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dots3-note Preview ialah ahli ringan dalam keluarga multimodal dots3 Dots Studio. Pengeluar menyenaraikan model mixture-of-experts dengan jumlah 280B parameter, 16B parameter aktif dan sokongan konteks sehingga 512K token. Model ini menerima teks, imej, video dan audio serta menghasilkan teks, dengan pengetahuan am, arahan, penaakulan, pengekodan dan kerja berorientasikan ejen antara tugasannya yang dinyatakan.

Teras bahasanya mempunyai satu lapisan padat dan 45 lapisan pakar, dengan lapan pakar berhala dipilih daripada 256 bersama satu pakar dikongsi. Perhatiannya menggabungkan 13 lapisan perhatian jarang dan 33 lapisan tetingkap gelongsor. Pengeluar menyenaraikan pengekod penglihatan dan audio yang berasingan serta lapisan ramalan dikongsi. Komponen ini menyokong pemahaman multimodal; output model kekal teks, bukannya imej, pertuturan atau video yang dijana.

Untuk analisis visual, bekalkan imej, halaman atau carta dan tanyakan ciri yang mempengaruhi keputusan. Tugasan dokumen yang berguna boleh membandingkan jadual yang kelihatan dengan keperluan bertulis dan mengembalikan baris berkaitan, tafsiran serta maklumat yang tiada. Untuk video, kenal pasti peristiwa atau urutan yang perlu diteliti; contoh input pengeluar menyertakan trek audio apabila klip mempunyai audio.

Untuk audio, nyatakan sama ada tugasan memerlukan transkrip atau penjelasan bahan, dan berikan sebarang nama atau istilah domain yang diperlukan untuk tafsiran. Tugasan gabungan boleh menggunakan rakaman bersama latar belakang bertulis dan meminta penemuan disusun mengikut soalan yang dijawabnya. Hasilnya ialah artifak teks untuk dipaparkan atau diproses oleh aplikasi.

Templat perbualan pengeluar membezakan pemikiran daripada respons langsung. Mengaktifkan pemikiran menambah peringkat penaakulan; menyahaktifkannya mengembalikan jawapan secara terus. Sampel yang didokumenkan menggunakan temperature 1.0 dan top-p 0.95. Pilih tugasan dan hasil yang dikehendaki dengan jelas, serta tinggalkan ruang penjanaan yang mencukupi untuk jawapan tanpa menganggap peruntukan token sampel sebagai had output mutlak model.

Untuk tugasan pengekodan, berikan sumber berkaitan, tingkah laku yang dijangkakan dan kegagalan yang diperhatikan atau perubahan yang diminta. Minta artifak cadangan dan semakan yang akan menilainya. Dalam aliran kerja ejen bersambung, model mencadangkan interaksi alat, manakala aplikasi melaksanakannya dan mengembalikan hasil. Pembangun menerbitkan penghurai panggilan alat khusus; aplikasi sekeliling membekalkan alat sebenar dan aksesnya.

Kerja interaktif boleh memerlukan penerokaan, penyesuaian dan pengemaskinian memori kerja tugasan. Simpan rekod ringkas tentang objektif, penemuan yang disahkan dan syarat yang belum diselesaikan. Minta giliran seterusnya mengenal pasti perubahan akibat bukti baharu dan perkara yang patut kekal dalam rekod itu. Penyimpanan rekod secara berterusan dan pelaksanaan tindakan menjadi tanggungjawab aplikasi sekeliling model.

Pengeluar menerbitkan artifak BF16 dan FP8 yang berbeza serta resipi penyajian setempat dengan panjang konteks terkonfigurasi yang berbeza. Panjang penyajian yang dikonfigurasikan berasingan daripada spesifikasi model 512K. Kekalkan perbezaan edisi Preview dan ketepatan berangka apabila mengenal pasti model, serta minta hasil akhir yang menyatakan penemuan, perubahan cadangan dan bukti yang benar-benar dikumpulkan oleh aliran kerja.

