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  "aboutHtml": "<p>NVIDIA Nemotron 3.5 Lightning adalah model bahasa untuk penalaran, percakapan, dan alur kerja agen khusus. Model ini memiliki total 30B parameter dengan 3B aktif, menggunakan arsitektur hibrida yang menyelingi lapisan Mamba-2, mixture-of-experts, dan perhatian. Lapisan Multi-Token Prediction menambahkan sinyal pelatihan untuk token mendatang dan mendukung resep generasi model yang dioptimalkan. Model ini memproses teks dan menghasilkan teks, termasuk penjelasan, kode, serta jawaban yang berlandaskan bahan yang diberikan.</p><p>Produsennya menjelaskan aplikasi dalam chatbot, retrieval-augmented generation, mengikuti instruksi, dan agen. Untuk jawaban basis pengetahuan, berikan pertanyaan serta bagian yang relevan dengan label sumber yang stabil. Mintalah model menjawab dari bagian tersebut, mengidentifikasi bagian yang mendukung setiap klaim penting, dan menyatakan hal yang masih belum diketahui. Misalnya: “Dengan menggunakan artikel dukungan ini, jelaskan perbedaan antara kedua metode instalasi dan kembalikan prasyarat, langkah, serta pemeriksaan untuk masing-masing.” Pertahankan prasyarat yang tidak tersedia tetap terlihat, alih-alih mengundang model untuk mengarangnya.</p><p>Untuk pekerjaan pemrograman, berikan kode yang relevan, perilaku yang diharapkan, dan kegagalan yang diamati. Permintaan praktis meminta revisi terfokus serta penjelasan kasus yang terdampak. Jika agen yang terhubung dengan alat menjalankan pemeriksaan, kembalikan keluaran aktualnya sebelum meminta perubahan berikutnya. Pelatihan model mencakup kode, penggunaan alat dengan beberapa langkah, dan tugas keluaran terstruktur, tetapi artefak yang selesai tetap harus sesuai dengan persyaratan asli. Mintalah kode yang direvisi, alasan setiap perubahan penting, serta pengamatan yang diperlukan untuk membuktikan bahwa masalah telah terselesaikan.</p><p>Pembuatnya mendokumentasikan proses berpikir yang diaktifkan secara bawaan serta mode jawaban langsung dengan proses berpikir dinonaktifkan melalui templat percakapan. Mode penalaran berguna untuk tugas dengan beberapa kondisi yang saling bergantung; jawaban langsung dapat cocok untuk transformasi atau ekstraksi sederhana. Produsennya merekomendasikan temperature 1.0 dan top-p 0.95 dalam contoh kliennya. Perlakukan nilai tersebut sebagai pengaturan resep pembuatnya dan pilih struktur respons akhir secara jelas, seperti penjelasan singkat, tabel perbandingan, atau jawaban yang diikuti bukti pendukung.</p><p>Model ini mendukung konteks hingga 1M token. Resep deployment BF16 yang dipublikasikan juga membedakan kemampuan model tersebut dari konfigurasi yang menggunakan jendela 256K karena keterbatasan memori. Siapkan bahan panjang sesuai jendela kerja yang berlaku, dengan mempertahankan struktur dokumen dan menyisakan ruang bagi respons. Konteks panjang paling berguna ketika prompt menentukan hubungan yang perlu ditemukan: pertentangan antar dokumen, dependensi lintas berkas sumber, atau bukti yang mendukung suatu kesimpulan. Ini bukan alasan untuk menyertakan riwayat yang tidak terkait atau berasumsi bahwa jawaban akhir dapat memenuhi seluruh jendela.</p><p>Bahasa Inggris dan bahasa pemrograman merupakan fokus utama, dengan bahasa Spanyol, Prancis, Jerman, Italia, dan Jepang juga tercantum. Nyatakan bahasa keluaran yang diperlukan serta pertahankan nama, pengenal, dan istilah sumber yang dikutip ketika ejaannya penting. Untuk pekerjaan dokumen multibahasa, tentukan apakah bahan perlu diterjemahkan, diringkas, atau dibandingkan; permintaan tersebut menghasilkan artefak yang berbeda. Mintalah istilah yang tidak pasti ditandai agar terjemahan yang lancar tidak diam-diam mengubah makna teknis.</p><p>NVIDIA memublikasikan rilis rujukan BF16 terutama untuk penyesuaian dan penelitian presisi penuh, serta rilis NVFP4 terpisah dengan resep inferensi yang dioptimalkan. Perbedaan ini penting ketika membandingkan panduan deployment: konfigurasi perangkat keras atau hasil throughput dari satu rilis tidak otomatis menjelaskan rilis lain. Nama model mengidentifikasi keluarga Lightning, sedangkan checkpoint yang tepat dan konfigurasi layanan menentukan resepnya. Pisahkan kemampuan tingkat model dari asumsi kinerja dan memori khusus resep.</p><p>Untuk pekerjaan berbasis alat, berikan deskripsi fungsi yang jelas dan kembalikan hasil aktual dari setiap langkah yang dijalankan. Operasi yang diusulkan menjadi bukti yang dapat digunakan hanya setelah aplikasi yang menaunginya melaksanakan operasi tersebut dan mencatat apa yang terjadi. Mintalah jawaban akhir membedakan pengamatan sumber, kesimpulan turunan, dan pemeriksaan yang belum selesai. Ketika perhitungan, perintah, atau bagian yang diambil bertentangan dengan hasil yang direncanakan, gunakan pertentangan itu untuk merevisi kesimpulan, alih-alih menghasilkan ringkasan rapi dari asumsi yang belum diverifikasi.</p>",
  "aboutText": "NVIDIA Nemotron 3.5 Lightning adalah model bahasa untuk penalaran, percakapan, dan alur kerja agen khusus. Model ini memiliki total 30B parameter dengan 3B aktif, menggunakan arsitektur hibrida yang menyelingi lapisan Mamba-2, mixture-of-experts, dan perhatian. Lapisan Multi-Token Prediction menambahkan sinyal pelatihan untuk token mendatang dan mendukung resep generasi model yang dioptimalkan. Model ini memproses teks dan menghasilkan teks, termasuk penjelasan, kode, serta jawaban yang berlandaskan bahan yang diberikan.\n\nProdusennya menjelaskan aplikasi dalam chatbot, retrieval-augmented generation, mengikuti instruksi, dan agen. Untuk jawaban basis pengetahuan, berikan pertanyaan serta bagian yang relevan dengan label sumber yang stabil. Mintalah model menjawab dari bagian tersebut, mengidentifikasi bagian yang mendukung setiap klaim penting, dan menyatakan hal yang masih belum diketahui. Misalnya: “Dengan menggunakan artikel dukungan ini, jelaskan perbedaan antara kedua metode instalasi dan kembalikan prasyarat, langkah, serta pemeriksaan untuk masing-masing.” Pertahankan prasyarat yang tidak tersedia tetap terlihat, alih-alih mengundang model untuk mengarangnya.\n\nUntuk pekerjaan pemrograman, berikan kode yang relevan, perilaku yang diharapkan, dan kegagalan yang diamati. Permintaan praktis meminta revisi terfokus serta penjelasan kasus yang terdampak. Jika agen yang terhubung dengan alat menjalankan pemeriksaan, kembalikan keluaran aktualnya sebelum meminta perubahan berikutnya. Pelatihan model mencakup kode, penggunaan alat dengan beberapa langkah, dan tugas keluaran terstruktur, tetapi artefak yang selesai tetap harus sesuai dengan persyaratan asli. Mintalah kode yang direvisi, alasan setiap perubahan penting, serta pengamatan yang diperlukan untuk membuktikan bahwa masalah telah terselesaikan.\n\nPembuatnya mendokumentasikan proses berpikir yang diaktifkan secara bawaan serta mode jawaban langsung dengan proses berpikir dinonaktifkan melalui templat percakapan. Mode penalaran berguna untuk tugas dengan beberapa kondisi yang saling bergantung; jawaban langsung dapat cocok untuk transformasi atau ekstraksi sederhana. Produsennya merekomendasikan temperature 1.0 dan top-p 0.95 dalam contoh kliennya. Perlakukan nilai tersebut sebagai pengaturan resep pembuatnya dan pilih struktur respons akhir secara jelas, seperti penjelasan singkat, tabel perbandingan, atau jawaban yang diikuti bukti pendukung.\n\nModel ini mendukung konteks hingga 1M token. Resep deployment BF16 yang dipublikasikan juga membedakan kemampuan model tersebut dari konfigurasi yang menggunakan jendela 256K karena keterbatasan memori. Siapkan bahan panjang sesuai jendela kerja yang berlaku, dengan mempertahankan struktur dokumen dan menyisakan ruang bagi respons. Konteks panjang paling berguna ketika prompt menentukan hubungan yang perlu ditemukan: pertentangan antar dokumen, dependensi lintas berkas sumber, atau bukti yang mendukung suatu kesimpulan. Ini bukan alasan untuk menyertakan riwayat yang tidak terkait atau berasumsi bahwa jawaban akhir dapat memenuhi seluruh jendela.\n\nBahasa Inggris dan bahasa pemrograman merupakan fokus utama, dengan bahasa Spanyol, Prancis, Jerman, Italia, dan Jepang juga tercantum. Nyatakan bahasa keluaran yang diperlukan serta pertahankan nama, pengenal, dan istilah sumber yang dikutip ketika ejaannya penting. Untuk pekerjaan dokumen multibahasa, tentukan apakah bahan perlu diterjemahkan, diringkas, atau dibandingkan; permintaan tersebut menghasilkan artefak yang berbeda. Mintalah istilah yang tidak pasti ditandai agar terjemahan yang lancar tidak diam-diam mengubah makna teknis.\n\nNVIDIA memublikasikan rilis rujukan BF16 terutama untuk penyesuaian dan penelitian presisi penuh, serta rilis NVFP4 terpisah dengan resep inferensi yang dioptimalkan. Perbedaan ini penting ketika membandingkan panduan deployment: konfigurasi perangkat keras atau hasil throughput dari satu rilis tidak otomatis menjelaskan rilis lain. Nama model mengidentifikasi keluarga Lightning, sedangkan checkpoint yang tepat dan konfigurasi layanan menentukan resepnya. Pisahkan kemampuan tingkat model dari asumsi kinerja dan memori khusus resep.\n\nUntuk pekerjaan berbasis alat, berikan deskripsi fungsi yang jelas dan kembalikan hasil aktual dari setiap langkah yang dijalankan. Operasi yang diusulkan menjadi bukti yang dapat digunakan hanya setelah aplikasi yang menaunginya melaksanakan operasi tersebut dan mencatat apa yang terjadi. Mintalah jawaban akhir membedakan pengamatan sumber, kesimpulan turunan, dan pemeriksaan yang belum selesai. Ketika perhitungan, perintah, atau bagian yang diambil bertentangan dengan hasil yang direncanakan, gunakan pertentangan itu untuk merevisi kesimpulan, alih-alih menghasilkan ringkasan rapi dari asumsi yang belum diverifikasi.",
