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  "aboutHtml": "<p>Llama Nemotron Rerank VL 1B V2評估候選文字與文件圖片相對於文字查詢的關聯程度，包含圖表、表格與混合媒體頁面。NVIDIA將其描述為1.7B參數的交叉編碼器模型。在檢索工作流程中，請先執行初始搜尋，再將選定候選項目傳送至重排序模型。實用結果是重新排序的候選集與關聯分數，應用程式可用來選擇回答所需上下文，或安排搜尋結果頁面。</p><p>請使用POST /v1/rerank，並提供application/json主體。將model設為&quot;nvidia/llama-nemotron-rerank-vl-1b-v2:free&quot;，query設為實際搜尋問題，documents設為非空陣列。每個候選項目可以是文字字串，或含有text及／或image的物件；結構化物件必須至少提供其中一個欄位。text為字串。image為遠端HTTP/HTTPS URL，或以data:image/開頭的base64 data URI。結合兩者的候選項目須提供兩個欄位。請保留輸入陣列的順序，以便將回傳索引對應至您儲存的文件ID。top_n為至少1的選用整數，用來要求回傳排名最高的文件數量。</p><p>例如，說明中心應用程式可先檢索配送、退貨與帳戶存取相關段落，再依客戶的配送問題重新排序這些段落。請傳入實際段落文字，不要使用檔名，或與儲存來源無關的搜尋引擎片段。在應用程式中，請讓各段落連結至其來源識別碼，讓選定證據之後可以引用或開啟。處理掃描文件、圖表、表格或資訊圖表時，請在文件物件中提供實際圖片，並在有助於識別內容時加入文字。</p><p>模型頁面記載每個查詢與文件的上限為10,240個詞元。準備候選清單前，請將較長來源資料拆成範圍受限的段落。請為各段落保留有用的前後文，包含會改變含義的標題或產品名稱。文件所述請求從您提供的候選項目開始；它不會代您搜尋文件集合。</p><p>重排序會回傳同步JSON結果。請讀取每個results項目，包含原始index、relevance_score與回傳document物件，後者可含有text及／或image，並保留任何回傳usage與回應識別碼。使用index將排序結果對應回輸入候選項目。請將關聯分數視為此查詢的排序訊號，而非經獨立驗證的事實回答。若下一步選擇多個段落，請保留完整結果。</p><p>此免費版本請使用公開或合成的候選資料；其文件所載使用條款排除機密資訊與個人資料。若請求結束時沒有完整結果，請在檢查該次嘗試時保留原始回應與請求識別碼。文件所述重排序流程會直接回傳結果，並未提供獨立的工作輪詢或取消工作流程。</p>",
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      "html": "<div class=\"sheet-head\"><span class=\"mav\" aria-hidden=\"true\">NV</span><h2 id=\"sheet-title\">NVIDIA: Llama Nemotron Rerank VL 1B V2 (free)</h2><button class=\"icon-btn\" type=\"button\" data-close-sheet aria-label=\"關閉\">×</button></div><div class=\"idline\"><span>NVIDIA /</span><code>nvidia/llama-nemotron-rerank-vl-1b-v2:free</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|rerank|/v1/rerank|nvidia%2Fllama-nemotron-rerank-vl-1b-v2%3Afree\">重新排序</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\">Llama Nemotron Rerank VL 1B V2是NVIDIA的交叉編碼器重排序模型，可依檢索資料與查詢的關聯程度排序。請傳送查詢與候選文字、圖片或兩者結合的文件，再使用回傳分數與原始索引，選擇搜尋結果或檢索增強回答所需段落。</p><dl class=\"card-io\" data-card-io><div><dt>接受的輸入</dt><dd>文字</dd></div><div><dt>結果</dt><dd>ranking</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>Llama Nemotron Rerank VL 1B V2評估候選文字與文件圖片相對於文字查詢的關聯程度，包含圖表、表格與混合媒體頁面。NVIDIA將其描述為1.7B參數的交叉編碼器模型。在檢索工作流程中，請先執行初始搜尋，再將選定候選項目傳送至重排序模型。實用結果是重新排序的候選集與關聯分數，應用程式可用來選擇回答所需上下文，或安排搜尋結果頁面。</p><p>請使用POST /v1/rerank，並提供application/json主體。將model設為&quot;nvidia/llama-nemotron-rerank-vl-1b-v2:free&quot;，query設為實際搜尋問題，documents設為非空陣列。每個候選項目可以是文字字串，或含有text及／或image的物件；結構化物件必須至少提供其中一個欄位。text為字串。image為遠端HTTP/HTTPS URL，或以data:image/開頭的base64 data URI。結合兩者的候選項目須提供兩個欄位。請保留輸入陣列的順序，以便將回傳索引對應至您儲存的文件ID。top_n為至少1的選用整數，用來要求回傳排名最高的文件數量。</p><p>例如，說明中心應用程式可先檢索配送、退貨與帳戶存取相關段落，再依客戶的配送問題重新排序這些段落。請傳入實際段落文字，不要使用檔名，或與儲存來源無關的搜尋引擎片段。在應用程式中，請讓各段落連結至其來源識別碼，讓選定證據之後可以引用或開啟。處理掃描文件、圖表、表格或資訊圖表時，請在文件物件中提供實際圖片，並在有助於識別內容時加入文字。</p><p>模型頁面記載每個查詢與文件的上限為10,240個詞元。準備候選清單前，請將較長來源資料拆成範圍受限的段落。請為各段落保留有用的前後文，包含會改變含義的標題或產品名稱。文件所述請求從您提供的候選項目開始；它不會代您搜尋文件集合。</p><p>重排序會回傳同步JSON結果。請讀取每個results項目，包含原始index、relevance_score與回傳document物件，後者可含有text及／或image，並保留任何回傳usage與回應識別碼。使用index將排序結果對應回輸入候選項目。請將關聯分數視為此查詢的排序訊號，而非經獨立驗證的事實回答。若下一步選擇多個段落，請保留完整結果。</p><p>此免費版本請使用公開或合成的候選資料；其文件所載使用條款排除機密資訊與個人資料。若請求結束時沒有完整結果，請在檢查該次嘗試時保留原始回應與請求識別碼。文件所述重排序流程會直接回傳結果，並未提供獨立的工作輪詢或取消工作流程。