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Ministral 3 8B Instruct 2512 是 Mistral AI 的 Ministral 3 系列中，規模居中的指令微調模型。發布的檢查點以 FP8 精度針對聊天與指令任務進行後訓練。它結合語言元件與視覺編碼器，接受文字與影像並回傳文字，而非影像或音訊成品。

架構與主要功能

原廠列出 84 億參數語言模型及 4 億參數視覺編碼器。其上下文視窗描述為 256k，公開使用說明中的預設設定長度為 262,144。這些描述屬於此 8B 規模版本；較小的 3B 及較大的 14B 系列成員，仍有各自的元件規模與設定。

視覺能力讓模型輸入不限於書面對話。文件影像可搭配關於特定欄位、段落或可見關係的問題。截圖可搭配使用者目標，要求辨識相關控制項。回答依賴視覺細節時，請要求列出支持每項結論的觀察，並保留解讀裁切影像所需的標題、標籤及單位。

模型卡描述涵蓋數十種語言的多語言工作，包括英語、法語、西班牙語、德語、義大利語、葡萄牙語、荷蘭語、中文、日語、韓語及阿拉伯語，也指出對系統指令的遵循、原生函式呼叫及 JSON 輸出。請明確定義最終語言、角色與輸出需求，而非讓模型從大量輸入自行推測預期成品。

文件、對話與代理任務

原廠的使用案例包括聊天介面、日常助理、影像與文件描述、翻譯、內容生成及專用代理。對文件助理，請提供頁面並指定要回傳的資訊。擷取請求可以列出欄位標籤、預期型別及缺漏值的處理方式。實用回答可包含文件識別碼、擷取值，以及對應可見來源的簡短說明。

對持續中的對話，請保留相關的先前回答，並提出聚焦的追問。使用者可以先要求文件摘要，再詢問哪項陳述支持某個結論。這會將所需輸出從一般概覽改為連結來源的說明，同時保留原始材料與對話目的。

進行多語言編輯時，請提供原始段落、目標讀者與術語表。要求修訂版本保留名稱、條件與單位，再視需要附上簡短的變更說明。生成內容時，先指定讀者及應出現的事實，再要求短篇草稿或替代措辭。

在代理任務中，應用程式提供工具及其參數。模型可以選擇函式並準備引數，而應用程式執行並回傳結果。模型卡的函式範例將影像問題與計算工具結合。請將工具結果與建議呼叫分開，讓後續書面回答使用操作實際回傳的資訊。

建議的準備與設定

原廠建議透過系統指令描述環境、使用案例及工具的使用方式。工具集合應定義清楚，並限於任務所需的最低數量。小型查詢工作流程可以提供與當前問題相關的函式，清楚命名必要引數，而非呈現大量無關操作。

對日常與正式環境型用途，模型卡建議 temperature 低於 0.1，創意探索則可使用較高溫度。請將此視為指令工作流程的建議，而非獨立的推理模式控制。此系列具有不同的 Base、Instruct 及 Reasoning 檢查點；本條目是 Instruct 2512 版本，並非同規模的獨立 Reasoning 發布版本。

對影像，原廠建議長寬比接近 1:1，避免過於狹長或寬扁的輸入。必要時裁切，同時保留問題所需的標籤與上下文。如果頁面包含數個無關區域，請指出要檢查的部分及要回傳的結果。清晰、聚焦的影像，比要求模型猜測寬廣頁面中的哪個小細節重要，更有幫助。

上下文與版本界線

請依設定的上下文規劃文字、影像、對話及期望回答。使用說明明確允許在不需要那麼多上下文時，減少設定的模型長度，因此完整視窗並非要求每次請求都填入所有可用材料。模型卡的 512 個 token 生成範例只是範例設定，已讀來源並未確立獨立的硬性最大回答長度。

FP8 Instruct 檢查點、預訓練 Base 版本及 Reasoning 版本是不同版本。原廠也將專門化與微調描述為使用案例。準備對話時，請保留具名檢查點及其 tokenizer，並將文字生成與儲存庫存取、函式執行或周邊應用程式提供的其他動作區分。