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      "html": "<div class=\"sheet-head\"><span class=\"mav\" aria-hidden=\"true\">NV</span><h2 id=\"sheet-title\">NVIDIA: Nemotron 3.5 Lightning (free)</h2><button class=\"icon-btn\" type=\"button\" data-close-sheet aria-label=\"Tutup\">×</button></div><div class=\"idline\"><span>NVIDIA /</span><code>nvidia/nemotron-3.5-lightning:free</code><button type=\"button\" id=\"copy-id\">Salin ID</button></div><nav class=\"card-jump-nav\" aria-label=\"Bagian kartu model\"><button type=\"button\" data-card-jump=\"overview\">Mulai</button><button type=\"button\" data-card-jump=\"methods\">Masukan &amp; metode</button><button type=\"button\" data-card-jump=\"pricing\">Paket</button><button type=\"button\" data-card-jump=\"examples\">Contoh</button><button type=\"button\" data-card-jump=\"results\">Hasil</button><button type=\"button\" data-card-jump=\"aliases\">Alias</button></nav><div class=\"card-method-tabs\" role=\"tablist\" aria-label=\"Metode API\"><button type=\"button\" role=\"tab\" tabindex=\"0\" aria-controls=\"card-method-content\" aria-selected=\"true\" id=\"card-method-tab-0\" data-card-method=\"Ultra|chat|/v1/chat/completions|nvidia%2Fnemotron-3.5-lightning%3Afree\">Chat</button><button type=\"button\" role=\"tab\" tabindex=\"-1\" aria-controls=\"card-method-content\" aria-selected=\"false\" id=\"card-method-tab-1\" data-card-method=\"Ultra|messages|/v1/messages|nvidia%2Fnemotron-3.5-lightning%3Afree\">Messages</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\">Mulai</h3><p class=\"mdesc-full\">NVIDIA Nemotron 3.5 Lightning adalah model penalaran teks dan percakapan dengan total 30B parameter dan 3B parameter aktif. Arsitektur hibrida Mamba–MoE-nya mendukung analisis berkonteks panjang, pemrograman, dan alur kerja berbasis alat, dengan mode berpikir atau jawaban langsung yang didokumentasikan dalam templat percakapan pembuatnya.</p><dl class=\"card-io\" data-card-io><div><dt>Masukan yang diterima</dt><dd>Teks</dd></div><div><dt>Hasil</dt><dd>Teks</dd></div></dl><details class=\"card-about\"><summary>Tentang model</summary><p class=\"note-s\" data-model-method-boundary>Deskripsi ini mencakup kemampuan model. Masukan, keluaran, dan opsi yang tersedia di Ailoot tercantum di bawah untuk metode yang dipilih.</p><div class=\"mabout\" id=\"m-about\"><p>NVIDIA Nemotron 3.5 Lightning adalah model bahasa untuk penalaran, percakapan, dan alur kerja agen khusus. Model ini memiliki total 30B parameter dengan 3B aktif, menggunakan arsitektur hibrida yang menyelingi lapisan Mamba-2, mixture-of-experts, dan perhatian. Lapisan Multi-Token Prediction menambahkan sinyal pelatihan untuk token mendatang dan mendukung resep generasi model yang dioptimalkan. Model ini memproses teks dan menghasilkan teks, termasuk penjelasan, kode, serta jawaban yang berlandaskan bahan yang diberikan.</p><p>Produsennya menjelaskan aplikasi dalam chatbot, retrieval-augmented generation, mengikuti instruksi, dan agen. Untuk jawaban basis pengetahuan, berikan pertanyaan serta bagian yang relevan dengan label sumber yang stabil. Mintalah model menjawab dari bagian tersebut, mengidentifikasi bagian yang mendukung setiap klaim penting, dan menyatakan hal yang masih belum diketahui. Misalnya: “Dengan menggunakan artikel dukungan ini, jelaskan perbedaan antara kedua metode instalasi dan kembalikan prasyarat, langkah, serta pemeriksaan untuk masing-masing.” Pertahankan prasyarat yang tidak tersedia tetap terlihat, alih-alih mengundang model untuk mengarangnya.</p><p>Untuk pekerjaan pemrograman, berikan kode yang relevan, perilaku yang diharapkan, dan kegagalan yang diamati. Permintaan praktis meminta revisi terfokus serta penjelasan kasus yang terdampak. Jika agen yang terhubung dengan alat menjalankan pemeriksaan, kembalikan keluaran aktualnya sebelum meminta perubahan berikutnya. Pelatihan model mencakup kode, penggunaan alat dengan beberapa langkah, dan tugas keluaran terstruktur, tetapi artefak yang selesai tetap harus sesuai dengan persyaratan asli. Mintalah kode yang direvisi, alasan setiap perubahan penting, serta pengamatan yang diperlukan untuk membuktikan bahwa masalah telah terselesaikan.</p><p>Pembuatnya mendokumentasikan proses berpikir yang diaktifkan secara bawaan serta mode jawaban langsung dengan proses berpikir dinonaktifkan melalui templat percakapan. Mode penalaran berguna untuk tugas dengan beberapa kondisi yang saling bergantung; jawaban langsung dapat cocok untuk transformasi atau ekstraksi sederhana. Produsennya merekomendasikan temperature 1.0 dan top-p 0.95 dalam contoh kliennya. Perlakukan nilai tersebut sebagai pengaturan resep pembuatnya dan pilih struktur respons akhir secara jelas, seperti penjelasan singkat, tabel perbandingan, atau jawaban yang diikuti bukti pendukung.</p><p>Model ini mendukung konteks hingga 1M token. Resep deployment BF16 yang dipublikasikan juga membedakan kemampuan model tersebut dari konfigurasi yang menggunakan jendela 256K karena keterbatasan memori. Siapkan bahan panjang sesuai jendela kerja yang berlaku, dengan mempertahankan struktur dokumen dan menyisakan ruang bagi respons. Konteks panjang paling berguna ketika prompt menentukan hubungan yang perlu ditemukan: pertentangan antar dokumen, dependensi lintas berkas sumber, atau bukti yang mendukung suatu kesimpulan. Ini bukan alasan untuk menyertakan riwayat yang tidak terkait atau berasumsi bahwa jawaban akhir dapat memenuhi seluruh jendela.</p><p>Bahasa Inggris dan bahasa pemrograman merupakan fokus utama, dengan bahasa Spanyol, Prancis, Jerman, Italia, dan Jepang juga tercantum. Nyatakan bahasa keluaran yang diperlukan serta pertahankan nama, pengenal, dan istilah sumber yang dikutip ketika ejaannya penting. Untuk pekerjaan dokumen multibahasa, tentukan apakah bahan perlu diterjemahkan, diringkas, atau dibandingkan; permintaan tersebut menghasilkan artefak yang berbeda. Mintalah istilah yang tidak pasti ditandai agar terjemahan yang lancar tidak diam-diam mengubah makna teknis.</p><p>NVIDIA memublikasikan rilis rujukan BF16 terutama untuk penyesuaian dan penelitian presisi penuh, serta rilis NVFP4 terpisah dengan resep inferensi yang dioptimalkan. Perbedaan ini penting ketika membandingkan panduan deployment: konfigurasi perangkat keras atau hasil throughput dari satu rilis tidak otomatis menjelaskan rilis lain. Nama model mengidentifikasi keluarga Lightning, sedangkan checkpoint yang tepat dan konfigurasi layanan menentukan resepnya. Pisahkan kemampuan tingkat model dari asumsi kinerja dan memori khusus resep.</p><p>Untuk pekerjaan berbasis alat, berikan deskripsi fungsi yang jelas dan kembalikan hasil aktual dari setiap langkah yang dijalankan. Operasi yang diusulkan menjadi bukti yang dapat digunakan hanya setelah aplikasi yang menaunginya melaksanakan operasi tersebut dan mencatat apa yang terjadi. Mintalah jawaban akhir membedakan pengamatan sumber, kesimpulan turunan, dan pemeriksaan yang belum selesai. Ketika perhitungan, perintah, atau bagian yang diambil bertentangan dengan hasil yang direncanakan, gunakan pertentangan itu untuk merevisi kesimpulan, alih-alih menghasilkan ringkasan rapi dari asumsi yang belum diverifikasi.</p></div></details></section><section class=\"card-section\" data-card-section=\"methods\"><h3 tabindex=\"-1\">Tersedia di Ailoot · masukan &amp; metode</h3><details class=\"card-method\" open><summary><b>Ailoot Ultra · OpenAI Chat</b> <code>POST /v1/chat/completions</code></summary><dl class=\"method-capabilities\"><div><dt>Masukan</dt><dd><code>text</code></dd></div><div><dt>Keluaran</dt><dd><code>text</code></dd></div><div><dt>Konteks</dt><dd>1.000.000 tokens</dd></div><div><dt>Keluaran maksimum</dt><dd>65.536 tokens</dd></div><div><dt>Format keluaran</dt><dd>JSON</dd></div></dl><div class=\"tw\" data-card-parameters data-typed-parameters><table><thead><tr><th>Kolom</th><th>Jenis</th><th>Persyaratan</th><th>Nilai &amp; batasan</th><th>Bawaan</th></tr></thead><tbody><tr><th data-cell-label=\"Kolom\" scope=\"row\"><span class=\"card-cell-label\">Kolom</span><code class=\"card-field-name\">model</code></th><td data-cell-label=\"Jenis\" data-field-type><span class=\"card-cell-label\">Jenis</span><code>string</code></td><td data-cell-label=\"Persyaratan\"><span class=\"card-cell-label\">Persyaratan</span>Wajib</td><td data-cell-label=\"Nilai &amp; batasan\"><span class=\"card-cell-label\">Nilai &amp; batasan</span><div>nvidia/nemotron-3.5-lightning:free</div></td><td data-cell-label=\"Bawaan\" data-default=\"unspecified\"><span class=\"card-cell-label\">Bawaan</span>—</td></tr><tr><th data-cell-label=\"Kolom\" scope=\"row\"><span class=\"card-cell-label\">Kolom</span><code class=\"card-field-name\">messages</code></th><td data-cell-label=\"Jenis\" data-field-type><span class=\"card-cell-label\">Jenis</span><code>array</code></td><td data-cell-label=\"Persyaratan\"><span class=\"card-cell-label\">Persyaratan</span>Wajib</td><td data-cell-label=\"Nilai &amp; batasan\"><span class=\"card-cell-label\">Nilai &amp; batasan</span></td><td data-cell-label=\"Bawaan\" data-default=\"unspecified\"><span class=\"card-cell-label\">Bawaan</span>—</td></tr><tr><th data-cell-label=\"Kolom\" scope=\"row\"><span class=\"card-cell-label\">Kolom</span><code class=\"card-field-name\">stream</code></th><td data-cell-label=\"Jenis\" data-field-type><span class=\"card-cell-label\">Jenis</span><code>boolean</code></td><td data-cell-label=\"Persyaratan\"><span class=\"card-cell-label\">Persyaratan</span>Opsional</td><td data-cell-label=\"Nilai &amp; batasan\"><span class=\"card-cell-label\">Nilai &amp; batasan</span><div>false</div></td><td data-cell-label=\"Bawaan\" data-default=\"known\"><span class=\"card-cell-label\">Bawaan</span>false</td></tr><tr><th data-cell-label=\"Kolom\" scope=\"row\"><span class=\"card-cell-label\">Kolom</span><code class=\"card-field-name\">max_tokens</code></th><td data-cell-label=\"Jenis\" data-field-type><span class=\"card-cell-label\">Jenis</span><code>integer</code></td><td data-cell-label=\"Persyaratan\"><span class=\"card-cell-label\">Persyaratan</span>Opsional</td><td data-cell-label=\"Nilai &amp; batasan\"><span class=\"card-cell-label\">Nilai &amp; batasan</span><div>Minimum: 1</div><div>Maksimum: 65.536</div></td><td data-cell-label=\"Bawaan\" data-default=\"unspecified\"><span class=\"card-cell-label\">Bawaan</span>—</td></tr><tr><th data-cell-label=\"Kolom\" scope=\"row\"><span class=\"card-cell-label\">Kolom</span><code class=\"card-field-name\">max_completion_tokens</code></th><td data-cell-label=\"Jenis\" data-field-type><span class=\"card-cell-label\">Jenis</span><code>integer</code></td><td data-cell-label=\"Persyaratan\"><span class=\"card-cell-label\">Persyaratan</span>Opsional</td><td data-cell-label=\"Nilai &amp; batasan\"><span class=\"card-cell-label\">Nilai &amp; batasan</span><div>Minimum: 1</div><div>Maksimum: 65.536</div></td><td data-cell-label=\"Bawaan\" data-default=\"unspecified\"><span class=\"card-cell-label\">Bawaan</span>—</td></tr><tr><th data-cell-label=\"Kolom\" scope=\"row\"><span class=\"card-cell-label\">Kolom</span><code class=\"card-field-name\">n</code></th><td data-cell-label=\"Jenis\" data-field-type><span class=\"card-cell-label\">Jenis</span><code>integer</code></td><td data-cell-label=\"Persyaratan\"><span class=\"card-cell-label\">Persyaratan</span>Opsional</td><td data-cell-label=\"Nilai &amp; batasan\"><span class=\"card-cell-label\">Nilai &amp; batasan</span><div>Minimum: 1</div><div>Maksimum: 128</div></td><td data-cell-label=\"Bawaan\" data-default=\"unspecified\"><span class=\"card-cell-label\">Bawaan</span>—</td></tr><tr><th data-cell-label=\"Kolom\" scope=\"row\"><span class=\"card-cell-label\">Kolom</span><code class=\"card-field-name\">temperature</code></th><td data-cell-label=\"Jenis\" data-field-type><span class=\"card-cell-label\">Jenis</span><code>number</code></td><td data-cell-label=\"Persyaratan\"><span class=\"card-cell-label\">Persyaratan</span>Opsional</td><td data-cell-label=\"Nilai &amp; batasan\"><span class=\"card-cell-label\">Nilai &amp; batasan</span></td><td data-cell-label=\"Bawaan\" data-default=\"unspecified\"><span class=\"card-cell-label\">Bawaan</span>—</td></tr><tr><th