{
  "aboutHtml": "<p>Whisper large-v3-turbo 也稱 Turbo，是 OpenAI 從 Whisper large-v3 衍生的最佳化轉錄模型。解碼器由 32 層減至四層，編碼器維持 32 層。發布模型約有 8.09 億參數。製造商目的是以小幅準確率取捨換取較快語音辨識，不是另一種音訊生成模式。輸入是錄製語音，結果是辨識文字。</p><p>發布公告將 Turbo 的準備方式與另外蒸餾的 Whisper 模型區分：Turbo 以多語言轉錄資料額外微調兩個訓練週期，不包含翻譯資料。這項差異對操作很重要。OpenAI 儲存庫指出，Turbo 未受訓將非英文語音翻成英文，即使要求翻譯任務，也可能回傳原始語言。請用此版本產生同語言逐字稿；翻譯需求屬於另一個合適模型，或轉錄後的獨立步驟。</p><p>來源語言偵測與明確語言選擇，仍是實用轉錄選項。若已知錄音語言，請在簡報中指出；否則文件記載的流程可偵測。要求任何編輯整理前，先保留姓名、數量與實際說出的字詞。會議紀錄、訪談逐字稿或課程文字，之後可透過另一項操作搜尋、註解或摘要。Turbo 辨識任務不應與聲音合成、模仿說話者，或對錄音人物作語意判斷混淆。</p><p>OpenAI 音訊載入器將輸入檔案解碼成 16 kHz 單聲道樣本，模型使用 30 秒聲學視窗及 128 個梅爾頻率頻帶。較長錄音需要長篇推論。依序處理會按順序移動視窗；分塊方法則轉錄重疊片段並銜接邊界。模型卡片將後者描述為處理單一長檔案、以周轉時間為主要優先時的實用方式，依序處理則是偏重準確率的選項。視窗與模型名稱都不能確立託管上傳的固定最大檔案大小。</p><p>確切 Turbo 設定列出單次解碼序列的 448 個解碼器位置。文件記載的推論流程可在逐字稿之外加入片段或逐詞時間；時間資訊支持導覽與後續字幕格式整理，不會自動新增字幕檔案格式或可靠說話者標籤。請說明需要純逐字稿還是附時間片段，並保留原始錄音檢查有爭議段落。長篇處理與任何最終格式整理，和檢查點身分分開。</p><p>Turbo 減少解碼工作，但實際所需時間取決於硬體、錄音長度、語言、說話速度與推論選擇。開發者指出，某些語言的品質下降較大，包括泰文與粵語，並非所有語言表現一致。將速度取向的取捨視為適用於全部資料前，請先比較目標語言的代表性摘錄。檔案庫處理任務應在審查樣本中納入困難詞彙、停頓、吵雜或重疊段落，不要只用清楚的開場句。</p><p>公開卡片保留 Whisper 的重要辨識限制：預測文字可能包含未說出的字詞，也可能重複。結果隨語言、口音與方言不同，訓練覆蓋有限處尤其如此。卡片未確立基礎模型的說話者分離或分類是穩健的標準能力。實用審查聚焦來源忠實度：重要姓名與數字、漏掉的語音、靜音時意外文字及重複。可讀逐字稿仍是需要與錄音比較的結果，不保證精確辨識。</p><p>實用完成成品是來源語言逐字稿，附所需時間資訊及清楚錄音連結。請將辨識版本與編輯後出版版本分開，讓修改可追溯。比較版本時保留 large-v3-turbo 名稱：它不是完整 large-v3 模型，不應默默繼承 large-v3 的英文翻譯任務。這個開放權重身分也不包含託管 whisper-1 服務的上傳限制、回應封裝格式或即時串流承諾。當文件記載的轉錄取捨符合實際資料與所需周轉時間時，選擇 Turbo。</p>",
  "aboutText": "Whisper large-v3-turbo 也稱 Turbo，是 OpenAI 從 Whisper large-v3 衍生的最佳化轉錄模型。解碼器由 32 層減至四層，編碼器維持 32 層。發布模型約有 8.09 億參數。製造商目的是以小幅準確率取捨換取較快語音辨識，不是另一種音訊生成模式。輸入是錄製語音，結果是辨識文字。\n\n發布公告將 Turbo 的準備方式與另外蒸餾的 Whisper 模型區分：Turbo 以多語言轉錄資料額外微調兩個訓練週期，不包含翻譯資料。這項差異對操作很重要。OpenAI 儲存庫指出，Turbo 未受訓將非英文語音翻成英文，即使要求翻譯任務，也可能回傳原始語言。請用此版本產生同語言逐字稿；翻譯需求屬於另一個合適模型，或轉錄後的獨立步驟。\n\n來源語言偵測與明確語言選擇，仍是實用轉錄選項。若已知錄音語言，請在簡報中指出；否則文件記載的流程可偵測。要求任何編輯整理前，先保留姓名、數量與實際說出的字詞。會議紀錄、訪談逐字稿或課程文字，之後可透過另一項操作搜尋、註解或摘要。Turbo 辨識任務不應與聲音合成、模仿說話者，或對錄音人物作語意判斷混淆。\n\nOpenAI 音訊載入器將輸入檔案解碼成 16 kHz 單聲道樣本，模型使用 30 秒聲學視窗及 128 個梅爾頻率頻帶。較長錄音需要長篇推論。依序處理會按順序移動視窗；分塊方法則轉錄重疊片段並銜接邊界。模型卡片將後者描述為處理單一長檔案、以周轉時間為主要優先時的實用方式，依序處理則是偏重準確率的選項。視窗與模型名稱都不能確立託管上傳的固定最大檔案大小。\n\n確切 Turbo 設定列出單次解碼序列的 448 個解碼器位置。文件記載的推論流程可在逐字稿之外加入片段或逐詞時間；時間資訊支持導覽與後續字幕格式整理，不會自動新增字幕檔案格式或可靠說話者標籤。請說明需要純逐字稿還是附時間片段，並保留原始錄音檢查有爭議段落。長篇處理與任何最終格式整理，和檢查點身分分開。\n\nTurbo 減少解碼工作，但實際所需時間取決於硬體、錄音長度、語言、說話速度與推論選擇。開發者指出，某些語言的品質下降較大，包括泰文與粵語，並非所有語言表現一致。將速度取向的取捨視為適用於全部資料前，請先比較目標語言的代表性摘錄。檔案庫處理任務應在審查樣本中納入困難詞彙、停頓、吵雜或重疊段落，不要只用清楚的開場句。\n\n公開卡片保留 Whisper 的重要辨識限制：預測文字可能包含未說出的字詞，也可能重複。結果隨語言、口音與方言不同，訓練覆蓋有限處尤其如此。卡片未確立基礎模型的說話者分離或分類是穩健的標準能力。實用審查聚焦來源忠實度：重要姓名與數字、漏掉的語音、靜音時意外文字及重複。可讀逐字稿仍是需要與錄音比較的結果，不保證精確辨識。\n\n實用完成成品是來源語言逐字稿，附所需時間資訊及清楚錄音連結。請將辨識版本與編輯後出版版本分開，讓修改可追溯。比較版本時保留 large-v3-turbo 名稱：它不是完整 large-v3 模型，不應默默繼承 large-v3 的英文翻譯任務。這個開放權重身分也不包含託管 whisper-1 服務的上傳限制、回應封裝格式或即時串流承諾。當文件記載的轉錄取捨符合實際資料與所需周轉時間時，選擇 Turbo。",
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      "html": "<div class=\"sheet-head\"><span class=\"mav\" aria-hidden=\"true\">O</span><h2 id=\"sheet-title\">OpenAI: Whisper Large V3 Turbo</h2><button class=\"icon-btn\" type=\"button\" data-close-sheet aria-label=\"關閉\">×</button></div><div class=\"idline\"><span>OpenAI /</span><code>openai/whisper-large-v3-turbo</code><button type=\"button\" id=\"copy-id\">複製 ID</button></div><nav class=\"card-jump-nav\" aria-label=\"模型卡片區段\"><button type=\"button\" data-card-jump=\"overview\">入門</button><button type=\"button\" data-card-jump=\"methods\">輸入與方法</button><button type=\"button\" data-card-jump=\"pricing\">方案</button><button type=\"button\" data-card-jump=\"examples\">範例</button><button type=\"button\" data-card-jump=\"results\">結果</button><button type=\"button\" data-card-jump=\"aliases\">別名</button></nav><div class=\"card-method-tabs\" role=\"tablist\" aria-label=\"API 方法\"><button type=\"button\" role=\"tab\" tabindex=\"0\" aria-controls=\"card-method-content\" aria-selected=\"true\" id=\"card-method-tab-0\" data-card-method=\"Ultra|transcriptions|/v1/audio/transcriptions|openai%2Fwhisper-large-v3-turbo\">辨識</button></div><div id=\"card-method-content\" role=\"tabpanel\" aria-labelledby=\"card-method-tab-0\"><section class=\"card-section\" data-card-section=\"overview\"><h3 tabindex=\"-1\">入門</h3><p class=\"mdesc-full\">Whisper large-v3-turbo 是 OpenAI 從 large-v3 衍生、速度較快的開放權重轉錄版本，具有四個解碼器層與 8.09 億參數。它針對多語言語音轉文字；製造商官方文件將語音翻譯成英文排除在 Turbo 的訓練任務之外。</p><dl class=\"card-io\" data-card-io><div><dt>接受的輸入</dt><dd>音訊</dd></div><div><dt>結果</dt><dd>文字</dd></div></dl><details class=\"card-about\"><summary>關於模型</summary><p class=\"note-s\" data-model-method-boundary>此說明介紹模型的能力。Ailoot 可用的輸入、輸出與選項，依所選方法列於下方。</p><div class=\"mabout\" id=\"m-about\"><p>Whisper large-v3-turbo 也稱 Turbo，是 OpenAI 從 Whisper large-v3 衍生的最佳化轉錄模型。解碼器由 32 層減至四層，編碼器維持 32 層。發布模型約有 8.09 億參數。製造商目的是以小幅準確率取捨換取較快語音辨識，不是另一種音訊生成模式。輸入是錄製語音，結果是辨識文字。</p><p>發布公告將 Turbo 的準備方式與另外蒸餾的 Whisper 模型區分：Turbo 以多語言轉錄資料額外微調兩個訓練週期，不包含翻譯資料。這項差異對操作很重要。OpenAI 儲存庫指出，Turbo 未受訓將非英文語音翻成英文，即使要求翻譯任務，也可能回傳原始語言。請用此版本產生同語言逐字稿；翻譯需求屬於另一個合適模型，或轉錄後的獨立步驟。</p><p>來源語言偵測與明確語言選擇，仍是實用轉錄選項。若已知錄音語言，請在簡報中指出；否則文件記載的流程可偵測。要求任何編輯整理前，先保留姓名、數量與實際說出的字詞。會議紀錄、訪談逐字稿或課程文字，之後可透過另一項操作搜尋、註解或摘要。Turbo 辨識任務不應與聲音合成、模仿說話者，或對錄音人物作語意判斷混淆。</p><p>OpenAI 音訊載入器將輸入檔案解碼成 16 kHz 單聲道樣本，模型使用 30 秒聲學視窗及 128 個梅爾頻率頻帶。較長錄音需要長篇推論。依序處理會按順序移動視窗；分塊方法則轉錄重疊片段並銜接邊界。模型卡片將後者描述為處理單一長檔案、以周轉時間為主要優先時的實用方式，依序處理則是偏重準確率的選項。視窗與模型名稱都不能確立託管上傳的固定最大檔案大小。</p><p>確切 Turbo 設定列出單次解碼序列的 448 個解碼器位置。文件記載的推論流程可在逐字稿之外加入片段或逐詞時間；時間資訊支持導覽與後續字幕格式整理，不會自動新增字幕檔案格式或可靠說話者標籤。請說明需要純逐字稿還是附時間片段，並保留原始錄音檢查有爭議段落。長篇處理與任何最終格式整理，和檢查點身分分開。</p><p>Turbo 減少解碼工作，但實際所需時間取決於硬體、錄音長度、語言、說話速度與推論選擇。開發者指出，某些語言的品質下降較大，包括泰文與粵語，並非所有語言表現一致。將速度取向的取捨視為適用於全部資料前，請先比較目標語言的代表性摘錄。檔案庫處理任務應在審查樣本中納入困難詞彙、停頓、吵雜或重疊段落，不要只用清楚的開場句。</p><p>公開卡片保留 Whisper 的重要辨識限制：預測文字可能包含未說出的字詞，也可能重複。結果隨語言、口音與方言不同，訓練覆蓋有限處尤其如此。卡片未確立基礎模型的說話者分離或分類是穩健的標準能力。實用審查聚焦來源忠實度：重要姓名與數字、漏掉的語音、靜音時意外文字及重複。可讀逐字稿仍是需要與錄音比較的結果，不保證精確辨識。</p><p>實用完成成品是來源語言逐字稿，附所需時間資訊及清楚錄音連結。請將辨識版本與編輯後出版版本分開，讓修改可追溯。比較版本時保留 large-v3-turbo 名稱：它不是完整 large-v3 模型，不應默默繼承 large-v3 的英文翻譯任務。這個開放權重身分也不包含託管 whisper-1 服務的上傳限制、回應封裝格式或即時串流承諾。當文件記載的轉錄取捨符合實際資料與所需周轉時間時，選擇 Turbo。