", "aboutText": "dots3-note Preview ialah ahli ringan dalam keluarga multimodal dots3 Dots Studio. Pengeluar menyenaraikan model mixture-of-experts dengan jumlah 280B parameter, 16B parameter aktif dan sokongan konteks sehingga 512K token. Model ini menerima teks, imej, video dan audio serta menghasilkan teks, dengan pengetahuan am, arahan, penaakulan, pengekodan dan kerja berorientasikan ejen antara tugasannya yang dinyatakan.\n\nTeras bahasanya mempunyai satu lapisan padat dan 45 lapisan pakar, dengan lapan pakar berhala dipilih daripada 256 bersama satu pakar dikongsi. Perhatiannya menggabungkan 13 lapisan perhatian jarang dan 33 lapisan tetingkap gelongsor. Pengeluar menyenaraikan pengekod penglihatan dan audio yang berasingan serta lapisan ramalan dikongsi. Komponen ini menyokong pemahaman multimodal; output model kekal teks, bukannya imej, pertuturan atau video yang dijana.\n\nUntuk analisis visual, bekalkan imej, halaman atau carta dan tanyakan ciri yang mempengaruhi keputusan. Tugasan dokumen yang berguna boleh membandingkan jadual yang kelihatan dengan keperluan bertulis dan mengembalikan baris berkaitan, tafsiran serta maklumat yang tiada. Untuk video, kenal pasti peristiwa atau urutan yang perlu diteliti; contoh input pengeluar menyertakan trek audio apabila klip mempunyai audio.\n\nUntuk audio, nyatakan sama ada tugasan memerlukan transkrip atau penjelasan bahan, dan berikan sebarang nama atau istilah domain yang diperlukan untuk tafsiran. Tugasan gabungan boleh menggunakan rakaman bersama latar belakang bertulis dan meminta penemuan disusun mengikut soalan yang dijawabnya. Hasilnya ialah artifak teks untuk dipaparkan atau diproses oleh aplikasi.\n\nTemplat perbualan pengeluar membezakan pemikiran daripada respons langsung. Mengaktifkan pemikiran menambah peringkat penaakulan; menyahaktifkannya mengembalikan jawapan secara terus. Sampel yang didokumenkan menggunakan temperature 1.0 dan top-p 0.95. Pilih tugasan dan hasil yang dikehendaki dengan jelas, serta tinggalkan ruang penjanaan yang mencukupi untuk jawapan tanpa menganggap peruntukan token sampel sebagai had output mutlak model.\n\nUntuk tugasan pengekodan, berikan sumber berkaitan, tingkah laku yang dijangkakan dan kegagalan yang diperhatikan atau perubahan yang diminta. Minta artifak cadangan dan semakan yang akan menilainya. Dalam aliran kerja ejen bersambung, model mencadangkan interaksi alat, manakala aplikasi melaksanakannya dan mengembalikan hasil. Pembangun menerbitkan penghurai panggilan alat khusus; aplikasi sekeliling membekalkan alat sebenar dan aksesnya.\n\nKerja interaktif boleh memerlukan penerokaan, penyesuaian dan pengemaskinian memori kerja tugasan. Simpan rekod ringkas tentang objektif, penemuan yang disahkan dan syarat yang belum diselesaikan. Minta giliran seterusnya mengenal pasti perubahan akibat bukti baharu dan perkara yang patut kekal dalam rekod itu. Penyimpanan rekod secara berterusan dan pelaksanaan tindakan menjadi tanggungjawab aplikasi sekeliling model.\n\nPengeluar menerbitkan artifak BF16 dan FP8 yang berbeza serta resipi penyajian setempat dengan panjang konteks terkonfigurasi yang berbeza. Panjang penyajian yang dikonfigurasikan berasingan daripada spesifikasi model 512K. Kekalkan perbezaan edisi Preview dan ketepatan berangka apabila mengenal pasti model, serta minta hasil akhir yang menyatakan penemuan, perubahan cadangan dan bukti yang benar-benar dikumpulkan oleh aliran kerja.", "editorialOverlay": { "copy_fields": null, "copy_sha256": null, "copy_source": null, "html_sha256": "ed4ef1080d2a0ce91895a9bc3552cd4923f31b3e78c0c1eb5f7b812485e90bb2", "module_sha256": "ee9dc1c50b1e6a8fb7fa062030fcb4646b9aaaeb08be513b723a5a92a7290f06", "raw_model_unchanged": true, "schema": "ailoot-native-model-editorial-v1" }, "locale": "ms", "methods": [ { "html": "
•

Dots Studio: Dots3-Note Preview (free)

Dots Studio /dots-studio/dots-3-note-preview:free

Pengenalan

dots3-note Preview daripada Dots Studio ialah model MoE multimodal untuk penaakulan, pengekodan dan aliran kerja ejen. Pengeluar menyenaraikan jumlah 280B parameter dengan 16B aktif, konteks 512K, input teks/imej/video/audio dan output teks.

Input yang diterima
Teks
Hasil
Teks
Tentang model

Huraian ini merangkumi keupayaan model. Input, output dan pilihan yang tersedia di Ailoot disenaraikan di bawah untuk kaedah yang dipilih.

dots3-note Preview ialah ahli ringan dalam keluarga multimodal dots3 Dots Studio. Pengeluar menyenaraikan model mixture-of-experts dengan jumlah 280B parameter, 16B parameter aktif dan sokongan konteks sehingga 512K token. Model ini menerima teks, imej, video dan audio serta menghasilkan teks, dengan pengetahuan am, arahan, penaakulan, pengekodan dan kerja berorientasikan ejen antara tugasannya yang dinyatakan.