data-cell-label=\"Kolom\" scope=\"row\"><span class=\"card-cell-label\">Kolom</span><code class=\"card-field-name\">top_p</code></th><td data-cell-label=\"Jenis\" data-field-type><span class=\"card-cell-label\">Jenis</span><code>number</code></td><td data-cell-label=\"Persyaratan\"><span class=\"card-cell-label\">Persyaratan</span>Opsional</td><td data-cell-label=\"Nilai &amp; batasan\"><span class=\"card-cell-label\">Nilai &amp; batasan</span></td><td data-cell-label=\"Bawaan\" data-default=\"unspecified\"><span class=\"card-cell-label\">Bawaan</span>—</td></tr><tr><th data-cell-label=\"Kolom\" scope=\"row\"><span class=\"card-cell-label\">Kolom</span><code class=\"card-field-name\">seed</code></th><td data-cell-label=\"Jenis\" data-field-type><span class=\"card-cell-label\">Jenis</span><code>integer</code></td><td data-cell-label=\"Persyaratan\"><span class=\"card-cell-label\">Persyaratan</span>Opsional</td><td data-cell-label=\"Nilai &amp; batasan\"><span class=\"card-cell-label\">Nilai &amp; batasan</span></td><td data-cell-label=\"Bawaan\" data-default=\"unspecified\"><span class=\"card-cell-label\">Bawaan</span>—</td></tr><tr><th data-cell-label=\"Kolom\" scope=\"row\"><span class=\"card-cell-label\">Kolom</span><code class=\"card-field-name\">stop</code></th><td data-cell-label=\"Jenis\" data-field-type><span class=\"card-cell-label\">Jenis</span><code></code></td><td data-cell-label=\"Persyaratan\"><span class=\"card-cell-label\">Persyaratan</span>Opsional</td><td data-cell-label=\"Nilai &amp; batasan\"><span class=\"card-cell-label\">Nilai &amp; batasan</span></td><td data-cell-label=\"Bawaan\" data-default=\"unspecified\"><span class=\"card-cell-label\">Bawaan</span>—</td></tr><tr><th data-cell-label=\"Kolom\" scope=\"row\"><span class=\"card-cell-label\">Kolom</span><code class=\"card-field-name\">frequency_penalty</code></th><td data-cell-label=\"Jenis\" data-field-type><span class=\"card-cell-label\">Jenis</span><code>number</code></td><td data-cell-label=\"Persyaratan\"><span class=\"card-cell-label\">Persyaratan</span>Opsional</td><td data-cell-label=\"Nilai &amp; batasan\"><span class=\"card-cell-label\">Nilai &amp; batasan</span></td><td data-cell-label=\"Bawaan\" data-default=\"unspecified\"><span class=\"card-cell-label\">Bawaan</span>—</td></tr><tr><th data-cell-label=\"Kolom\" scope=\"row\"><span class=\"card-cell-label\">Kolom</span><code class=\"card-field-name\">presence_penalty</code></th><td data-cell-label=\"Jenis\" data-field-type><span class=\"card-cell-label\">Jenis</span><code>number</code></td><td data-cell-label=\"Persyaratan\"><span class=\"card-cell-label\">Persyaratan</span>Opsional</td><td data-cell-label=\"Nilai &amp; batasan\"><span class=\"card-cell-label\">Nilai &amp; batasan</span></td><td data-cell-label=\"Bawaan\" data-default=\"unspecified\"><span class=\"card-cell-label\">Bawaan</span>—</td></tr><tr><th data-cell-label=\"Kolom\" scope=\"row\"><span class=\"card-cell-label\">Kolom</span><code class=\"card-field-name\">user</code></th><td data-cell-label=\"Jenis\" data-field-type><span class=\"card-cell-label\">Jenis</span><code>string</code></td><td data-cell-label=\"Persyaratan\"><span class=\"card-cell-label\">Persyaratan</span>Opsional</td><td data-cell-label=\"Nilai &amp; batasan\"><span class=\"card-cell-label\">Nilai &amp; batasan</span></td><td data-cell-label=\"Bawaan\" data-default=\"unspecified\"><span class=\"card-cell-label\">Bawaan</span>—</td></tr></tbody></table></div><details class=\"note-s\" data-method-contract><summary>Parameter metode dan siklus hidup</summary><div class=\"tw\" data-card-table=\"contract\"><table><thead><tr><th>Parameter</th><th>Kontrak</th></tr></thead><tbody><tr><th data-cell-label=\"Parameter\" scope=\"row\"><span class=\"card-cell-label\">Parameter</span><code>content_type</code></th><td data-cell-label=\"Kontrak\"><span class=\"card-cell-label\">Kontrak</span>application/json</td></tr><tr><th data-cell-label=\"Parameter\" scope=\"row\"><span class=\"card-cell-label\">Parameter</span><code>required</code></th><td data-cell-label=\"Kontrak\"><span class=\"card-cell-label\">Kontrak</span>model, messages</td></tr><tr><th data-cell-label=\"Parameter\" scope=\"row\"><span class=\"card-cell-label\">Parameter</span><code>optional</code></th><td data-cell-label=\"Kontrak\"><span class=\"card-cell-label\">Kontrak</span>stream, max_tokens, max_completion_tokens, n, temperature, top_p, seed, stop, frequency_penalty, presence_penalty, user</td></tr><tr><th data-cell-label=\"Parameter\" scope=\"row\"><span class=\"card-cell-label\">Parameter</span><code>material_types</code></th><td data-cell-label=\"Kontrak\"><span class=\"card-cell-label\">Kontrak</span>text</td></tr><tr><th data-cell-label=\"Parameter\" scope=\"row\"><span class=\"card-cell-label\">Parameter</span><code>conditions</code></th><td data-cell-label=\"Kontrak\"><span class=\"card-cell-label\">Kontrak</span>Use literal text messages only. Cache controls, tools, image/audio/video content and streamed responses are unavailable for this method., The complete encoded JSON request must not exceed 1000000 bytes.</td></tr></tbody></table></div><p>Siklus hidup: <code>synchronous_json</code></p></details></details></section><section class=\"card-section\" data-card-section=\"pricing\"><h3 tabindex=\"-1\">Paket</h3><div data-native-semantic-method=\"v1\" data-tariff-reference-only><p class=\"note-s\" data-rate-support-note>Referensi tarif tidak menambah opsi permintaan. Parameter yang didukung tercantum pada metode yang dipilih.</p><dl data-price-conditions><dt>Mode Fast</dt><dd>Tarif standar <span class=\"note-s\">Saat mode fast dipilih</span></dd><dt>Mode Flex</dt><dd>Tarif standar <span class=\"note-s\">Saat mode flex dipilih</span></dd><dt>Upaya penalaran maksimum</dt><dd>Tarif standar <span class=\"note-s\">Saat upaya penalaran maksimum menggunakan penyesuaian default</span></dd><dt>Harga cache eksplisit</dt><dd>Tidak diaktifkan <span class=\"note-s\">Saat cache eksplisit diminta</span></dd><dt>Tarif nol khusus teks</dt><dd>Text input and output only. Cache, tools, media and streaming are unavailable. <span class=\"note-s\">Untuk masukan dan keluaran yang hanya berupa teks</span></dd></dl></div><div data-declared-tariff-pricing><h4>Tarif Ailoot</h4><h4>Harga menurut konfigurasi</h4><div class=\"tw\" data-pricing-profiles><table><thead><tr><th>Konfigurasi</th><th>Jadwal tarif</th><th>Biaya</th></tr></thead><tbody><tr><th data-cell-label=\"Konfigurasi\" scope=\"row\"><span class=\"card-cell-label\">Konfigurasi</span>Tarif dasar token</th><td data-cell-label=\"Jadwal tarif\"><span class=\"card-cell-label\">Jadwal tarif</span>Tarif dasar</td><td data-cell-label=\"Biaya\"><span class=\"card-cell-label\">Biaya</span><div><span>Masukan · Token masukan</span> <b>$0</b> <span class=\"price-unit\">/ 1K token</span></div><div><span>Keluaran · Token keluaran</span> <b>$0</b> <span class=\"price-unit\">/ 1K token</span></div><div><span>Masukan · Pembacaan cache</span> <b>—</b> <span class=\"price-unit\">/ 1K token</span></div><div><span>Masukan · Penulisan cache</span> <b>—</b> <span class=\"price-unit\">/ 1K token</span></div><div><span>Masukan · Penulisan cache, 1 jam</span> <b>—</b> <span class=\"price-unit\">/ 1K token</span></div></td></tr></tbody></table></div></div><p class=\"note-s\">Ailoot mencadangkan perkiraan dana sebelum permintaan. Setelah hasil diterima, tagihan akhir diselesaikan berdasarkan penggunaan yang terukur. Penyelesaian tagihan streaming menggunakan catatan penggunaan akhir. <a href=\"/docs/id/billing/reserve/\">Cara kerja cadangan dan penyelesaian tagihan →</a></p></section><section class=\"card-section\" data-card-section=\"examples\"><h3 tabindex=\"-1\">Contoh permintaan</h3><h4>Ailoot Ultra · OpenAI Chat</h4><div class=\"code-group\"><div class=\"cg-bar\"><div class=\"cg-tabs\" role=\"tablist\" aria-label=\"Pilihan kode\"><button class=\"cg-tab\" id=\"model-code-54-tab-0\" role=\"tab\" type=\"button\" aria-controls=\"model-code-54-panel-0\" aria-selected=\"true\" tabindex=\"0\">curl · buat sekali dan simpan hasil secara lengkap</button></div><div class=\"cg-tools\"><button class=\"cg-btn cg-copy\" type=\"button\" aria-label=\"Salin kode\"><svg class=\"cp\" viewBox=\"0 0 16 16\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"1.4\"><rect x=\"5.25\" y=\"5.25\" width=\"8.5\" height=\"8.5\" rx=\"1.75\"/><path d=\"M10.75 5.25V3.5a1.25 1.25 0 0 0-1.25-1.25H3.5A1.25 1.25 0 0 0 2.25 3.5v6a1.25 1.25 0 0 0 1.25 1.25h1.75\"/></svg><svg class=\"ok\" viewBox=\"0 0 16 16\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"1.4\"><path d=\"m3 8.5 3.25 3.25L13 5\"/></svg></button></div></div><div class=\"cg-body\"><div class=\"cg-pane\" id=\"model-code-54-panel-0\" role=\"tabpanel\" aria-labelledby=\"model-code-54-tab-0\"><pre data-lang=\"bash\"><code>set -eu\n: &quot;${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;model&quot;: &quot;nvidia/nemotron-3.5-lightning:free&quot;, &quot;messages&quot;: [{&quot;role&quot;: &quot;user&quot;, &quot;content&quot;: &quot;Summarize the supplied text in three concise points.&quot;}], &quot;stream&quot;: false}&#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/chat/completions \\\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\">Terima dan simpan hasil</h3><h4>Ailoot Ultra · OpenAI Chat</h4><p class=\"note-s\">JSON</p><div class=\"card-result-process\" data-all-results><h5>Simpan semua hasil yang selesai</h5><p class=\"note-s\">Simpan setiap respons lengkap, berkas, dan bagian konten yang dikembalikan.</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>Jika respons asli perlu diperiksa</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></section><section class=\"card-section\" data-card-section=\"aliases\"><h3 tabindex=\"-1\">Alias</h3><h4>Alias model</h4><p class=\"note-s\"><span data-model-alias-route=\"Ultra\"><b>Ailoot Ultra</b> <a href=\"#m=nvidia%2Fnemotron-3.5-lightning%3Afree&amp;route=Ultra&amp;caller=nvidia%2Fnemotron-3.5-lightning%3Afree&amp;fmt=chat\"><code>nvidia/nemotron-3.5-lightning:free</code></a></span></p><h4>Alias jalur metode</h4><p class=\"note-s\">Gunakan jalur metode yang ditampilkan di atas.</p><h4>ID pemanggil terkait</h4><p class=\"note-s\"><a href=\"#m=nvidia%2Fnemotron-3.5-lightning%3Afree&amp;route=Ultra&amp;caller=nvidia%2Fnemotron-3.5-lightning%3Afree&amp;fmt=chat\"><code>nvidia/nemotron-3.5-lightning:free</code></a></p></section></div>",
      "method_identity": {
        "effective_request_model_id": "nvidia/nemotron-3.5-lightning:free",
        "fmt": "chat",
        "http": "POST",
        "path": "/v1/chat/completions",
        "request_model_id": "nvidia/nemotron-3.5-lightning:free",
        "route_label": "Ultra"
      },
      "method_key": "Ultra|chat|/v1/chat/completions|nvidia%2Fnemotron-3.5-lightning%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": {
              "messages": [
                {
                  "content": "Summarize the supplied text in three concise points.",
