{
  "aboutHtml": "<p>Llama Nemotron Rerank VL 1B V2 nomzod matn va hujjat tasvirlarining matnli so‘rovga mosligini baholaydi, jumladan diagrammalar, jadvallar va aralash media sahifalarini. NVIDIA uni 1.7B parametrli kross-enkoder model deb tavsiflaydi. Ma’lumot topish jarayonida avval boshlang‘ich qidiruvni bajaring, keyin tanlangan nomzodlarni qayta tartiblash modeliga yuboring. Foydali natija — moslik ballari bilan qayta tartiblangan o‘sha nomzodlar to‘plami; ilova undan javob uchun kontekst tanlash yoki qidiruv natijalari sahifasini tartiblashda foydalanishi mumkin.</p><p>application/json tanasi bilan POST /v1/rerank dan foydalaning. model ni &quot;nvidia/llama-nemotron-rerank-vl-1b-v2:free&quot;, query ni haqiqiy qidiruv savoli, documents ni esa bo‘sh bo‘lmagan massiv qilib belgilang. Har bir nomzod matn satri yoki text va/yoki image bo‘lgan obyekt bo‘lishi mumkin; tuzilgan obyekt shu maydonlardan kamida bittasini berishi kerak. text satrdir. image masofaviy HTTP/HTTPS URL manzili yoki data:image/ bilan boshlanadigan base64 ma’lumot URI qiymatidir. Aralash nomzod ikkala maydonni ham beradi. Qaytarilgan indekslarni saqlangan hujjat ID qiymatlaringiz bilan moslash uchun kirish massivining tartibini saqlang. top_n kamida 1 bo‘lgan ixtiyoriy butun son bo‘lib, eng yuqori o‘rinli hujjatlarning qaytariladigan sonini so‘raydi.</p><p>Masalan, yordam markazi ilovasi yetkazish, qaytarish va akkauntga kirish haqidagi parchalarni topishi, keyin ularni mijozning yetkazish savoliga nisbatan qayta tartiblashi mumkin. Fayl nomlari yoki saqlangan manbaga aloqasiz qidiruv tizimi parchalarini emas, haqiqiy parcha matnini bering. Tanlangan dalilni keyin keltirish yoki ochish mumkin bo‘lishi uchun har bir parchani ilovadagi o‘z manba identifikatoriga bog‘liq holda saqlang. Skanerlangan hujjat, diagramma, jadval yoki infografika uchun uning haqiqiy tasvirini hujjat obyektida bering va mazmunni aniqlashga yordam bersa, matn qo‘shing.</p><p>Model sahifasi har bir so‘rov va hujjat uchun 10 240 token chegarasini hujjatlashtiradi. Nomzodlar ro‘yxatini tayyorlashdan oldin uzunroq manba materialini chegaralangan parchalarga ajrating. Ma’noni o‘zgartirsa, sarlavha yoki mahsulot nomini ham qo‘shib, har bir parcha bilan foydali atrof kontekstini saqlang. Hujjatlashtirilgan so‘rov siz bergan nomzodlardan boshlanadi; u sizning nomingizdan hujjatlar to‘plamini qidirmaydi.</p><p>Qayta tartiblash sinxron JSON natija qaytaradi. Har bir results elementini, jumladan dastlabki index, relevance_score va text va/yoki image tashishi mumkin bo‘lgan qaytarilgan document obyektini o‘qing hamda qaytarilgan har qanday usage va javob identifikatorlarini saqlang. Tartiblangan natijani kirish nomzodiga qayta moslash uchun index dan foydalaning. Moslik ballini mustaqil tekshirilgan faktik javob sifatida emas, shu so‘rov uchun tartiblash signali sifatida qabul qiling. Keyingi bosqich uchun bir nechta parcha tanlansa, to‘liq natijani saqlang.</p><p>Ushbu bepul nashr uchun ommaviy yoki sun’iy nomzod materialini tayyorlang; uning hujjatlashtirilgan foydalanish shartlari maxfiy axborot va shaxsiy ma’lumotlarni istisno qiladi. So‘rov to‘liq natijasiz tugasa, o‘sha urinishni tekshirish davomida dastlabki javob va so‘rov identifikatorini saqlang. Hujjatlashtirilgan qayta tartiblash jarayoni natijani bevosita qaytaradi va alohida topshiriq holatini so‘rash yoki bekor qilish jarayonini bermaydi.</p>",