Teras bahasanya mempunyai satu lapisan padat dan 45 lapisan pakar, dengan lapan pakar berhala dipilih daripada 256 bersama satu pakar dikongsi. Perhatiannya menggabungkan 13 lapisan perhatian jarang dan 33 lapisan tetingkap gelongsor. Pengeluar menyenaraikan pengekod penglihatan dan audio yang berasingan serta lapisan ramalan dikongsi. Komponen ini menyokong pemahaman multimodal; output model kekal teks, bukannya imej, pertuturan atau video yang dijana.

Untuk analisis visual, bekalkan imej, halaman atau carta dan tanyakan ciri yang mempengaruhi keputusan. Tugasan dokumen yang berguna boleh membandingkan jadual yang kelihatan dengan keperluan bertulis dan mengembalikan baris berkaitan, tafsiran serta maklumat yang tiada. Untuk video, kenal pasti peristiwa atau urutan yang perlu diteliti; contoh input pengeluar menyertakan trek audio apabila klip mempunyai audio.

Untuk audio, nyatakan sama ada tugasan memerlukan transkrip atau penjelasan bahan, dan berikan sebarang nama atau istilah domain yang diperlukan untuk tafsiran. Tugasan gabungan boleh menggunakan rakaman bersama latar belakang bertulis dan meminta penemuan disusun mengikut soalan yang dijawabnya. Hasilnya ialah artifak teks untuk dipaparkan atau diproses oleh aplikasi.

Templat perbualan pengeluar membezakan pemikiran daripada respons langsung. Mengaktifkan pemikiran menambah peringkat penaakulan; menyahaktifkannya mengembalikan jawapan secara terus. Sampel yang didokumenkan menggunakan temperature 1.0 dan top-p 0.95. Pilih tugasan dan hasil yang dikehendaki dengan jelas, serta tinggalkan ruang penjanaan yang mencukupi untuk jawapan tanpa menganggap peruntukan token sampel sebagai had output mutlak model.

Untuk tugasan pengekodan, berikan sumber berkaitan, tingkah laku yang dijangkakan dan kegagalan yang diperhatikan atau perubahan yang diminta. Minta artifak cadangan dan semakan yang akan menilainya. Dalam aliran kerja ejen bersambung, model mencadangkan interaksi alat, manakala aplikasi melaksanakannya dan mengembalikan hasil. Pembangun menerbitkan penghurai panggilan alat khusus; aplikasi sekeliling membekalkan alat sebenar dan aksesnya.

Kerja interaktif boleh memerlukan penerokaan, penyesuaian dan pengemaskinian memori kerja tugasan. Simpan rekod ringkas tentang objektif, penemuan yang disahkan dan syarat yang belum diselesaikan. Minta giliran seterusnya mengenal pasti perubahan akibat bukti baharu dan perkara yang patut kekal dalam rekod itu. Penyimpanan rekod secara berterusan dan pelaksanaan tindakan menjadi tanggungjawab aplikasi sekeliling model.

Pengeluar menerbitkan artifak BF16 dan FP8 yang berbeza serta resipi penyajian setempat dengan panjang konteks terkonfigurasi yang berbeza. Panjang penyajian yang dikonfigurasikan berasingan daripada spesifikasi model 512K. Kekalkan perbezaan edisi Preview dan ketepatan berangka apabila mengenal pasti model, serta minta hasil akhir yang menyatakan penemuan, perubahan cadangan dan bukti yang benar-benar dikumpulkan oleh aliran kerja.

Tersedia di Ailoot · input & kaedah

Ailoot Ultra · OpenAI Chat POST /v1/chat/completions
Input
text
Output
text
Konteks
512,000 tokens
Output maksimum
460,800 tokens
Format output
JSON
MedanJenisKeperluanNilai & hadLalai
MedanmodelJenisstringKeperluanDiperlukanNilai & had
dots-studio/dots-3-note-preview:free
Lalai—
MedanmessagesJenisarrayKeperluanDiperlukanNilai & hadLalai—
MedanstreamJenisbooleanKeperluanPilihanNilai & had
false
Lalaifalse
Medanmax_tokensJenisintegerKeperluanPilihanNilai & had
Minimum: 1
Maksimum: 460,800
Lalai—
Medanmax_completion_tokensJenisintegerKeperluanPilihanNilai & had
Minimum: 1
Maksimum: 460,800
Lalai—
MedannJenisintegerKeperluanPilihanNilai & had
Minimum: 1
Maksimum: 128
Lalai—
MedantemperatureJenisnumberKeperluanPilihanNilai & hadLalai—
Medantop_pJenisnumberKeperluanPilihanNilai & hadLalai—
MedanseedJenisintegerKeperluanPilihanNilai & hadLalai—
MedanstopJenisKeperluanPilihanNilai & hadLalai—
Medanfrequency_penaltyJenisnumberKeperluanPilihanNilai & hadLalai—
Medanpresence_penaltyJenisnumberKeperluanPilihanNilai & hadLalai—
MedanuserJenisstringKeperluanPilihanNilai & hadLalai—
Parameter kaedah dan kitar hayat
ParameterKontrak
Parametercontent_typeKontrakapplication/json
ParameterrequiredKontrakmodel, messages
ParameteroptionalKontrakstream, max_tokens, max_completion_tokens, n, temperature, top_p, seed, stop, frequency_penalty, presence_penalty, user
Parametermaterial_typesKontraktext
ParameterconditionsKontrakUse 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 512000 bytes.

