[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"article-geekbench-7-realistic-cpu-gpu-benchmark-setup-zh":3,"article-related-geekbench-7-realistic-cpu-gpu-benchmark-setup-zh":30,"series-tools-b6aa4cba-e0e5-46c6-bfff-b9b9402f101c":75},{"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":23,"views":27,"created_at":28,"published_at":29,"topic_cluster_id":11},"b6aa4cba-e0e5-46c6-bfff-b9b9402f101c","geekbench-7-realistic-cpu-gpu-benchmark-setup-zh","Geekbench 7 CPU 與 GPU 測試設定","\u003Cp data-speakable=\"summary\">這篇\u003Ca href=\"\u002Fnews\u002Fopenai-incident-postmortem-security-template-zh\">教你\u003C\u002Fa>安裝 Geekbench 7、跑 CPU 與 \u003Ca href=\"\u002Ftag\u002Fgpu\">GPU\u003C\u002Fa> 基準測試，並用正確規則記錄與比較結果。\u003C\u002Fp>\u003Cp>這篇給開發者、PC 組裝者和效能評測者看，目標是把 Geekbench 7 裝好、跑出可重現的 CPU 與 GPU 分數，並避免把新舊版本混在一起比。\u003C\u002Fp>\u003Cp>照著做完，你會得到一套可重複執行的測試流程、清楚的結果紀錄，以及能直接用來做硬體選購或回歸檢查的基準\u003Ca href=\"\u002Fnews\u002Fvector-databases-financial-search-market-growth-zh\">資料\u003C\u002Fa>。\u003C\u002Fp>\u003Ch2>開始之前\u003C\u002Fh2>\u003Cul>\u003Cli>需要一個可上網的裝置，並能連到官方 \u003Ca href=\"https:\u002F\u002Fwww.geekbench.com\u002F\" target=\"_blank\" rel=\"noopener noreferrer\">Geekbench 網站\u003C\u002Fa>與 \u003Ca href=\"https:\u002F\u002Fgithub.com\u002Fprimate-labs\u002Fgeekbench\" target=\"_blank\" rel=\"noopener noreferrer\">GitHub repository\u003C\u002Fa>。\u003C\u002Fli>\u003Cli>桌機或筆電需具備 Windows 10+、macOS 12+、Ubuntu 22.04 LTS+，或支援的 Android／iOS 裝置。\u003C\u002Fli>\u003Cli>GPU 測試若要用 CUDA，需 NVIDIA 顯示卡與目前版本驅動程式。\u003C\u002Fli>\u003Cli>至少 4 GB RAM，桌機建議 8 GB 以上，避免背景程序干擾。\u003C\u002Fli>\u003Cli>需要管理員權限，才能完成安裝與必要的系統授權。\u003C\u002Fli>\u003Cli>若要使用 Pro 功能，需準備 Geekbench Pro 授權。\u003C\u002Fli>\u003C\u002Ful>\u003Ch2>Step 1: 下載 Geekbench 7 安裝檔\u003C\u002Fh2>\u003Cp>這一步的目的是拿到正確版本，避免把 Geekbench 6 當成 Geekbench 7。請只從官方下載頁取得安裝包，並確認副檔名符合你的作業系統。\u003C\u002Fp>\n\u003Cfigure class=\"my-6\">\u003Cimg src=\"https:\u002F\u002Fxxdpdyhzhpamafnrdkyq.supabase.co\u002Fstorage\u002Fv1\u002Fobject\u002Fpublic\u002Fcovers\u002Finline-1785119572418-qq3i.png\" alt=\"Geekbench 7 CPU 與 GPU 測試設定\" class=\"rounded-xl w-full\" loading=\"lazy\" \u002F>\u003C\u002Ffigure>\n\u003Cpre>\u003Ccode>Windows: 下載 .exe 安裝檔\u003C\u002Fcode>\u003C\u002Fpre>\u003Cpre>\u003Ccode>macOS: 下載 .dmg 安裝檔\u003C\u002Fcode>\u003C\u002Fpre>\u003Cpre>\u003Ccode>Linux: 下載 .tar.gz 套件\u003C\u002Fcode>\u003C\u002Fpre>\u003Cp>你應該看到一個標示為 Geekbench 7 的檔案，且檔名與\u003Ca href=\"\u002Fnews\u002Fsap-design-system-ai-cross-platform-ui-kits-zh\">平台\u003C\u002Fa>相符。