  "aboutText": "Llama Nemotron Rerank VL 1B V2 nomzod matn va hujjat tasvirlarining matnli so‘rovga mosligini baholaydi, jumladan diagrammalar, jadvallar va aralash media sahifalarini. NVIDIA uni 1.7B parametrli kross-enkoder model deb tavsiflaydi. Ma’lumot topish jarayonida avval boshlang‘ich qidiruvni bajaring, keyin tanlangan nomzodlarni qayta tartiblash modeliga yuboring. Foydali natija — moslik ballari bilan qayta tartiblangan o‘sha nomzodlar to‘plami; ilova undan javob uchun kontekst tanlash yoki qidiruv natijalari sahifasini tartiblashda foydalanishi mumkin.\n\napplication/json tanasi bilan POST /v1/rerank dan foydalaning. model ni \"nvidia/llama-nemotron-rerank-vl-1b-v2:free\", query ni haqiqiy qidiruv savoli, documents ni esa bo‘sh bo‘lmagan massiv qilib belgilang. Har bir nomzod matn satri yoki text va/yoki image bo‘lgan obyekt bo‘lishi mumkin; tuzilgan obyekt shu maydonlardan kamida bittasini berishi kerak. text satrdir. image masofaviy HTTP/HTTPS URL manzili yoki data:image/ bilan boshlanadigan base64 ma’lumot URI qiymatidir. Aralash nomzod ikkala maydonni ham beradi. Qaytarilgan indekslarni saqlangan hujjat ID qiymatlaringiz bilan moslash uchun kirish massivining tartibini saqlang. top_n kamida 1 bo‘lgan ixtiyoriy butun son bo‘lib, eng yuqori o‘rinli hujjatlarning qaytariladigan sonini so‘raydi.\n\nMasalan, yordam markazi ilovasi yetkazish, qaytarish va akkauntga kirish haqidagi parchalarni topishi, keyin ularni mijozning yetkazish savoliga nisbatan qayta tartiblashi mumkin. Fayl nomlari yoki saqlangan manbaga aloqasiz qidiruv tizimi parchalarini emas, haqiqiy parcha matnini bering. Tanlangan dalilni keyin keltirish yoki ochish mumkin bo‘lishi uchun har bir parchani ilovadagi o‘z manba identifikatoriga bog‘liq holda saqlang. Skanerlangan hujjat, diagramma, jadval yoki infografika uchun uning haqiqiy tasvirini hujjat obyektida bering va mazmunni aniqlashga yordam bersa, matn qo‘shing.\n\nModel sahifasi har bir so‘rov va hujjat uchun 10 240 token chegarasini hujjatlashtiradi. Nomzodlar ro‘yxatini tayyorlashdan oldin uzunroq manba materialini chegaralangan parchalarga ajrating. Ma’noni o‘zgartirsa, sarlavha yoki mahsulot nomini ham qo‘shib, har bir parcha bilan foydali atrof kontekstini saqlang. Hujjatlashtirilgan so‘rov siz bergan nomzodlardan boshlanadi; u sizning nomingizdan hujjatlar to‘plamini qidirmaydi.\n\nQayta tartiblash sinxron JSON natija qaytaradi. Har bir results elementini, jumladan dastlabki index, relevance_score va text va/yoki image tashishi mumkin bo‘lgan qaytarilgan document obyektini o‘qing hamda qaytarilgan har qanday usage va javob identifikatorlarini saqlang. Tartiblangan natijani kirish nomzodiga qayta moslash uchun index dan foydalaning. Moslik ballini mustaqil tekshirilgan faktik javob sifatida emas, shu so‘rov uchun tartiblash signali sifatida qabul qiling. Keyingi bosqich uchun bir nechta parcha tanlansa, to‘liq natijani saqlang.\n\nUshbu bepul nashr uchun ommaviy yoki sun’iy nomzod materialini tayyorlang; uning hujjatlashtirilgan foydalanish shartlari maxfiy axborot va shaxsiy ma’lumotlarni istisno qiladi. So‘rov to‘liq natijasiz tugasa, o‘sha urinishni tekshirish davomida dastlabki javob va so‘rov identifikatorini saqlang. Hujjatlashtirilgan qayta tartiblash jarayoni natijani bevosita qaytaradi va alohida topshiriq holatini so‘rash yoki bekor qilish jarayonini bermaydi.",
  "editorialOverlay": {
    "copy_fields": null,
    "copy_sha256": null,
    "copy_source": null,
    "html_sha256": "54386029e6bc1df3971cec0914615523af13ea9db15f5bf3ab99bcd8ba2eff13",
    "module_sha256": "ee9dc1c50b1e6a8fb7fa062030fcb4646b9aaaeb08be513b723a5a92a7290f06",
    "raw_model_unchanged": true,
    "schema": "ailoot-native-model-editorial-v1"
  },
  "locale": "uz",
  "methods": [
    {
