[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"article-free-llm-api-platforms-2026-complete-guide-zh":3,"tags-free-llm-api-platforms-2026-complete-guide-zh":30,"related-lang-free-llm-api-platforms-2026-complete-guide-zh":41,"related-posts-free-llm-api-platforms-2026-complete-guide-zh":45,"series-tools-15f45aa9-9941-40c9-a6fe-211b51af0b99":82},{"id":4,"title":5,"content":6,"summary":7,"source":8,"source_url":9,"author":9,"image_url":10,"keywords":11,"language":17,"translated_content":9,"views":18,"is_premium":19,"created_at":20,"updated_at":20,"cover_image":10,"published_at":21,"rewrite_status":22,"rewrite_error":9,"rewritten_from_id":9,"slug":23,"category":24,"related_article_id":25,"status":26,"google_indexed_at":27,"x_posted_at":9,"tweet_text":9,"title_rewritten_at":28,"title_original":29,"key_takeaways":9,"topic_cluster_id":9,"embedding":9,"is_canonical_seed":19},"15f45aa9-9941-40c9-a6fe-211b51af0b99","2026 免費 LLM API 推薦：30+平台比較","\u003Cp>2026 年的大語言模型生態已經成熟到一個有趣的階段：免費額度變成了基本標配，而不是稀罕功能。無論你是學生、開發者還是創業團隊，都能找到至少一個支持你實驗想法的免費平台。但正因為選擇太多，如何挑選反而成了新問題。\u003C\u002Fp>\u003Ch2>國內平台：多模型競爭，差異化策略明顯\u003C\u002Fh2>\u003Cp>\u003Ca href=\"https:\u002F\u002Fopen.bigmodel.cn\" target=\"_blank\" rel=\"noopener\">智谱 AI\u003C\u002Fa> 的 GLM-4-Flash 永久免費政策打破了業界慣例。新使用者一次性獲得 2000 萬 Token，足以執行數千次高品質推理。更重要的是，它承諾「永久免費」——在國內大模型廠商中相當罕見。該服務支援 30 個並發請求，對於 POC（概念驗證）階段的應用已經夠用。\u003C\u002Fp>\n\u003Cfigure class=\"my-6\">\u003Cimg src=\"https:\u002F\u002Fxxdpdyhzhpamafnrdkyq.supabase.co\u002Fstorage\u002Fv1\u002Fobject\u002Fpublic\u002Fcovers\u002Finline-1774848502484-eexg.png\" alt=\"2026 年免費大模型 API 完整地圖：超過 30 個平台對比與實戰指南\" class=\"rounded-xl w-full\" loading=\"lazy\" \u002F>\u003C\u002Ffigure>\n\u003Cp>\u003Ca href=\"https:\u002F\u002Fplatform.moonshot.cn\" target=\"_blank\" rel=\"noopener\">月之暗面 Kimi\u003C\u002Fa> 走的是「超長上下文」路線。256K Token 的窗口對於處理長文檔、技術文件或完整程式碼庫有決定性優勢。雖然限流是每分鐘 3 次請求，但 Token 額度不限，適合需要一次性處理大量資訊的場景，比如程式碼審查或文檔總結。\u003C\u002Fp>\u003Cp>\u003Ca href=\"https:\u002F\u002Fapi.siliconflow.cn\" target=\"_blank\" rel=\"noopener\">硅基流动\u003C\u002Fa>主打開源模型的多樣性。DeepSeek、Qwen 系列的 API 都能透過統一介面存取，速率限制為 1000 RPM per 模型，可以承載中等規模流量。如果你想測試各家開源模型而不想逐一註冊，硅基流动是捷徑。\u003C\u002Fp>\u003Cp>字節豆包、阿里通義千問、百度文心、騰訊混元、訊飛星火等平台各有側重，但免費額度通常需要主動申請或參與活動才能獲得。這些廠商傾向於用免費層吸引長期使用者，而非無條件開放。\u003C\u002Fp>\u003Ch2>國際平台：生態成熟，額度最大\u003C\u002Fh2>\u003Cp>\u003Ca href=\"https:\u002F\u002Fai.google.dev\" target=\"_blank\" rel=\"noopener\">Google AI Studio\u003C\u002Fa> 提供了可能是現階段最慷慨的免費配額。Gemini 2.5 Flash 每分鐘 30 個請求，每天 1440 個請求，額度高到足以支撐小型應用的日常運作。Google 的算力基礎設施意味著穩定性有保障，而 Gemini 的多模態能力（圖文音頻）在同級免費服務中獨樹一幟。\u003C\u002Fp>\u003Cp>\u003Ca href=\"https:\u002F\u002Fmodels.github.ai\" target=\"_blank\" rel=\"noopener\">GitHub Models\u003C\u002Fa> 的創新之處在於門檻最低——只需 GitHub 帳戶即可使用。