                  "role": "user"
                }
              ],
              "model": "nvidia/nemotron-3.5-lightning:free",
              "stream": false
            },
            "lifecycle": {
              "cancel_endpoint": null,
              "create": {
                "http": "POST",
                "path": "/v1/chat/completions"
              },
              "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": "text",
              "format": "JSON"
            },
            "parameters": [
              {
                "default_known": false,
                "enum": [
                  "nvidia/nemotron-3.5-lightning:free"
                ],
                "enum_known": true,
                "name": "model",
                "required": true,
                "type": "string"
              },
              {
                "default_known": false,
                "enum_known": false,
                "items": {
                  "additionalProperties": false,
                  "properties": {
                    "content": {
                      "type": "string"
                    },
                    "role": {
                      "enum": [
                        "user",
                        "assistant",
                        "system",
                        "developer"
                      ],
                      "type": "string"
                    }
                  },
                  "required": [
                    "role",
                    "content"
                  ],
                  "type": "object"
                },
                "minItems": 1,
                "name": "messages",
                "required": true,
                "type": "array"
              },
              {
                "default": false,
                "default_known": true,
                "enum": [
                  false
                ],
                "enum_known": true,
                "name": "stream",
                "required": false,
                "type": "boolean"
              },
              {
                "default_known": false,
                "enum_known": false,
                "maximum": 65536,
                "minimum": 1,
                "name": "max_tokens",
                "required": false,
                "type": "integer"
              },
              {
                "default_known": false,
                "enum_known": false,
                "maximum": 65536,
                "minimum": 1,
                "name": "max_completion_tokens",
                "required": false,
                "type": "integer"
              },
              {
                "default_known": false,
                "enum_known": false,
                "maximum": 128,
                "minimum": 1,
                "name": "n",
                "required": false,
                "type": "integer"
              },
              {
                "default_known": false,
                "enum_known": false,
                "name": "temperature",
                "required": false,
                "type": "number"
              },
              {
                "default_known": false,
                "enum_known": false,
                "name": "top_p",
                "required": false,
                "type": "number"
              },
              {
                "default_known": false,
                "enum_known": false,
                "name": "seed",
                "required": false,
                "type": "integer"
              },
              {
                "default_known": false,
                "enum_known": false,
                "name": "stop",
                "oneOf": [
                  {
                    "type": "string"
                  },
                  {
                    "items": {
                      "type": "string"
                    },
                    "type": "array"
                  }
                ],
                "required": false
              },
              {
                "default_known": false,
                "enum_known": false,
                "name": "frequency_penalty",
                "required": false,
                "type": "number"
              },
              {
                "default_known": false,
                "enum_known": false,
                "name": "presence_penalty",
                "required": false,
                "type": "number"
              },
              {
                "default_known": false,
                "enum_known": false,
                "name": "user",
                "required": false,
                "type": "string"
              }
            ],
            "request_schema": {
              "additionalProperties": false,
              "properties": {
                "frequency_penalty": {
                  "type": "number"
                },
                "max_completion_tokens": {
                  "maximum": 65536,
                  "minimum": 1,
                  "type": "integer"
                },
                "max_tokens": {
                  "maximum": 65536,
                  "minimum": 1,
                  "type": "integer"
                },
                "messages": {
                  "items": {
                    "additionalProperties": false,
                    "properties": {
                      "content": {
                        "type": "string"
                      },
                      "role": {
                        "enum": [
                          "user",
                          "assistant",
                          "system",
                          "developer"
                        ],
                        "type": "string"
                      }
                    },
                    "required": [
                      "role",
                      "content"
                    ],
                    "type": "object"
                  },
                  "minItems": 1,
                  "type": "array"
                },
                "model": {
                  "enum": [
                    "nvidia/nemotron-3.5-lightning:free"
                  ],
                  "type": "string"
                },
                "n": {
                  "maximum": 128,
                  "minimum": 1,
                  "type": "integer"
                },
                "presence_penalty": {
                  "type": "number"
                },
                "seed": {
                  "type": "integer"
                },
                "stop": {
                  "oneOf": [
                    {
                      "type": "string"
                    },
                    {
                      "items": {
                        "type": "string"
                      },
                      "type": "array"
                    }
                  ]
                },
                "stream": {
                  "default": false,
                  "enum": [
                    false
                  ],
                  "type": "boolean"
                },
                "temperature": {
                  "type": "number"
                },
                "top_p": {
                  "type": "number"
                },
                "user": {
                  "type": "string"
                }
              },
              "required": [
                "model",
                "messages"
              ],
              "type": "object"
            },
            "schema_template": {
              "body": {
                "messages": [
                  {
                    "content": "Summarize the supplied text in three concise points.",
                    "role": "user"
                  }
                ],
                "model": "nvidia/nemotron-3.5-lightning:free",
                "stream": false
              },
              "content_type": "application/json"
            }
          },
          "input": {
            "conditions": [
              "Use literal text messages only. Cache controls, tools, image/audio/video content and streamed responses are unavailable for this method.",
              "The complete encoded JSON request must not exceed 1000000 bytes."
            ],
            "content_type": "application/json",
            "material_types": [
              "text"
            ],
            "optional": [
              "stream",
              "max_tokens",
              "max_completion_tokens",
              "n",
              "temperature",
              "top_p",
              "seed",
              "stop",
              "frequency_penalty",
              "presence_penalty",
              "user"
            ],
            "required": [
              "model",
              "messages"
            ]
          },
          "lifecycle": {
            "cancel_endpoint": null,
            "create": {
              "http": "POST",
              "path": "/v1/chat/completions"
            },
            "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/chat/completions"
          },
          "method_aliases": [],
          "output": {
            "all_results": "Retain the complete response, all actual results, original identifiers, usage and response headers.",
            "family": "text",
            "format": "JSON"
          }
        },
        "ctx": 1000000,
        "declared_pricing_profiles": [
          {
            "dimensions": {
              "regime": "base"
            },
            "label": "Base token rates",
            "units": [
              {
                "amount": "0",
                "amount_unit": "usd_per_thousand_tokens",
                "billing_input": true,
                "estimate_only": false,
                "key": "input_price",
                "label": "Input tokens",
                "native_amount_usd_per_unit": "0",
                "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": "0",
                "amount_unit": "usd_per_thousand_tokens",
                "billing_input": true,
                "estimate_only": false,
                "key": "output_price",
                "label": "Output tokens",
                "native_amount_usd_per_unit": "0",
                "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"
              }
            ]
          }
        ],
        "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('{\"model\": \"nvidia/nemotron-3.5-lightning:free\", \"messages\": [{\"role\": \"user\", \"content\": \"Summarize the supplied text in three concise points.\"}], \"stream\": false}')\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/chat/completions \\\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": 1,
        "flex_multiplier": 1,
        "fmt": "chat",
        "hints": [
          "Send exact model ID with messages.",
          "Context length is not an output cap.",
          "A text file may supply literal text; image/audio/file-object inputs need exact binding."