", "aboutText": "Ministral 3 8B Instruct 2512 是 Mistral AI 的 Ministral 3 系列中，規模居中的指令微調模型。發布的檢查點以 FP8 精度針對聊天與指令任務進行後訓練。它結合語言元件與視覺編碼器，接受文字與影像並回傳文字，而非影像或音訊成品。\n\n架構與主要功能\n\n原廠列出 84 億參數語言模型及 4 億參數視覺編碼器。其上下文視窗描述為 256k，公開使用說明中的預設設定長度為 262,144。這些描述屬於此 8B 規模版本；較小的 3B 及較大的 14B 系列成員，仍有各自的元件規模與設定。\n\n視覺能力讓模型輸入不限於書面對話。文件影像可搭配關於特定欄位、段落或可見關係的問題。截圖可搭配使用者目標，要求辨識相關控制項。回答依賴視覺細節時，請要求列出支持每項結論的觀察，並保留解讀裁切影像所需的標題、標籤及單位。\n\n模型卡描述涵蓋數十種語言的多語言工作，包括英語、法語、西班牙語、德語、義大利語、葡萄牙語、荷蘭語、中文、日語、韓語及阿拉伯語，也指出對系統指令的遵循、原生函式呼叫及 JSON 輸出。請明確定義最終語言、角色與輸出需求，而非讓模型從大量輸入自行推測預期成品。\n\n文件、對話與代理任務\n\n原廠的使用案例包括聊天介面、日常助理、影像與文件描述、翻譯、內容生成及專用代理。對文件助理，請提供頁面並指定要回傳的資訊。擷取請求可以列出欄位標籤、預期型別及缺漏值的處理方式。實用回答可包含文件識別碼、擷取值，以及對應可見來源的簡短說明。\n\n對持續中的對話，請保留相關的先前回答，並提出聚焦的追問。使用者可以先要求文件摘要，再詢問哪項陳述支持某個結論。這會將所需輸出從一般概覽改為連結來源的說明，同時保留原始材料與對話目的。\n\n進行多語言編輯時，請提供原始段落、目標讀者與術語表。要求修訂版本保留名稱、條件與單位，再視需要附上簡短的變更說明。生成內容時，先指定讀者及應出現的事實，再要求短篇草稿或替代措辭。\n\n在代理任務中，應用程式提供工具及其參數。模型可以選擇函式並準備引數，而應用程式執行並回傳結果。模型卡的函式範例將影像問題與計算工具結合。請將工具結果與建議呼叫分開，讓後續書面回答使用操作實際回傳的資訊。\n\n建議的準備與設定\n\n原廠建議透過系統指令描述環境、使用案例及工具的使用方式。工具集合應定義清楚，並限於任務所需的最低數量。小型查詢工作流程可以提供與當前問題相關的函式，清楚命名必要引數，而非呈現大量無關操作。\n\n對日常與正式環境型用途，模型卡建議 temperature 低於 0.1，創意探索則可使用較高溫度。請將此視為指令工作流程的建議，而非獨立的推理模式控制。此系列具有不同的 Base、Instruct 及 Reasoning 檢查點；本條目是 Instruct 2512 版本，並非同規模的獨立 Reasoning 發布版本。\n\n對影像，原廠建議長寬比接近 1:1，避免過於狹長或寬扁的輸入。必要時裁切，同時保留問題所需的標籤與上下文。如果頁面包含數個無關區域，請指出要檢查的部分及要回傳的結果。清晰、聚焦的影像，比要求模型猜測寬廣頁面中的哪個小細節重要，更有幫助。\n\n上下文與版本界線\n\n請依設定的上下文規劃文字、影像、對話及期望回答。使用說明明確允許在不需要那麼多上下文時，減少設定的模型長度，因此完整視窗並非要求每次請求都填入所有可用材料。模型卡的 512 個 token 生成範例只是範例設定，已讀來源並未確立獨立的硬性最大回答長度。\n\nFP8 Instruct 檢查點、預訓練 Base 版本及 Reasoning 版本是不同版本。原廠也將專門化與微調描述為使用案例。準備對話時，請保留具名檢查點及其 tokenizer，並將文字生成與儲存庫存取、函式執行或周邊應用程式提供的其他動作區分。", "editorialOverlay": { "copy_fields": null, "copy_sha256": null, "copy_source": null, "html_sha256": "1d277a1acd05d3e9e36df0352b07626efd532cea3e1b13ec3ee6b45dcc46a1cd", "module_sha256": "ee9dc1c50b1e6a8fb7fa062030fcb4646b9aaaeb08be513b723a5a92a7290f06", "raw_model_unchanged": true, "schema": "ailoot-native-model-editorial-v1" }, "locale": "zh-hant-tw", "methods": [ { "html": "

•

Mistral: Ministral 3 8B 2512 (batch)

Mistral /mistralai/ministral-8b-2512:batch

入門

Ministral 3 8B Instruct 2512 是多語言文字與影像指令模型，具備 84 億參數語言元件與 4 億參數視覺編碼器。它支援原廠提供的 256k 上下文、系統指令、JSON 及原生函式呼叫，適用於助理與文件工作流程。

接受的輸入: 文字
結果: 文字

關於模型

此說明介紹模型的能力。Ailoot 可用的輸入、輸出與選項，依所選方法列於下方。

Ministral 3 8B Instruct 2512 是 Mistral AI 的 Ministral 3 系列中，規模居中的指令微調模型。發布的檢查點以 FP8 精度針對聊天與指令任務進行後訓練。它結合語言元件與視覺編碼器，接受文字與影像並回傳文字，而非影像或音訊成品。

架構與主要功能

原廠列出 84 億參數語言模型及 4 億參數視覺編碼器。其上下文視窗描述為 256k，公開使用說明中的預設設定長度為 262,144。這些描述屬於此 8B 規模版本；較小的 3B 及較大的 14B 系列成員，仍有各自的元件規模與設定。

視覺能力讓模型輸入不限於書面對話。文件影像可搭配關於特定欄位、段落或可見關係的問題。截圖可搭配使用者目標，要求辨識相關控制項。回答依賴視覺細節時，請要求列出支持每項結論的觀察，並保留解讀裁切影像所需的標題、標籤及單位。

模型卡描述涵蓋數十種語言的多語言工作，包括英語、法語、西班牙語、德語、義大利語、葡萄牙語、荷蘭語、中文、日語、韓語及阿拉伯語，也指出對系統指令的遵循、原生函式呼叫及 JSON 輸出。請明確定義最終語言、角色與輸出需求，而非讓模型從大量輸入自行推測預期成品。

文件、對話與代理任務

原廠的使用案例包括聊天介面、日常助理、影像與文件描述、翻譯、內容生成及專用代理。對文件助理，請提供頁面並指定要回傳的資訊。擷取請求可以列出欄位標籤、預期型別及缺漏值的處理方式。實用回答可包含文件識別碼、擷取值，以及對應可見來源的簡短說明。

對持續中的對話，請保留相關的先前回答，並提出聚焦的追問。使用者可以先要求文件摘要，再詢問哪項陳述支持某個結論。這會將所需輸出從一般概覽改為連結來源的說明，同時保留原始材料與對話目的。