      "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=\"Yopish\">×</button></div><div class=\"idline\"><span>NVIDIA /</span><code>nvidia/llama-nemotron-rerank-vl-1b-v2:free</code><button type=\"button\" id=\"copy-id\">ID ni nusxalash</button></div><nav class=\"card-jump-nav\" aria-label=\"Model kartochkasi bo‘limlari\"><button type=\"button\" data-card-jump=\"overview\">Boshlash</button><button type=\"button\" data-card-jump=\"methods\">Kirish ma’lumotlari va usullar</button><button type=\"button\" data-card-jump=\"pricing\">Tariflar</button><button type=\"button\" data-card-jump=\"examples\">Namunalar</button><button type=\"button\" data-card-jump=\"results\">Natijalar</button><button type=\"button\" data-card-jump=\"aliases\">Taxalluslar</button></nav><div class=\"card-method-tabs\" role=\"tablist\" aria-label=\"API usullari\"><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\">Qayta saralash</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\">Boshlash</h3><p class=\"mdesc-full\">Llama Nemotron Rerank VL 1B V2 — NVIDIA kompaniyasining topilgan materialni so‘rovga mosligi bo‘yicha tartiblaydigan kross-enkoder qayta tartiblash modeli. So‘rov va nomzod matn, tasvir yoki aralash hujjatlarni yuboring, so‘ng qidiruv natijalari yoki topilgan ma’lumotlar bilan boyitilgan javob uchun parchalarni tanlashda qaytarilgan ballar va dastlabki indekslardan foydalaning.</p><dl class=\"card-io\" data-card-io><div><dt>Qabul qilinadigan kirish ma’lumotlari</dt><dd>Matn</dd></div><div><dt>Natijalar</dt><dd>ranking</dd></div></dl><details class=\"card-about\"><summary>Model haqida</summary><p class=\"note-s\" data-model-method-boundary>Bu tavsif model imkoniyatlarini yoritadi. Ailoot da tanlangan usul uchun mavjud kirish, chiqish va parametrlar quyida keltirilgan.</p><div class=\"mabout\" id=\"m-about\"><p>Llama Nemotron Rerank VL 1B V2 nomzod matn va hujjat tasvirlarining matnli so‘rovga mosligini baholaydi, jumladan diagrammalar, jadvallar va aralash media sahifalarini. NVIDIA uni 1.7B parametrli kross-enkoder model deb tavsiflaydi. Ma’lumot topish jarayonida avval boshlang‘ich qidiruvni bajaring, keyin tanlangan nomzodlarni qayta tartiblash modeliga yuboring. Foydali natija — moslik ballari bilan qayta tartiblangan o‘sha nomzodlar to‘plami; ilova undan javob uchun kontekst tanlash yoki qidiruv natijalari sahifasini tartiblashda foydalanishi mumkin.</p><p>application/json tanasi bilan POST /v1/rerank dan foydalaning. model ni &quot;nvidia/llama-nemotron-rerank-vl-1b-v2:free&quot;, query ni haqiqiy qidiruv savoli, documents ni esa bo‘sh bo‘lmagan massiv qilib belgilang. Har bir nomzod matn satri yoki text va/yoki image bo‘lgan obyekt bo‘lishi mumkin; tuzilgan obyekt shu maydonlardan kamida bittasini berishi kerak. text satrdir. image masofaviy HTTP/HTTPS URL manzili yoki data:image/ bilan boshlanadigan base64 ma’lumot URI qiymatidir. Aralash nomzod ikkala maydonni ham beradi. Qaytarilgan indekslarni saqlangan hujjat ID qiymatlaringiz bilan moslash uchun kirish massivining tartibini saqlang. top_n kamida 1 bo‘lgan ixtiyoriy butun son bo‘lib, eng yuqori o‘rinli hujjatlarning qaytariladigan sonini so‘raydi.</p><p>Masalan, yordam markazi ilovasi yetkazish, qaytarish va akkauntga kirish haqidagi parchalarni topishi, keyin ularni mijozning yetkazish savoliga nisbatan qayta tartiblashi mumkin. Fayl nomlari yoki saqlangan manbaga aloqasiz qidiruv tizimi parchalarini emas, haqiqiy parcha matnini bering. Tanlangan dalilni keyin keltirish yoki ochish mumkin bo‘lishi uchun har bir parchani ilovadagi o‘z manba identifikatoriga bog‘liq holda saqlang. Skanerlangan hujjat, diagramma, jadval yoki infografika uchun uning haqiqiy tasvirini hujjat obyektida bering va mazmunni aniqlashga yordam bersa, matn qo‘shing.