</p></div></details></section><section class=\"card-section\" data-card-section=\"methods\"><h3 tabindex=\"-1\">Ailoot 可用 · 輸入與方法</h3><details class=\"card-method\" open><summary><b>Ailoot Ultra · 語音轉文字</b> <code>POST /v1/audio/transcriptions</code></summary><dl class=\"method-capabilities\"><div><dt>輸入</dt><dd><code>audio</code></dd></div><div><dt>輸出</dt><dd><code>text</code></dd></div></dl><div class=\"tw\" data-card-parameters data-typed-parameters><table><thead><tr><th>欄位</th><th>類型</th><th>要求</th><th>值與限制</th><th>預設值</th></tr></thead><tbody><tr><th data-cell-label=\"欄位\" scope=\"row\"><span class=\"card-cell-label\">欄位</span><code class=\"card-field-name\">model</code></th><td data-cell-label=\"類型\" data-field-type><span class=\"card-cell-label\">類型</span><code>string</code></td><td data-cell-label=\"要求\"><span class=\"card-cell-label\">要求</span>必填</td><td data-cell-label=\"值與限制\"><span class=\"card-cell-label\">值與限制</span><div>openai/whisper-large-v3-turbo</div></td><td data-cell-label=\"預設值\" data-default=\"unspecified\"><span class=\"card-cell-label\">預設值</span>—</td></tr><tr><th data-cell-label=\"欄位\" scope=\"row\"><span class=\"card-cell-label\">欄位</span><code class=\"card-field-name\">input_audio</code></th><td data-cell-label=\"類型\" data-field-type><span class=\"card-cell-label\">類型</span><code>object</code></td><td data-cell-label=\"要求\"><span class=\"card-cell-label\">要求</span>必填</td><td data-cell-label=\"值與限制\"><span class=\"card-cell-label\">值與限制</span></td><td data-cell-label=\"預設值\" data-default=\"unspecified\"><span class=\"card-cell-label\">預設值</span>—</td></tr></tbody></table></div><details class=\"note-s\" data-method-contract><summary>方法參數與生命週期</summary><div class=\"tw\" data-card-table=\"contract\"><table><thead><tr><th>參數</th><th>規格</th></tr></thead><tbody><tr><th data-cell-label=\"參數\" scope=\"row\"><span class=\"card-cell-label\">參數</span><code>content_type</code></th><td data-cell-label=\"規格\"><span class=\"card-cell-label\">規格</span>application/json</td></tr><tr><th data-cell-label=\"參數\" scope=\"row\"><span class=\"card-cell-label\">參數</span><code>required</code></th><td data-cell-label=\"規格\"><span class=\"card-cell-label\">規格</span>model, input_audio</td></tr><tr><th data-cell-label=\"參數\" scope=\"row\"><span class=\"card-cell-label\">參數</span><code>material_types</code></th><td data-cell-label=\"規格\"><span class=\"card-cell-label\">規格</span>audio</td></tr><tr><th data-cell-label=\"參數\" scope=\"row\"><span class=\"card-cell-label\">參數</span><code>material_conditions</code></th><td data-cell-label=\"規格\"><span class=\"card-cell-label\">規格</span>此範例會讀取您實際使用且非空的 PCM WAV 檔案，將完整檔案位元組編碼為 base64，並將 input_audio.format 設為 wav 傳送。</td></tr></tbody></table></div><p>生命週期： <code>synchronous_result_then_owned_library</code></p><p class=\"note-s\"><code>GET /v1/media/tasks/{task_id}</code> · 現有自有媒體紀錄中完全相符的 task_id</p><p class=\"note-s\"><code>GET /v1/media/assets/{asset_id}/content</code></p><p class=\"note-s\"><code>GET /v1/media/assets</code></p><p class=\"note-s\"><code>GET /v1/media/assets/{asset_id}</code></p></details></details></section><section class=\"card-section\" data-card-section=\"pricing\"><h3 tabindex=\"-1\">方案</h3><div data-native-semantic-method=\"v1\" data-tariff-reference-only><p class=\"note-s\" data-rate-support-note>費率資訊不會增加請求選項。支援的參數列於所選方法中。</p><dl data-price-conditions><dt>快速模式</dt><dd>未指定 <span class=\"note-s\">選取快速模式時</span></dd><dt>flex 模式</dt><dd>未指定 <span class=\"note-s\">選取 flex 模式時</span></dd><dt>最高推理強度</dt><dd>未指定 <span class=\"note-s\">最高推理強度採用 default 調整值時</span></dd></dl></div><div data-declared-tariff-pricing><h4>Ailoot 費率</h4><h4>各設定的價格</h4><p class=\"note-s\">請逐一核對各項費用與所列條件。每組互為替代選項的設定只套用一種費率。</p><div class=\"tw\" data-pricing-profiles><table><thead><tr><th>設定</th><th>費率表</th><th>計費單位</th><th>費用</th></tr></thead><tbody><tr><th data-cell-label=\"設定\" scope=\"row\"><span class=\"card-cell-label\">設定</span>基礎 token 費率</th><td data-cell-label=\"費率表\"><span class=\"card-cell-label\">費率表</span>基本費率</td><td data-cell-label=\"計費單位\"><span class=\"card-cell-label\">計費單位</span>—</td><td data-cell-label=\"費用\"><span class=\"card-cell-label\">費用</span><div><span>輸入 · 輸入 Token</span> <b>—</b> <span class=\"price-unit\">/ 1K Token</span></div><div><span>輸出 · 輸出 Token</span> <b>—</b> <span class=\"price-unit\">/ 1K Token</span></div><div><span>輸入 · 讀取快取</span> <b>—</b> <span class=\"price-unit\">/ 1K Token</span></div><div><span>輸入 · 寫入快取</span> <b>—</b> <span class=\"price-unit\">/ 1K Token</span></div><div><span>輸入 · 寫入快取，1 小時</span> <b>—</b> <span class=\"price-unit\">/ 1K Token</span></div></td></tr><tr><th data-cell-label=\"設定\" scope=\"row\"><span class=\"card-cell-label\">設定</span>輸入音訊秒數</th><td data-cell-label=\"費率表\"><span class=\"card-cell-label\">費率表</span>—</td><td data-cell-label=\"計費單位\"><span class=\"card-cell-label\">計費單位</span>每秒輸入音訊</td><td data-cell-label=\"費用\"><span class=\"card-cell-label\">費用</span><div><span>輸入 · 輸入音訊秒數</span> <b>$0.00000666</b> <span class=\"price-unit\">每秒輸入音訊</span></div></td></tr></tbody></table></div></div><p class=\"note-s\">Ailoot 會在請求前預留估算金額。取得結果後，依實測用量結算最終費用。串流結算採用最終用量紀錄。<a href=\"/docs/zh-hant-tw/billing/reserve/\">預留金額與結算的運作方式 →</a></p></section><section class=\"card-section\" data-card-section=\"examples\"><h3 tabindex=\"-1\">請求範例</h3><h4>Ailoot Ultra · 語音轉文字</h4><div class=\"code-group\"><div class=\"cg-bar\"><div class=\"cg-tabs\" role=\"tablist\" aria-label=\"程式碼版本\"><button class=\"cg-tab\" id=\"model-code-2186-tab-0\" role=\"tab\" type=\"button\" aria-controls=\"model-code-2186-panel-0\" aria-selected=\"true\" tabindex=\"0\">curl · 實際 WAV 檔案與完整的原始結果</button></div><div class=\"cg-tools\"><button class=\"cg-btn cg-copy\" type=\"button\" aria-label=\"複製程式碼\"><svg class=\"cp\" viewBox=\"0 0 16 16\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"1.4\"><rect x=\"5.25\" y=\"5.25\" width=\"8.5\" height=\"8.5\" rx=\"1.75\"/><path d=\"M10.75 5.25V3.5a1.25 1.25 0 0 0-1.25-1.25H3.5A1.25 1.25 0 0 0 2.25 3.5v6a1.25 1.25 0 0 0 1.25 1.25h1.75\"/></svg><svg class=\"ok\" viewBox=\"0 0 16 16\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"1.4\"><path d=\"m3 8.5 3.25 3.25L13 5\"/></svg></button></div></div><div class=\"cg-body\"><div class=\"cg-pane\" id=\"model-code-2186-panel-0\" role=\"tabpanel\" aria-labelledby=\"model-code-2186-tab-0\"><pre data-lang=\"bash\"><code>set -eu\n: &quot;${AILOOT_API_KEY:?Set your Ailoot API key}&quot;\n: &quot;${AILOOT_AUDIO_FILE:?Set the path to your actual PCM WAV recording}&quot;\nexport AILOOT_AUDIO_FILE\npython3 - &lt;&lt;&#39;PY_REQUEST&#39;\nimport base64, io, json, os, wave\nfrom pathlib import Path\naudio = Path(os.environ[&#39;AILOOT_AUDIO_FILE&#39;]).read_bytes()\nif not (audio[:4] == b&#39;RIFF&#39; and audio[8:12] == b&#39;WAVE&#39;):\n    raise SystemExit(&#39;Supply your actual PCM WAV audio file&#39;)\nwith wave.open(io.BytesIO(audio), &#39;rb&#39;) as recording:\n    if recording.getcomptype() != &#39;NONE&#39; or recording.getnframes() &lt;= 0:\n        raise SystemExit(&#39;Supply a nonempty PCM WAV recording&#39;)\nrequest = {&#39;model&#39;: &#39;openai/whisper-large-v3-turbo&#39;, &#39;input_audio&#39;: {&#39;data&#39;: base64.b64encode(audio).decode(&#39;ascii&#39;), &#39;format&#39;: &#39;wav&#39;}}\nPath(&#39;request.json&#39;).write_text(json.dumps(request, ensure_ascii=False), encoding=&#39;utf-8&#39;)\nPY_REQUEST\ncurl --fail-with-body --silent --show-error https://api.ailoot.ai/v1/audio/transcriptions \\\n  -H &quot;Authorization: Bearer $AILOOT_API_KEY&quot; -H &#39;Content-Type: application/json&#39; \\\n  --data-binary @request.json -D response-headers.txt -o response.bin\n# Retain the complete original response, headers and actual X-Client-Request-ID.