        ],
        "http": "POST",
        "img_in": null,
        "img_out": null,
        "in": 0,
        "input": [
          "text"
        ],
        "label": "OpenAI Chat",
        "max_out": 65536,
        "max_reasoning_effort_multiplier": 1,
        "method_aliases": [],
        "out": 0,
        "output": [
          "text"
        ],
        "path": "/v1/chat/completions",
        "price_conditions": [
          {
            "label": "Fast mode",
            "value": "Standard rate",
            "when": "When fast mode is selected"
          },
          {
            "label": "Flex mode",
            "value": "Standard rate",
            "when": "When flex mode is selected"
          },
          {
            "label": "Maximum reasoning effort",
            "value": "Standard rate",
            "when": "When maximum reasoning effort uses the default adjustment"
          },
          {
            "label": "Explicit cache pricing",
            "value": "Not enabled",
            "when": "When explicit cache is requested"
          },
          {
            "label": "Text-only zero rates",
            "value": "Text input and output only. Cache, tools, media and streaming are unavailable.",
            "when": "For text-only input and output"
          }
        ],
        "pricing": {
          "allow_explicit_cache": false,
          "billing_mode": "token",
          "cache_read_price": null,
          "cache_write_1h_price": null,
          "cache_write_price": null,
          "fast_multiplier": 1,
          "flex_multiplier": 1,
          "image_input_price": null,
          "image_output_price": null,
          "input_price": 0,
          "intervals": [],
          "max_reasoning_effort_multiplier": 1,
          "output_price": 0,
          "per_request_price": null
        },
        "pricing_profiles": [
          {
            "dimensions": {
              "regime": "base"
            },
            "label": "Base token rates",
            "units": [
              {
                "amount": "0",
                "amount_unit": "usd_per_thousand_tokens",
                "billing_input": true,
                "estimate_only": false,
                "key": "input_price",
                "label": "Input tokens",
                "native_amount_usd_per_unit": "0",
                "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": "0",
                "amount_unit": "usd_per_thousand_tokens",
                "billing_input": true,
                "estimate_only": false,
                "key": "output_price",
                "label": "Output tokens",
                "native_amount_usd_per_unit": "0",
                "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"
              }
            ]
          }
        ],
        "request_model_id": "nvidia/nemotron-3.5-lightning:free",
        "route_label": "Ultra",
        "status_reads": [],
        "tiers": [],
        "unit": "token",
        "units": [
          {
            "amount": "0",
            "amount_unit": "usd_per_thousand_tokens",
            "billing_input": true,
            "estimate_only": false,
            "key": "input_price",
            "label": "Input tokens",
            "native_amount_usd_per_unit": "0",
            "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": "0",
            "amount_unit": "usd_per_thousand_tokens",
            "billing_input": true,
            "estimate_only": false,
            "key": "output_price",
            "label": "Output tokens",
            "native_amount_usd_per_unit": "0",
            "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"
          }
        ]
      }
    },
    {
      "html": "<div class=\"sheet-head\"><span class=\"mav\" aria-hidden=\"true\">NV</span><h2 id=\"sheet-title\">NVIDIA: Nemotron 3.5 Lightning (free)</h2><button class=\"icon-btn\" type=\"button\" data-close-sheet aria-label=\"Tutup\">×</button></div><div class=\"idline\"><span>NVIDIA /</span><code>nvidia/nemotron-3.5-lightning:free</code><button type=\"button\" id=\"copy-id\">Salin ID</button></div><nav class=\"card-jump-nav\" aria-label=\"Bagian kartu model\"><button type=\"button\" data-card-jump=\"overview\">Mulai</button><button type=\"button\" data-card-jump=\"methods\">Masukan &amp; metode</button><button type=\"button\" data-card-jump=\"pricing\">Paket</button><button type=\"button\" data-card-jump=\"examples\">Contoh</button><button type=\"button\" data-card-jump=\"results\">Hasil</button><button type=\"button\" data-card-jump=\"aliases\">Alias</button></nav><div class=\"card-method-tabs\" role=\"tablist\" aria-label=\"Metode API\"><button type=\"button\" role=\"tab\" tabindex=\"-1\" aria-controls=\"card-method-content\" aria-selected=\"false\" id=\"card-method-tab-0\" data-card-method=\"Ultra|chat|/v1/chat/completions|nvidia%2Fnemotron-3.5-lightning%3Afree\">Chat</button><button type=\"button\" role=\"tab\" tabindex=\"0\" aria-controls=\"card-method-content\" aria-selected=\"true\" id=\"card-method-tab-1\" data-card-method=\"Ultra|messages|/v1/messages|nvidia%2Fnemotron-3.5-lightning%3Afree\">Messages</button></div><div id=\"card-method-content\" role=\"tabpanel\" aria-labelledby=\"card-method-tab-1\"><section class=\"card-section\" data-card-section=\"overview\"><h3 tabindex=\"-1\">Mulai</h3><p class=\"mdesc-full\">NVIDIA Nemotron 3.5 Lightning adalah model penalaran teks dan percakapan dengan total 30B parameter dan 3B parameter aktif. Arsitektur hibrida Mamba–MoE-nya mendukung analisis berkonteks panjang, pemrograman, dan alur kerja berbasis alat, dengan mode berpikir atau jawaban langsung yang didokumentasikan dalam templat percakapan pembuatnya.</p><dl class=\"card-io\" data-card-io><div><dt>Masukan yang diterima</dt><dd>Teks</dd></div><div><dt>Hasil</dt><dd>Teks</dd></div></dl><details class=\"card-about\"><summary>Tentang model</summary><p class=\"note-s\" data-model-method-boundary>Deskripsi ini mencakup kemampuan model. Masukan, keluaran, dan opsi yang tersedia di Ailoot tercantum di bawah untuk metode yang dipilih.</p><div class=\"mabout\" id=\"m-about\"><p>NVIDIA Nemotron 3.5 Lightning adalah model bahasa untuk penalaran, percakapan, dan alur kerja agen khusus. Model ini memiliki total 30B parameter dengan 3B aktif, menggunakan arsitektur hibrida yang menyelingi lapisan Mamba-2, mixture-of-experts, dan perhatian. Lapisan Multi-Token Prediction menambahkan sinyal pelatihan untuk token mendatang dan mendukung resep generasi model yang dioptimalkan. Model ini memproses teks dan menghasilkan teks, termasuk penjelasan, kode, serta jawaban yang berlandaskan bahan yang diberikan.</p><p>Produsennya menjelaskan aplikasi dalam chatbot, retrieval-augmented generation, mengikuti instruksi, dan agen. Untuk jawaban basis pengetahuan, berikan pertanyaan serta bagian yang relevan dengan label sumber yang stabil. Mintalah model menjawab dari bagian tersebut, mengidentifikasi bagian yang mendukung setiap klaim penting, dan menyatakan hal yang masih belum diketahui. Misalnya: “Dengan menggunakan artikel dukungan ini, jelaskan perbedaan antara kedua metode instalasi dan kembalikan prasyarat, langkah, serta pemeriksaan untuk masing-masing.” Pertahankan prasyarat yang tidak tersedia tetap terlihat, alih-alih mengundang model untuk mengarangnya.</p><p>Untuk pekerjaan pemrograman, berikan kode yang relevan, perilaku yang diharapkan, dan kegagalan yang diamati. Permintaan praktis meminta revisi terfokus serta penjelasan kasus yang terdampak. Jika agen yang terhubung dengan alat menjalankan pemeriksaan, kembalikan keluaran aktualnya sebelum meminta perubahan berikutnya. Pelatihan model mencakup kode, penggunaan alat dengan beberapa langkah, dan tugas keluaran terstruktur, tetapi artefak yang selesai tetap harus sesuai dengan persyaratan asli. Mintalah kode yang direvisi, alasan setiap perubahan penting, serta pengamatan yang diperlukan untuk membuktikan bahwa masalah telah terselesaikan.</p><p>Pembuatnya mendokumentasikan proses berpikir yang diaktifkan secara bawaan serta mode jawaban langsung dengan proses berpikir dinonaktifkan melalui templat percakapan. Mode penalaran berguna untuk tugas dengan beberapa kondisi yang saling bergantung; jawaban langsung dapat cocok untuk transformasi atau ekstraksi sederhana. Produsennya merekomendasikan temperature 1.0 dan top-p 0.95 dalam contoh kliennya. Perlakukan nilai tersebut sebagai pengaturan resep pembuatnya dan pilih struktur respons akhir secara jelas, seperti penjelasan singkat, tabel perbandingan, atau jawaban yang diikuti bukti pendukung.</p><p>Model ini mendukung konteks hingga 1M token. Resep deployment BF16 yang dipublikasikan juga membedakan kemampuan model tersebut dari konfigurasi yang menggunakan jendela 256K karena keterbatasan memori. Siapkan bahan panjang sesuai jendela kerja yang berlaku, dengan mempertahankan struktur dokumen dan menyisakan ruang bagi respons. Konteks panjang paling berguna ketika prompt menentukan hubungan yang perlu ditemukan: pertentangan antar dokumen, dependensi lintas berkas sumber, atau bukti yang mendukung suatu kesimpulan. Ini bukan alasan untuk menyertakan riwayat yang tidak terkait atau berasumsi bahwa jawaban akhir dapat memenuhi seluruh jendela.</p><p>Bahasa Inggris dan bahasa pemrograman merupakan fokus utama, dengan bahasa Spanyol, Prancis, Jerman, Italia, dan Jepang juga tercantum. Nyatakan bahasa keluaran yang diperlukan serta pertahankan nama, pengenal, dan istilah sumber yang dikutip ketika ejaannya penting. Untuk pekerjaan dokumen multibahasa, tentukan apakah bahan perlu diterjemahkan, diringkas, atau dibandingkan; permintaan tersebut menghasilkan artefak yang berbeda. Mintalah istilah yang tidak pasti ditandai agar terjemahan yang lancar tidak diam-diam mengubah makna teknis.</p><p>NVIDIA memublikasikan rilis rujukan BF16 terutama untuk penyesuaian dan penelitian presisi penuh, serta rilis NVFP4 terpisah dengan resep inferensi yang dioptimalkan. Perbedaan ini penting ketika membandingkan panduan deployment: konfigurasi perangkat keras atau hasil throughput dari satu rilis tidak otomatis menjelaskan rilis lain. Nama model mengidentifikasi keluarga Lightning, sedangkan checkpoint yang tepat dan konfigurasi layanan menentukan resepnya. Pisahkan kemampuan tingkat model dari asumsi kinerja dan memori khusus resep.