GPT-4o、4-turbo 等高級模型都開放試用，限額是每分鐘 15 個、每天 150 個請求。對於 GitHub 使用者來說，這可能是最快上手的選擇。\u003C\u002Fp>\u003Cp>\u003Ca href=\"https:\u002F\u002Fgroq.com\" target=\"_blank\" rel=\"noopener\">Groq\u003C\u002Fa> 代表了推理速度的極致。其 LPU（Language Processing Unit）硬體加速讓生成速度快 5-10 倍，免費版提供每天 1000 次請求。如果你的應用對延遲敏感（比如實時聊天應用），Groq 的性能優勢值得測試。\u003C\u002Fp>\u003Cp>\u003Ca href=\"https:\u002F\u002Fdevelopers.cloudflare.com\u002Fworkers-ai\u002F\" target=\"_blank\" rel=\"noopener\">Cloudflare Workers AI\u003C\u002Fa> 運用全球 CDN 基礎設施，每天 10000 Neurons 的免費額度可以透過邊緣計算節點就近執行推理。延遲低、成本低，特別適合全球分布式應用。\u003Ca href=\"https:\u002F\u002Fopenrouter.ai\" target=\"_blank\" rel=\"noopener\">OpenRouter\u003C\u002Fa> 聚合了多家廠商的 API，國內可直連，無需代理，模型選擇最豐富。\u003C\u002Fp>\u003Ch2>第三方代理與風險考量\u003C\u002Fh2>\u003Cp>ChatAnywhere、GemAI、API520 等代理平台以「統一介面」和「規避地理限制」為賣點。雖然方便，但代理層增加了安全風險，而且免費政策往往不穩定。一旦廠商修改政策，代理服務可能突然失效。生產環境應該避免依賴這類服務。\u003C\u002Fp>\n\u003Cfigure class=\"my-6\">\u003Cimg src=\"https:\u002F\u002Fxxdpdyhzhpamafnrdkyq.supabase.co\u002Fstorage\u002Fv1\u002Fobject\u002Fpublic\u002Fcovers\u002Finline-1774848525451-pvo1.png\" alt=\"2026 年免費大模型 API 完整地圖：超過 30 個平台對比與實戰指南\" class=\"rounded-xl w-full\" loading=\"lazy\" \u002F>\u003C\u002Ffigure>\n\u003Ch2>實戰選擇指南\u003C\u002Fh2>\u003Cp>選擇哪個平台取決於三個維度：使用場景、預算容量和地理位置。學習和測試優先 Google AI Studio 或 GitHub Models，額度大且穩定。國內開發推薦 OpenRouter（可直連、模型多）或硅基流动（開源模型友好）。如果需要超長上下文，Kimi 的 256K 窗口無人能及。高速推理就選 Groq，多模態應用就用 Gemini。\u003C\u002Fp>\u003Cp>重要提醒：速率限制要做好降級處理，準備備用方案。免費政策隨時可能變動，定期檢查官方文檔。最後，即使有免費額度，生產環境仍應採用付費 API 保證穩定性。多平台組合能有效分散風險。\u003C\u002Fp>","免費 LLM API 的競爭已進入激烈階段。從國內的智谱、月之暗面到國際的 Google AI Studio、GitHub Models，以及專注推理速度的 Groq，開發者現在有超過 30 個選擇。本文詳細比較各平台的額度、速率限制、模型陣容和適用場景，幫助你選出最適合當前專案的方案。","OraCore",null,"https:\u002F\u002Fxxdpdyhzhpamafnrdkyq.supabase.co\u002Fstorage\u002Fv1\u002Fobject\u002Fpublic\u002Fcovers\u002Finline-1774848502484-eexg.png",[12,13,14,15,16],"free LLM API","AI model","GPT","Gemini","Groq","zh",3,false,"2026-03-30T05:24:01.048449+00:00","2026-03-30T05:28:45.728+00:00","done","free-llm-api-platforms-2026-complete-guide-zh","tools","071f1624-a2d9-4fbd-9e7f-a9d60da7f5f7","published","2026-04-09T09:00:57.86+00:00","2026-05-04T02:00:09.432+00:00","2026 免費 LLM API 全攻略：30+ 平台實戰比較",[31,33,35,37,39],{"name":14,"slug":32},"gpt",{"name":16,"slug":34},"groq",{"name":13,"slug":36},"ai-model",{"name":15,"slug":38},"gemini",{"name":12,"slug":40},"free-llm-api",{"id":25,"slug":42,"title":43,"language":44},"free-llm-api-platforms-2026-complete-guide-en","The Best Free LLM APIs of 2026: 30+ Platforms Tested","en",[46,52,58,64,70,76],{"id":47,"slug":48,"title":49,"cover_image":50,"image_url":50,"created_at":51,"category":24},"d058a76f-6548-4135-8970-f3a97f255446","why-gemini-api-pricing-is-cheaper-than-it-looks-zh","為什麼 Gemini API 