進行多語言編輯時，請提供原始段落、目標讀者與術語表。要求修訂版本保留名稱、條件與單位，再視需要附上簡短的變更說明。生成內容時，先指定讀者及應出現的事實，再要求短篇草稿或替代措辭。

在代理任務中，應用程式提供工具及其參數。模型可以選擇函式並準備引數，而應用程式執行並回傳結果。模型卡的函式範例將影像問題與計算工具結合。請將工具結果與建議呼叫分開，讓後續書面回答使用操作實際回傳的資訊。

建議的準備與設定

原廠建議透過系統指令描述環境、使用案例及工具的使用方式。工具集合應定義清楚，並限於任務所需的最低數量。小型查詢工作流程可以提供與當前問題相關的函式，清楚命名必要引數，而非呈現大量無關操作。

對日常與正式環境型用途，模型卡建議 temperature 低於 0.1，創意探索則可使用較高溫度。請將此視為指令工作流程的建議，而非獨立的推理模式控制。此系列具有不同的 Base、Instruct 及 Reasoning 檢查點；本條目是 Instruct 2512 版本，並非同規模的獨立 Reasoning 發布版本。

對影像，原廠建議長寬比接近 1:1，避免過於狹長或寬扁的輸入。必要時裁切，同時保留問題所需的標籤與上下文。如果頁面包含數個無關區域，請指出要檢查的部分及要回傳的結果。清晰、聚焦的影像，比要求模型猜測寬廣頁面中的哪個小細節重要，更有幫助。

上下文與版本界線

請依設定的上下文規劃文字、影像、對話及期望回答。使用說明明確允許在不需要那麼多上下文時，減少設定的模型長度，因此完整視窗並非要求每次請求都填入所有可用材料。模型卡的 512 個 token 生成範例只是範例設定，已讀來源並未確立獨立的硬性最大回答長度。

FP8 Instruct 檢查點、預訓練 Base 版本及 Reasoning 版本是不同版本。原廠也將專門化與微調描述為使用案例。準備對話時，請保留具名檢查點及其 tokenizer，並將文字生成與儲存庫存取、函式執行或周邊應用程式提供的其他動作區分。

Ailoot 可用 · 輸入與方法

Ailoot Ultra · 批次處理（Batch） POST /v1/batches

輸入: text
輸出: text
輸出格式: 內嵌的 results[].response.body JSON

欄位	類型	要求	值與限制	預設值
欄位`endpoint`	類型`string`	要求必填	值與限制 /v1/chat/completions	預設值—
欄位`model`	類型`string`	要求必填	值與限制 mistralai/ministral-8b-2512:batch	預設值—
欄位`requests`	類型`batch_item[]`	要求必填	值與限制項目數下限: 1	預設值—
欄位`requests[].custom_id`	類型`string`	要求必填	值與限制	預設值—
欄位`requests[].body.messages`	類型`message[]`	要求必填	值與限制	預設值—
欄位`completion_window`	類型`string`	要求選填	值與限制 24h	預設值—
欄位`provider`	類型`object\|null`	要求選填	值與限制	預設值—
欄位`requests[].body.model`	類型`string`	要求選填	值與限制 mistralai/ministral-8b-2512:batch, mistralai/ministral-8b-2512	預設值—
欄位`provider.only`	類型`string[]`	要求選填	值與限制 mistral	預設值—
欄位`provider.allow_fallbacks`	類型`boolean\|null`	要求選填	值與限制 false, null	預設值—

方法參數與生命週期

參數	規格
參數`content_type`	規格application/json
參數`required`	規格endpoint, model, requests
參數`material_types`	規格text
參數`representation`	規格內嵌的 requests[]；每個項目皆含 custom_id 與 body
參數`request_endpoint_profile`	規格/v1/chat/completions
參數`file_material`	規格呼叫端可在本機將實際的 UTF-8 JSONL 讀入 requests[]。此流程不使用上傳用途、input_file_id 或檔案參照。若缺少客戶素材或素材為空，應在 POST 前停止準備。
參數`serialization_order`	規格endpoint, model, provider（如有提供）, completion_window（如有提供）, requests 放在最後
參數`optional_controls`	規格provider.only, provider.allow_fallbacks, completion_window
參數`schema_scope`	規格依文件規定的內嵌 Batch 封裝格式提供文字 Chat Completions 請求主體。

生命週期： asynchronous

GET /v1/batches/{operation_id} · 原始建立回應中實際回傳的 response.id；使用相同使用者／金鑰／群組

方案

費率資訊不會增加請求選項。支援的參數列於所選方法中。

快速模式: 未指定選取快速模式時
flex 模式: 未指定選取 flex 模式時
最高推理強度: 未指定最高推理強度採用 default 調整值時
顯式快取計價: 未啟用請求顯式快取時

Ailoot 費率

各設定的價格

請逐一核對各項費用與所列條件。每組互為替代選項的設定只套用一種費率。

設定	費率表	上下文 Token 數大於	上下文 Token 數小於或等於	費用
設定詞元基本費率	費率表基本費率	上下文 Token 數大於—	上下文 Token 數小於或等於無上限	費用輸入 · 輸入 Token $0.00015 / 1K Token 輸出 · 輸出 Token $0.00015 / 1K Token 輸入 · 讀取快取 $0.000015 / 1K Token 輸入 · 寫入快取 — / 1K Token 輸入 · 寫入快取，1 小時 — / 1K Token
設定請求長度級距 1	費率表—	上下文 Token 數大於0	上下文 Token 數小於或等於無上限	費用輸入 · 輸入 Token $0.00015 / 1K Token 輸出 · 輸出 Token $0.00015 / 1K Token 輸入 · 讀取快取 $0.000015 / 1K Token 輸入 · 寫入快取 — / 1K Token 輸入 · 寫入快取，1 小時 — / 1K Token