\u003C\u002Fp>\u003Ch2>Step 2: 安裝並啟動 Geekbench 7\u003C\u002Fh2>\u003Cp>這一步的目的是把程式安裝到系統中，並確認它能正常開啟。先依平台完成安裝，再啟動一次檢查有沒有缺少元件或權限問題。\u003C\u002Fp>\n\u003Cfigure class=\"my-6\">\u003Cimg src=\"https:\u002F\u002Fxxdpdyhzhpamafnrdkyq.supabase.co\u002Fstorage\u002Fv1\u002Fobject\u002Fpublic\u002Fcovers\u002Finline-1785119573166-xcrd.png\" alt=\"Geekbench 7 CPU 與 GPU 測試設定\" class=\"rounded-xl w-full\" loading=\"lazy\" \u002F>\u003C\u002Ffigure>\n\u003Cpre>\u003Ccode>Windows: 執行安裝程式並完成精靈\u003C\u002Fcode>\u003C\u002Fpre>\u003Cpre>\u003Ccode>macOS: 開啟 .dmg，將 Geekbench 拖到 Applications\u003C\u002Fcode>\u003C\u002Fpre>\u003Cpre>\u003Ccode>Linux: 解壓縮後執行 Geekbench 主程式\u003C\u002Fcode>\u003C\u002Fpre>\u003Cp>你應該看到 Geekbench 7 主畫面，並且能找到 CPU 與 GPU 測試入口。\u003C\u002Fp>\u003Ch2>Step 3: 跑出 CPU 基準分數\u003C\u002Fh2>\u003Cp>這一步的目的是取得一組新的 CPU 分數，之後只拿來跟其他 Geekbench 7 結果比較。先關掉大型下載、同步工具與瀏覽器分頁，再開始測試。\u003C\u002Fp>\u003Cpre>\u003Ccode>開啟 Geekbench 7\u003C\u002Fcode>\u003C\u002Fpre>\u003Cpre>\u003Ccode>選擇 CPU Benchmark\u003C\u002Fcode>\u003C\u002Fpre>\u003Cpre>\u003Ccode>關閉背景重載程式後開始測試\u003C\u002Fcode>\u003C\u002Fpre>\u003Cpre>\u003Ccode>完成後儲存結果連結或報告\u003C\u002Fcode>\u003C\u002Fpre>\u003Cp>你應該看到單核心與多核心分數，且多核心成績會反映新版工作負載模型。\u003C\u002Fp>\u003Ch2>Step 4: 選對 GPU 計算 API\u003C\u002Fh2>\u003Cp>這一步的目的是取得能代表你硬體的 GPU 分數。Geekbench 7 支援 OpenCL、Vulkan、Metal，且在 \u003Ca href=\"\u002Ftag\u002Fnvidia\">NVIDIA\u003C\u002Fa> 平台上可用 \u003Ca href=\"\u002Ftag\u002Fcuda\">CUDA\u003C\u002Fa>；不同 \u003Ca href=\"\u002Ftag\u002Fapi\">API\u003C\u002Fa> 會影響結果。\u003C\u002Fp>\u003Cpre>\u003Ccode>開啟 Geekbench 7\u003C\u002Fcode>\u003C\u002Fpre>\u003Cpre>\u003Ccode>選擇 GPU Benchmark\u003C\u002Fcode>\u003C\u002Fpre>\u003Cpre>\u003Ccode>在 NVIDIA 上優先選 CUDA\u003C\u002Fcode>\u003C\u002Fpre>\u003Cpre>\u003Ccode>再用 OpenCL 或 Vulkan 跑一次對照\u003C\u002Fcode>\u003C\u002Fpre>\u003Cp>你應該看到不同 API 對應的 GPU 分數，且 NVIDIA 上的 CUDA 結果會和其他路徑明顯不同。\u003C\u002Fp>\u003Ch2>Step 5: 用同版本規則保存結果\u003C\u002Fh2>\u003Cp>這一步的目的是建立可追溯的測試紀錄。Geekbench 7 以 AMD Ryzen 7 7700 正規化到 2,500 分為新基準，所以不能直接拿 Geekbench 6 分數對照。