</p><p>Untuk pekerjaan berbasis alat, berikan deskripsi fungsi yang jelas dan kembalikan hasil aktual dari setiap langkah yang dijalankan. Operasi yang diusulkan menjadi bukti yang dapat digunakan hanya setelah aplikasi yang menaunginya melaksanakan operasi tersebut dan mencatat apa yang terjadi. Mintalah jawaban akhir membedakan pengamatan sumber, kesimpulan turunan, dan pemeriksaan yang belum selesai. Ketika perhitungan, perintah, atau bagian yang diambil bertentangan dengan hasil yang direncanakan, gunakan pertentangan itu untuk merevisi kesimpulan, alih-alih menghasilkan ringkasan rapi dari asumsi yang belum diverifikasi.</p></div></details></section><section class=\"card-section\" data-card-section=\"methods\"><h3 tabindex=\"-1\">Tersedia di Ailoot · masukan &amp; metode</h3><details class=\"card-method\" open><summary><b>Ailoot Ultra · Anthropic Messages</b> <code>POST /v1/messages</code></summary><dl class=\"method-capabilities\"><div><dt>Masukan</dt><dd><code>text</code></dd></div><div><dt>Keluaran</dt><dd><code>text</code></dd></div><div><dt>Konteks</dt><dd>1.000.000 tokens</dd></div><div><dt>Keluaran maksimum</dt><dd>65.536 tokens</dd></div><div><dt>Format keluaran</dt><dd>JSON</dd></div></dl><div class=\"tw\" data-card-parameters data-typed-parameters><table><thead><tr><th>Kolom</th><th>Jenis</th><th>Persyaratan</th><th>Nilai &amp; batasan</th><th>Bawaan</th></tr></thead><tbody><tr><th data-cell-label=\"Kolom\" scope=\"row\"><span class=\"card-cell-label\">Kolom</span><code class=\"card-field-name\">model</code></th><td data-cell-label=\"Jenis\" data-field-type><span class=\"card-cell-label\">Jenis</span><code>string</code></td><td data-cell-label=\"Persyaratan\"><span class=\"card-cell-label\">Persyaratan</span>Wajib</td><td data-cell-label=\"Nilai &amp; batasan\"><span class=\"card-cell-label\">Nilai &amp; batasan</span><div>nvidia/nemotron-3.5-lightning:free</div></td><td data-cell-label=\"Bawaan\" data-default=\"unspecified\"><span class=\"card-cell-label\">Bawaan</span>—</td></tr><tr><th data-cell-label=\"Kolom\" scope=\"row\"><span class=\"card-cell-label\">Kolom</span><code class=\"card-field-name\">messages</code></th><td data-cell-label=\"Jenis\" data-field-type><span class=\"card-cell-label\">Jenis</span><code>array</code></td><td data-cell-label=\"Persyaratan\"><span class=\"card-cell-label\">Persyaratan</span>Wajib</td><td data-cell-label=\"Nilai &amp; batasan\"><span class=\"card-cell-label\">Nilai &amp; batasan</span></td><td data-cell-label=\"Bawaan\" data-default=\"unspecified\"><span class=\"card-cell-label\">Bawaan</span>—</td></tr><tr><th data-cell-label=\"Kolom\" scope=\"row\"><span class=\"card-cell-label\">Kolom</span><code class=\"card-field-name\">stream</code></th><td data-cell-label=\"Jenis\" data-field-type><span class=\"card-cell-label\">Jenis</span><code>boolean</code></td><td data-cell-label=\"Persyaratan\"><span class=\"card-cell-label\">Persyaratan</span>Opsional</td><td data-cell-label=\"Nilai &amp; batasan\"><span class=\"card-cell-label\">Nilai &amp; batasan</span><div>false</div></td><td data-cell-label=\"Bawaan\" data-default=\"known\"><span class=\"card-cell-label\">Bawaan</span>false</td></tr><tr><th data-cell-label=\"Kolom\" scope=\"row\"><span class=\"card-cell-label\">Kolom</span><code class=\"card-field-name\">system</code></th><td data-cell-label=\"Jenis\" data-field-type><span class=\"card-cell-label\">Jenis</span><code>string</code></td><td data-cell-label=\"Persyaratan\"><span class=\"card-cell-label\">Persyaratan</span>Opsional</td><td data-cell-label=\"Nilai &amp; batasan\"><span class=\"card-cell-label\">Nilai &amp; batasan</span></td><td data-cell-label=\"Bawaan\" data-default=\"unspecified\"><span class=\"card-cell-label\">Bawaan</span>—</td></tr><tr><th data-cell-label=\"Kolom\" scope=\"row\"><span class=\"card-cell-label\">Kolom</span><code class=\"card-field-name\">max_tokens</code></th><td data-cell-label=\"Jenis\" data-field-type><span class=\"card-cell-label\">Jenis</span><code>integer</code></td><td data-cell-label=\"Persyaratan\"><span class=\"card-cell-label\">Persyaratan</span>Wajib</td><td data-cell-label=\"Nilai &amp; batasan\"><span class=\"card-cell-label\">Nilai &amp; batasan</span><div>Minimum: 1</div><div>Maksimum: 65.536</div></td><td data-cell-label=\"Bawaan\" data-default=\"unspecified\"><span class=\"card-cell-label\">Bawaan</span>—</td></tr><tr><th data-cell-label=\"Kolom\" scope=\"row\"><span class=\"card-cell-label\">Kolom</span><code class=\"card-field-name\">temperature</code></th><td data-cell-label=\"Jenis\" data-field-type><span class=\"card-cell-label\">Jenis</span><code>number</code></td><td data-cell-label=\"Persyaratan\"><span class=\"card-cell-label\">Persyaratan</span>Opsional</td><td data-cell-label=\"Nilai &amp; batasan\"><span class=\"card-cell-label\">Nilai &amp; batasan</span></td><td data-cell-label=\"Bawaan\" data-default=\"unspecified\"><span class=\"card-cell-label\">Bawaan</span>—</td></tr><tr><th data-cell-label=\"Kolom\" scope=\"row\"><span class=\"card-cell-label\">Kolom</span><code class=\"card-field-name\">top_p</code></th><td data-cell-label=\"Jenis\" data-field-type><span class=\"card-cell-label\">Jenis</span><code>number</code></td><td data-cell-label=\"Persyaratan\"><span class=\"card-cell-label\">Persyaratan</span>Opsional</td><td data-cell-label=\"Nilai &amp; batasan\"><span class=\"card-cell-label\">Nilai &amp; batasan</span></td><td data-cell-label=\"Bawaan\" data-default=\"unspecified\"><span class=\"card-cell-label\">Bawaan</span>—</td></tr><tr><th data-cell-label=\"Kolom\" scope=\"row\"><span class=\"card-cell-label\">Kolom</span><code class=\"card-field-name\">top_k</code></th><td data-cell-label=\"Jenis\" data-field-type><span class=\"card-cell-label\">Jenis</span><code>integer</code></td><td data-cell-label=\"Persyaratan\"><span class=\"card-cell-label\">Persyaratan</span>Opsional</td><td data-cell-label=\"Nilai &amp; batasan\"><span class=\"card-cell-label\">Nilai &amp; batasan</span></td><td data-cell-label=\"Bawaan\" data-default=\"unspecified\"><span class=\"card-cell-label\">Bawaan</span>—</td></tr><tr><th data-cell-label=\"Kolom\" scope=\"row\"><span class=\"card-cell-label\">Kolom</span><code class=\"card-field-name\">stop_sequences</code></th><td data-cell-label=\"Jenis\" data-field-type><span class=\"card-cell-label\">Jenis</span><code>array</code></td><td data-cell-label=\"Persyaratan\"><span class=\"card-cell-label\">Persyaratan</span>Opsional</td><td data-cell-label=\"Nilai &amp; batasan\"><span class=\"card-cell-label\">Nilai &amp; batasan</span></td><td data-cell-label=\"Bawaan\" data-default=\"unspecified\"><span class=\"card-cell-label\">Bawaan</span>—</td></tr><tr><th data-cell-label=\"Kolom\" scope=\"row\"><span class=\"card-cell-label\">Kolom</span><code class=\"card-field-name\">metadata</code></th><td data-cell-label=\"Jenis\" data-field-type><span class=\"card-cell-label\">Jenis</span><code>object</code></td><td data-cell-label=\"Persyaratan\"><span class=\"card-cell-label\">Persyaratan</span>Opsional</td><td data-cell-label=\"Nilai &amp; batasan\"><span class=\"card-cell-label\">Nilai &amp; batasan</span></td><td data-cell-label=\"Bawaan\" data-default=\"unspecified\"><span class=\"card-cell-label\">Bawaan</span>—</td></tr></tbody></table></div><details class=\"note-s\" data-method-contract><summary>Parameter metode dan siklus hidup</summary><div class=\"tw\" data-card-table=\"contract\"><table><thead><tr><th>Parameter</th><th>Kontrak</th></tr></thead><tbody><tr><th data-cell-label=\"Parameter\" scope=\"row\"><span class=\"card-cell-label\">Parameter</span><code>content_type</code></th><td data-cell-label=\"Kontrak\"><span class=\"card-cell-label\">Kontrak</span>application/json</td></tr><tr><th data-cell-label=\"Parameter\" scope=\"row\"><span class=\"card-cell-label\">Parameter</span><code>required</code></th><td data-cell-label=\"Kontrak\"><span class=\"card-cell-label\">Kontrak</span>model, messages, max_tokens</td></tr><tr><th data-cell-label=\"Parameter\" scope=\"row\"><span class=\"card-cell-label\">Parameter</span><code>optional</code></th><td data-cell-label=\"Kontrak\"><span class=\"card-cell-label\">Kontrak</span>stream, system, temperature, top_p, top_k, stop_sequences, metadata</td></tr><tr><th data-cell-label=\"Parameter\" scope=\"row\"><span class=\"card-cell-label\">Parameter</span><code>material_types</code></th><td data-cell-label=\"Kontrak\"><span class=\"card-cell-label\">Kontrak</span>text</td></tr><tr><th data-cell-label=\"Parameter\" scope=\"row\"><span class=\"card-cell-label\">Parameter</span><code>conditions</code></th><td data-cell-label=\"Kontrak\"><span class=\"card-cell-label\">Kontrak</span>Use literal text messages only. Cache controls, tools, image/audio/video content and streamed responses are unavailable for this method., The complete encoded JSON request must not exceed 1000000 bytes.</td></tr></tbody></table></div><p>Siklus hidup: <code>synchronous_json</code></p></details></details></section><section class=\"card-section\" data-card-section=\"pricing\"><h3 tabindex=\"-1\">Paket</h3><div data-native-semantic-method=\"v1\" data-tariff-reference-only><p class=\"note-s\" data-rate-support-note>Referensi tarif tidak menambah opsi permintaan. Parameter yang didukung tercantum pada metode yang dipilih.