Ailoot 會在請求前預留估算金額。取得結果後，依實測用量結算最終費用。串流結算採用最終用量紀錄。預留金額與結算的運作方式 →

請求範例

Ailoot Ultra · 批次處理（Batch）

set -eu\n: "${AILOOT_API_KEY:?Set your Ailoot API key}"\npython3 - <<'PY_REQUEST'\nimport json\nfrom pathlib import Path\nbody=json.loads('{"endpoint":"/v1/chat/completions","model":"mistralai/ministral-8b-2512:batch","requests":[{"custom_id":"req-0001","body":{"messages":[{"role":"user","content":"Hello!"}],"max_tokens":16}}]}')\nPath("batch-request.json").write_text(json.dumps(body,ensure_ascii=False),encoding="utf-8")\nPY_REQUEST\ncurl --fail-with-body --silent --show-error https://api.ailoot.ai/v1/batches \\\n  -H "Authorization: Bearer $AILOOT_API_KEY" -H 'Content-Type: application/json' \\\n  --data-binary @batch-request.json -D batch-response-headers.txt -o batch-create-response.json\n

import json, os\nfrom pathlib import Path\nfrom urllib.request import Request, urlopen\n\ndef prepare_requests(customer_path):\n    path = Path(customer_path)\n    if not path.is_file(): raise ValueError("Customer JSONL file is missing")\n    items = [json.loads(line) for line in path.read_text(encoding="utf-8").splitlines() if line.strip()]\n    if not items: raise ValueError("Customer JSONL contains no requests")\n    ids = set()\n    for item in items:\n        if set(item) != {"custom_id", "body"}: raise ValueError("Each item needs custom_id and body")\n        cid = item["custom_id"]\n        if not isinstance(cid, str) or not cid.strip() or cid in ids: raise ValueError("custom_id must be nonempty and unique")\n        ids.add(cid)\n        if not isinstance(item["body"], dict) or not item["body"].get("messages"): raise ValueError("Supply actual text messages")\n        supplied_model = item["body"].get("model")\n        if supplied_model is not None and supplied_model not in ['mistralai/ministral-8b-2512:batch', 'mistralai/ministral-8b-2512']: raise ValueError("body.model must be an exact documented caller or wire ID")\n    return {"endpoint":"/v1/chat/completions", "model":"mistralai/ministral-8b-2512:batch", "requests":items}\n\nif __name__ == "__main__":\n    material = os.environ.get("AILOOT_BATCH_REQUESTS_JSONL", "")\n    if not material: raise SystemExit("Set AILOOT_BATCH_REQUESTS_JSONL to your actual customer file")\n    body = prepare_requests(material)\n    key = os.environ.get("AILOOT_API_KEY", "")\n    if not key: raise SystemExit("Set AILOOT_API_KEY")\n    request = Request("https://api.ailoot.ai/v1/batches", data=json.dumps(body, ensure_ascii=False).encode("utf-8"), headers={"Authorization":"Bearer " + key, "Content-Type":"application/json"}, method="POST")\n    with urlopen(request) as response:\n        raw = response.read()\n        Path("batch-create-response.json").write_bytes(raw)\n        print(raw.decode("utf-8"))\n

import json\nfrom pathlib import Path\nraw = Path("batch-status-response.json").read_bytes()\nresponse = json.loads(raw)\nif response.get("status") != "completed":\n    raise SystemExit("Keep the original operation; read its status without resubmitting")\nresults = response.get("results")\nif not isinstance(results, list) or not results:\n    raise SystemExit("Preserve the original response; completed results are missing")\nPath("batch-results.jsonl").write_text("".join(json.dumps(item, ensure_ascii=False) + "\\n" for item in results), encoding="utf-8")\n# Preserve batch-status-response.json with aggregate usage and every result/error.\n

接收並儲存結果

Ailoot Ultra · 批次處理（Batch）

內嵌的 results[].response.body JSON

GET /v1/batches/{operation_id}

查看工作狀態

set -eu\n: "${AILOOT_API_KEY:?Set your Ailoot API key}"\nBATCH_OPERATION_ID="$(python3 - <<'PY_ID'\nimport json\nfrom pathlib import Path\nfrom urllib.parse import quote\nresponse = json.loads(Path("batch-create-response.json").read_text(encoding="utf-8"))\noperation = response.get("id")\nif not isinstance(operation, str) or not operation: raise SystemExit("No actual original operation ID; preserve the response and do not resubmit")\nprint(quote(operation, safe=""))\nPY_ID\n)"\ncurl --fail-with-body --silent --show-error "https://api.ailoot.ai/v1/batches/$BATCH_OPERATION_ID" \\\n  -H "Authorization: Bearer $AILOOT_API_KEY" -o batch-status-response.json\n

保留所有已完成的結果

請保留所有完整傳回的回應、檔案與內容區塊。

保留完整的原始狀態 JSON、每個結果／custom_id，以及完整的回應或錯誤主體。將已完成的 results[] 儲存為 JSONL，不得篩除任何項目。

需要檢查原始回應時

保留原始作業 ID。503 result_pending_check 回應帶有 X-Should-Retry:false；請勿重新提交狀態不明的原始批次。

回應欄位

欄位	類型
欄位`results[].custom_id`	類型string
欄位`results[].response.body.choices[].message.content`	類型string\|null
欄位`results[].error`	類型object\|null
欄位`usage`	類型object\|null
欄位`id`	類型string
欄位`model`	類型string
欄位`endpoint`	類型string
欄位`status`	類型string
欄位`request_counts`	類型object
欄位`results[].id`	類型string
欄位`results[].response.status_code`	類型integer
欄位`results[].response.request_id`	類型string