\u003C\u002Fp>\u003Cpre>\u003Ccode>儲存 Geekbench 結果網址\u003C\u002Fcode>\u003C\u002Fpre>\u003Cpre>\u003Ccode>記錄 CPU 型號、GPU 型號、驅動版本、OS 版本、API\u003C\u002Fcode>\u003C\u002Fpre>\u003Cpre>\u003Ccode>只和其他 Geekbench 7 結果比較\u003C\u002Fcode>\u003C\u002Fpre>\u003Cp>你應該能清楚說明分數來自哪台機器、哪個驅動、哪個 API，這樣結果才可用於採購與回歸分析。\u003C\u002Fp>\u003Ctable>\u003Cthead>\u003Ctr>\u003Cth>指標\u003C\u002Fth>\u003Cth>基準／優化前\u003C\u002Fth>\u003Cth>結果／優化後\u003C\u002Fth>\u003C\u002Ftr>\u003C\u002Fthead>\u003Ctbody>\u003Ctr>\u003Ctd>CPU 基準\u003C\u002Ftd>\u003Ctd>Geekbench 6 使用舊基準\u003C\u002Ftd>\u003Ctd>Geekbench 7 以 AMD Ryzen 7 7700 正規化到 2,500 分\u003C\u002Ftd>\u003C\u002Ftr>\u003Ctr>\u003Ctd>多核心模型\u003C\u002Ftd>\u003Ctd>較多子測試會全面分散到各核心\u003C\u002Ftd>\u003Ctd>只在真實應用會擴展的工作上並行\u003C\u002Ftd>\u003C\u002Ftr>\u003Ctr>\u003Ctd>GPU API\u003C\u002Ftd>\u003Ctd>OpenCL、Vulkan、Metal\u003C\u002Ftd>\u003Ctd>OpenCL、Vulkan、Metal，外加 NVIDIA 上的 CUDA\u003C\u002Ftd>\u003C\u002Ftr>\u003Ctr>\u003Ctd>GPU 工作負載\u003C\u002Ftd>\u003Ctd>較舊的圖形導向項目\u003C\u002Ftd>\u003Ctd>ML upscaling、face tracking、background blur、RAW processing、path tracing\u003C\u002Ftd>\u003C\u002Ftr>\u003C\u002Ftbody>\u003C\u002Ftable>\u003Ch2>常見錯誤\u003C\u002Fh2>\u003Cul>\u003Cli>把 Geekbench 7 和 Geekbench 6 混著比。修法：只比較同版本結果，因為基準與負載模型都變了。\u003C\u002Fli>\u003Cli>NVIDIA 顯卡沒有選到 CUDA。修法：先更新驅動，再重新跑 GPU 測試並手動切換 CUDA。\u003C\u002Fli>\u003Cli>背景程式太多，分數不穩。修法：每次測試前關閉瀏覽器、同步工具與啟動器。\u003C\u002Fli>\u003C\u002Ful>\u003Ch2>接下來可以看什麼\u003C\u002Fh2>\u003Cp>下一步可以把 Geekbench 7 結果整理成一份小型效能紀錄表，連同驅動版本、BIOS 更新與溫度條件一起保存，方便你追蹤真正的效能變化。\u003C\u002Fp>","這篇教你安裝 Geekbench 7、跑 CPU 與 GPU 基準測試，並用正確規則記錄與比較結果。","basic-tutorials.com","https:\u002F\u002Fbasic-tutorials.com\u002Fnews\u002Fgeekbench-7-is-here-cuda-support-and-a-completely-new-multi-core-test\u002F",null,"https:\u002F\u002Fxxdpdyhzhpamafnrdkyq.supabase.co\u002Fstorage\u002Fv1\u002Fobject\u002Fpublic\u002Fcovers\u002Finline-1785119572418-qq3i.png","tools","zh","1b7715b0-0594-43bc-b603-1dde7cff7664",[17,18,19,20,21,22],"Geekbench 7","CPU benchmark","GPU benchmark","CUDA","OpenCL","效能測試",[24,25,26],"只比較 Geekbench 7 同版本結果，不要混用 Geekbench 6。","GPU 測試要依硬體選對 API，NVIDIA 可優先測 CUDA。","保存結果時要記錄 CPU、GPU、驅動、OS 與 