</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 · Rerank</b> <code>POST /v1/rerank</code></summary><dl class=\"method-capabilities\"><div><dt>輸入</dt><dd><code>text</code></dd></div><div><dt>輸出</dt><dd><code>ranking</code></dd></div><div><dt>輸出格式</dt><dd>JSON</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>nvidia/llama-nemotron-rerank-vl-1b-v2:free</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\">query</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></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\">documents</code></th><td data-cell-label=\"類型\" data-field-type><span class=\"card-cell-label\">類型</span><code>array</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><tr><th data-cell-label=\"欄位\" scope=\"row\"><span class=\"card-cell-label\">欄位</span><code class=\"card-field-name\">top_n</code></th><td data-cell-label=\"類型\" data-field-type><span class=\"card-cell-label\">類型</span><code>integer</code></td><td data-cell-label=\"要求\"><span class=\"card-cell-label\">要求</span>選填</td><td data-cell-label=\"值與限制\"><span class=\"card-cell-label\">值與限制</span><div>最小值: 1</div></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, query, documents</td></tr><tr><th data-cell-label=\"參數\" scope=\"row\"><span class=\"card-cell-label\">參數</span><code>optional</code></th><td data-cell-label=\"規格\"><span class=\"card-cell-label\">規格</span>top_n</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>text</td></tr><tr><th data-cell-label=\"參數\" scope=\"row\"><span class=\"card-cell-label\">參數</span><code>conditions</code></th><td data-cell-label=\"規格\"><span class=\"card-cell-label\">規格</span></td></tr></tbody></table></div><p>生命週期： <code>synchronous_json</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>計費數量</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=\"計費數量\"><span class=\"card-cell-label\">計費數量</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>每次請求</th><td data-cell-label=\"費率表\"><span class=\"card-cell-label\">費率表</span>—</td><td data-cell-label=\"計費數量\"><span class=\"card-cell-label\">計費數量</span>1 次請求</td><td data-cell-label=\"費用\"><span class=\"card-cell-label\">費用</span><div><span>輸入</span> <b>$0</b> <span class=\"price-unit\">每次請求</span></div></td></tr></tbody></table></div></div><p class=\"note-s\">Ailoot 會在請求前預留估算金額。取得結果後，依實測用量結算最終費用。串流結算採用最終用量紀錄。<a href=\"/docs/zh-hant-tw/billing/reserve/\">預留金額與結算的運作方式 →</a></p></section><section class=\"card-section\" data-card-section=\"examples\"><h3 tabindex=\"-1\">請求範例</h3><h4>Ailoot Ultra · Rerank</h4><div class=\"code-group\"><div class=\"cg-bar\"><div class=\"cg-tabs\" role=\"tablist\" aria-label=\"程式碼版本\"><button class=\"cg-tab\" id=\"model-code-32-tab-0\" role=\"tab\" type=\"button\" aria-controls=\"model-code-32-panel-0\" aria-selected=\"true\" tabindex=\"0\">curl · 僅建立一次並保留完整結果</button></div><div class=\"cg-tools\"><button class=\"cg-btn cg-copy\" type=\"button\" aria-label=\"複製程式碼\"><svg class=\"cp\" viewBox=\"0 0 16 16\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"1.4\"><rect x=\"5.25\" y=\"5.25\" width=\"8.5\" height=\"8.5\" rx=\"1.75\"/><path d=\"M10.75 5.25V3.5a1.25 1.25 0 0 0-1.25-1.25H3.5A1.25 1.25 0 0 0 2.25 3.5v6a1.25 1.25 0 0 0 1.25 1.25h1.75\"/></svg><svg class=\"ok\" viewBox=\"0 0 16 