\n# Read existing owned records for recovery; do not resubmit an uncertain operation.\n</code></pre></div></div></div></section><section class=\"card-section\" data-card-section=\"results\"><h3 tabindex=\"-1\">接收並儲存結果</h3><h4>Ailoot Ultra · 語音轉文字</h4><p class=\"note-s\">完整的原始回應本文、狀態與轉送標頭。此處理常式不會加入通用的 JSON 結構、文字欄位或工作封裝。</p><ul class=\"card-result-paths\"><li><code>GET /v1/media/tasks/{task_id}</code></li><li><code>GET /v1/media/assets/{asset_id}/content</code></li><li><code>GET /v1/media/assets</code></li><li><code>GET /v1/media/assets/{asset_id}</code></li></ul><div class=\"card-result-process\" data-all-results><h5>保留所有已完成的結果</h5><p class=\"note-s\">請保留所有完整傳回的回應、檔案與內容區塊。</p><p class=\"note-s\">保留完整回應與標頭、所有實際輸出、原始回傳的識別碼，以及所有用量欄位。恢復原始作業時，請勿再次提交建立請求。</p></div><div class=\"card-result-process\" data-unknown-recovery><h5>需要檢查原始回應時</h5><p class=\"note-s\">請保留實際的 X-Client-Request-ID 與完整回應。請讀取原始自有資產及其完全相符的簽署內容 URL；切勿重新提交結果不明的建立請求。</p></div><details class=\"card-about\" data-output-fields><summary>回應欄位</summary><div class=\"tw\" data-card-table=\"output\"><table><thead><tr><th>欄位</th><th>類型</th></tr></thead><tbody><tr><th data-cell-label=\"欄位\" scope=\"row\"><span class=\"card-cell-label\">欄位</span><code class=\"card-field-name\">text (when present)</code></th><td data-cell-label=\"類型\" data-field-type><span class=\"card-cell-label\">類型</span></td></tr><tr><th data-cell-label=\"欄位\" scope=\"row\"><span class=\"card-cell-label\">欄位</span><code class=\"card-field-name\">usage (when present)</code></th><td data-cell-label=\"類型\" data-field-type><span class=\"card-cell-label\">類型</span></td></tr></tbody></table></div></details><details class=\"card-about\" data-method-errors><summary>錯誤與後續步驟</summary><div class=\"tw\" data-card-table=\"errors\"><table><thead><tr><th>回應</th><th>條件</th><th>下一步</th></tr></thead><tbody><tr><th data-cell-label=\"回應\" scope=\"row\"><span class=\"card-cell-label\">回應</span>400 · <code>invalid_request_error</code></th><td data-cell-label=\"條件\"><span class=\"card-cell-label\">條件</span>JSON 本文或明確的標準模型 ID 無效。</td><td data-cell-label=\"下一步\"><span class=\"card-cell-label\">下一步</span>請保留回應，並修正指出的請求欄位。</td></tr><tr><th data-cell-label=\"回應\" scope=\"row\"><span class=\"card-cell-label\">回應</span>401 · <code>authentication_error</code></th><td data-cell-label=\"條件\"><span class=\"card-cell-label\">條件</span>Ailoot API 金鑰無效。</td><td data-cell-label=\"下一步\"><span class=\"card-cell-label\">下一步</span>請使用您已獲授權的 Ailoot API 金鑰。</td></tr><tr><th data-cell-label=\"回應\" scope=\"row\"><span class=\"card-cell-label\">回應</span>403 · <code>permission_error</code></th><td data-cell-label=\"條件\"><span class=\"card-cell-label\">條件</span>此金鑰群組未獲准使用該方法。</td><td data-cell-label=\"下一步\"><span class=\"card-cell-label\">下一步</span>請保留回傳的錯誤詳細資訊。</td></tr><tr><th data-cell-label=\"回應\" scope=\"row\"><span class=\"card-cell-label\">回應</span>404 · <code>not_found_error</code></th><td data-cell-label=\"條件\"><span class=\"card-cell-label\">條件</span>所選方法沒有獲准使用的路由。</td><td data-cell-label=\"下一步\"><span class=\"card-cell-label\">下一步</span>請保留回傳的錯誤詳細資訊。</td></tr><tr><th data-cell-label=\"回應\" scope=\"row\"><span class=\"card-cell-label\">回應</span>422 · <code>price_unavailable</code></th><td data-cell-label=\"條件\"><span class=\"card-cell-label\">條件</span>已接受的費率無法取得其所需的輸入數量或界限。</td><td data-cell-label=\"下一步\"><span class=\"card-cell-label\">下一步</span>請保留回應，並使用已接受費率所要求的輸入表示方式。</td></tr><tr><th data-cell-label=\"回應\" scope=\"row\"><span class=\"card-cell-label\">回應</span>503 · <code></code></th><td data-cell-label=\"條件\"><span class=\"card-cell-label\">條件</span>所需的儲存系統、路由、方法價格或預留額度無法使用。</td><td data-cell-label=\"下一步\"><span class=\"card-cell-label\">下一步</span>請保留完整的原始回應。預留額度狀態不明並不代表可以重新提交。</td></tr><tr><th data-cell-label=\"回應\" scope=\"row\"><span class=\"card-cell-label\">回應</span>502 · <code>server_error</code></th><td data-cell-label=\"條件\"><span class=\"card-cell-label\">條件</span>原始結果、用量或結算需要查核。</td><td data-cell-label=\"下一步\"><span class=\"card-cell-label\">下一步</span>請保留實際的請求 ID 與原始回應。請讀取現有的自有紀錄，切勿重新提交建立請求。</td></tr></tbody></table></div></details></section><section class=\"card-section\" data-card-section=\"aliases\"><h3 tabindex=\"-1\">別名</h3><h4>模型別名</h4><p class=\"note-s\"><span data-model-alias-route=\"Ultra\"><b>Ailoot Ultra</b> <a href=\"#m=openai%2Fwhisper-large-v3-turbo&amp;route=Ultra&amp;caller=openai%2Fwhisper-large-v3-turbo&amp;fmt=transcriptions\"><code>openai/whisper-large-v3-turbo</code></a></span></p><h4>方法路徑別名</h4><p class=\"note-s\">請使用上方列出的 API 方法路徑。</p><h4>相關呼叫用 ID</h4><p class=\"note-s\"><a href=\"#m=openai%2Fwhisper-large-v3-turbo&amp;route=Ultra&amp;caller=openai%2Fwhisper-large-v3-turbo&amp;fmt=transcriptions\"><code>openai/whisper-large-v3-turbo</code></a></p></section></div>",
      "method_identity": {
        "effective_request_model_id": "openai/whisper-large-v3-turbo",
        "fmt": "transcriptions",
        "http": "POST",
        "path": "/v1/audio/transcriptions",
        "request_model_id": "openai/whisper-large-v3-turbo",
        "route_label": "Ultra"
      },
      "method_key": "Ultra|transcriptions|/v1/audio/transcriptions|openai%2Fwhisper-large-v3-turbo",
      "ordinal": 0,
      "rawMethod": {
        "available": null,
        "cache_read": null,
        "cache_write": null,
        "cache_write_1h": null,
        "contract": {
          "data": {
            "all_results": "Retain the complete response and headers, every actual output, original returned identifiers and all usage fields. Recover the original operation without submitting creation again.",
            "errors": [
              {
                "code": null,
                "condition": "JSON 本文或明確的標準模型 ID 無效。",
                "http_status": 400,
                "recovery": "請保留回應，並修正指出的請求欄位。",
                "type": "invalid_request_error"
              },
              {
                "code": null,
                "condition": "Ailoot API 金鑰無效。",
                "http_status": 401,
                "recovery": "請使用您已獲授權的 Ailoot API 金鑰。",
                "type": "authentication_error"
              },
              {
                "code": null,
                "condition": "此金鑰群組未獲准使用該方法。",
                "http_status": 403,
                "recovery": "請保留回傳的錯誤詳細資訊。",
                "type": "permission_error"
              },
              {
                "code": null,
                "condition": "所選方法沒有獲准使用的路由。",
                "http_status": 404,
                "recovery": "請保留回傳的錯誤詳細資訊。",
                "type": "not_found_error"
              },
              {
                "code": null,