API，才能重現。",0,"2026-07-27T02:32:23.411062+00:00","2026-07-27T02:32:23.397+00:00",{"tags":31,"relatedLang":34,"relatedPosts":38},[32],{"name":20,"slug":33},"cuda",{"id":15,"slug":35,"title":36,"language":37},"geekbench-7-realistic-cpu-gpu-benchmark-setup-en","Geekbench 7 setup for realistic CPU and GPU tests","en",[39,45,51,57,63,69],{"id":40,"slug":41,"title":42,"cover_image":43,"image_url":43,"created_at":44,"category":13},"5c82774f-9220-475a-ba1d-ef35c8d180d5","spark-42-turns-ai-search-into-sql-zh","Spark 4.2 把 AI 搜尋收進 SQL","https:\u002F\u002Fxxdpdyhzhpamafnrdkyq.supabase.co\u002Fstorage\u002Fv1\u002Fobject\u002Fpublic\u002Fcovers\u002Finline-1785067404325-tkwt.png","2026-07-26T12:02:55.376028+00:00",{"id":46,"slug":47,"title":48,"cover_image":49,"image_url":49,"created_at":50,"category":13},"6f9cbc0e-712e-438e-9b75-96431bdcdf33","openai-incident-postmortem-security-template-zh","OpenAI 事故帖教你寫安全復盤","https:\u002F\u002Fxxdpdyhzhpamafnrdkyq.supabase.co\u002Fstorage\u002Fv1\u002Fobject\u002Fpublic\u002Fcovers\u002Finline-1785024220921-qols.png","2026-07-26T00:03:15.743094+00:00",{"id":52,"slug":53,"title":54,"cover_image":55,"image_url":55,"created_at":56,"category":13},"08c27def-4f0f-4959-b7bd-e112d1dd8f8d","sap-design-system-ai-cross-platform-ui-kits-zh","SAP Design System 加入 AI 與跨平台 UI Kit","https:\u002F\u002Fxxdpdyhzhpamafnrdkyq.supabase.co\u002Fstorage\u002Fv1\u002Fobject\u002Fpublic\u002Fcovers\u002Finline-1785009771871-nkf6.png","2026-07-25T20:02:25.288494+00:00",{"id":58,"slug":59,"title":60,"cover_image":61,"image_url":61,"created_at":62,"category":13},"60e3efb8-e6dd-4c31-9b56-d91cc2bd04d7","chatgpt-health-turns-chat-into-health-layer-zh","ChatGPT Health 直接進主對話","https:\u002F\u002Fxxdpdyhzhpamafnrdkyq.supabase.co\u002Fstorage\u002Fv1\u002Fobject\u002Fpublic\u002Fcovers\u002Finline-1785002596802-9crh.png","2026-07-25T18:02:50.190152+00:00",{"id":64,"slug":65,"title":66,"cover_image":67,"image_url":67,"created_at":68,"category":13},"d1580f53-26f0-4bc7-8788-d8ba029bb096","microsoft-azure-amd-ai-hpc-2026-zh","Microsoft 把 AMD 晶片帶進 Azure AI","https:\u002F\u002Fxxdpdyhzhpamafnrdkyq.supabase.co\u002Fstorage\u002Fv1\u002Fobject\u002Fpublic\u002Fcovers\u002Finline-1784964760772-c01a.png","2026-07-25T07:32:15.638692+00:00",{"id":70,"slug":71,"title":72,"cover_image":73,"image_url":73,"created_at":74,"category":13},"0461ca72-072e-40dd-a2b4-0521afd6c7a7","openai-compatible-model-comparison-script-zh","一套 