16\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"1.4\"><path d=\"m3 8.5 3.25 3.25L13 5\"/></svg></button></div></div><div class=\"cg-body\"><div class=\"cg-pane\" id=\"model-code-32-panel-0\" role=\"tabpanel\" aria-labelledby=\"model-code-32-tab-0\"><pre data-lang=\"bash\"><code>set -eu\n: &quot;${AILOOT_API_KEY:?Set your Ailoot API key}&quot;\nexport AILOOT_API_KEY\npython3 - &lt;&lt;&#39;PY_REQUEST&#39;\nimport json,os\nfrom pathlib import Path\np=json.loads(&#39;{&quot;documents&quot;: [&quot;Paris is the capital of France.&quot;, &quot;Berlin is the capital of Germany.&quot;], &quot;model&quot;: &quot;nvidia/llama-nemotron-rerank-vl-1b-v2:free&quot;, &quot;query&quot;: &quot;What is the capital of France?&quot;, &quot;top_n&quot;: 3}&#39;)\n\nPath(&quot;request.json&quot;).write_text(json.dumps(p,ensure_ascii=False))\nPY_REQUEST\ncurl --fail-with-body --silent --show-error https://api.ailoot.ai/v1/rerank \\\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 result.json\n# Submit once. Retain the complete result, original identifiers and every response header.\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 · Rerank</h4><p class=\"note-s\">JSON</p><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\">Retain the complete response, all actual results, original identifiers, usage and response headers.</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\">Preserve the original response, headers and X-Client-Request-ID. An uncertain outcome does not authorize another creation.</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\">results</code></th><td data-cell-label=\"類型\" data-field-type><span class=\"card-cell-label\">類型</span>array</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=nvidia%2Fllama-nemotron-rerank-vl-1b-v2%3Afree&amp;route=Ultra&amp;caller=nvidia%2Fllama-nemotron-rerank-vl-1b-v2%3Afree&amp;fmt=rerank\"><code>nvidia/llama-nemotron-rerank-vl-1b-v2:free</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=nvidia%2Fllama-nemotron-rerank-vl-1b-v2%3Afree&amp;route=Ultra&amp;caller=nvidia%2Fllama-nemotron-rerank-vl-1b-v2%3Afree&amp;fmt=rerank\"><code>nvidia/llama-nemotron-rerank-vl-1b-v2:free</code></a></p></section></div>",
      "method_identity": {
        "effective_request_model_id": "nvidia/llama-nemotron-rerank-vl-1b-v2:free",
        "fmt": "rerank",
        "http": "POST",
        "path": "/v1/rerank",
        "request_model_id": "nvidia/llama-nemotron-rerank-vl-1b-v2:free",
        "route_label": "Ultra"
      },
      "method_key": "Ultra|rerank|/v1/rerank|nvidia%2Fllama-nemotron-rerank-vl-1b-v2%3Afree",
      "ordinal": 0,
      "rawMethod": {
        "available": null,
        "cache_read": null,
        "cache_write": null,
        "cache_write_1h": null,
        "contract": {
          "data": {
            "all_results": "Retain the complete response, all actual results, original identifiers, usage and response headers.",
            "authentication": {
              "api_key_source": "AILOOT_API_KEY",
              "header": "Authorization: Bearer"
            },
            "example_body": {
              "documents": [
                "Paris is the capital of France.",
                "Berlin is the capital of Germany."