Kitar hayat: synchronous_json

Pelan harga

Rujukan tarif tidak menambah pilihan permintaan. Parameter yang disokong disenaraikan untuk kaedah yang dipilih.

Mod pantas
Kadar standard Apabila mod pantas dipilih
Mod flex
Kadar standard Apabila mod flex dipilih
Usaha penaakulan maksimum
Kadar standard Apabila usaha penaakulan maksimum menggunakan pelarasan default
Harga cache eksplisit
Tidak diaktifkan Apabila cache eksplisit diminta
Kadar sifar untuk teks sahaja
Text input and output only. Cache, tools, media and streaming are unavailable. Untuk input dan output teks sahaja

Kadar Ailoot

Harga mengikut konfigurasi

KonfigurasiJadual kadarCaj
KonfigurasiKadar asas tokenJadual kadarKadar asasCaj
Input · Token input $0 / 1K token
Output · Token output $0 / 1K token
Input · Bacaan cache — / 1K token
Input · Penulisan cache — / 1K token
Input · Penulisan cache, 1 jam — / 1K token

Ailoot merizabkan anggaran amaun sebelum permintaan. Selepas hasil diterima, caj akhir diselesaikan berdasarkan penggunaan terukur. Penyelesaian caj penstriman menggunakan rekod penggunaan akhir. Cara rizab dan penyelesaian caj berfungsi →

Contoh permintaan

Ailoot Ultra · OpenAI Chat

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": "dots-studio/dots-3-note-preview: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

Terima dan simpan hasil

Ailoot Ultra · OpenAI Chat

JSON

Simpan semua hasil yang selesai

Simpan setiap respons lengkap, fail dan bahagian kandungan yang dikembalikan.

Retain the complete response, all actual results, original identifiers, usage and response headers.

Jika respons asal perlu disemak

Preserve the original response, headers and X-Client-Request-ID. An uncertain outcome does not authorize another creation.

Alias

Alias model

Ailoot Ultra dots-studio/dots-3-note-preview:free

Alias laluan kaedah

Gunakan laluan kaedah yang dipaparkan di atas.

ID pemanggil berkaitan

dots-studio/dots-3-note-preview:free

", "method_identity": { "effective_request_model_id": "dots-studio/dots-3-note-preview:free", "fmt": "chat", "http": "POST", "path": "/v1/chat/completions", "request_model_id": "dots-studio/dots-3-note-preview:free", "route_label": "Ultra" }, "method_key": "Ultra|chat|/v1/chat/completions|dots-studio%2Fdots-3-note-preview%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": "dots-studio/dots-3-note-preview: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": [ "dots-studio/dots-3-note-preview: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": 460800, "minimum": 1, "name": "max_tokens", "required": false, "type": "integer" }, { "default_known": false, "enum_known": false, "maximum": 460800, "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": 460800, "minimum": 1, "type": "integer" }, "max_tokens": { "maximum": 460800, "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": [ "dots-studio/dots-3-note-preview: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": "dots-studio/dots-3-note-preview: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 512000 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": 512000, "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\": \"dots-studio/dots-3-note-preview: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": 460800, "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": "dots-studio/dots-3-note-preview: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": "
•

Dots Studio: Dots3-Note Preview (free)

Dots Studio /dots-studio/dots-3-note-preview:free

Pengenalan

dots3-note Preview daripada Dots Studio ialah model MoE multimodal untuk penaakulan, pengekodan dan aliran kerja ejen. Pengeluar menyenaraikan jumlah 280B parameter dengan 16B aktif, konteks 512K, input teks/imej/video/audio dan output teks.