                "condition": "已接受的費率無法取得其所需的輸入數量或界限。",
                "http_status": 422,
                "recovery": "請保留回應，並使用已接受費率所要求的輸入表示方式。",
                "type": "price_unavailable"
              },
              {
                "code": null,
                "condition": "所需的儲存系統、路由、方法價格或預留額度無法使用。",
                "http_status": 503,
                "recovery": "請保留完整的原始回應。預留額度狀態不明並不代表可以重新提交。",
                "type": null
              },
              {
                "code": null,
                "condition": "原始結果、用量或結算需要查核。",
                "http_status": 502,
                "operation_id_source": "actual X-Client-Request-ID",
                "recovery": "請保留實際的請求 ID 與原始回應。請讀取現有的自有紀錄，切勿重新提交建立請求。",
                "response_headers": {
                  "x-should-retry": "false"
                },
                "type": "server_error"
              }
            ],
            "lifecycle": {
              "assets": [
                {
                  "http": "GET",
                  "path": "/v1/media/assets"
                },
                {
                  "http": "GET",
                  "path": "/v1/media/assets/{asset_id}"
                }
              ],
              "content": [
                {
                  "http": "GET",
                  "path": "/v1/media/assets/{asset_id}/content",
                  "url_source": "exact returned signed content URL"
                }
              ],
              "dedicated_method_polling_or_cancel": false,
              "mode": "synchronous_result_then_owned_library",
              "original_POST_adds_task_envelope": false,
              "status": [
                {
                  "http": "GET",
                  "id_source": "exact task_id from an existing owned media record",
                  "path": "/v1/media/tasks/{task_id}"
                }
              ],
              "unknown": "請保留實際的 X-Client-Request-ID 與完整回應。請讀取原始自有資產及其完全相符的簽署內容 URL；切勿重新提交結果不明的建立請求。"
            },
            "outputs": {
              "all_results": "保留完整回應與標頭、所有實際輸出、原始回傳的識別碼，以及所有用量欄位。恢復原始作業時，請勿再次提交建立請求。",
              "family": "text",
              "fields": [
                {
                  "description": null,
                  "name": "text (when present)",
                  "type": null
                },
                {
                  "description": null,
                  "name": "usage (when present)",
                  "type": null
                }
              ],
              "result": "完整的原始回應本文、狀態與轉送標頭。此處理常式不會加入通用的 JSON 結構、文字欄位或工作封裝。"
            },
            "parameters": [
              {
                "default_known": false,
                "enum": [
                  "openai/whisper-large-v3-turbo"
                ],
                "enum_known": true,
                "name": "model",
                "required": true,
                "type": "string"
              },
              {
                "default_known": false,
                "enum_known": false,
                "name": "input_audio",
                "required": true,
                "type": "object"
              }
            ],
            "request_schema": {
              "properties": {
                "input_audio": {
                  "properties": {
                    "data": {
                      "contentEncoding": "base64",
                      "type": "string"
                    },
                    "format": {
                      "type": "string"
                    }
                  },
                  "required": [
                    "data",
                    "format"
                  ],
                  "type": "object"
                },
                "model": {
                  "enum": [
                    "openai/whisper-large-v3-turbo"
                  ],
                  "type": "string"
                }
              },
              "required": [
                "model",
                "input_audio"
              ],
              "type": "object"
            },
            "schema_template": {
              "actual_file_preparation_required": true,
              "body": {
                "input_audio": {
                  "data": "${BASE64_ACTUAL_WAV_BYTES}",
                  "format": "wav"
                },
                "model": "openai/whisper-large-v3-turbo"
              },
              "content_type": "application/json"
            }
          },
          "input": {
            "content_type": "application/json",
            "material_conditions": [
              "此範例會讀取您實際使用且非空的 PCM WAV 檔案，將完整檔案位元組編碼為 base64，並將 input_audio.format 設為 wav 傳送。"
            ],
            "material_types": [
              "audio"
            ],
            "required": [
              "model",
              "input_audio"
            ]
          },
          "lifecycle": {
            "assets": [
              {
                "http": "GET",
                "path": "/v1/media/assets"
              },
              {
                "http": "GET",
                "path": "/v1/media/assets/{asset_id}"
              }
            ],
            "content": [
              {
                "http": "GET",
                "path": "/v1/media/assets/{asset_id}/content",
                "url_source": "exact returned signed content URL"
              }
            ],
            "dedicated_method_polling_or_cancel": false,
            "mode": "synchronous_result_then_owned_library",
            "original_POST_adds_task_envelope": false,
            "status": [
              {
                "http": "GET",
                "id_source": "現有自有媒體紀錄中完全相符的 task_id",
                "path": "/v1/media/tasks/{task_id}"
              }
            ],
            "unknown": "Retain the actual X-Client-Request-ID and complete response. Read the original owned assets and their exact signed content URLs; never resubmit an uncertain creation."
          },
          "method": {
            "http": "POST",
            "path": "/v1/audio/transcriptions"
          },
          "output": {
            "all_results": "Retain the complete response and headers, every actual output, original returned identifiers and all usage fields. Recover the original operation without submitting creation again.",
            "family": "text",
            "fields": [
              {
                "description": null,
                "name": "text (when present)",
                "type": null
              },
              {
                "description": null,
                "name": "usage (when present)",
                "type": null
              }
            ],
            "result": "Complete original response body, status and forwarded headers. No universal JSON shape, text field or task envelope is added by this handler."