              ],
              "model": "nvidia/llama-nemotron-rerank-vl-1b-v2:free",
              "query": "What is the capital of France?",
              "top_n": 3
            },
            "lifecycle": {
              "cancel_endpoint": null,
              "create": {
                "http": "POST",
                "path": "/v1/rerank"
              },
              "mode": "synchronous_json",
              "status": [],
              "unknown": "Preserve the original response, headers and X-Client-Request-ID. An uncertain outcome does not authorize another creation.",
              "unknown_no_replay": true
            },
            "outputs": {
              "all_results": "Retain the complete response, all actual results, original identifiers, usage and response headers.",
              "family": "ranking",
              "fields": [
                {
                  "name": "results",
                  "type": "array"
                }
              ],
              "format": "JSON"
            },
            "parameters": [
              {
                "default_known": false,
                "enum": [
                  "nvidia/llama-nemotron-rerank-vl-1b-v2:free"
                ],
                "enum_known": true,
                "name": "model",
                "required": true,
                "type": "string"
              },
              {
                "default_known": false,
                "enum_known": false,
                "name": "query",
                "required": true,
                "type": "string"
              },
              {
                "default_known": false,
                "enum_known": false,
                "items": {
                  "type": "string"
                },
                "minItems": 1,
                "name": "documents",
                "required": true,
                "type": "array"
              },
              {
                "default_known": false,
                "enum_known": false,
                "minimum": 1,
                "name": "top_n",
                "required": false,
                "type": "integer"
              }
            ],
            "request_schema": {
              "additionalProperties": true,
              "properties": {
                "documents": {
                  "items": {
                    "type": "string"
                  },
                  "minItems": 1,
                  "type": "array"
                },
                "model": {
                  "enum": [
                    "nvidia/llama-nemotron-rerank-vl-1b-v2:free"
                  ],
                  "type": "string"
                },
                "query": {
                  "type": "string"
                },
                "top_n": {
                  "minimum": 1,
                  "type": "integer"
                }
              },
              "required": [
                "model",
                "query",
                "documents"
              ],
              "type": "object"
            },
            "schema_template": {
              "body": {
                "documents": [
                  "Paris is the capital of France.",
                  "Berlin is the capital of Germany."