</p><dl data-price-conditions><dt>Mode Fast</dt><dd>Tarif standar <span class=\"note-s\">Saat mode fast dipilih</span></dd><dt>Mode Flex</dt><dd>Tarif standar <span class=\"note-s\">Saat mode flex dipilih</span></dd><dt>Upaya penalaran maksimum</dt><dd>Tarif standar <span class=\"note-s\">Saat upaya penalaran maksimum menggunakan penyesuaian default</span></dd><dt>Tarif nol khusus teks</dt><dd>Text input and output only. Cache, tools, media and streaming are unavailable. <span class=\"note-s\">Untuk masukan dan keluaran yang hanya berupa teks</span></dd></dl></div><div data-declared-tariff-pricing><h4>Tarif Ailoot</h4><h4>Harga menurut konfigurasi</h4><div class=\"tw\" data-pricing-profiles><table><thead><tr><th>Konfigurasi</th><th>Jadwal tarif</th><th>Biaya</th></tr></thead><tbody><tr><th data-cell-label=\"Konfigurasi\" scope=\"row\"><span class=\"card-cell-label\">Konfigurasi</span>Tarif dasar token</th><td data-cell-label=\"Jadwal tarif\"><span class=\"card-cell-label\">Jadwal tarif</span>Tarif dasar</td><td data-cell-label=\"Biaya\"><span class=\"card-cell-label\">Biaya</span><div><span>Masukan · Token masukan</span> <b>$0</b> <span class=\"price-unit\">/ 1K token</span></div><div><span>Keluaran · Token keluaran</span> <b>$0</b> <span class=\"price-unit\">/ 1K token</span></div><div><span>Masukan · Pembacaan cache</span> <b>—</b> <span class=\"price-unit\">/ 1K token</span></div><div><span>Masukan · Penulisan cache</span> <b>—</b> <span class=\"price-unit\">/ 1K token</span></div><div><span>Masukan · Penulisan cache, 1 jam</span> <b>—</b> <span class=\"price-unit\">/ 1K token</span></div></td></tr></tbody></table></div></div><p class=\"note-s\">Ailoot mencadangkan perkiraan dana sebelum permintaan. Setelah hasil diterima, tagihan akhir diselesaikan berdasarkan penggunaan yang terukur. Penyelesaian tagihan streaming menggunakan catatan penggunaan akhir. <a href=\"/docs/id/billing/reserve/\">Cara kerja cadangan dan penyelesaian tagihan →</a></p></section><section class=\"card-section\" data-card-section=\"examples\"><h3 tabindex=\"-1\">Contoh permintaan</h3><h4>Ailoot Ultra · Anthropic Messages</h4><div class=\"code-group\"><div class=\"cg-bar\"><div class=\"cg-tabs\" role=\"tablist\" aria-label=\"Pilihan kode\"><button class=\"cg-tab\" id=\"model-code-55-tab-0\" role=\"tab\" type=\"button\" aria-controls=\"model-code-55-panel-0\" aria-selected=\"true\" tabindex=\"0\">curl · buat sekali dan simpan hasil secara lengkap</button></div><div class=\"cg-tools\"><button class=\"cg-btn cg-copy\" type=\"button\" aria-label=\"Salin kode\"><svg class=\"cp\" viewBox=\"0 0 16 16\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"1.4\"><rect x=\"5.25\" y=\"5.25\" width=\"8.5\" height=\"8.5\" rx=\"1.75\"/><path d=\"M10.75 5.25V3.5a1.25 1.25 0 0 0-1.25-1.25H3.5A1.25 1.25 0 0 0 2.25 3.5v6a1.25 1.25 0 0 0 1.25 1.25h1.75\"/></svg><svg class=\"ok\" viewBox=\"0 0 16 16\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"1.4\"><path d=\"m3 8.5 3.25 3.25L13 5\"/></svg></button></div></div><div class=\"cg-body\"><div class=\"cg-pane\" id=\"model-code-55-panel-0\" role=\"tabpanel\" aria-labelledby=\"model-code-55-tab-0\"><pre data-lang=\"bash\"><code>set -eu\n: &quot;${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;model&quot;: &quot;nvidia/nemotron-3.5-lightning:free&quot;, &quot;messages&quot;: [{&quot;role&quot;: &quot;user&quot;, &quot;content&quot;: &quot;Summarize the supplied text in three concise points.&quot;}], &quot;stream&quot;: false, &quot;max_tokens&quot;: 256}&#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/messages \\\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\">Terima dan simpan hasil</h3><h4>Ailoot Ultra · Anthropic Messages</h4><p class=\"note-s\">JSON</p><div class=\"card-result-process\" data-all-results><h5>Simpan semua hasil yang selesai</h5><p class=\"note-s\">Simpan setiap respons lengkap, berkas, dan bagian konten yang dikembalikan.</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>Jika respons asli perlu diperiksa</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></section><section class=\"card-section\" data-card-section=\"aliases\"><h3 tabindex=\"-1\">Alias</h3><h4>Alias model</h4><p class=\"note-s\"><span data-model-alias-route=\"Ultra\"><b>Ailoot Ultra</b> <a href=\"#m=nvidia%2Fnemotron-3.5-lightning%3Afree&amp;route=Ultra&amp;caller=nvidia%2Fnemotron-3.5-lightning%3Afree&amp;fmt=messages\"><code>nvidia/nemotron-3.5-lightning:free</code></a></span></p><h4>Alias jalur metode</h4><p class=\"note-s\">Gunakan jalur metode yang ditampilkan di atas.</p><h4>ID pemanggil terkait</h4><p class=\"note-s\"><a href=\"#m=nvidia%2Fnemotron-3.5-lightning%3Afree&amp;route=Ultra&amp;caller=nvidia%2Fnemotron-3.5-lightning%3Afree&amp;fmt=messages\"><code>nvidia/nemotron-3.5-lightning:free</code></a></p></section></div>",
      "method_identity": {
        "effective_request_model_id": "nvidia/nemotron-3.5-lightning:free",
        "fmt": "messages",
        "http": "POST",
        "path": "/v1/messages",
        "request_model_id": "nvidia/nemotron-3.5-lightning:free",
        "route_label": "Ultra"
      },
      "method_key": "Ultra|messages|/v1/messages|nvidia%2Fnemotron-3.5-lightning%3Afree",
      "ordinal": 1,
      "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": {
              "max_tokens": 256,
              "messages": [
                {
                  "content": "Summarize the supplied text in three concise points.",
                  "role": "user"
                }
              ],
              "model": "nvidia/nemotron-3.5-lightning:free",
              "stream": false
            },
            "lifecycle": {
              "cancel_endpoint": null,
              "create": {
                "http": "POST",
                "path": "/v1/messages"
              },
              "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": "text",
              "format": "JSON"
            },
            "parameters": [
              {
                "default_known": false,
                "enum": [
                  "nvidia/nemotron-3.5-lightning:free"
                ],
                "enum_known": true,
                "name": "model",
                "required": true,
                "type": "string"
              },
              {
                "default_known": false,
                "enum_known": false,
                "items": {
                  "additionalProperties": false,
                  "properties": {
                    "content": {
                      "type": "string"
                    },
                    "role": {
                      "enum": [
                        "user",
                        "assistant"
                      ],
                      "type": "string"
                    }
                  },
                  "required": [
                    "role",
                    "content"
                  ],
                  "type": "object"
                },
                "minItems": 1,
                "name": "messages",
                "required": true,
                "type": "array"
              },
              {
                "default": false,
                "default_known": true,
                "enum": [
                  false
                ],
                "enum_known": true,
                "name": "stream",
                "required": false,
                "type": "boolean"
              },
              {
                "default_known": false,
                "enum_known": false,
                "name": "system",
                "required": false,
                "type": "string"
              },
              {
                "default_known": false,
                "enum_known": false,
                "maximum": 65536,
                "minimum": 1,
                "name": "max_tokens",
                "required": true,
                "type": "integer"
              },
              {
                "default_known": false,
                "enum_known": false,
                "name": "temperature",
                "required": false,
                "type": "number"
              },
              {
                "default_known": false,
                "enum_known": false,
                "name": "top_p",
                "required": false,
                "type": "number"
              },
              {
                "default_known": false,
                "enum_known": false,
                "name": "top_k",
                "required": false,
                "type": "integer"
              },
              {
                "default_known": false,
                "enum_known": false,
                "items": {
                  "type": "string"
                },
                "name": "stop_sequences",
                "required": false,
                "type": "array"
              },
              {
                "default_known": false,
                "enum_known": false,
                "name": "metadata",
                "required": false,
                "type": "object"
              }
            ],
            "request_schema": {
              "additionalProperties": false,
              "properties": {
                "max_tokens": {
                  "maximum": 65536,
                  "minimum": 1,
                  "type": "integer"
                },
                "messages": {
                  "items": {
                    "additionalProperties": false,
                    "properties": {
                      "content": {
                        "type": "string"
                      },
                      "role": {
                        "enum": [
                          "user",
                          "assistant"
                        ],
                        "type": "string"
                      }
                    },
                    "required": [
                      "role",
                      "content"
                    ],
                    "type": "object"
                  },
                  "minItems": 1,
                  "type": "array"
                },
                "metadata": {
                  "type": "object"
                },
                "model": {
                  "enum": [
                    "nvidia/nemotron-3.5-lightning:free"
                  ],
                  "type": "string"
                },
                "stop_sequences": {
                  "items": {
                    "type": "string"
                  },
                  "type": "array"
                },
                "stream": {
                  "default": false,
                  "enum": [
                    false
                  ],
                  "type": "boolean"
                },
                "system": {
                  "type": "string"
                },
                "temperature": {
                  "type": "number"
                },
                "top_k": {
                  "type": "integer"
                },
                "top_p": {
                  "type": "number"
                }
              },
              "required": [
                "model",
                "messages",
                "max_tokens"
              ],
              "type": "object"
            },
            "schema_template": {
              "body": {
                "max_tokens": 256,
                "messages": [
                  {
                    "content": "Summarize the supplied text in three concise points.",
                    "role": "user"
                  }
                ],
                "model": "nvidia/nemotron-3.5-lightning:free",
                "stream": false
              },
              "content_type": "application/json"
            }
          },
          "input": {
            "conditions": [
              "Use literal text messages only. Cache controls, tools, image/audio/video content and streamed responses are unavailable for this method.",
              "The complete encoded JSON request must not exceed 1000000 bytes."