          }
        },
        "ctx": null,
        "declared_pricing_profiles": [
          {
            "dimensions": {
              "regime": "base"
            },
            "label": "Base token rates",
            "units": [
              {
                "amount": null,
                "amount_unit": "usd_per_thousand_tokens",
                "billing_input": true,
                "estimate_only": false,
                "key": "input_price",
                "label": "Input tokens",
                "native_amount_usd_per_unit": null,
                "native_quantity": 1,
                "native_unit": "input_token",
                "public_unit_label": "/ 1K tokens",
                "quantity": 1000,
                "quantity_is_estimate": false,
                "rate_role": "typed_native_retail_rate",
                "side": "in",
                "unit": "input_token"
              },
              {
                "amount": null,
                "amount_unit": "usd_per_thousand_tokens",
                "billing_input": true,
                "estimate_only": false,
                "key": "output_price",
                "label": "Output tokens",
                "native_amount_usd_per_unit": null,
                "native_quantity": 1,
                "native_unit": "output_token",
                "public_unit_label": "/ 1K tokens",
                "quantity": 1000,
                "quantity_is_estimate": false,
                "rate_role": "typed_native_retail_rate",
                "side": "out",
                "unit": "output_token"
              },
              {
                "amount": null,
                "amount_unit": "usd_per_thousand_tokens",
                "billing_input": true,
                "estimate_only": false,
                "key": "cache_read_price",
                "label": "Cache read",
                "native_amount_usd_per_unit": null,
                "native_quantity": 1,
                "native_unit": "cached_input_token",
                "public_unit_label": "/ 1K tokens",
                "quantity": 1000,
                "quantity_is_estimate": false,
                "rate_role": "typed_native_retail_rate",
                "side": "in",
                "unit": "cached_input_token"
              },
              {
                "amount": null,
                "amount_unit": "usd_per_thousand_tokens",
                "billing_input": true,
                "estimate_only": false,
                "key": "cache_write_price",
                "label": "Cache write",
                "native_amount_usd_per_unit": null,
                "native_quantity": 1,
                "native_unit": "generic_cache_creation_token",
                "public_unit_label": "/ 1K tokens",
                "quantity": 1000,
                "quantity_is_estimate": false,
                "rate_role": "typed_native_retail_rate",
                "side": "in",
                "unit": "generic_cache_creation_token"
              },
              {
                "amount": null,
                "amount_unit": "usd_per_thousand_tokens",
                "billing_input": true,
                "estimate_only": false,
                "key": "cache_write_1h_price",
                "label": "Cache write, 1 hour",
                "native_amount_usd_per_unit": null,
                "native_quantity": 1,
                "native_unit": "one_hour_cache_creation_token",
                "public_unit_label": "/ 1K tokens",
                "quantity": 1000,
                "quantity_is_estimate": false,
                "rate_role": "typed_native_retail_rate",
                "side": "in",
                "unit": "one_hour_cache_creation_token"
              }
            ]
          },
          {
            "dimensions": {
              "quoted_unit": "per input audio second"
            },
            "label": "input audio second",
            "units": [
              {
                "amount": "0.00000666",
                "amount_unit": "usd_per_exact_native_unit",
                "billing_input": true,
                "estimate_only": false,
                "key": "audio_input_second",
                "label": "input audio second",
                "native_amount_usd_per_unit": "0.00000666",
                "native_quantity": 1,
                "public_unit_label": "per input audio second",
                "quantity": 1,
                "quantity_is_estimate": false,
                "rate_role": "typed_native_retail_rate",
                "side": "in",
                "unit": "audio_input_second"
              }
            ]
          }
        ],
        "examples": [
          {
            "code": "set -eu\n: \"${AILOOT_API_KEY:?Set your Ailoot API key}\"\n: \"${AILOOT_AUDIO_FILE:?Set the path to your actual PCM WAV recording}\"\nexport AILOOT_AUDIO_FILE\npython3 - <<'PY_REQUEST'\nimport base64, io, json, os, wave\nfrom pathlib import Path\naudio = Path(os.environ['AILOOT_AUDIO_FILE']).read_bytes()\nif not (audio[:4] == b'RIFF' and audio[8:12] == b'WAVE'):\n    raise SystemExit('Supply your actual PCM WAV audio file')\nwith wave.open(io.BytesIO(audio), 'rb') as recording:\n    if recording.getcomptype() != 'NONE' or recording.getnframes() <= 0:\n        raise SystemExit('Supply a nonempty PCM WAV recording')\nrequest = {'model': 'openai/whisper-large-v3-turbo', 'input_audio': {'data': base64.b64encode(audio).decode('ascii'), 'format': 'wav'}}\nPath('request.json').write_text(json.dumps(request, ensure_ascii=False), encoding='utf-8')\nPY_REQUEST\ncurl --fail-with-body --silent --show-error https://api.ailoot.ai/v1/audio/transcriptions \\\n  -H \"Authorization: Bearer $AILOOT_API_KEY\" -H 'Content-Type: application/json' \\\n  --data-binary @request.json -D response-headers.txt -o response.bin\n# Retain the complete original response, headers and actual X-Client-Request-ID.\n# Read existing owned records for recovery; do not resubmit an uncertain operation.\n",
            "label": "curl · actual WAV file and complete original result",
            "language": "bash"
          }
        ],
        "family": "openai",
        "fast_multiplier": null,
        "flex_multiplier": null,
        "fmt": "transcriptions",
        "hints": [
          "The example reads your actual nonempty PCM WAV file, encodes the complete file bytes as base64 and sends input_audio.format as wav.",
          "The format value in the example is the documented recipe; no model-specific format list, limit or default is asserted.",
          "Retain the complete response and headers, every actual output, original returned identifiers and all usage fields. Recover the original operation without submitting creation again."
        ],
        "http": "POST",
        "in": null,
        "input": [
          "audio"
        ],
        "label": "語音轉文字",
        "max_out": null,
        "max_reasoning_effort_multiplier": null,
        "method_aliases": [],
        "native_endpoint": "audio_transcriptions",
        "out": null,
        "output": [
          "text"
        ],
        "path": "/v1/audio/transcriptions",
        "price_conditions": [
          {
            "label": "Fast mode",
            "value": "Not specified",
            "when": "When fast mode is selected"
          },
          {
            "label": "Flex mode",
            "value": "Not specified",
            "when": "When flex mode is selected"
          },
          {
            "label": "Maximum reasoning effort",
            "value": "Not specified",
            "when": "When maximum reasoning effort uses the default adjustment"
          }
        ],
        "pricing": {
          "billing_mode": "per_request",
          "image_input_price": null,
          "image_output_price": null,
          "per_request_price": null,
          "unit_prices": {
            "audio_input_second": 6.66e-06
          }
        },
        "pricing_profiles": [
          {
            "dimensions": {
              "regime": "base"
            },
            "label": "Base token rates",
            "units": [
              {
                "amount": null,
                "amount_unit": "usd_per_thousand_tokens",
                "billing_input": true,
                "estimate_only": false,
                "key": "input_price",
                "label": "Input tokens",
                "native_amount_usd_per_unit": null,
                "native_quantity": 1,
                "native_unit": "input_token",
                "public_unit_label": "/ 1K tokens",
                "quantity": 1000,
                "quantity_is_estimate": false,
                "rate_role": "typed_native_retail_rate",
                "side": "in",
                "unit": "input_token"
              },
              {
                "amount": null,
                "amount_unit": "usd_per_thousand_tokens",
                "billing_input": true,
                "estimate_only": false,
                "key": "output_price",
                "label": "Output tokens",
                "native_amount_usd_per_unit": null,
                "native_quantity": 1,
                "native_unit": "output_token",
                "public_unit_label": "/ 1K tokens",
                "quantity": 1000,
                "quantity_is_estimate": false,
                "rate_role": "typed_native_retail_rate",
                "side": "out",
                "unit": "output_token"
              },
              {
                "amount": null,
                "amount_unit": "usd_per_thousand_tokens",
                "billing_input": true,
                "estimate_only": false,
                "key": "cache_read_price",
                "label": "Cache read",
                "native_amount_usd_per_unit": null,
                "native_quantity": 1,
                "native_unit": "cached_input_token",
                "public_unit_label": "/ 1K tokens",
                "quantity": 1000,
                "quantity_is_estimate": false,
                "rate_role": "typed_native_retail_rate",
                "side": "in",
                "unit": "cached_input_token"
              },
              {
                "amount": null,
                "amount_unit": "usd_per_thousand_tokens",
                "billing_input": true,
                "estimate_only": false,
                "key": "cache_write_price",
                "label": "Cache write",
                "native_amount_usd_per_unit": null,
                "native_quantity": 1,
                "native_unit": "generic_cache_creation_token",
                "public_unit_label": "/ 1K tokens",
                "quantity": 1000,
                "quantity_is_estimate": false,
                "rate_role": "typed_native_retail_rate",
                "side": "in",
                "unit": "generic_cache_creation_token"
              },
              {
                "amount": null,
                "amount_unit": "usd_per_thousand_tokens",
                "billing_input": true,
                "estimate_only": false,
                "key": "cache_write_1h_price",
                "label": "Cache write, 1 hour",
                "native_amount_usd_per_unit": null,
                "native_quantity": 1,
                "native_unit": "one_hour_cache_creation_token",
                "public_unit_label": "/ 1K tokens",
                "quantity": 1000,
                "quantity_is_estimate": false,
                "rate_role": "typed_native_retail_rate",
                "side": "in",
                "unit": "one_hour_cache_creation_token"
              }
            ]
          },
          {
            "dimensions": {
              "quoted_unit": "per input audio second"