                ],
                "model": "nvidia/llama-nemotron-rerank-vl-1b-v2:free",
                "query": "What is the capital of France?",
                "top_n": 3
              },
              "content_type": "application/json"
            }
          },
          "input": {
            "conditions": [],
            "content_type": "application/json",
            "material_types": [
              "text"
            ],
            "optional": [
              "top_n"
            ],
            "required": [
              "model",
              "query",
              "documents"
            ]
          },
          "lifecycle": {
            "cancel_endpoint": null,
            "create": {
              "http": "POST",
              "path": "/v1/rerank"
            },
            "mode": "synchronous_json",
            "status": [],
            "unknown": "Preserve the original response, headers and X-Client-Request-ID. An uncertain outcome does not authorize another creation.",
            "unknown_no_replay": true
          },
          "method": {
            "http": "POST",
            "path": "/v1/rerank"
          },
          "method_aliases": [],
          "output": {
            "all_results": "Retain the complete response, all actual results, original identifiers, usage and response headers.",
            "family": "ranking",
            "fields": [
              {
                "name": "results",
                "type": "array"
              }
            ],
            "format": "JSON"
          }
        },
        "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": {
              "billing_quantity": "one request"
            },
            "label": "Per request",
            "units": [
              {
                "amount": "0",
                "amount_unit": "usd_per_exact_native_unit",
                "billing_input": true,
                "estimate_only": false,
                "key": "per_request",
                "label": "per request",
                "native_amount_usd_per_unit": "0",
                "native_quantity": 1,
                "public_unit_label": "per request",
                "quantity": 1,
                "quantity_is_estimate": false,
                "rate_role": "typed_native_retail_rate",
                "side": "in",
                "unit": "per_request"
              }
            ]
          }
        ],
        "examples": [
          {
            "code": "set -eu\n: \"${AILOOT_API_KEY:?Set your Ailoot API key}\"\nexport AILOOT_API_KEY\npython3 - <<'PY_REQUEST'\nimport json,os\nfrom pathlib import Path\np=json.loads('{\"documents\": [\"Paris is the capital of France.\", \"Berlin is the capital of Germany.\"], \"model\": \"nvidia/llama-nemotron-rerank-vl-1b-v2:free\", \"query\": \"What is the capital of France?\", \"top_n\": 3}')\n\nPath(\"request.json\").write_text(json.dumps(p,ensure_ascii=False))\nPY_REQUEST\ncurl --fail-with-body --silent --show-error https://api.ailoot.ai/v1/rerank \\\n  -H \"Authorization: Bearer $AILOOT_API_KEY\" -H 'Content-Type: application/json' \\\n  --data-binary @request.json -D response-headers.txt -o result.json\n# Submit once. Retain the complete result, original identifiers and every response header.\n",
            "label": "curl · create once and retain the complete result",
            "language": "bash"
          }
        ],
        "family": "openai",
        "fast_multiplier": null,
        "flex_multiplier": null,
        "fmt": "rerank",
        "http": "POST",
        "img_in": null,
        "img_out": null,
        "in": null,
        "input": [
          "text"
        ],
        "label": "Rerank",
        "max_out": null,
        "max_reasoning_effort_multiplier": null,
        "method_aliases": [],
        "out": null,
        "output": [
          "ranking"
        ],
        "path": "/v1/rerank",
        "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",
          "cache_read_price": null,
          "cache_write_1h_price": null,
          "cache_write_price": null,
          "fast_multiplier": null,
          "flex_multiplier": null,
          "image_input_price": null,
          "image_output_price": null,
          "input_price": null,
          "intervals": null,