定價其實比看起來更便宜","https:\u002F\u002Fxxdpdyhzhpamafnrdkyq.supabase.co\u002Fstorage\u002Fv1\u002Fobject\u002Fpublic\u002Fcovers\u002Finline-1778869845081-j4m7.png","2026-05-15T18:30:25.797639+00:00",{"id":53,"slug":54,"title":55,"cover_image":56,"image_url":56,"created_at":57,"category":24},"68e4be16-dc38-4524-a6ea-5ebe22a6c4fb","why-vidhub-huiyuan-hutong-bushi-quan-shebei-tongyong-zh","為什麼 VidHub 會員互通不是「買一次全設備通用」","https:\u002F\u002Fxxdpdyhzhpamafnrdkyq.supabase.co\u002Fstorage\u002Fv1\u002Fobject\u002Fpublic\u002Fcovers\u002Finline-1778789450987-advz.png","2026-05-14T20:10:24.048988+00:00",{"id":59,"slug":60,"title":61,"cover_image":62,"image_url":62,"created_at":63,"category":24},"7a1e174f-746b-4e82-a0e3-b2475ab39747","why-buns-zig-to-rust-experiment-is-right-zh","為什麼 Bun 的 Zig-to-Rust 實驗是對的","https:\u002F\u002Fxxdpdyhzhpamafnrdkyq.supabase.co\u002Fstorage\u002Fv1\u002Fobject\u002Fpublic\u002Fcovers\u002Finline-1778767879127-5dna.png","2026-05-14T14:10:26.886397+00:00",{"id":65,"slug":66,"title":67,"cover_image":68,"image_url":68,"created_at":69,"category":24},"e742fc73-5a65-4db3-ad17-88c99262ceb7","why-openai-api-pricing-is-product-strategy-zh","為什麼 OpenAI API 定價是產品策略，不是註腳","https:\u002F\u002Fxxdpdyhzhpamafnrdkyq.supabase.co\u002Fstorage\u002Fv1\u002Fobject\u002Fpublic\u002Fcovers\u002Finline-1778749859485-chvz.png","2026-05-14T09:10:26.003818+00:00",{"id":71,"slug":72,"title":73,"cover_image":74,"image_url":74,"created_at":75,"category":24},"c757c5d8-eda9-45dc-9020-4b002f4d6237","why-claude-code-prompt-design-beats-ide-copilots-zh","為什麼 Claude Code 的提示設計贏過 IDE Copilot","https:\u002F\u002Fxxdpdyhzhpamafnrdkyq.supabase.co\u002Fstorage\u002Fv1\u002Fobject\u002Fpublic\u002Fcovers\u002Finline-1778742645084-dao9.png","2026-05-14T07:10:29.371901+00:00",{"id":77,"slug":78,"title":79,"cover_image":80,"image_url":80,"created_at":81,"category":24},"4adef3ab-9f07-4970-91cf-77b8b581b348","why-databricks-model-serving-is-right-default-zh","為什麼 Databricks Model Serving 是生產推論的正確預設","https:\u002F\u002Fxxdpdyhzhpamafnrdkyq.supabase.co\u002Fstorage\u002Fv1\u002Fobject\u002Fpublic\u002Fcovers\u002Finline-1778692245329-a2wt.png","2026-05-13T17:10:30.659153+00:00",[83,88,93,98,103,108,113,118,123,128],{"id":84,"slug":85,"title":86,"created_at":87},"de769291-4574-4c46-a76d-772bd99e6ec9","googles-biggest-gemini-launches-in-2026-zh","Google 2026 最大 Gemini 盤點","2026-03-26T07:26:39.21072+00:00",{"id":89,"slug":90,"title":91,"created_at":92},"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":94,"slug":95,"title":96,"created_at":97},"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":99,"slug":100,"title":101,"created_at":102},"af9c46c3-7a28-410b-9f04-32b3de30a68c","prompting-in-2026-what-actually-works-zh","2026 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