            },
            "label": "input audio second",
            "units": [
              {
                "amount": "0.00000666",
                "amount_unit": "usd_per_exact_native_unit",
                "billing_input": true,
                "estimate_only": false,
                "key": "audio_input_second",
                "label": "input audio second",
                "native_amount_usd_per_unit": "0.00000666",
                "native_quantity": 1,
                "public_unit_label": "per input audio second",
                "quantity": 1,
                "quantity_is_estimate": false,
                "rate_role": "typed_native_retail_rate",
                "side": "in",
                "unit": "audio_input_second"
              }
            ]
          }
        ],
        "request_model_id": "openai/whisper-large-v3-turbo",
        "route_label": "Ultra",
        "status_reads": [
          "GET /v1/media/tasks/{task_id}"
        ],
        "tiers": [],
        "units": [
          {
            "amount": null,
            "amount_unit": "usd_per_thousand_tokens",
            "billing_input": true,
            "estimate_only": false,
            "key": "input_price",
            "label": "Input tokens",
            "native_amount_usd_per_unit": null,
            "native_quantity": 1,
            "native_unit": "input_token",
            "public_unit_label": "/ 1K tokens",
            "quantity": 1000,
            "quantity_is_estimate": false,
            "rate_role": "typed_native_retail_rate",
            "side": "in",
            "unit": "input_token"
          },
          {
            "amount": null,
            "amount_unit": "usd_per_thousand_tokens",
            "billing_input": true,
            "estimate_only": false,
            "key": "output_price",
            "label": "Output tokens",
            "native_amount_usd_per_unit": null,
            "native_quantity": 1,
            "native_unit": "output_token",
            "public_unit_label": "/ 1K tokens",
            "quantity": 1000,
            "quantity_is_estimate": false,
            "rate_role": "typed_native_retail_rate",
            "side": "out",
            "unit": "output_token"
          },
          {
            "amount": null,
            "amount_unit": "usd_per_thousand_tokens",
            "billing_input": true,
            "estimate_only": false,
            "key": "cache_read_price",
            "label": "Cache read",
            "native_amount_usd_per_unit": null,
            "native_quantity": 1,
            "native_unit": "cached_input_token",
            "public_unit_label": "/ 1K tokens",
            "quantity": 1000,
            "quantity_is_estimate": false,
            "rate_role": "typed_native_retail_rate",
            "side": "in",
            "unit": "cached_input_token"
          },
          {
            "amount": null,
            "amount_unit": "usd_per_thousand_tokens",
            "billing_input": true,
            "estimate_only": false,
            "key": "cache_write_price",
            "label": "Cache write",
            "native_amount_usd_per_unit": null,
            "native_quantity": 1,
            "native_unit": "generic_cache_creation_token",
            "public_unit_label": "/ 1K tokens",
            "quantity": 1000,
            "quantity_is_estimate": false,
            "rate_role": "typed_native_retail_rate",
            "side": "in",
            "unit": "generic_cache_creation_token"
          },
          {
            "amount": null,
            "amount_unit": "usd_per_thousand_tokens",
            "billing_input": true,
            "estimate_only": false,
            "key": "cache_write_1h_price",
            "label": "Cache write, 1 hour",
            "native_amount_usd_per_unit": null,
            "native_quantity": 1,
            "native_unit": "one_hour_cache_creation_token",
            "public_unit_label": "/ 1K tokens",
            "quantity": 1000,
            "quantity_is_estimate": false,
            "rate_role": "typed_native_retail_rate",
            "side": "in",
            "unit": "one_hour_cache_creation_token"
          },
          {
            "amount": "0.00000666",
            "amount_unit": "usd_per_exact_native_unit",
            "billing_input": true,
            "estimate_only": false,
            "key": "audio_input_second",
            "label": "input audio second",
            "native_amount_usd_per_unit": "0.00000666",
            "native_quantity": 1,
            "public_unit_label": "per input audio second",
            "quantity": 1,
            "quantity_is_estimate": false,
            "rate_role": "typed_native_retail_rate",
            "side": "in",
            "unit": "audio_input_second"
          }
        ]
      }
    }
  ],
  "model_id": "openai/whisper-large-v3-turbo",
  "nativeProvenance": {
    "input_facts_canonical_sha256": "26f056f5e3e3655e37d59013d0ab6eb11fe3292a15acfc2bb7012a6ff3c4445d",
    "input_html_sha256": "b710d036fcc1cd2c9981e3f42fd403ba45531e3c2f3bffd2f37561617d854b29",
    "private_audit_sha256": "b32694b63b1425fb72da21c0a7fc2cf0b558f429d1c8b2694a84822ceaf28f9b",
    "role": "historical-normalized-input-audit-hashes",
    "schema": "ailoot-native-model-provenance-v2"
  },
  "page": {
    "canonical": "https://ailoot.ai/models/zh-hant-tw/openai-whisper-large-v3-turbo/",
    "description": "Whisper large-v3-turbo 是 OpenAI 從 large-v3 衍生、速度較快的開放權重轉錄版本，具有四個解碼器層與 8.09 億參數。它針對多語言語音轉文字；製造商官方文件將語音翻譯成英文排除在 Turbo 的訓練任務之外。",
    "locale": "zh-hant-tw",
    "md_url": "https://ailoot.ai/models/zh-hant-tw/openai-whisper-large-v3-turbo/index.md",
    "title": "OpenAI: Whisper Large V3 Turbo — Ailoot",
    "url": "https://ailoot.ai/models/zh-hant-tw/openai-whisper-large-v3-turbo/"
  },
  "rawModel": {
    "about": "Whisper large-v3-turbo 也稱 Turbo，是 OpenAI 從 Whisper large-v3 衍生的最佳化轉錄模型。解碼器由 32 層減至四層，編碼器維持 32 層。發布模型約有 8.09 億參數。製造商目的是以小幅準確率取捨換取較快語音辨識，不是另一種音訊生成模式。輸入是錄製語音，結果是辨識文字。\n\n發布公告將 Turbo 的準備方式與另外蒸餾的 Whisper 模型區分：Turbo 以多語言轉錄資料額外微調兩個訓練週期，不包含翻譯資料。這項差異對操作很重要。OpenAI 儲存庫指出，Turbo 未受訓將非英文語音翻成英文，即使要求翻譯任務，也可能回傳原始語言。請用此版本產生同語言逐字稿；翻譯需求屬於另一個合適模型，或轉錄後的獨立步驟。\n\n來源語言偵測與明確語言選擇，仍是實用轉錄選項。若已知錄音語言，請在簡報中指出；否則文件記載的流程可偵測。要求任何編輯整理前，先保留姓名、數量與實際說出的字詞。會議紀錄、訪談逐字稿或課程文字，之後可透過另一項操作搜尋、註解或摘要。Turbo 辨識任務不應與聲音合成、模仿說話者，或對錄音人物作語意判斷混淆。\n\nOpenAI 音訊載入器將輸入檔案解碼成 16 kHz 單聲道樣本，模型使用 30 秒聲學視窗及 128 個梅爾頻率頻帶。較長錄音需要長篇推論。依序處理會按順序移動視窗；分塊方法則轉錄重疊片段並銜接邊界。模型卡片將後者描述為處理單一長檔案、以周轉時間為主要優先時的實用方式，依序處理則是偏重準確率的選項。視窗與模型名稱都不能確立託管上傳的固定最大檔案大小。\n\n確切 Turbo 設定列出單次解碼序列的 448 個解碼器位置。文件記載的推論流程可在逐字稿之外加入片段或逐詞時間；時間資訊支持導覽與後續字幕格式整理，不會自動新增字幕檔案格式或可靠說話者標籤。請說明需要純逐字稿還是附時間片段，並保留原始錄音檢查有爭議段落。長篇處理與任何最終格式整理，和檢查點身分分開。\n\nTurbo 減少解碼工作，但實際所需時間取決於硬體、錄音長度、語言、說話速度與推論選擇。開發者指出，某些語言的品質下降較大，包括泰文與粵語，並非所有語言表現一致。將速度取向的取捨視為適用於全部資料前，請先比較目標語言的代表性摘錄。檔案庫處理任務應在審查樣本中納入困難詞彙、停頓、吵雜或重疊段落，不要只用清楚的開場句。\n\n公開卡片保留 Whisper 的重要辨識限制：預測文字可能包含未說出的字詞，也可能重複。結果隨語言、口音與方言不同，訓練覆蓋有限處尤其如此。卡片未確立基礎模型的說話者分離或分類是穩健的標準能力。實用審查聚焦來源忠實度：重要姓名與數字、漏掉的語音、靜音時意外文字及重複。可讀逐字稿仍是需要與錄音比較的結果，不保證精確辨識。\n\n實用完成成品是來源語言逐字稿，附所需時間資訊及清楚錄音連結。請將辨識版本與編輯後出版版本分開，讓修改可追溯。比較版本時保留 large-v3-turbo 名稱：它不是完整 large-v3 模型，不應默默繼承 large-v3 的英文翻譯任務。這個開放權重身分也不包含託管 whisper-1 服務的上傳限制、回應封裝格式或即時串流承諾。當文件記載的轉錄取捨符合實際資料與所需周轉時間時，選擇 Turbo。",
    "alias_of": null,
    "aliases": [],
    "author": "OpenAI",
    "capabilities": {
      "context_length": 0,
      "manufacturer_input": [
        "audio"
      ],
      "manufacturer_output": [
        "transcription"
      ]
    },
    "card_routes": [
      {
        "label": "Ultra",
        "rates": [
          {
            "amount": "0.00000666",
            "amount_unit": "usd_per_exact_native_unit",
            "billing_input": true,
            "estimate_only": false,
            "key": "audio_input_second",
            "label": "input audio second",
            "native_amount_usd_per_unit": "0.00000666",
            "native_quantity": 1,
            "public_unit_label": "per input audio second",
            "quantity": 1,
            "quantity_is_estimate": false,
            "rate_role": "typed_native_retail_rate",
            "side": "in",
            "unit": "audio_input_second"
          }
        ],
        "summary": "完整的設定價格資訊請見詳細資料。"
      }
    ],
    "ctx": null,
    "formats": [
      "transcriptions"
    ],
    "id": "openai/whisper-large-v3-turbo",
    "input": [
      "audio"
    ],
    "kind": "audio",
    "max_out": null,
    "methods": [
      {
        "available": null,
        "cache_read": null,
        "cache_write": null,
        "cache_write_1h": null,
        "contract": {
          "data": {
            "all_results": "Retain the complete response and headers, every actual output, original returned identifiers and all usage fields. Recover the original operation without submitting creation again.",
            "errors": [
              {
                "code": null,
                "condition": "JSON 本文或明確的標準模型 ID 無效。",
                "http_status": 400,
                "recovery": "請保留回應，並修正指出的請求欄位。",
                "type": "invalid_request_error"
              },
              {
                "code": null,
                "condition": "Ailoot API 金鑰無效。",
                "http_status": 401,
                "recovery": "請使用您已獲授權的 Ailoot API 金鑰。",
                "type": "authentication_error"
              },
              {
                "code": null,
                "condition": "此金鑰群組未獲准使用該方法。",
                "http_status": 403,
                "recovery": "請保留回傳的錯誤詳細資訊。",
                "type": "permission_error"
              },
              {
                "code": null,
                "condition": "所選方法沒有獲准使用的路由。",
                "http_status": 404,
                "recovery": "請保留回傳的錯誤詳細資訊。",
                "type": "not_found_error"
              },
              {
                "code": null,
                "condition": "已接受的費率無法取得其所需的輸入數量或界限。",
                "http_status": 422,
                "recovery": "請保留回應，並使用已接受費率所要求的輸入表示方式。",
                "type": "price_unavailable"
              },
              {
                "code": null,
                "condition": "所需的儲存系統、路由、方法價格或預留額度無法使用。",
                "http_status": 503,
                "recovery": "請保留完整的原始回應。預留額度狀態不明並不代表可以重新提交。",
                "type": null
              },
              {
                "code": null,
                "condition": "原始結果、用量或結算需要查核。",
                "http_status": 502,
                "operation_id_source": "actual X-Client-Request-ID",
                "recovery": "請保留實際的請求 ID 與原始回應。請讀取現有的自有紀錄，切勿重新提交建立請求。",
                "response_headers": {
                  "x-should-retry": "false"
                },
                "type": "server_error"
              }
            ],
            "lifecycle": {
              "assets": [
                {
                  "http": "GET",
                  "path": "/v1/media/assets"
                },
                {
                  "http": "GET",
                  "path": "/v1/media/assets/{asset_id}"
                }
              ],
              "content": [
                {
                  "http": "GET",
                  "path": "/v1/media/assets/{asset_id}/content",
                  "url_source": "exact returned signed content URL"
                }
              ],
              "dedicated_method_polling_or_cancel": false,
              "mode": "synchronous_result_then_owned_library",
              "original_POST_adds_task_envelope": false,
              "status": [
                {
                  "http": "GET",
                  "id_source": "exact task_id from an existing owned media record",
                  "path": "/v1/media/tasks/{task_id}"
                }