            ],
            "content_type": "application/json",
            "material_types": [
              "text"
            ],
            "optional": [
              "stream",
              "system",
              "temperature",
              "top_p",
              "top_k",
              "stop_sequences",
              "metadata"
            ],
            "required": [
              "model",
              "messages",
              "max_tokens"
            ]
          },
          "lifecycle": {
            "cancel_endpoint": null,
            "create": {
              "http": "POST",
              "path": "/v1/messages"
            },
            "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/messages"
          },
          "method_aliases": [],
          "output": {
            "all_results": "Retain the complete response, all actual results, original identifiers, usage and response headers.",
            "family": "text",
            "format": "JSON"
          }
        },
        "ctx": 1000000,
        "declared_pricing_profiles": [
          {
            "dimensions": {
              "regime": "base"
            },
            "label": "Base token rates",
            "units": [
              {
                "amount": "0",
                "amount_unit": "usd_per_thousand_tokens",
                "billing_input": true,
                "estimate_only": false,
                "key": "input_price",
                "label": "Input tokens",
                "native_amount_usd_per_unit": "0",
                "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": "0",
                "amount_unit": "usd_per_thousand_tokens",
                "billing_input": true,
                "estimate_only": false,
                "key": "output_price",
                "label": "Output tokens",
                "native_amount_usd_per_unit": "0",
                "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"
              }
            ]
          }
        ],
        "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('{\"model\": \"nvidia/nemotron-3.5-lightning:free\", \"messages\": [{\"role\": \"user\", \"content\": \"Summarize the supplied text in three concise points.\"}], \"stream\": false, \"max_tokens\": 256}')\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/messages \\\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": "anthropic",
        "fast_multiplier": 1,
        "flex_multiplier": 1,
        "fmt": "messages",
        "http": "POST",
        "img_in": null,
        "img_out": null,
        "in": 0,
        "input": [
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            "label": "Base token rates",
            "units": [
              {
                "amount": "0",
                "amount_unit": "usd_per_thousand_tokens",
                "billing_input": true,
                "estimate_only": false,
                "key": "input_price",
                "label": "Input tokens",
                "native_amount_usd_per_unit": "0",
                "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": "0",
                "amount_unit": "usd_per_thousand_tokens",
                "billing_input": true,
                "estimate_only": false,
                "key": "output_price",
                "label": "Output tokens",
                "native_amount_usd_per_unit": "0",
                "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"
              }
            ]
          }
        ],
        "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('{\"model\": \"nvidia/nemotron-3.5-lightning:free\", \"messages\": [{\"role\": \"user\", \"content\": \"Summarize the supplied text in three concise points.\"}], \"stream\": false}')\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/chat/completions \\\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": 1,
        "flex_multiplier": 1,
        "fmt": "chat",
        "hints": [
          "Send exact model ID with messages.",
          "Context length is not an output cap.",
          "A text file may supply literal text; image/audio/file-object inputs need exact binding."
        ],
        "http": "POST",
        "img_in": null,
        "img_out": null,
        "in": 0,
        "input": [
          "text"
        ],
        "label": "OpenAI Chat",
        "max_out": 65536,
        "max_reasoning_effort_multiplier": 1,
        "method_aliases": [],
        "out": 0,
        "output": [
          "text"
        ],
        "path": "/v1/chat/completions",
        "price_conditions": [
          {
            "label": "Fast mode",
            "value": "Standard rate",
            "when": "When fast mode is selected"
          },
          {
            "label": "Flex mode",
            "value": "Standard rate",
            "when": "When flex mode is selected"
          },
          {
            "label": "Maximum reasoning effort",
            "value": "Standard rate",
            "when": "When maximum reasoning effort uses the default adjustment"
          },
          {
            "label": "Explicit cache pricing",
            "value": "Not enabled",
            "when": "When explicit cache is requested"
          },
          {
            "label": "Text-only zero rates",
            "value": "Text input and output only. Cache, tools, media and streaming are unavailable.",
            "when": "For text-only input and output"
          }
        ],
        "pricing": {
          "allow_explicit_cache": false,
          "billing_mode": "token",
          "cache_read_price": null,
          "cache_write_1h_price": null,
          "cache_write_price": null,
          "fast_multiplier": 1,
          "flex_multiplier": 1,
          "image_input_price": null,
          "image_output_price": null,
          "input_price": 0,
          "intervals": [],
          "max_reasoning_effort_multiplier": 1,
          "output_price": 0,
          "per_request_price": null
        },
        "pricing_profiles": [
          {
            "dimensions": {
              "regime": "base"
            },
            "label": "Base token rates",
            "units": [
              {
                "amount": "0",
                "amount_unit": "usd_per_thousand_tokens",
                "billing_input": true,
                "estimate_only": false,
                "key": "input_price",
                "label": "Input tokens",
                "native_amount_usd_per_unit": "0",
                "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": "0",
                "amount_unit": "usd_per_thousand_tokens",
                "billing_input": true,
                "estimate_only": false,
                "key": "output_price",
                "label": "Output tokens",
                "native_amount_usd_per_unit": "0",
                "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"
              }
            ]
          }
        ],
        "request_model_id": "nvidia/nemotron-3.5-lightning:free",
        "route_label": "Ultra",
        "status_reads": [],
        "tiers": [],
        "unit": "token",
        "units": [
          {
            "amount": "0",
            "amount_unit": "usd_per_thousand_tokens",
            "billing_input": true,
            "estimate_only": false,
            "key": "input_price",
            "label": "Input tokens",
            "native_amount_usd_per_unit": "0",
            "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": "0",
            "amount_unit": "usd_per_thousand_tokens",
            "billing_input": true,
            "estimate_only": false,
            "key": "output_price",
            "label": "Output tokens",
            "native_amount_usd_per_unit": "0",
            "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"
          }
        ]
      },
      {
        "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": {
              "max_tokens": 256,
              "messages": [
                {
                  "content": "Summarize the supplied text in three concise points.",
                  "role": "user"
                }
              ],
              "model": "nvidia/nemotron-3.5-lightning:free",
              "stream": false
            },
            "lifecycle": {
              "cancel_endpoint": null,
              "create": {
                "http": "POST",
                "path": "/v1/messages"
              },
              "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": "text",
              "format": "JSON"
            },
            "parameters": [
              {
                "default_known": false,
                "enum": [
                  "nvidia/nemotron-3.5-lightning:free"
                ],
                "enum_known": true,
                "name": "model",
                "required": true,
                "type": "string"
              },
              {
                "default_known": false,
                "enum_known": false,
                "items": {
                  "additionalProperties": false,
                  "properties": {
                    "content": {
                      "type": "string"
                    },
                    "role": {
                      "enum": [
                        "user",
                        "assistant"
                      ],
                      "type": "string"
                    }
                  },
                  "required": [
                    "role",
                    "content"
                  ],
                  "type": "object"
                },
                "minItems": 1,
                "name": "messages",
                "required": true,
                "type": "array"
              },
              {
                "default": false,
                "default_known": true,
                "enum": [
                  false
                ],
                "enum_known": true,
                "name": "stream",
                "required": false,
                "type": "boolean"
              },
              {
                "default_known": false,
                "enum_known": false,
                "name": "system",
                "required": false,
                "type": "string"
              },
              {
                "default_known": false,
                "enum_known": false,
                "maximum": 65536,
                "minimum": 1,
                "name": "max_tokens",
                "required": true,
                "type": "integer"
              },
              {
                "default_known": false,
                "enum_known": false,
                "name": "temperature",
                "required": false,
                "type": "number"
              },
              {
                "default_known": false,
                "enum_known": false,
                "name": "top_p",
                "required": false,
                "type": "number"
              },
              {
                "default_known": false,
                "enum_known": false,
                "name": "top_k",
                "required": false,
                "type": "integer"
              },
              {
                "default_known": false,
                "enum_known": false,
                "items": {
                  "type": "string"
                },
                "name": "stop_sequences",
                "required": false,
                "type": "array"
              },
              {
                "default_known": false,
                "enum_known": false,
                "name": "metadata",
                "required": false,
                "type": "object"
              }
            ],
            "request_schema": {
              "additionalProperties": false,
              "properties": {
                "max_tokens": {
                  "maximum": 65536,
                  "minimum": 1,
                  "type": "integer"
                },
                "messages": {
                  "items": {
                    "additionalProperties": false,
                    "properties": {
                      "content": {
                        "type": "string"
                      },
                      "role": {
                        "enum": [
                          "user",
                          "assistant"
                        ],
                        "type": "string"
                      }
                    },
                    "required": [
                      "role",
                      "content"
                    ],
                    "type": "object"
                  },
                  "minItems": 1,
                  "type": "array"
                },
                "metadata": {
                  "type": "object"
                },
                "model": {
                  "enum": [
                    "nvidia/nemotron-3.5-lightning:free"
                  ],
                  "type": "string"
                },
                "stop_sequences": {
                  "items": {
                    "type": "string"
                  },
                  "type": "array"
                },
                "stream": {
                  "default": false,
                  "enum": [
                    false
                  ],
                  "type": "boolean"
                },
                "system": {
                  "type": "string"
                },
                "temperature": {
                  "type": "number"
                },
                "top_k": {
                  "type": "integer"
                },
                "top_p": {
                  "type": "number"
                }
              },
              "required": [
                "model",
                "messages",
                "max_tokens"
              ],
              "type": "object"
            },
            "schema_template": {
              "body": {
                "max_tokens": 256,
                "messages": [
                  {
                    "content": "Summarize the supplied text in three concise points.",
                    "role": "user"
                  }
                ],
                "model": "nvidia/nemotron-3.5-lightning:free",
                "stream": false
              },
              "content_type": "application/json"
            }
          },
          "input": {
            "conditions": [
              "Use literal text messages only. Cache controls, tools, image/audio/video content and streamed responses are unavailable for this method.",
              "The complete encoded JSON request must not exceed 1000000 bytes."
            ],
            "content_type": "application/json",
            "material_types": [
              "text"
            ],
            "optional": [
              "stream",
              "system",
              "temperature",
              "top_p",
              "top_k",
              "stop_sequences",
              "metadata"
            ],
            "required": [
              "model",
              "messages",
              "max_tokens"
            ]
          },
          "lifecycle": {
            "cancel_endpoint": null,
            "create": {
              "http": "POST",
              "path": "/v1/messages"
            },
            "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/messages"
          },
          "method_aliases": [],
          "output": {
            "all_results": "Retain the complete response, all actual results, original identifiers, usage and response headers.",
            "family": "text",
            "format": "JSON"
          }
        },
        "ctx": 1000000,
        "declared_pricing_profiles": [
          {
            "dimensions": {
              "regime": "base"
            },
            "label": "Base token rates",
            "units": [
              {
                "amount": "0",
                "amount_unit": "usd_per_thousand_tokens",
                "billing_input": true,
                "estimate_only": false,
                "key": "input_price",
                "label": "Input tokens",
                "native_amount_usd_per_unit": "0",
                "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": "0",
                "amount_unit": "usd_per_thousand_tokens",
                "billing_input": true,
                "estimate_only": false,
                "key": "output_price",
                "label": "Output tokens",
                "native_amount_usd_per_unit": "0",
                "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"
              }
            ]
          }
        ],
        "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('{\"model\": \"nvidia/nemotron-3.5-lightning:free\", \"messages\": [{\"role\": \"user\", \"content\": \"Summarize the supplied text in three concise points.\"}], \"stream\": false, \"max_tokens\": 256}')\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/messages \\\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": "anthropic",
        "fast_multiplier": 1,
        "flex_multiplier": 1,
        "fmt": "messages",
        "http": "POST",
        "img_in": null,
        "img_out": null,
        "in": 0,
        "input": [
          "text"
        ],
        "label": "Anthropic Messages",
        "max_out": 65536,
        "max_reasoning_effort_multiplier": 1,
        "method_aliases": [],
        "out": 0,
        "output": [
          "text"
        ],
        "path": "/v1/messages",
        "price_conditions": [
          {
            "label": "Fast mode",
            "value": "Standard rate",
            "when": "When fast mode is selected"
          },
          {
            "label": "Flex mode",
            "value": "Standard rate",
            "when": "When flex mode is selected"
          },
          {
            "label": "Maximum reasoning effort",
            "value": "Standard rate",
            "when": "When maximum reasoning effort uses the default adjustment"
          },
          {
            "label": "Text-only zero rates",
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