OpenAI 兼容脚本測出差距","https:\u002F\u002Fxxdpdyhzhpamafnrdkyq.supabase.co\u002Fstorage\u002Fv1\u002Fobject\u002Fpublic\u002Fcovers\u002Finline-1784918020667-jwkd.png","2026-07-24T18:33:10.378548+00:00",[76,81,86,91,96,101,106,111,116,121],{"id":77,"slug":78,"title":79,"created_at":80},"855cd52f-6fab-46cc-a7c1-42195e8a0de4","surepath-real-time-mcp-policy-controls-zh","SurePath 推出即時 MCP 政策控管","2026-03-26T07:57:40.77233+00:00",{"id":82,"slug":83,"title":84,"created_at":85},"9b19ab54-edef-4dbd-9ce4-a51e4bae4ebb","mcp-in-2026-the-ai-tool-layer-teams-use-zh","2026 年 MCP：團隊真的在用的 AI 工具層","2026-03-26T08:01:46.589694+00:00",{"id":87,"slug":88,"title":89,"created_at":90},"af9c46c3-7a28-410b-9f04-32b3de30a68c","prompting-in-2026-what-actually-works-zh","2026 提示工程，真正有用的是什麼","2026-03-26T08:08:12.453028+00:00",{"id":92,"slug":93,"title":94,"created_at":95},"05553086-6ed0-4758-81fd-6cab24b575e0","garry-tan-open-sources-claude-code-toolkit-zh","Garry Tan 開源 Claude Code 工具包","2026-03-26T08:26:20.068737+00:00",{"id":97,"slug":98,"title":99,"created_at":100},"042a73a2-18a2-433d-9e8f-9802b9559aac","github-ai-projects-to-watch-in-2026-zh","2026 必看 20 個 GitHub AI 專案","2026-03-26T08:28:09.619964+00:00",{"id":102,"slug":103,"title":104,"created_at":105},"a5f94120-ac0d-4483-9a8b-63590071ac6a","claude-code-vs-cursor-2026-zh","Claude Code 與 Cursor 深度對比：202…","2026-03-26T13:27:14.279193+00:00",{"id":107,"slug":108,"title":109,"created_at":110},"0975afa1-e0c7-4130-a20d-d890eaed995e","practical-github-guide-learning-ml-2026-zh","2026 機器學習入門 GitHub 實用指南","2026-03-27T01:16:49.712576+00:00",{"id":112,"slug":113,"title":114,"created_at":115},"bfdb467a-290f-4a80-b3a9-6f081afb6dff","aiml-2026-student-ai-ml-lab-repo-review-zh","AIML-2026：像課綱的學生實驗 Repo","2026-03-27T01:21:51.467798+00:00",{"id":117,"slug":118,"title":119,"created_at":120},"80cabc3e-09fc-4ff5-8f07-b8d68f5ae545","ai-trending-github-repos-and-research-feeds-zh","AI Trending：把 AI 資源收成一張表","2026-03-27T01:31:35.262183+00:00",{"id":122,"slug":123,"title":124,"created_at":125},"3ce6e6e2-bac5-463e-9f8d-45caabcc61f7","awesome-ai-for-science-research-tools-map-zh","AI 科研工具清單，開始像地圖了","2026-03-27T01:46:50.521945+00:00"]