              ],
              "unknown": "請保留實際的 X-Client-Request-ID 與完整回應。請讀取原始自有資產及其完全相符的簽署內容 URL；切勿重新提交結果不明的建立請求。"
            },
            "outputs": {
              "all_results": "保留完整回應與標頭、所有實際輸出、原始回傳的識別碼，以及所有用量欄位。恢復原始作業時，請勿再次提交建立請求。",
              "family": "text",
              "fields": [
                {
                  "description": null,
                  "name": "text (when present)",
                  "type": null
                },
                {
                  "description": null,
                  "name": "usage (when present)",
                  "type": null
                }
              ],
              "result": "完整的原始回應本文、狀態與轉送標頭。此處理常式不會加入通用的 JSON 結構、文字欄位或工作封裝。"
            },
            "parameters": [
              {
                "default_known": false,
                "enum": [
                  "openai/whisper-large-v3-turbo"
                ],
                "enum_known": true,
                "name": "model",
                "required": true,
                "type": "string"
              },
              {
                "default_known": false,
                "enum_known": false,
                "name": "input_audio",
                "required": true,
                "type": "object"
              }
            ],
            "request_schema": {
              "properties": {
                "input_audio": {
                  "properties": {
                    "data": {
                      "contentEncoding": "base64",
                      "type": "string"
                    },
                    "format": {
                      "type": "string"
                    }
                  },
                  "required": [
                    "data",
                    "format"
                  ],
                  "type": "object"
                },
                "model": {
                  "enum": [
                    "openai/whisper-large-v3-turbo"
                  ],
                  "type": "string"
                }
              },
              "required": [
                "model",
                "input_audio"
              ],
              "type": "object"
            },
            "schema_template": {
              "actual_file_preparation_required": true,
              "body": {
                "input_audio": {
                  "data": "${BASE64_ACTUAL_WAV_BYTES}",
                  "format": "wav"
                },
                "model": "openai/whisper-large-v3-turbo"
              },
              "content_type": "application/json"
            }
          },
          "input": {
            "content_type": "application/json",
            "material_conditions": [
              "此範例會讀取您實際使用且非空的 PCM WAV 檔案，將完整檔案位元組編碼為 base64，並將 input_audio.format 設為 wav 傳送。"
            ],
            "material_types": [
              "audio"
            ],
            "required": [
              "model",
              "input_audio"
            ]
          },
          "lifecycle": {
            "assets": [
              {
                "http": "GET",
                "path": "/v1/media/assets"
              },
              {
                "http": "GET",
                "path": "/v1/media/assets/{asset_id}"
              }
            ],
            "content": [
              {
                "http": "GET",
                "path": "/v1/media/assets/{asset_id}/content",
                "url_source": "exact returned signed content URL"
              }
            ],
            "dedicated_method_polling_or_cancel": false,
            "mode": "synchronous_result_then_owned_library",
            "original_POST_adds_task_envelope": false,
            "status": [
              {
                "http": "GET",
                "id_source": "現有自有媒體紀錄中完全相符的 task_id",
                "path": "/v1/media/tasks/{task_id}"
              }
            ],
            "unknown": "Retain the actual X-Client-Request-ID and complete response. Read the original owned assets and their exact signed content URLs; never resubmit an uncertain creation."
          },
          "method": {
            "http": "POST",
            "path": "/v1/audio/transcriptions"
          },
          "output": {
            "all_results": "Retain the complete response and headers, every actual output, original returned identifiers and all usage fields. Recover the original operation without submitting creation again.",
            "family": "text",
            "fields": [
              {
                "description": null,
                "name": "text (when present)",
                "type": null
              },
              {
                "description": null,
                "name": "usage (when present)",
                "type": null
              }
            ],
            "result": "Complete original response body, status and forwarded headers. No universal JSON shape, text field or task envelope is added by this handler."
          }
        },
        "ctx": null,
        "declared_pricing_profiles": [
          {
            "dimensions": {
              "regime": "base"
            },
            "label": "Base token rates",
            "units": [
              {
                "amount": null,
                "amount_unit": "usd_per_thousand_tokens",
                "billing_input": true,
                "estimate_only": false,
                "key": "input_price",
                "label": "Input tokens",
                "native_amount_usd_per_unit": null,
                "native_quantity": 1,
                "native_unit": "input_token",
                "public_unit_label": "/ 1K tokens",
                "quantity": 1000,
                "quantity_is_estimate": false,
                "rate_role": "typed_native_retail_rate",
                "side": "in",
                "unit": "input_token"
              },
              {
                "amount": null,
                "amount_unit": "usd_per_thousand_tokens",
                "billing_input": true,
                "estimate_only": false,
                "key": "output_price",
                "label": "Output tokens",
                "native_amount_usd_per_unit": null,
                "native_quantity": 1,
                "native_unit": "output_token",
                "public_unit_label": "/ 1K tokens",
                "quantity": 1000,
                "quantity_is_estimate": false,
                "rate_role": "typed_native_retail_rate",
                "side": "out",
                "unit": "output_token"
              },
              {
                "amount": null,
                "amount_unit": "usd_per_thousand_tokens",
                "billing_input": true,
                "estimate_only": false,
                "key": "cache_read_price",
                "label": "Cache read",
                "native_amount_usd_per_unit": null,
                "native_quantity": 1,
                "native_unit": "cached_input_token",
                "public_unit_label": "/ 1K tokens",
                "quantity": 1000,
                "quantity_is_estimate": false,
                "rate_role": "typed_native_retail_rate",
                "side": "in",
                "unit": "cached_input_token"
              },
              {
                "amount": null,
                "amount_unit": "usd_per_thousand_tokens",
                "billing_input": true,
                "estimate_only": false,
                "key": "cache_write_price",
                "label": "Cache write",
                "native_amount_usd_per_unit": null,
                "native_quantity": 1,
                "native_unit": "generic_cache_creation_token",
                "public_unit_label": "/ 1K tokens",
                "quantity": 1000,
                "quantity_is_estimate": false,
                "rate_role": "typed_native_retail_rate",
                "side": "in",
                "unit": "generic_cache_creation_token"
              },
              {
                "amount": null,
                "amount_unit": "usd_per_thousand_tokens",
                "billing_input": true,
                "estimate_only": false,
                "key": "cache_write_1h_price",
                "label": "Cache write, 1 hour",
                "native_amount_usd_per_unit": null,
                "native_quantity": 1,
                "native_unit": "one_hour_cache_creation_token",
                "public_unit_label": "/ 1K tokens",
                "quantity": 1000,
                "quantity_is_estimate": false,
                "rate_role": "typed_native_retail_rate",
                "side": "in",
                "unit": "one_hour_cache_creation_token"
              }
            ]
          },
          {
            "dimensions": {
              "quoted_unit": "per input audio second"
            },
            "label": "input audio second",
            "units": [
              {
                "amount": "0.00000666",
                "amount_unit": "usd_per_exact_native_unit",
                "billing_input": true,
                "estimate_only": false,
                "key": "audio_input_second",
                "label": "input audio second",
                "native_amount_usd_per_unit": "0.00000666",
                "native_quantity": 1,
                "public_unit_label": "per input audio second",
                "quantity": 1,
                "quantity_is_estimate": false,
                "rate_role": "typed_native_retail_rate",
                "side": "in",
                "unit": "audio_input_second"
              }
            ]
          }
        ],
        "examples": [
          {
            "code": "set -eu\n: \"${AILOOT_API_KEY:?Set your Ailoot API key}\"\n: \"${AILOOT_AUDIO_FILE:?Set the path to your actual PCM WAV recording}\"\nexport AILOOT_AUDIO_FILE\npython3 - <<'PY_REQUEST'\nimport base64, io, json, os, wave\nfrom pathlib import Path\naudio = Path(os.environ['AILOOT_AUDIO_FILE']).read_bytes()\nif not (audio[:4] == b'RIFF' and audio[8:12] == b'WAVE'):\n    raise SystemExit('Supply your actual PCM WAV audio file')\nwith wave.open(io.BytesIO(audio), 'rb') as recording:\n    if recording.getcomptype() != 'NONE' or recording.getnframes() <= 0:\n        raise SystemExit('Supply a nonempty PCM WAV recording')\nrequest = {'model': 'openai/whisper-large-v3-turbo', 'input_audio': {'data': base64.b64encode(audio).decode('ascii'), 'format': 'wav'}}\nPath('request.json').write_text(json.dumps(request, ensure_ascii=False), encoding='utf-8')\nPY_REQUEST\ncurl --fail-with-body --silent --show-error https://api.ailoot.ai/v1/audio/transcriptions \\\n  -H \"Authorization: Bearer $AILOOT_API_KEY\" -H 'Content-Type: application/json' \\\n  --data-binary @request.json -D response-headers.txt -o response.bin\n# Retain the complete original response, headers and actual X-Client-Request-ID.\n# Read existing owned records for recovery; do not resubmit an uncertain operation.\n",
            "label": "curl · actual WAV file and complete original result",
            "language": "bash"
          }
        ],
        "family": "openai",
        "fast_multiplier": null,
        "flex_multiplier": null,
        "fmt": "transcriptions",
        "hints": [
          "The example reads your actual nonempty PCM WAV file, encodes the complete file bytes as base64 and sends input_audio.format as wav.",
          "The format value in the example is the documented recipe; no model-specific format list, limit or default is asserted.",
          "Retain the complete response and headers, every actual output, original returned identifiers and all usage fields. Recover the original operation without submitting creation again."