Input yang diterima
Teks
Hasil
Teks
Tentang model

Huraian ini merangkumi keupayaan model. Input, output dan pilihan yang tersedia di Ailoot disenaraikan di bawah untuk kaedah yang dipilih.

dots3-note Preview ialah ahli ringan dalam keluarga multimodal dots3 Dots Studio. Pengeluar menyenaraikan model mixture-of-experts dengan jumlah 280B parameter, 16B parameter aktif dan sokongan konteks sehingga 512K token. Model ini menerima teks, imej, video dan audio serta menghasilkan teks, dengan pengetahuan am, arahan, penaakulan, pengekodan dan kerja berorientasikan ejen antara tugasannya yang dinyatakan.

Teras bahasanya mempunyai satu lapisan padat dan 45 lapisan pakar, dengan lapan pakar berhala dipilih daripada 256 bersama satu pakar dikongsi. Perhatiannya menggabungkan 13 lapisan perhatian jarang dan 33 lapisan tetingkap gelongsor. Pengeluar menyenaraikan pengekod penglihatan dan audio yang berasingan serta lapisan ramalan dikongsi. Komponen ini menyokong pemahaman multimodal; output model kekal teks, bukannya imej, pertuturan atau video yang dijana.

Untuk analisis visual, bekalkan imej, halaman atau carta dan tanyakan ciri yang mempengaruhi keputusan. Tugasan dokumen yang berguna boleh membandingkan jadual yang kelihatan dengan keperluan bertulis dan mengembalikan baris berkaitan, tafsiran serta maklumat yang tiada. Untuk video, kenal pasti peristiwa atau urutan yang perlu diteliti; contoh input pengeluar menyertakan trek audio apabila klip mempunyai audio.

Untuk audio, nyatakan sama ada tugasan memerlukan transkrip atau penjelasan bahan, dan berikan sebarang nama atau istilah domain yang diperlukan untuk tafsiran. Tugasan gabungan boleh menggunakan rakaman bersama latar belakang bertulis dan meminta penemuan disusun mengikut soalan yang dijawabnya. Hasilnya ialah artifak teks untuk dipaparkan atau diproses oleh aplikasi.

Templat perbualan pengeluar membezakan pemikiran daripada respons langsung. Mengaktifkan pemikiran menambah peringkat penaakulan; menyahaktifkannya mengembalikan jawapan secara terus. Sampel yang didokumenkan menggunakan temperature 1.0 dan top-p 0.95. Pilih tugasan dan hasil yang dikehendaki dengan jelas, serta tinggalkan ruang penjanaan yang mencukupi untuk jawapan tanpa menganggap peruntukan token sampel sebagai had output mutlak model.

Untuk tugasan pengekodan, berikan sumber berkaitan, tingkah laku yang dijangkakan dan kegagalan yang diperhatikan atau perubahan yang diminta. Minta artifak cadangan dan semakan yang akan menilainya. Dalam aliran kerja ejen bersambung, model mencadangkan interaksi alat, manakala aplikasi melaksanakannya dan mengembalikan hasil. Pembangun menerbitkan penghurai panggilan alat khusus; aplikasi sekeliling membekalkan alat sebenar dan aksesnya.

Kerja interaktif boleh memerlukan penerokaan, penyesuaian dan pengemaskinian memori kerja tugasan. Simpan rekod ringkas tentang objektif, penemuan yang disahkan dan syarat yang belum diselesaikan. Minta giliran seterusnya mengenal pasti perubahan akibat bukti baharu dan perkara yang patut kekal dalam rekod itu. Penyimpanan rekod secara berterusan dan pelaksanaan tindakan menjadi tanggungjawab aplikasi sekeliling model.

Pengeluar menerbitkan artifak BF16 dan FP8 yang berbeza serta resipi penyajian setempat dengan panjang konteks terkonfigurasi yang berbeza. Panjang penyajian yang dikonfigurasikan berasingan daripada spesifikasi model 512K. Kekalkan perbezaan edisi Preview dan ketepatan berangka apabila mengenal pasti model, serta minta hasil akhir yang menyatakan penemuan, perubahan cadangan dan bukti yang benar-benar dikumpulkan oleh aliran kerja.