</p><p>Model sahifasi har bir so‘rov va hujjat uchun 10 240 token chegarasini hujjatlashtiradi. Nomzodlar ro‘yxatini tayyorlashdan oldin uzunroq manba materialini chegaralangan parchalarga ajrating. Ma’noni o‘zgartirsa, sarlavha yoki mahsulot nomini ham qo‘shib, har bir parcha bilan foydali atrof kontekstini saqlang. Hujjatlashtirilgan so‘rov siz bergan nomzodlardan boshlanadi; u sizning nomingizdan hujjatlar to‘plamini qidirmaydi.</p><p>Qayta tartiblash sinxron JSON natija qaytaradi. Har bir results elementini, jumladan dastlabki index, relevance_score va text va/yoki image tashishi mumkin bo‘lgan qaytarilgan document obyektini o‘qing hamda qaytarilgan har qanday usage va javob identifikatorlarini saqlang. Tartiblangan natijani kirish nomzodiga qayta moslash uchun index dan foydalaning. Moslik ballini mustaqil tekshirilgan faktik javob sifatida emas, shu so‘rov uchun tartiblash signali sifatida qabul qiling. Keyingi bosqich uchun bir nechta parcha tanlansa, to‘liq natijani saqlang.</p><p>Ushbu bepul nashr uchun ommaviy yoki sun’iy nomzod materialini tayyorlang; uning hujjatlashtirilgan foydalanish shartlari maxfiy axborot va shaxsiy ma’lumotlarni istisno qiladi. So‘rov to‘liq natijasiz tugasa, o‘sha urinishni tekshirish davomida dastlabki javob va so‘rov identifikatorini saqlang. Hujjatlashtirilgan qayta tartiblash jarayoni natijani bevosita qaytaradi va alohida topshiriq holatini so‘rash yoki bekor qilish jarayonini bermaydi.</p></div></details></section><section class=\"card-section\" data-card-section=\"methods\"><h3 tabindex=\"-1\">Ailoot da mavjud · kirish ma’lumotlari va usullar</h3><details class=\"card-method\" open><summary><b>Ailoot Ultra · Rerank</b> <code>POST /v1/rerank</code></summary><dl class=\"method-capabilities\"><div><dt>Kirish</dt><dd><code>text</code></dd></div><div><dt>Chiqish</dt><dd><code>ranking</code></dd></div><div><dt>Chiqish formati</dt><dd>JSON</dd></div></dl><div class=\"tw\" data-card-parameters data-typed-parameters><table><thead><tr><th>Maydon</th><th>Tur</th><th>Talab</th><th>Qiymatlar va cheklovlar</th><th>Standart</th></tr></thead><tbody><tr><th data-cell-label=\"Maydon\" scope=\"row\"><span class=\"card-cell-label\">Maydon</span><code class=\"card-field-name\">model</code></th><td data-cell-label=\"Tur\" data-field-type><span class=\"card-cell-label\">Tur</span><code>string</code></td><td data-cell-label=\"Talab\"><span class=\"card-cell-label\">Talab</span>Majburiy</td><td data-cell-label=\"Qiymatlar va cheklovlar\"><span class=\"card-cell-label\">Qiymatlar va cheklovlar</span><div>nvidia/llama-nemotron-rerank-vl-1b-v2:free</div></td><td data-cell-label=\"Standart\" data-default=\"unspecified\"><span class=\"card-cell-label\">Standart</span>—</td></tr><tr><th data-cell-label=\"Maydon\" scope=\"row\"><span class=\"card-cell-label\">Maydon</span><code class=\"card-field-name\">query</code></th><td data-cell-label=\"Tur\" data-field-type><span class=\"card-cell-label\">Tur</span><code>string</code></td><td data-cell-label=\"Talab\"><span class=\"card-cell-label\">Talab</span>Majburiy</td><td data-cell-label=\"Qiymatlar va cheklovlar\"><span class=\"card-cell-label\">Qiymatlar va cheklovlar</span></td><td data-cell-label=\"Standart\" data-default=\"unspecified\"><span class=\"card-cell-label\">Standart</span>—</td></tr><tr><th data-cell-label=\"Maydon\" scope=\"row\"><span class=\"card-cell-label\">Maydon</span><code class=\"card-field-name\">documents</code></th><td data-cell-label=\"Tur\" data-field-type><span class=\"card-cell-label\">Tur</span><code>array</code></td><td data-cell-label=\"Talab\"><span class=\"card-cell-label\">Talab</span>Majburiy</td><td data-cell-label=\"Qiymatlar va