        ],
        "http": "POST",
        "in": null,
        "input": [
          "audio"
        ],
        "label": "語音轉文字",
        "max_out": null,
        "max_reasoning_effort_multiplier": null,
        "method_aliases": [],
        "native_endpoint": "audio_transcriptions",
        "out": null,
        "output": [
          "text"
        ],
        "path": "/v1/audio/transcriptions",
        "price_conditions": [
          {
            "label": "Fast mode",
            "value": "Not specified",
            "when": "When fast mode is selected"
          },
          {
            "label": "Flex mode",
            "value": "Not specified",
            "when": "When flex mode is selected"
          },
          {
            "label": "Maximum reasoning effort",
            "value": "Not specified",
            "when": "When maximum reasoning effort uses the default adjustment"
          }
        ],
        "pricing": {
          "billing_mode": "per_request",
          "image_input_price": null,
          "image_output_price": null,
          "per_request_price": null,
          "unit_prices": {
            "audio_input_second": 6.66e-06
          }
        },
        "pricing_profiles": [
          {
            "dimensions": {
              "regime": "base"
            },
            "label": "Base token rates",
            "units": [
              {
                "amount": null,
                "amount_unit": "usd_per_thousand_tokens",
                "billing_input": true,
                "estimate_only": false,
                "key": "input_price",
                "label": "Input tokens",
                "native_amount_usd_per_unit": null,
                "native_quantity": 1,
                "native_unit": "input_token",
                "public_unit_label": "/ 1K tokens",
                "quantity": 1000,
                "quantity_is_estimate": false,
                "rate_role": "typed_native_retail_rate",
                "side": "in",
                "unit": "input_token"
              },
              {
                "amount": null,
                "amount_unit": "usd_per_thousand_tokens",
                "billing_input": true,
                "estimate_only": false,
                "key": "output_price",
                "label": "Output tokens",
                "native_amount_usd_per_unit": null,
                "native_quantity": 1,
                "native_unit": "output_token",
                "public_unit_label": "/ 1K tokens",
                "quantity": 1000,
                "quantity_is_estimate": false,
                "rate_role": "typed_native_retail_rate",
                "side": "out",
                "unit": "output_token"
              },
              {
                "amount": null,
                "amount_unit": "usd_per_thousand_tokens",
                "billing_input": true,
                "estimate_only": false,
                "key": "cache_read_price",
                "label": "Cache read",
                "native_amount_usd_per_unit": null,
                "native_quantity": 1,
                "native_unit": "cached_input_token",
                "public_unit_label": "/ 1K tokens",
                "quantity": 1000,
                "quantity_is_estimate": false,
                "rate_role": "typed_native_retail_rate",
                "side": "in",
                "unit": "cached_input_token"
              },
              {
                "amount": null,
                "amount_unit": "usd_per_thousand_tokens",
                "billing_input": true,
                "estimate_only": false,
                "key": "cache_write_price",
                "label": "Cache write",
                "native_amount_usd_per_unit": null,
                "native_quantity": 1,
                "native_unit": "generic_cache_creation_token",
                "public_unit_label": "/ 1K tokens",
                "quantity": 1000,
                "quantity_is_estimate": false,
                "rate_role": "typed_native_retail_rate",
                "side": "in",
                "unit": "generic_cache_creation_token"
              },
              {
                "amount": null,
                "amount_unit": "usd_per_thousand_tokens",
                "billing_input": true,
                "estimate_only": false,
                "key": "cache_write_1h_price",
                "label": "Cache write, 1 hour",
                "native_amount_usd_per_unit": null,
                "native_quantity": 1,
                "native_unit": "one_hour_cache_creation_token",
                "public_unit_label": "/ 1K tokens",
                "quantity": 1000,
                "quantity_is_estimate": false,
                "rate_role": "typed_native_retail_rate",
                "side": "in",
                "unit": "one_hour_cache_creation_token"
              }
            ]
          },
          {
            "dimensions": {
              "quoted_unit": "per input audio second"
            },
            "label": "input audio second",
            "units": [
              {
                "amount": "0.00000666",
                "amount_unit": "usd_per_exact_native_unit",
                "billing_input": true,
                "estimate_only": false,
                "key": "audio_input_second",
                "label": "input audio second",
                "native_amount_usd_per_unit": "0.00000666",
                "native_quantity": 1,
                "public_unit_label": "per input audio second",
                "quantity": 1,
                "quantity_is_estimate": false,
                "rate_role": "typed_native_retail_rate",
                "side": "in",
                "unit": "audio_input_second"
              }
            ]
          }
        ],
        "request_model_id": "openai/whisper-large-v3-turbo",
        "route_label": "Ultra",
        "status_reads": [
          "GET /v1/media/tasks/{task_id}"
        ],
        "tiers": [],
        "units": [
          {
            "amount": null,
            "amount_unit": "usd_per_thousand_tokens",
            "billing_input": true,
            "estimate_only": false,
            "key": "input_price",
            "label": "Input tokens",
            "native_amount_usd_per_unit": null,
            "native_quantity": 1,
            "native_unit": "input_token",
            "public_unit_label": "/ 1K tokens",
            "quantity": 1000,
            "quantity_is_estimate": false,
            "rate_role": "typed_native_retail_rate",
            "side": "in",
            "unit": "input_token"
          },
          {
            "amount": null,
            "amount_unit": "usd_per_thousand_tokens",
            "billing_input": true,
            "estimate_only": false,
            "key": "output_price",
            "label": "Output tokens",
            "native_amount_usd_per_unit": null,
            "native_quantity": 1,
            "native_unit": "output_token",
            "public_unit_label": "/ 1K tokens",
            "quantity": 1000,
            "quantity_is_estimate": false,
            "rate_role": "typed_native_retail_rate",
            "side": "out",
            "unit": "output_token"
          },
          {
            "amount": null,
            "amount_unit": "usd_per_thousand_tokens",
            "billing_input": true,
            "estimate_only": false,
            "key": "cache_read_price",
            "label": "Cache read",
            "native_amount_usd_per_unit": null,
            "native_quantity": 1,
            "native_unit": "cached_input_token",
            "public_unit_label": "/ 1K tokens",
            "quantity": 1000,
            "quantity_is_estimate": false,
            "rate_role": "typed_native_retail_rate",
            "side": "in",
            "unit": "cached_input_token"
          },
          {
            "amount": null,
            "amount_unit": "usd_per_thousand_tokens",
            "billing_input": true,
            "estimate_only": false,
            "key": "cache_write_price",
            "label": "Cache write",
            "native_amount_usd_per_unit": null,
            "native_quantity": 1,
            "native_unit": "generic_cache_creation_token",
            "public_unit_label": "/ 1K tokens",
            "quantity": 1000,
            "quantity_is_estimate": false,
            "rate_role": "typed_native_retail_rate",
            "side": "in",
            "unit": "generic_cache_creation_token"
          },
          {
            "amount": null,
            "amount_unit": "usd_per_thousand_tokens",
            "billing_input": true,
            "estimate_only": false,
            "key": "cache_write_1h_price",
            "label": "Cache write, 1 hour",
            "native_amount_usd_per_unit": null,
            "native_quantity": 1,
            "native_unit": "one_hour_cache_creation_token",
            "public_unit_label": "/ 1K tokens",
            "quantity": 1000,
            "quantity_is_estimate": false,
            "rate_role": "typed_native_retail_rate",
            "side": "in",
            "unit": "one_hour_cache_creation_token"
          },
          {
            "amount": "0.00000666",
            "amount_unit": "usd_per_exact_native_unit",
            "billing_input": true,
            "estimate_only": false,
            "key": "audio_input_second",
            "label": "input audio second",
            "native_amount_usd_per_unit": "0.00000666",
            "native_quantity": 1,
            "public_unit_label": "per input audio second",
            "quantity": 1,
            "quantity_is_estimate": false,
            "rate_role": "typed_native_retail_rate",
            "side": "in",
            "unit": "audio_input_second"
          }
        ]
      }
    ],
    "model_aliases": [
      {
        "canonical_model_id": "openai/whisper-large-v3-turbo",
        "request_model_id": "openai/whisper-large-v3-turbo",
        "route_label": "Ultra"
      }
    ],
    "name": "OpenAI: Whisper Large V3 Turbo",
    "price": {
      "in": null,
      "in_label": null,
      "out": null,
      "out_label": null,
      "sort_in": null,
      "sort_out": null,
      "varies": true
    },
    "short": "Whisper large-v3-turbo 是 OpenAI 從 large-v3 衍生、速度較快的開放權重轉錄版本，具有四個解碼器層與 8.09 億參數。它針對多語言語音轉文字；製造商官方文件將語音翻譯成英文排除在 Turbo 的訓練任務之外。"
  },
  "renderer_schema": {
    "method_order": "Original DTO methods order; every exact route/format/path/caller survives.",
    "prices": "Original public DTO fields and original native display HTML; no flattened or normalized offers."
  },
  "representation": "exact-public-dto-and-native-renderer-html",
  "representationNotes": {
    "current_reference": {
      "about_json_pointer": "/aboutHtml",
      "methods": [
        {
          "contract_json_pointer": "/methods/0/rawMethod/contract",
          "html_json_pointer": "/methods/0/html",
          "method_ordinal": 0
        }
      ],
      "role": "current-semantic-reference"
    },
    "raw_input": {
      "examples_role": "historical-input-not-current-ready-examples",
      "json_pointers": [
        "/rawModel",
        "/methods/0/rawMethod"
      ],
      "role": "historical-owner-input"
    },
    "schema": "ailoot-native-model-representations-v1"
  },
  "schema": "ailoot-static-model-facts-v1",
  "schema_version": 1,
  "shortText": "Whisper large-v3-turbo 是 OpenAI 從 large-v3 衍生、速度較快的開放權重轉錄版本，具有四個解碼器層與 8.09 億參數。它針對多語言語音轉文字；製造商官方文件將語音翻譯成英文排除在 Turbo 的訓練任務之外。",
  "source": {
    "audit_sha256": "2e00086bcbfc28e64d0cebe97aa47c17d8d5618963027f8ffb9dc6123d7d25b1",
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