          "max_reasoning_effort_multiplier": null,
          "output_price": null,
          "per_request_price": 0
        },
        "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": {
              "billing_quantity": "one request"
            },
            "label": "Per request",
            "units": [
              {
                "amount": "0",
                "amount_unit": "usd_per_exact_native_unit",
                "billing_input": true,
                "estimate_only": false,
                "key": "per_request",
                "label": "per request",
                "native_amount_usd_per_unit": "0",
                "native_quantity": 1,
                "public_unit_label": "per request",
                "quantity": 1,
                "quantity_is_estimate": false,
                "rate_role": "typed_native_retail_rate",
                "side": "in",
                "unit": "per_request"
              }
            ]
          }
        ],
        "request_model_id": "nvidia/llama-nemotron-rerank-vl-1b-v2:free",
        "route_label": "Ultra",
        "status_reads": [],
        "tiers": [],
        "unit": "per_request",
        "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,
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  "model_id": "nvidia/llama-nemotron-rerank-vl-1b-v2:free",
  "nativeProvenance": {
    "input_facts_canonical_sha256": "8f95dd8198e03d254ea67f71b8076df2e0e48d2c0fe6ee62f331f1c9c42ec43b",
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    "role": "historical-normalized-input-audit-hashes",
    "schema": "ailoot-native-model-provenance-v2"
  },
  "page": {
    "canonical": "https://ailoot.ai/models/zh-hant-tw/nvidia-llama-nemotron-rerank-vl-1b-v2-u003a-free/",
    "description": "Llama Nemotron Rerank VL 1B V2是NVIDIA的交叉編碼器重排序模型，可依檢索資料與查詢的關聯程度排序。請傳送查詢與候選文字、圖片或兩者結合的文件，再使用回傳分數與原始索引，選擇搜尋結果或檢索增強回答所需段落。",
    "locale": "zh-hant-tw",
    "md_url": "https://ailoot.ai/models/zh-hant-tw/nvidia-llama-nemotron-rerank-vl-1b-v2-u003a-free/index.md",
    "title": "NVIDIA: Llama Nemotron Rerank VL 1B V2 (free) — Ailoot",
    "url": "https://ailoot.ai/models/zh-hant-tw/nvidia-llama-nemotron-rerank-vl-1b-v2-u003a-free/"
  },
  "rawModel": {
    "about": "Llama Nemotron Rerank VL 1B V2評估候選文字與文件圖片相對於文字查詢的關聯程度，包含圖表、表格與混合媒體頁面。NVIDIA將其描述為1.7B參數的交叉編碼器模型。在檢索工作流程中，請先執行初始搜尋，再將選定候選項目傳送至重排序模型。實用結果是重新排序的候選集與關聯分數，應用程式可用來選擇回答所需上下文，或安排搜尋結果頁面。\n\n請使用POST /v1/rerank，並提供application/json主體。將model設為\"nvidia/llama-nemotron-rerank-vl-1b-v2:free\"，query設為實際搜尋問題，documents設為非空陣列。每個候選項目可以是文字字串，或含有text及／或image的物件；結構化物件必須至少提供其中一個欄位。text為字串。image為遠端HTTP/HTTPS URL，或以data:image/開頭的base64 data URI。結合兩者的候選項目須提供兩個欄位。請保留輸入陣列的順序，以便將回傳索引對應至您儲存的文件ID。top_n為至少1的選用整數，用來要求回傳排名最高的文件數量。\n\n例如，說明中心應用程式可先檢索配送、退貨與帳戶存取相關段落，再依客戶的配送問題重新排序這些段落。請傳入實際段落文字，不要使用檔名，或與儲存來源無關的搜尋引擎片段。在應用程式中，請讓各段落連結至其來源識別碼，讓選定證據之後可以引用或開啟。處理掃描文件、圖表、表格或資訊圖表時，請在文件物件中提供實際圖片，並在有助於識別內容時加入文字。\n\n模型頁面記載每個查詢與文件的上限為10,240個詞元。準備候選清單前，請將較長來源資料拆成範圍受限的段落。請為各段落保留有用的前後文，包含會改變含義的標題或產品名稱。文件所述請求從您提供的候選項目開始；它不會代您搜尋文件集合。\n\n重排序會回傳同步JSON結果。請讀取每個results項目，包含原始index、relevance_score與回傳document物件，後者可含有text及／或image，並保留任何回傳usage與回應識別碼。使用index將排序結果對應回輸入候選項目。請將關聯分數視為此查詢的排序訊號，而非經獨立驗證的事實回答。若下一步選擇多個段落，請保留完整結果。\n\n此免費版本請使用公開或合成的候選資料；其文件所載使用條款排除機密資訊與個人資料。若請求結束時沒有完整結果，請在檢查該次嘗試時保留原始回應與請求識別碼。文件所述重排序流程會直接回傳結果，並未提供獨立的工作輪詢或取消工作流程。",
    "alias_of": null,
    "aliases": [],
    "author": "NVIDIA",
    "ctx": 10240,
    "formats": [
      "rerank"
    ],
    "id": "nvidia/llama-nemotron-rerank-vl-1b-v2:free",
    "input": [
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    ],
    "kind": "text",
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    "methods": [
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        "cache_read": null,
        "cache_write": null,
        "cache_write_1h": null,
        "contract": {
          "data": {
            "all_results": "Retain the complete response, all actual results, original identifiers, usage and response headers.",
            "authentication": {
              "api_key_source": "AILOOT_API_KEY",
              "header": "Authorization: Bearer"
            },
            "example_body": {
              "documents": [
                "Paris is the capital of France.",
                "Berlin is the capital of Germany."