錯誤與後續步驟

回應	條件	下一步
回應400 · `invalid_request_error`	條件文件規定的內嵌封裝格式無效、索引鍵重複、項目識別有誤，或與已設定的模型能力衝突。	下一步再次提交前，請先修正指出的欄位。
回應401 · `authentication_error`	條件API 金鑰無效。	下一步使用已獲授權的 Ailoot 金鑰。
回應403 · `permission_error`	條件批次處理群組無法使用。	下一步檢查金鑰／群組的使用權限。
回應422 · `invalid_request_error`	條件批次處理採用餘額計費；透過訂閱建立批次的請求會遭拒絕。	下一步使用已獲授權、以餘額計費的群組。
回應422 · `price_unavailable`	條件無法為批次輸入估價。	下一步保留回應；使用文件規定的該 API 家族輸入格式。
回應402 · `billing_error`	條件批次處理的預留額度無法取得。	下一步提交新請求前，請先解決請求受理問題。
回應503 · `price_unavailable`	條件批次處理方法的價格／原生費率無法取得。	下一步保留回應；請勿替換價格。
回應503 · `api_error`	條件指定的供應商路由無法使用。	下一步保留回應，以供修復路由。
回應503 · `result_pending_check`	條件原始結果需要檢查；X-Should-Retry:false。	下一步保留原始 operation_id/id 並讀取其狀態；請勿重複原始 POST。
回應404 · `not_found`	條件查詢批次狀態所需的作業不存在，或屬於其他身分。	下一步使用完全相同的原始 id，以及相同的使用者／金鑰／群組。

