",{"id":92,"slug":93,"title":94,"created_at":95},"0dcc2c61-c2a6-480d-adb8-dd225fc68914","march-2026-ai-model-news-what-mattered-zh","2026 年 3 月 AI 模型新聞重點","2026-03-26T07:32:08.386348+00:00",{"id":97,"slug":98,"title":99,"created_at":100},"214ab08b-5ce5-4b5c-8b72-47619d8675dd","why-small-models-are-winning-on-device-ai-zh","小模型為何吃下裝置端 AI","2026-03-26T07:36:30.488966+00:00",{"id":102,"slug":103,"title":104,"created_at":105},"785624b2-0355-4b82-adc3-de5e45eecd88","midjourney-v8-faster-images-higher-costs-zh","Midjourney V8 變快了，也變貴了","2026-03-26T07:52:03.562971+00:00",{"id":107,"slug":108,"title":109,"created_at":110},"cda76b92-d209-4134-86c1-a60f5bc7b128","xiaomi-mimo-trio-agents-robots-voice-zh","小米 MiMo 三模型瞄準代理、機器人與語音","2026-03-28T03:05:08.779489+00:00",{"id":112,"slug":113,"title":114,"created_at":115},"9e1044b4-946d-47fe-9e2a-c2ee032e1164","xiaomi-mimo-v2-pro-1t-moe-agents-zh","小米 MiMo-V2-Pro 登場：1T MoE 模型","2026-03-28T03:06:19.002353+00:00",{"id":117,"slug":118,"title":119,"created_at":120},"c4b6186f-bd84-4598-997e-c6e31d543c0d","cursor-composer-2-agentic-coding-model-zh","Cursor Composer 2 走向代理式寫碼","2026-03-28T03:13:06.422716+00:00",{"id":122,"slug":123,"title":124,"created_at":125},"e112e76f-ec3b-408f-810e-e93ae21a888a","apple-siri-gemini-distilled-models-zh","Apple Siri 牽手 Gemini 的真相","2026-03-29T04:52:57.886544+00:00",{"id":127,"slug":128,"title":129,"created_at":130},"c679b51f-194a-463b-87fc-7695256ff752","mimo-v2-pro-vs-omni-vs-flash-2026-zh","MiMo V2 Pro、Omni、Flash 怎麼選","2026-04-02T01:18:43.576128+00:00",{"id":132,"slug":133,"title":134,"created_at":135},"3b988fd7-6749-4f01-ba25-c0ad7486dc31","z-ai-glm-5v-turbo-design2code-claude-zh","GLM-5V-Turbo 在 Design2Code 贏了…","2026-04-02T04:03:36.31741+00:00"]