              ],
              "model": "nvidia/llama-nemotron-rerank-vl-1b-v2:free",
              "query": "What is the capital of France?",
              "top_n": 3
            },
            "lifecycle": {
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              "create": {
                "http": "POST",
                "path": "/v1/rerank"
              },
              "mode": "synchronous_json",
              "status": [],
              "unknown": "Preserve the original response, headers and X-Client-Request-ID. An uncertain outcome does not authorize another creation.",
              "unknown_no_replay": true
            },
            "outputs": {
              "all_results": "Retain the complete response, all actual results, original identifiers, usage and response headers.",
              "family": "ranking",
              "fields": [
                {
                  "name": "results",
                  "type": "array"
                }
              ],
              "format": "JSON"
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            "parameters": [
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                "default_known": false,
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                ],
                "enum_known": true,
                "name": "model",
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                "items": {
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                "name": "documents",
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                "type": "array"
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                "minimum": 1,
                "name": "top_n",
                "required": false,
                "type": "integer"
              }
            ],
            "request_schema": {
              "additionalProperties": true,
              "properties": {
                "documents": {
                  "items": {
                    "type": "string"
                  },
                  "minItems": 1,
                  "type": "array"
                },
                "model": {
                  "enum": [
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                  ],
                  "type": "string"
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                "query": {
                  "type": "string"
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                "top_n": {
                  "minimum": 1,
                  "type": "integer"
                }
              },
              "required": [
                "model",
                "query",
                "documents"
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              "type": "object"
            },
            "schema_template": {
              "body": {
                "documents": [
                  "Paris is the capital of France.",
                  "Berlin is the capital of Germany."
                ],
                "model": "nvidia/llama-nemotron-rerank-vl-1b-v2:free",
                "query": "What is the capital of France?",
                "top_n": 3
              },
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            }
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            "content_type": "application/json",
            "material_types": [
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            "optional": [
              "top_n"
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            "required": [
              "model",
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              "documents"
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            "create": {
              "http": "POST",
              "path": "/v1/rerank"
            },
            "mode": "synchronous_json",
            "status": [],
            "unknown": "Preserve the original response, headers and X-Client-Request-ID. An uncertain outcome does not authorize another creation.",
            "unknown_no_replay": true
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            "family": "ranking",
            "fields": [
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                "type": "array"
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                "amount_unit": "usd_per_thousand_tokens",
                "billing_input": true,
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                "native_quantity": 1,
                "native_unit": "output_token",
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                "quantity": 1000,
                "quantity_is_estimate": false,
                "rate_role": "typed_native_retail_rate",
                "side": "out",
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              },
              {
                "amount": null,
                "amount_unit": "usd_per_thousand_tokens",
                "billing_input": true,
                "estimate_only": false,
                "key": "cache_read_price",
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                "native_quantity": 1,
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                "key": "cache_write_price",
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                "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"
              }
            ]
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            "dimensions": {
              "billing_quantity": "one request"
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            "units": [
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                "amount": "0",
                "amount_unit": "usd_per_exact_native_unit",
                "billing_input": true,
                "estimate_only": false,
                "key": "per_request",
                "label": "per request",
                "native_amount_usd_per_unit": "0",
                "native_quantity": 1,
                "public_unit_label": "per request",
                "quantity": 1,
                "quantity_is_estimate": false,
                "rate_role": "typed_native_retail_rate",
                "side": "in",
                "unit": "per_request"
              }
            ]
          }
        ],
        "examples": [
          {