別名

模型別名

Ailoot Ultra mistralai/ministral-8b-2512:batch

方法路徑別名

請使用上方列出的 API 方法路徑。

相關呼叫用 ID

mistralai/ministral-8b-2512:batch

", "method_identity": { "effective_request_model_id": "mistralai/ministral-8b-2512:batch", "fmt": "batches", "http": "POST", "path": "/v1/batches", "request_model_id": "mistralai/ministral-8b-2512:batch", "route_label": "Ultra" }, "method_key": "Ultra|batches|/v1/batches|mistralai%2Fministral-8b-2512%3Abatch", "ordinal": 0, "rawMethod": { "available": null, "cache_read": 0.015, "cache_write": null, "cache_write_1h": null, "contract": { "data": { "all_results": "Preserve full JSON and every result; provider real IDs are only read from actual returned responses.", "authentication": { "api_key_source": "AILOOT_API_KEY", "header": "Authorization: Bearer" }, "errors": [ { "code": null, "condition": "文件規定的內嵌封裝格式無效、索引鍵重複、項目識別有誤，或與已設定的模型能力衝突。", "http_status": 400, "recovery": "再次提交前，請先修正指出的欄位。", "type": "invalid_request_error" }, { "code": null, "condition": "API 金鑰無效。", "http_status": 401, "recovery": "使用已獲授權的 Ailoot 金鑰。", "type": "authentication_error" }, { "code": null, "condition": "批次處理群組無法使用。", "http_status": 403, "recovery": "檢查金鑰／群組的使用權限。", "type": "permission_error" }, { "code": null, "condition": "批次處理採用餘額計費；透過訂閱建立批次的請求會遭拒絕。", "http_status": 422, "recovery": "使用已獲授權、以餘額計費的群組。", "type": "invalid_request_error" }, { "code": null, "condition": "無法為批次輸入估價。", "http_status": 422, "recovery": "保留回應；使用文件規定的該 API 家族輸入格式。", "type": "price_unavailable" }, { "code": null, "condition": "批次處理的預留額度無法取得。", "http_status": 402, "recovery": "提交新請求前，請先解決請求受理問題。", "type": "billing_error" }, { "code": null, "condition": "批次處理方法的價格／原生費率無法取得。", "http_status": 503, "recovery": "保留回應；請勿替換價格。", "type": "price_unavailable" }, { "code": null, "condition": "指定的供應商路由無法使用。", "http_status": 503, "recovery": "保留回應，以供修復路由。", "type": "api_error" }, { "code": "result_pending_check", "condition": "原始結果需要檢查；X-Should-Retry:false。", "http_status": 503, "recovery": "保留原始 operation_id/id 並讀取其狀態；請勿重複原始 POST。", "type": null }, { "code": "not_found", "condition": "查詢批次狀態所需的作業不存在，或屬於其他身分。", "http_status": 404, "recovery": "使用完全相同的原始 id，以及相同的使用者／金鑰／群組。", "type": null } ], "example_body": { "endpoint": "/v1/chat/completions", "model": "mistralai/ministral-8b-2512:batch", "requests": [ { "body": { "max_tokens": 16, "messages": [ { "content": "Hello!", "role": "user" } ] }, "custom_id": "req-0001" } ] }, "input_constraints": [ "Use the exact shown :batch model ID.", "Each custom_id must be nonempty and unique within the batch.", "Keep requests last in the serialized body; duplicate JSON keys are rejected.", "Each body.model is omitted or equals the exact batch caller or its documented base ID.", "Per-item provider, service_tier and input_type are outside this batch profile.", "stream is omitted or false.", "Supply text messages for this Chat batch profile; image/audio/file/video objects, hosted tools and cache-control fields are outside this profile.", "If body.model is present, use only the exact caller or wire ID listed here; no suffix conversion is needed.", "For google/ wire IDs, all items use an identical response_format." ], "outputs": { "all_results": "保留完整的原始狀態 JSON、每個結果／custom_id，以及完整的回應或錯誤主體。將已完成的 results[] 儲存為 JSONL，不得篩除任何項目。", "enclosing_family": "batch", "family": "text", "fields": [ { "name": "results[].custom_id", "type": "string" }, { "name": "results[].response.body.choices[].message.content", "type": "string|null" }, { "name": "results[].error", "type": "object|null" }, { "name": "usage", "type": "object|null" }, { "description": null, "name": "id", "type": "string" }, { "description": null, "name": "model", "type": "string" }, { "description": null, "name": "endpoint", "type": "string" }, { "description": null, "name": "status", "type": "string" }, { "description": null, "name": "request_counts", "type": "object" }, { "description": null, "name": "results[].id", "type": "string" }, { "description": null, "name": "results[].response.status_code", "type": "integer" }, { "description": null, "name": "results[].response.request_id", "type": "string" } ], "format": "內嵌的 results[].response.body JSON" }, "parameters": [ { "availability": "source_interface", "default": null, "default_known": false, "enum": [ "/v1/chat/completions" ], "enum_known": true, "name": "endpoint", "required": true, "type": "string" }, { "availability": "source_interface", "default": null, "default_known": false, "enum": [ "mistralai/ministral-8b-2512:batch" ], "enum_known": true, "name": "model", "required": true, "type": "string" }, { "availability": "source_interface", "default": null, "default_known": false, "enum": null, "enum_known": false, "min_items": 1, "name": "requests", "required": true, "type": "batch_item[]" }, { "availability": "source_interface", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "requests[].custom_id", "required": true, "type": "string", "unique_within_batch": true }, { "availability": "source_interface", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "requests[].body.messages", "required": true, "type": "message[]" }, { "availability": "source_interface", "default": null, "default_known": false, "enum": [ "24h" ], "enum_known": true, "name": "completion_window", "required": false, "type": "string" }, { "availability": "source_interface", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "provider", "required": false, "type": "object|null" }, { "availability": "source_interface", "default": null, "default_known": false, "enum": [ "mistralai/ministral-8b-2512:batch", "mistralai/ministral-8b-2512" ], "enum_known": true, "name": "requests[].body.model", "required": false, "type": "string" }, { "availability": "source_interface", "default": null, "default_known": false, "enum": [ [ "mistral" ] ], "enum_known": true, "name": "provider.only", "required": false, "type": "string[]" }, { "availability": "source_interface", "default": null, "default_known": false, "enum": [ false, null ], "enum_known": true, "name": "provider.allow_fallbacks", "required": false, "type": "boolean|null" } ], "provider_policy": { "allow_fallbacks": false, "configured_only": [ "mistral" ], "per_item_override": false, "when_omitted": "Current Source injects the exact persisted declaration before fresh submission." }, "request_schema": { "additionalProperties": false, "properties": { "completion_window": { "enum": [ "24h" ], "type": "string" }, "endpoint": { "enum": [ "/v1/chat/completions" ], "type": "string" }, "model": { "enum": [ "mistralai/ministral-8b-2512:batch" ], "type": "string" }, "provider": { "additionalProperties": false, "properties": { "allow_fallbacks": { "enum": [ false, null ], "type": [ "boolean", "null" ] }, "only": { "enum": [ [ "mistral" ] ], "items": { "enum": [ "mistral" ], "type": "string" }, "maxItems": 1, "minItems": 1, "type": "array" } }, "type": [ "object", "null" ] }, "requests": { "items": { "additionalProperties": false, "properties": { "body": { "additionalProperties": true, "properties": { "max_tokens": { "minimum": 1, "type": "integer" }, "messages": { "items": { "properties": { "content": { "type": "string" }, "role": { "type": "string" } }, "required": [ "role", "content" ], "type": "object" }, "minItems": 1, "type": "array" }, "model": { "enum": [ "mistralai/ministral-8b-2512:batch", "mistralai/ministral-8b-2512" ], "type": "string" } }, "required": [ "messages" ], "type": "object" }, "custom_id": { "minLength": 1, "type": "string" } }, "required": [ "custom_id", "body" ], "type": "object" }, "minItems": 1, "type": "array" } }, "required": [ "endpoint", "model", "requests" ], "type": "object" }, "schema_template": { "endpoint": "/v1/chat/completions", "model": "mistralai/ministral-8b-2512:batch", "requests": [ { "body": { "max_tokens": 16, "messages": [ { "content": "Hello!", "role": "user" } ] }, "custom_id": "req-0001" } ] }, "unsupported": [ "Files/input_file_id batch upload workflow", "active cancel route", "public batch list/delete/result-download route", "model-name-derived capability or weights equivalence" ] }, "input": { "content_type": "application/json", "file_material": "呼叫端可在本機將實際的 UTF-8 JSONL 讀入 requests[]。此流程不使用上傳用途、input_file_id 或檔案參照。若缺少客戶素材或素材為空，應在 POST 前停止準備。", "material_types": [ "text" ], "optional_controls": [ "provider.only", "provider.allow_fallbacks", "completion_window" ], "representation": "內嵌的 requests[]；每個項目皆含 custom_id 與 body", "request_endpoint_profile": "/v1/chat/completions", "required": [ "endpoint", "model", "requests" ], "schema_scope": "依文件規定的內嵌 Batch 封裝格式提供文字 Chat Completions 請求主體。", "serialization_order": [ "endpoint", "model", "provider（如有提供）", "completion_window（如有提供）", "requests 放在最後" ] }, "lifecycle": { "cancel": null, "create": { "accepted_status": 202, "http": "POST", "path": "/v1/batches" }, "delete": null, "file_upload": null, "mode": "asynchronous", "observed_status_values": [ "validating", "in_progress", "finalizing", "completed", "failed", "expired", "cancelling", "cancelled" ], "owned_results": { "behavior": "Completed results are saved as owned JSONL, read back byte-for-byte and registered in the existing media library before publication after settlement. Status returns inline results; no separate Batch download route is added.", "format": "application/x-ndjson", "public_url_field_in_status": null }, "status": { "http": "GET", "id_source": "原始建立回應中實際回傳的 response.id；使用相同使用者／金鑰／群組", "path": "/v1/batches/{operation_id}" }, "terminal": [ "completed", "failed", "expired", "cancelled" ], "unknown": "保留原始作業 ID。503 result_pending_check 回應帶有 X-Should-Retry:false；請勿重新提交狀態不明的原始批次。" }, "manufacturer_capability": null, "method": { "http": "POST", "path": "/v1/batches" }, "output": { "all_results": "Preserve the full original status JSON, every result/custom_id and complete response or error body. Save completed results[] as JSONL without filtering.", "family": "batch", "format": "JSON; completed results[] are returned inline and can be saved as JSONL." } }, "ctx": null, "declared_pricing_profiles": [ { "dimensions": { "regime": "base" }, "label": "詞元基本費率", "units": [ { "amount": "0.00015000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "input_price", "label": "Input tokens", "native_amount_usd_per_unit": "0.00000015", "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": "0.00015000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "output_price", "label": "Output tokens", "native_amount_usd_per_unit": "0.00000015", "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": "0.000015000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "cache_read_price", "label": "Cache read", "native_amount_usd_per_unit": "0.000000015", "native_quantity": 1, "native_unit": "cached_input_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "cached_input_token" }, { "amount": null, "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "cache_write_price", "label": "Cache write", "native_amount_usd_per_unit": null, "native_quantity": 1, "native_unit": "generic_cache_creation_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "generic_cache_creation_token" }, { "amount": null, "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "cache_write_1h_price", "label": "Cache write, 1 hour", "native_amount_usd_per_unit": null, "native_quantity": 1, "native_unit": "one_hour_cache_creation_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "one_hour_cache_creation_token" } ] }, { "dimensions": { "max_context_tokens_inclusive": null, "min_context_tokens_exclusive": 0 }, "label": "請求長度級距 1", "units": [ { "amount": "0.00015000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "input_price", "label": "Input tokens", "native_amount_usd_per_unit": "0.00000015", "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": "0.00015000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "output_price", "label": "Output tokens", "native_amount_usd_per_unit": "0.00000015", "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": "0.000015000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "cache_read_price", "label": "Cache read", "native_amount_usd_per_unit": "0.000000015", "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}\"\npython3 - <<'PY_REQUEST'\nimport json\nfrom pathlib import Path\nbody=json.loads('{\"endpoint\":\"/v1/chat/completions\",\"model\":\"mistralai/ministral-8b-2512:batch\",\"requests\":[{\"custom_id\":\"req-0001\",\"body\":{\"messages\":[{\"role\":\"user\",\"content\":\"Hello!\"}],\"max_tokens\":16}}]}')\nPath(\"batch-request.json\").write_text(json.dumps(body,ensure_ascii=False),encoding=\"utf-8\")\nPY_REQUEST\ncurl --fail-with-body --silent --show-error https://api.ailoot.ai/v1/batches \\\n -H \"Authorization: Bearer $AILOOT_API_KEY\" -H 'Content-Type: application/json' \\\n --data-binary @batch-request.json -D batch-response-headers.txt -o batch-create-response.json\n", "label": "curl · retained fixture", "language": "bash" }, { "code": "import json, os\nfrom pathlib import Path\nfrom urllib.request import Request, urlopen\n\ndef prepare_requests(customer_path):\n path = Path(customer_path)\n if not path.is_file(): raise ValueError(\"Customer JSONL file is missing\")\n items = [json.loads(line) for line in path.read_text(encoding=\"utf-8\").splitlines() if line.strip()]\n if not items: raise ValueError(\"Customer JSONL contains no requests\")\n ids = set()\n for item in items:\n if set(item) != {\"custom_id\", \"body\"}: raise ValueError(\"Each item needs custom_id and body\")\n cid = item[\"custom_id\"]\n if not isinstance(cid, str) or not cid.strip() or cid in ids: raise ValueError(\"custom_id must be nonempty and unique\")\n ids.add(cid)\n if not isinstance(item[\"body\"], dict) or not item[\"body\"].get(\"messages\"): raise ValueError(\"Supply actual