cheklovlar\"><span class=\"card-cell-label\">Qiymatlar va cheklovlar</span></td><td data-cell-label=\"Standart\" data-default=\"unspecified\"><span class=\"card-cell-label\">Standart</span>—</td></tr><tr><th data-cell-label=\"Maydon\" scope=\"row\"><span class=\"card-cell-label\">Maydon</span><code class=\"card-field-name\">top_n</code></th><td data-cell-label=\"Tur\" data-field-type><span class=\"card-cell-label\">Tur</span><code>integer</code></td><td data-cell-label=\"Talab\"><span class=\"card-cell-label\">Talab</span>Ixtiyoriy</td><td data-cell-label=\"Qiymatlar va cheklovlar\"><span class=\"card-cell-label\">Qiymatlar va cheklovlar</span><div>Eng kam: 1</div></td><td data-cell-label=\"Standart\" data-default=\"unspecified\"><span class=\"card-cell-label\">Standart</span>—</td></tr></tbody></table></div><details class=\"note-s\" data-method-contract><summary>Usul parametrlari va hayot sikli</summary><div class=\"tw\" data-card-table=\"contract\"><table><thead><tr><th>Parametr</th><th>Parametr talablari</th></tr></thead><tbody><tr><th data-cell-label=\"Parametr\" scope=\"row\"><span class=\"card-cell-label\">Parametr</span><code>content_type</code></th><td data-cell-label=\"Parametr talablari\"><span class=\"card-cell-label\">Parametr talablari</span>application/json</td></tr><tr><th data-cell-label=\"Parametr\" scope=\"row\"><span class=\"card-cell-label\">Parametr</span><code>required</code></th><td data-cell-label=\"Parametr talablari\"><span class=\"card-cell-label\">Parametr talablari</span>model, query, documents</td></tr><tr><th data-cell-label=\"Parametr\" scope=\"row\"><span class=\"card-cell-label\">Parametr</span><code>optional</code></th><td data-cell-label=\"Parametr talablari\"><span class=\"card-cell-label\">Parametr talablari</span>top_n</td></tr><tr><th data-cell-label=\"Parametr\" scope=\"row\"><span class=\"card-cell-label\">Parametr</span><code>material_types</code></th><td data-cell-label=\"Parametr talablari\"><span class=\"card-cell-label\">Parametr talablari</span>text</td></tr><tr><th data-cell-label=\"Parametr\" scope=\"row\"><span class=\"card-cell-label\">Parametr</span><code>conditions</code></th><td data-cell-label=\"Parametr talablari\"><span class=\"card-cell-label\">Parametr talablari</span></td></tr></tbody></table></div><p>Hayot sikli: <code>synchronous_json</code></p></details></details></section><section class=\"card-section\" data-card-section=\"pricing\"><h3 tabindex=\"-1\">Tariflar</h3><div data-native-semantic-method=\"v1\" data-tariff-reference-only><p class=\"note-s\" data-rate-support-note>Tarif ma’lumotlari so‘rov imkoniyatlarini qo‘shmaydi. Qo‘llab-quvvatlanadigan parametrlar tanlangan usulda ko‘rsatilgan.</p><dl data-price-conditions><dt>Tezkor rejim</dt><dd>Ko‘rsatilmagan <span class=\"note-s\">Tezkor rejim tanlanganda</span></dd><dt>Flex rejimi</dt><dd>Ko‘rsatilmagan <span class=\"note-s\">flex rejimi tanlanganda</span></dd><dt>Maksimal fikrlash darajasi</dt><dd>Ko‘rsatilmagan <span class=\"note-s\">Maksimal fikrlash darajasi uchun standart (default) tuzatish qo‘llanganda</span></dd></dl></div><div data-declared-tariff-pricing><h4>Ailoot tariflari</h4><h4>Sozlamalar bo‘yicha narxlar</h4><p class=\"note-s\">Har bir to‘lovni ko‘rsatilgan shartlarga moslang. Har bir muqobil sozlamalar to‘plami uchun bitta tarifdan foydalaning.