Tersedia di Ailoot · input & kaedah

Ailoot Ultra · Anthropic Messages POST /v1/messages
Input
text
Output
text
Konteks
512,000 tokens
Output maksimum
460,800 tokens
Format output
JSON
MedanJenisKeperluanNilai & hadLalai
MedanmodelJenisstringKeperluanDiperlukanNilai & had
dots-studio/dots-3-note-preview:free
Lalai—
MedanmessagesJenisarrayKeperluanDiperlukanNilai & hadLalai—
MedanstreamJenisbooleanKeperluanPilihanNilai & had
false
Lalaifalse
MedansystemJenisstringKeperluanPilihanNilai & hadLalai—
Medanmax_tokensJenisintegerKeperluanDiperlukanNilai & had
Minimum: 1
Maksimum: 460,800
Lalai—
MedantemperatureJenisnumberKeperluanPilihanNilai & hadLalai—
Medantop_pJenisnumberKeperluanPilihanNilai & hadLalai—
Medantop_kJenisintegerKeperluanPilihanNilai & hadLalai—
Medanstop_sequencesJenisarrayKeperluanPilihanNilai & hadLalai—
MedanmetadataJenisobjectKeperluanPilihanNilai & hadLalai—
Parameter kaedah dan kitar hayat
ParameterKontrak
Parametercontent_typeKontrakapplication/json
ParameterrequiredKontrakmodel, messages, max_tokens
ParameteroptionalKontrakstream, system, temperature, top_p, top_k, stop_sequences, metadata
Parametermaterial_typesKontraktext
ParameterconditionsKontrakUse 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 512000 bytes.

Kitar hayat: synchronous_json

Pelan harga

Rujukan tarif tidak menambah pilihan permintaan. Parameter yang disokong disenaraikan untuk kaedah yang dipilih.

Mod pantas
Kadar standard Apabila mod pantas dipilih
Mod flex
Kadar standard Apabila mod flex dipilih
Usaha penaakulan maksimum
Kadar standard Apabila usaha penaakulan maksimum menggunakan pelarasan default
Kadar sifar untuk teks sahaja
Text input and output only. Cache, tools, media and streaming are unavailable. Untuk input dan output teks sahaja

Kadar Ailoot

Harga mengikut konfigurasi

KonfigurasiJadual kadarCaj
KonfigurasiKadar asas tokenJadual kadarKadar asasCaj
Input · Token input $0 / 1K token
Output · Token output $0 / 1K token
Input · Bacaan cache — / 1K token
Input · Penulisan cache — / 1K token
Input · Penulisan cache, 1 jam — / 1K token

Ailoot merizabkan anggaran amaun sebelum permintaan. Selepas hasil diterima, caj akhir diselesaikan berdasarkan penggunaan terukur. Penyelesaian caj penstriman menggunakan rekod penggunaan akhir. Cara rizab dan penyelesaian caj berfungsi →

Contoh permintaan

Ailoot Ultra · Anthropic Messages

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": "dots-studio/dots-3-note-preview: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

Terima dan simpan hasil

Ailoot Ultra · Anthropic Messages

JSON

Simpan semua hasil yang selesai

Simpan setiap respons lengkap, fail dan bahagian kandungan yang dikembalikan.

Retain the complete response, all actual results, original identifiers, usage and response headers.

Jika respons asal perlu disemak

Preserve the original response, headers and X-Client-Request-ID. An uncertain outcome does not authorize another creation.

Alias

Alias model

Ailoot Ultra dots-studio/dots-3-note-preview:free

Alias laluan kaedah

Gunakan laluan kaedah yang dipaparkan di atas.