            "code": "set -eu\n: \"${AILOOT_API_KEY:?Set your Ailoot API key}\"\nexport AILOOT_API_KEY\npython3 - <<'PY_REQUEST'\nimport json,os\nfrom pathlib import Path\np=json.loads('{\"documents\": [\"Paris is the capital of France.\", \"Berlin is the capital of Germany.\"], \"model\": \"nvidia/llama-nemotron-rerank-vl-1b-v2:free\", \"query\": \"What is the capital of France?\", \"top_n\": 3}')\n\nPath(\"request.json\").write_text(json.dumps(p,ensure_ascii=False))\nPY_REQUEST\ncurl --fail-with-body --silent --show-error https://api.ailoot.ai/v1/rerank \\\n  -H \"Authorization: Bearer $AILOOT_API_KEY\" -H 'Content-Type: application/json' \\\n  --data-binary @request.json -D response-headers.txt -o result.json\n# Submit once. Retain the complete result, original identifiers and every response header.\n",
            "label": "curl · create once and retain the complete result",
            "language": "bash"
          }
        ],
        "family": "openai",
        "fast_multiplier": null,
        "flex_multiplier": null,
        "fmt": "rerank",
        "http": "POST",
        "img_in": null,
        "img_out": null,
        "in": null,
        "input": [
          "text"
        ],
        "label": "Rerank",
        "max_out": null,
        "max_reasoning_effort_multiplier": null,
        "method_aliases": [],
        "out": null,
        "output": [
          "ranking"
        ],
        "path": "/v1/rerank",
        "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",
          "cache_read_price": null,
          "cache_write_1h_price": null,
          "cache_write_price": null,
          "fast_multiplier": null,
          "flex_multiplier": null,
          "image_input_price": null,
          "image_output_price": null,
          "input_price": null,
          "intervals": null,
          "max_reasoning_effort_multiplier": null,
          "output_price": null,
          "per_request_price": 0
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        "pricing_profiles": [
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            "label": "Base token rates",
            "units": [
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                "public_unit_label": "/ 1K tokens",
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                "rate_role": "typed_native_retail_rate",
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                "amount_unit": "usd_per_thousand_tokens",
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                "estimate_only": false,
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                "native_quantity": 1,
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                "amount_unit": "usd_per_thousand_tokens",
                "billing_input": true,
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                "key": "cache_write_price",
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                "native_quantity": 1,
                "native_unit": "generic_cache_creation_token",
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                "quantity_is_estimate": false,
                "rate_role": "typed_native_retail_rate",
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                "amount": null,
                "amount_unit": "usd_per_thousand_tokens",
                "billing_input": true,
                "estimate_only": false,
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                "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": {
              "billing_quantity": "one request"
            },
            "label": "Per request",
            "units": [
              {
                "amount": "0",
                "amount_unit": "usd_per_exact_native_unit",
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                "unit": "per_request"
              }
            ]
          }
        ],
        "request_model_id": "nvidia/llama-nemotron-rerank-vl-1b-v2:free",
        "route_label": "Ultra",
        "status_reads": [],
        "tiers": [],
        "unit": "per_request",
        "units": [
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            "amount": null,
            "amount_unit": "usd_per_thousand_tokens",
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            "billing_input": true,
            "estimate_only": false,
            "key": "cache_read_price",
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            "native_unit": "cached_input_token",
            "public_unit_label": "/ 1K tokens",
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            "rate_role": "typed_native_retail_rate",
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            "amount_unit": "usd_per_thousand_tokens",
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            "native_quantity": 1,
            "native_unit": "generic_cache_creation_token",
            "public_unit_label": "/ 1K tokens",
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            "native_quantity": 1,
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            "amount_unit": "usd_per_exact_native_unit",
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            "quantity_is_estimate": false,
            "rate_role": "typed_native_retail_rate",
            "side": "in",
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        ]
      }
    ],
    "model_aliases": [
      {
        "canonical_model_id": "nvidia/llama-nemotron-rerank-vl-1b-v2:free",
        "request_model_id": "nvidia/llama-nemotron-rerank-vl-1b-v2:free",
        "route_label": "Ultra"
      }
    ],
    "name": "NVIDIA: Llama Nemotron Rerank VL 1B V2 (free)",
    "price": {
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      "in_label": "per request",
      "out": null,
      "out_label": null,
      "sort_in": null,
      "sort_out": null,
      "varies": false
    },
    "short": "Llama Nemotron Rerank VL 1B V2是NVIDIA的交叉編碼器重排序模型，可依檢索資料與查詢的關聯程度排序。請傳送查詢與候選文字、圖片或兩者結合的文件，再使用回傳分數與原始索引，選擇搜尋結果或檢索增強回答所需段落。"
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    "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": [
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          "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": [
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        "/methods/0/rawMethod"
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      "role": "historical-owner-input"
    },
    "schema": "ailoot-native-model-representations-v1"
  },
  "schema": "ailoot-static-model-facts-v1",
  "schema_version": 1,
  "shortText": "Llama Nemotron Rerank VL 1B V2是NVIDIA的交叉編碼器重排序模型，可依檢索資料與查詢的關聯程度排序。請傳送查詢與候選文字、圖片或兩者結合的文件，再使用回傳分數與原始索引，選擇搜尋結果或檢索增強回答所需段落。",
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}