</p><div class=\"tw\" data-pricing-profiles><table><thead><tr><th>Sozlama</th><th>Tariflar jadvali</th><th>Hisoblanadigan miqdor</th><th>To‘lov</th></tr></thead><tbody><tr><th data-cell-label=\"Sozlama\" scope=\"row\"><span class=\"card-cell-label\">Sozlama</span>Tokenlar uchun bazaviy tariflar</th><td data-cell-label=\"Tariflar jadvali\"><span class=\"card-cell-label\">Tariflar jadvali</span>Asosiy tarif</td><td data-cell-label=\"Hisoblanadigan miqdor\"><span class=\"card-cell-label\">Hisoblanadigan miqdor</span>—</td><td data-cell-label=\"To‘lov\"><span class=\"card-cell-label\">To‘lov</span><div><span>Kirish · Kirish tokenlari</span> <b>—</b> <span class=\"price-unit\">/ 1K token</span></div><div><span>Chiqish · Chiqish tokenlari</span> <b>—</b> <span class=\"price-unit\">/ 1K token</span></div><div><span>Kirish · Keshdan o‘qish</span> <b>—</b> <span class=\"price-unit\">/ 1K token</span></div><div><span>Kirish · Keshga yozish</span> <b>—</b> <span class=\"price-unit\">/ 1K token</span></div><div><span>Kirish · Keshga yozish, 1 soat</span> <b>—</b> <span class=\"price-unit\">/ 1K token</span></div></td></tr><tr><th data-cell-label=\"Sozlama\" scope=\"row\"><span class=\"card-cell-label\">Sozlama</span>Har bir so‘rov uchun</th><td data-cell-label=\"Tariflar jadvali\"><span class=\"card-cell-label\">Tariflar jadvali</span>—</td><td data-cell-label=\"Hisoblanadigan miqdor\"><span class=\"card-cell-label\">Hisoblanadigan miqdor</span>bitta so‘rov</td><td data-cell-label=\"To‘lov\"><span class=\"card-cell-label\">To‘lov</span><div><span>Kirish</span> <b>$0</b> <span class=\"price-unit\">har bir so‘rov uchun</span></div></td></tr></tbody></table></div></div><p class=\"note-s\">Ailoot so‘rovdan oldin taxminiy summani band qiladi. Natijadan keyin o‘lchangan sarf asosidagi yakuniy to‘lovni yechadi. Oqimli javob bo‘yicha yakuniy hisob-kitob yakuniy sarf yozuviga asoslanadi. <a href=\"/docs/uz/billing/reserve/\">Summani band qilish va to‘lovni hisoblash tartibi →</a></p></section><section class=\"card-section\" data-card-section=\"examples\"><h3 tabindex=\"-1\">So‘rov namunalari</h3><h4>Ailoot Ultra · Rerank</h4><div class=\"code-group\"><div class=\"cg-bar\"><div class=\"cg-tabs\" role=\"tablist\" aria-label=\"Kod variantlari\"><button class=\"cg-tab\" id=\"model-code-32-tab-0\" role=\"tab\" type=\"button\" aria-controls=\"model-code-32-panel-0\" aria-selected=\"true\" tabindex=\"0\">curl · Bir marta yarating va natijani to‘liq saqlang</button></div><div class=\"cg-tools\"><button class=\"cg-btn cg-copy\" type=\"button\" aria-label=\"Kodni nusxalash\"><svg class=\"cp\" viewBox=\"0 0 16 16\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"1.4\"><rect x=\"5.25\" y=\"5.25\" width=\"8.5\" height=\"8.5\" rx=\"1.75\"/><path d=\"M10.75 5.25V3.5a1.25 1.25 0 0 0-1.25-1.25H3.5A1.25 1.25 0 0 0 2.25 3.5v6a1.25 1.25 0 0 0 1.25 1.25h1.75\"/></svg><svg class=\"ok\" viewBox=\"0 0 16 16\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"1.4\"><path d=\"m3 8.5 3.25 3.25L13 5\"/></svg></button></div></div><div class=\"cg-body\"><div class=\"cg-pane\" id=\"model-code-32-panel-0\" role=\"tabpanel\" aria-labelledby=\"model-code-32-tab-0\"><pre data-lang=\"bash\"><code>set -eu\n: &quot;${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\">Natijalarni olish va saqlash</h3><h4>Ailoot Ultra · Rerank</h4><p class=\"note-s\">JSON</p><div class=\"card-result-process\" data-all-results><h5>Barcha tayyor natijalarni saqlash</h5><p class=\"note-s\">Qaytarilgan har bir to‘liq javob, fayl va kontent qismini saqlang.</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>Asl javobni tekshirish kerak bo‘lsa</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>Javob maydonlari</summary><div class=\"tw\" data-card-table=\"output\"><table><thead><tr><th>Maydon</th><th>Tur</th></tr></thead><tbody><tr><th data-cell-label=\"Maydon\" scope=\"row\"><span class=\"card-cell-label\">Maydon</span><code class=\"card-field-name\">results</code></th><td data-cell-label=\"Tur\" data-field-type><span class=\"card-cell-label\">Tur</span>array</td></tr></tbody></table></div></details></section><section class=\"card-section\" data-card-section=\"aliases\"><h3 tabindex=\"-1\">Taxalluslar</h3><h4>Model taxalluslari</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>Usul yo‘llari taxalluslari</h4><p class=\"note-s\">Yuqorida ko‘rsatilgan usul yo‘llaridan foydalaning.</p><h4>Chaqirish uchun tegishli ID lar</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,