ID pemanggil berkaitan

dots-studio/dots-3-note-preview:free

", "method_identity": { "effective_request_model_id": "dots-studio/dots-3-note-preview:free", "fmt": "messages", "http": "POST", "path": "/v1/messages", "request_model_id": "dots-studio/dots-3-note-preview:free", "route_label": "Ultra" }, "method_key": "Ultra|messages|/v1/messages|dots-studio%2Fdots-3-note-preview%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": "dots-studio/dots-3-note-preview: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": [ "dots-studio/dots-3-note-preview: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": 460800, "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": 460800, "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": [ "dots-studio/dots-3-note-preview: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": "dots-studio/dots-3-note-preview: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 512000 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": 512000, "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\": \"dots-studio/dots-3-note-preview: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": 460800, "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", "value": "Text input and output only. Cache, tools, media and streaming are unavailable.", "when": "For text-only input and output" } ], "pricing": { "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": "dots-studio/dots-3-note-preview: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" } ] } } ], "model_id": "dots-studio/dots-3-note-preview:free", "nativeProvenance": { "input_facts_canonical_sha256": "36568ef88ad958fa159230b9983bbab083cdfea9473053220bdbf1869ef817a6", "input_html_sha256": "369153a5525ad8a6b2a996233e9635497eb26359c17511a74257dbeab8f4a723", "private_audit_sha256": "8ce025f6a141b480d442a2e029efd44b94c0099037ba8f4528b7b08de5c0ba58", "role": "historical-normalized-input-audit-hashes", "schema": "ailoot-native-model-provenance-v2" }, "page": { "canonical": "https://ailoot.ai/models/ms/dots-studio-dots-3-note-preview-u003a-free/", "description": "dots3-note Preview daripada Dots Studio ialah model MoE multimodal untuk penaakulan, pengekodan dan aliran kerja ejen. Pengeluar menyenaraikan jumlah 280B parameter dengan 16B aktif, konteks 512K, input teks/imej/video/audio dan output teks.", "locale": "ms", "md_url": "https://ailoot.ai/models/ms/dots-studio-dots-3-note-preview-u003a-free/index.md", "title": "Dots Studio: Dots3-Note Preview (free) — Ailoot", "url": "https://ailoot.ai/models/ms/dots-studio-dots-3-note-preview-u003a-free/" }, "rawModel": { "about": "dots3-note Preview ialah ahli ringan dalam keluarga multimodal dots3 Dots Studio. Pengeluar menyenaraikan model mixture-of-experts dengan jumlah 280B parameter, 16B parameter aktif dan sokongan konteks sehingga 512K token. Model ini menerima teks, imej, video dan audio serta menghasilkan teks, dengan pengetahuan am, arahan, penaakulan, pengekodan dan kerja berorientasikan ejen antara tugasannya yang dinyatakan.\n\nTeras bahasanya mempunyai satu lapisan padat dan 45 lapisan pakar, dengan lapan pakar berhala dipilih daripada 256 bersama satu pakar dikongsi. Perhatiannya menggabungkan 13 lapisan perhatian jarang dan 33 lapisan tetingkap gelongsor. Pengeluar menyenaraikan pengekod penglihatan dan audio yang berasingan serta lapisan ramalan dikongsi. Komponen ini menyokong pemahaman multimodal; output model kekal teks, bukannya imej, pertuturan atau video yang dijana.\n\nUntuk analisis visual, bekalkan imej, halaman atau carta dan tanyakan ciri yang mempengaruhi keputusan. Tugasan dokumen yang berguna boleh membandingkan jadual yang kelihatan dengan keperluan bertulis dan mengembalikan baris berkaitan, tafsiran serta maklumat yang tiada. Untuk video, kenal pasti peristiwa atau urutan yang perlu diteliti; contoh input pengeluar menyertakan trek audio apabila klip mempunyai audio.\n\nUntuk audio, nyatakan sama ada tugasan memerlukan transkrip atau penjelasan bahan, dan berikan sebarang nama atau istilah domain yang diperlukan untuk tafsiran. Tugasan gabungan boleh menggunakan rakaman bersama latar belakang bertulis dan meminta penemuan disusun mengikut soalan yang dijawabnya. Hasilnya ialah artifak teks untuk dipaparkan atau diproses oleh aplikasi.\n\nTemplat perbualan pengeluar membezakan pemikiran daripada respons langsung. Mengaktifkan pemikiran menambah peringkat penaakulan; menyahaktifkannya mengembalikan jawapan secara terus. Sampel yang didokumenkan menggunakan temperature 1.0 dan top-p 0.95. Pilih tugasan dan hasil yang dikehendaki dengan jelas, serta tinggalkan ruang penjanaan yang mencukupi untuk jawapan tanpa menganggap peruntukan token sampel sebagai had output mutlak model.\n\nUntuk tugasan pengekodan, berikan sumber berkaitan, tingkah laku yang dijangkakan dan kegagalan yang diperhatikan atau perubahan yang diminta. Minta artifak cadangan dan semakan yang akan menilainya. Dalam aliran kerja ejen bersambung, model mencadangkan interaksi alat, manakala aplikasi melaksanakannya dan mengembalikan hasil. Pembangun menerbitkan penghurai panggilan alat khusus; aplikasi sekeliling membekalkan alat sebenar dan aksesnya.\n\nKerja interaktif boleh memerlukan penerokaan, penyesuaian dan pengemaskinian memori kerja tugasan. Simpan rekod ringkas tentang objektif, penemuan yang disahkan dan syarat yang belum diselesaikan. Minta giliran seterusnya mengenal pasti perubahan akibat bukti baharu dan perkara yang patut kekal dalam rekod itu. Penyimpanan rekod secara berterusan dan pelaksanaan tindakan menjadi tanggungjawab aplikasi sekeliling model.