            "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",
            "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"
          }
        ]
      }
    }
  ],
  "model_id": "nvidia/llama-nemotron-rerank-vl-1b-v2:free",
  "nativeProvenance": {
    "input_facts_canonical_sha256": "7427ab6824df8b506a42e39736a1881a2a51351c554abc0aabb2e7a0017f9297",
    "input_html_sha256": "15251a4dacca6554b10aef4465ece4981bee3cc12c271a57dc81e76ec14f8ba5",
    "private_audit_sha256": "959035064ceb706b17d94f3b270acd0332cbe3e4f38360dac96acb354408aefb",
    "role": "historical-normalized-input-audit-hashes",
    "schema": "ailoot-native-model-provenance-v2"
  },
  "page": {
    "canonical": "https://ailoot.ai/models/uz/nvidia-llama-nemotron-rerank-vl-1b-v2-u003a-free/",
    "description": "Llama Nemotron Rerank VL 1B V2 — NVIDIA kompaniyasining topilgan materialni so‘rovga mosligi bo‘yicha tartiblaydigan kross-enkoder qayta tartiblash modeli. So‘rov va nomzod matn, tasvir yoki aralash hujjatlarni yuboring, so‘ng qidiruv natijalari yoki topilgan ma’lumotlar bilan boyitilgan javob uchun parchalarni tanlashda qaytarilgan ballar va dastlabki indekslardan foydalaning.",
    "locale": "uz",
    "md_url": "https://ailoot.ai/models/uz/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/uz/nvidia-llama-nemotron-rerank-vl-1b-v2-u003a-free/"
  },
  "rawModel": {
    "about": "Llama Nemotron Rerank VL 1B V2 nomzod matn va hujjat tasvirlarining matnli so‘rovga mosligini baholaydi, jumladan diagrammalar, jadvallar va aralash media sahifalarini. NVIDIA uni 1.7B parametrli kross-enkoder model deb tavsiflaydi. Ma’lumot topish jarayonida avval boshlang‘ich qidiruvni bajaring, keyin tanlangan nomzodlarni qayta tartiblash modeliga yuboring. Foydali natija — moslik ballari bilan qayta tartiblangan o‘sha nomzodlar to‘plami; ilova undan javob uchun kontekst tanlash yoki qidiruv natijalari sahifasini tartiblashda foydalanishi mumkin.\n\napplication/json tanasi bilan POST /v1/rerank dan foydalaning. model ni \"nvidia/llama-nemotron-rerank-vl-1b-v2:free\", query ni haqiqiy qidiruv savoli, documents ni esa bo‘sh bo‘lmagan massiv qilib belgilang. Har bir nomzod matn satri yoki text va/yoki image bo‘lgan obyekt bo‘lishi mumkin; tuzilgan obyekt shu maydonlardan kamida bittasini berishi kerak. text satrdir. image masofaviy HTTP/HTTPS URL manzili yoki data:image/ bilan boshlanadigan base64 ma’lumot URI qiymatidir. Aralash nomzod ikkala maydonni ham beradi. Qaytarilgan indekslarni saqlangan hujjat ID qiymatlaringiz bilan moslash uchun kirish massivining tartibini saqlang. top_n kamida 1 bo‘lgan ixtiyoriy butun son bo‘lib, eng yuqori o‘rinli hujjatlarning qaytariladigan sonini so‘raydi.\n\nMasalan, yordam markazi ilovasi yetkazish, qaytarish va akkauntga kirish haqidagi parchalarni topishi, keyin ularni mijozning yetkazish savoliga nisbatan qayta tartiblashi mumkin. Fayl nomlari yoki saqlangan manbaga aloqasiz qidiruv tizimi parchalarini emas, haqiqiy parcha matnini bering. Tanlangan dalilni keyin keltirish yoki ochish mumkin bo‘lishi uchun har bir parchani ilovadagi o‘z manba identifikatoriga bog‘liq holda saqlang. Skanerlangan hujjat, diagramma, jadval yoki infografika uchun uning haqiqiy tasvirini hujjat obyektida bering va mazmunni aniqlashga yordam bersa, matn qo‘shing.\n\nModel sahifasi har bir so‘rov va hujjat uchun 10 240 token chegarasini hujjatlashtiradi. Nomzodlar ro‘yxatini tayyorlashdan oldin uzunroq manba materialini chegaralangan parchalarga ajrating. Ma’noni o‘zgartirsa, sarlavha yoki mahsulot nomini ham qo‘shib, har bir parcha bilan foydali atrof kontekstini saqlang. Hujjatlashtirilgan so‘rov siz bergan nomzodlardan boshlanadi; u sizning nomingizdan hujjatlar to‘plamini qidirmaydi.\n\nQayta tartiblash sinxron JSON natija qaytaradi. Har bir results elementini, jumladan dastlabki index, relevance_score va text va/yoki image tashishi mumkin bo‘lgan qaytarilgan document obyektini o‘qing hamda qaytarilgan har qanday usage va javob identifikatorlarini saqlang. Tartiblangan natijani kirish nomzodiga qayta moslash uchun index dan foydalaning. Moslik ballini mustaqil tekshirilgan faktik javob sifatida emas, shu so‘rov uchun tartiblash signali sifatida qabul qiling. Keyingi bosqich uchun bir nechta parcha tanlansa, to‘liq natijani saqlang.\n\nUshbu bepul nashr uchun ommaviy yoki sun’iy nomzod materialini tayyorlang; uning hujjatlashtirilgan foydalanish shartlari maxfiy axborot va shaxsiy ma’lumotlarni istisno qiladi. So‘rov to‘liq natijasiz tugasa, o‘sha urinishni tekshirish davomida dastlabki javob va so‘rov identifikatorini saqlang. Hujjatlashtirilgan qayta tartiblash jarayoni natijani bevosita qaytaradi va alohida topshiriq holatini so‘rash yoki bekor qilish jarayonini bermaydi.",
    "alias_of": null,
    "aliases": [],
    "author": "NVIDIA",
    "ctx": 10240,
    "formats": [
      "rerank"
    ],
    "id": "nvidia/llama-nemotron-rerank-vl-1b-v2:free",
    "input": [
      "text"
    ],
    "kind": "text",
    "max_out": null,
    "methods": [
      {
        "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,
            "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",
            "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"
          }
        ]
      }
    ],
    "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": {
      "in": "0",
      "in_label": "per request",
      "out": null,
      "out_label": null,
      "sort_in": null,
      "sort_out": null,
      "varies": false
    },
    "short": "Llama Nemotron Rerank VL 1B V2 — NVIDIA kompaniyasining topilgan materialni so‘rovga mosligi bo‘yicha tartiblaydigan kross-enkoder qayta tartiblash modeli. So‘rov va nomzod matn, tasvir yoki aralash hujjatlarni yuboring, so‘ng qidiruv natijalari yoki topilgan ma’lumotlar bilan boyitilgan javob uchun parchalarni tanlashda qaytarilgan ballar va dastlabki indekslardan foydalaning."
  },
  "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": "Llama Nemotron Rerank VL 1B V2 — NVIDIA kompaniyasining topilgan materialni so‘rovga mosligi bo‘yicha tartiblaydigan kross-enkoder qayta tartiblash modeli. So‘rov va nomzod matn, tasvir yoki aralash hujjatlarni yuboring, so‘ng qidiruv natijalari yoki topilgan ma’lumotlar bilan boyitilgan javob uchun parchalarni tanlashda qaytarilgan ballar va dastlabki indekslardan foydalaning.",
  "source": {
    "audit_sha256": "2e00086bcbfc28e64d0cebe97aa47c17d8d5618963027f8ffb9dc6123d7d25b1",
    "bridge_map_sha256": "1125275768b9636fc8461bc7da5061239a81ddfe508e2557843ca42c58ab0036",
    "raw_model_json_sha256": "d96d122cafd4647a17344bbb06e6250915e58905ba551b62170d44478512bbab",
    "renderer_sha256": "aa8a0fca1bd770c042b64987512b6187fca2067aea3ddc877f68b163d80e7df6"
  },
  "sourceRevision": "026e7d453a7cfafe0f0c0ef36c0803800ce13b008f732b7a7a6a7b6f7e2bc0fb"
}