\n\nPengeluar menerbitkan artifak BF16 dan FP8 yang berbeza serta resipi penyajian setempat dengan panjang konteks terkonfigurasi yang berbeza. Panjang penyajian yang dikonfigurasikan berasingan daripada spesifikasi model 512K. Kekalkan perbezaan edisi Preview dan ketepatan berangka apabila mengenal pasti model, serta minta hasil akhir yang menyatakan penemuan, perubahan cadangan dan bukti yang benar-benar dikumpulkan oleh aliran kerja.", "alias_of": null, "aliases": [], "author": "Dots Studio", "capabilities": { "context_length": 512000, "manufacturer_input": [ "text", "image" ], "manufacturer_output": [ "text" ] }, "card_routes": [ { "label": "Ultra", "rates": [ { "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" } ], "summary": "Maklumat lengkap tentang harga konfigurasi terdapat dalam butiran." } ], "ctx": null, "formats": [ "chat", "messages" ], "id": "dots-studio/dots-3-note-preview:free", "input": [ "text" ], "kind": "text", "max_out": null, "methods": [ { "available": null, "cache_read": null, "cache_write": null, "cache_write_1h": null, "contract": { "data": { "all_results": "Retain the complete response, all actual results, original identifiers, usage and response headers.", "authentication": { "api_key_source": "AILOOT_API_KEY", "header": "Authorization: Bearer" }, "example_body": { "messages": [ { "content": "Summarize the supplied text in three concise points.", "role": "user" } ], "model": "dots-studio/dots-3-note-preview: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": [ "dots-studio/dots-3-note-preview: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": 460800, "minimum": 1, "name": "max_tokens", "required": false, "type": "integer" }, { "default_known": false, "enum_known": false, "maximum": 460800, "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": 460800, "minimum": 1, "type": "integer" }, "max_tokens": { "maximum": 460800, "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": [ "dots-studio/dots-3-note-preview: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": "dots-studio/dots-3-note-preview: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 512000 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": 512000, "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\": \"dots-studio/dots-3-note-preview: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": 460800, "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": "dots-studio/dots-3-note-preview: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": "dots-studio/dots-3-note-preview: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": [ "dots-studio/dots-3-note-preview: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": 460800, "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": 460800, "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": [ "dots-studio/dots-3-note-preview: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": "dots-studio/dots-3-note-preview: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 512000 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": 512000, "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\": \"dots-studio/dots-3-note-preview: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": 460800, "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", "value": "Text input and output only. Cache, tools, media and streaming are unavailable.", "when": "For text-only input and output" } ], "pricing": { "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": "dots-studio/dots-3-note-preview: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" } ] } ], "model_aliases": [ { "canonical_model_id": "dots-studio/dots-3-note-preview:free", "request_model_id": "dots-studio/dots-3-note-preview:free", "route_label": "Ultra" } ], "name": "Dots Studio: Dots3-Note Preview (free)", "price": { "in": 0, "in_label": null, "out": 0, "out_label": null, "scope_label": "Token rates", "sort_in": 0, "sort_out": 0, "varies": true }, "short": "dots3-note Preview daripada Dots Studio ialah model MoE multimodal untuk penaakulan, pengekodan dan aliran kerja ejen. Pengeluar menyenaraikan jumlah 280B parameter dengan 16B aktif, konteks 512K, input teks/imej/video/audio dan output teks." }, "renderer_schema": { "method_order": "Original DTO methods order; every exact route/format/path/caller survives.", "prices": "Original public DTO fields and original native display HTML; no flattened or normalized offers." }, "representation": "exact-public-dto-and-native-renderer-html", "representationNotes": { "current_reference": { "about_json_pointer": "/aboutHtml", "methods": [ { "contract_json_pointer": "/methods/0/rawMethod/contract", "html_json_pointer": "/methods/0/html", "method_ordinal": 0 }, { "contract_json_pointer": "/methods/1/rawMethod/contract", "html_json_pointer": "/methods/1/html", "method_ordinal": 1 } ], "role": "current-semantic-reference" }, "raw_input": { "examples_role": "historical-input-not-current-ready-examples", "json_pointers": [ "/rawModel", "/methods/0/rawMethod", "/methods/1/rawMethod" ], "role": "historical-owner-input" }, "schema": "ailoot-native-model-representations-v1" }, "schema": "ailoot-static-model-facts-v1", "schema_version": 1, "shortText": "dots3-note Preview daripada Dots Studio ialah model MoE multimodal untuk penaakulan, pengekodan dan aliran kerja ejen. Pengeluar menyenaraikan jumlah 280B parameter dengan 16B aktif, konteks 512K, input teks/imej/video/audio dan output teks.", "source": { "audit_sha256": "2e00086bcbfc28e64d0cebe97aa47c17d8d5618963027f8ffb9dc6123d7d25b1", "bridge_map_sha256": "1125275768b9636fc8461bc7da5061239a81ddfe508e2557843ca42c58ab0036", "raw_model_json_sha256": "ad29539800bc6c0301e436a019a8aaf15c15812687a1e0c0a0dacd74e58c4a2f", "renderer_sha256": "1dab5ba62521e9568c8b7c82005622cabbf330a075df7cce1f83274a04009460" }, "sourceRevision": "45becc919b2237ebeeba47b9f3ee0a3485b92e5a6f13f4c555906d3ea86dd4e7" }