text messages\")\n supplied_model = item[\"body\"].get(\"model\")\n if supplied_model is not None and supplied_model not in ['mistralai/ministral-8b-2512:batch', 'mistralai/ministral-8b-2512']: raise ValueError(\"body.model must be an exact documented caller or wire ID\")\n return {\"endpoint\":\"/v1/chat/completions\", \"model\":\"mistralai/ministral-8b-2512:batch\", \"requests\":items}\n\nif __name__ == \"__main__\":\n material = os.environ.get(\"AILOOT_BATCH_REQUESTS_JSONL\", \"\")\n if not material: raise SystemExit(\"Set AILOOT_BATCH_REQUESTS_JSONL to your actual customer file\")\n body = prepare_requests(material)\n key = os.environ.get(\"AILOOT_API_KEY\", \"\")\n if not key: raise SystemExit(\"Set AILOOT_API_KEY\")\n request = Request(\"https://api.ailoot.ai/v1/batches\", data=json.dumps(body, ensure_ascii=False).encode(\"utf-8\"), headers={\"Authorization\":\"Bearer \" + key, \"Content-Type\":\"application/json\"}, method=\"POST\")\n with urlopen(request) as response:\n raw = response.read()\n Path(\"batch-create-response.json\").write_bytes(raw)\n print(raw.decode(\"utf-8\"))\n", "label": "Python HTTP · actual customer JSONL", "language": "python" }, { "code": "set -eu\n: \"${AILOOT_API_KEY:?Set your Ailoot API key}\"\nBATCH_OPERATION_ID=\"$(python3 - <<'PY_ID'\nimport json\nfrom pathlib import Path\nfrom urllib.parse import quote\nresponse = json.loads(Path(\"batch-create-response.json\").read_text(encoding=\"utf-8\"))\noperation = response.get(\"id\")\nif not isinstance(operation, str) or not operation: raise SystemExit(\"No actual original operation ID; preserve the response and do not resubmit\")\nprint(quote(operation, safe=\"\"))\nPY_ID\n)\"\ncurl --fail-with-body --silent --show-error \"https://api.ailoot.ai/v1/batches/$BATCH_OPERATION_ID\" \\\n -H \"Authorization: Bearer $AILOOT_API_KEY\" -o batch-status-response.json\n", "label": "curl · original operation status", "language": "bash" }, { "code": "import json\nfrom pathlib import Path\nraw = Path(\"batch-status-response.json\").read_bytes()\nresponse = json.loads(raw)\nif response.get(\"status\") != \"completed\":\n raise SystemExit(\"Keep the original operation; read its status without resubmitting\")\nresults = response.get(\"results\")\nif not isinstance(results, list) or not results:\n raise SystemExit(\"Preserve the original response; completed results are missing\")\nPath(\"batch-results.jsonl\").write_text(\"\".join(json.dumps(item, ensure_ascii=False) + \"\\n\" for item in results), encoding=\"utf-8\")\n# Preserve batch-status-response.json with aggregate usage and every result/error.\n", "label": "Python · save every completed result", "language": "python" } ], "family": "batch", "fast_multiplier": null, "flex_multiplier": null, "fmt": "batches", "hints": [ "Read your actual request items before submission; inline requests are required.", "Keep the returned operation ID and every result. Never replay an unknown submission." ], "http": "POST", "in": 0.15, "input": [ "text" ], "label": "批次處理（Batch）", "max_out": null, "max_reasoning_effort_multiplier": null, "out": 0.15, "output": [ "text" ], "path": "/v1/batches", "price_conditions": [ { "label": "Fast mode", "value": "Not specified", "when": "When fast mode is selected" }, { "label": "Flex mode", "value": "Not specified", "when": "When flex mode is selected" }, { "label": "Maximum reasoning effort", "value": "Not specified", "when": "When maximum reasoning effort uses the default adjustment" }, { "label": "Explicit cache pricing", "value": "Not enabled", "when": "When explicit cache is requested" } ], "pricing": { "billing_mode": "token", "image_input_price": null, "image_output_price": null, "per_request_price": null }, "pricing_profiles": [ { "dimensions": { "regime": "base" }, "label": "Base token rates", "units": [ { "amount": "0.00015000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "input_price", "label": "Input tokens", "native_amount_usd_per_unit": "0.00000015", "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": "0.00015000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "output_price", "label": "Output tokens", "native_amount_usd_per_unit": "0.00000015", "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": "0.000015000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "cache_read_price", "label": "Cache read", "native_amount_usd_per_unit": "0.000000015", "native_quantity": 1, "native_unit": "cached_input_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "cached_input_token" }, { "amount": null, "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "cache_write_price", "label": "Cache write", "native_amount_usd_per_unit": null, "native_quantity": 1, "native_unit": "generic_cache_creation_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "generic_cache_creation_token" }, { "amount": null, "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "cache_write_1h_price", "label": "Cache write, 1 hour", "native_amount_usd_per_unit": null, "native_quantity": 1, "native_unit": "one_hour_cache_creation_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "one_hour_cache_creation_token" } ] }, { "dimensions": { "max_context_tokens_inclusive": null, "min_context_tokens_exclusive": 0 }, "label": "Request-length tier 1", "units": [ { "amount": "0.00015000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "input_price", "label": "Input tokens", "native_amount_usd_per_unit": "0.00000015", "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": "0.00015000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "output_price", "label": "Output tokens", "native_amount_usd_per_unit": "0.00000015", "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": "0.000015000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "cache_read_price", "label": "Cache read", "native_amount_usd_per_unit": "0.000000015", "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": "mistralai/ministral-8b-2512:batch", "route_label": "Ultra", "status_reads": [ "GET /v1/batches/{operation_id}" ], "tiers": [ { "cache_read": 0.015, "cache_read_multiplier": null, "cache_write": null, "cache_write_1h": null, "cache_write_multiplier": null, "created_at": "0001-01-01T00:00:00Z", "in": 0.15, "input_multiplier": null, "max": null, "max_tokens": null, "min": 0, "min_tokens": 0, "out": 0.15, "output_multiplier": null, "per_request_price": null, "sort_order": 0, "tier_label": "", "updated_at": "0001-01-01T00:00:00Z" } ], "units": [ { "amount": "0.00015000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "input_price", "label": "Input tokens", "native_amount_usd_per_unit": "0.00000015", "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": "0.00015000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "output_price", "label": "Output tokens", "native_amount_usd_per_unit": "0.00000015", "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": "0.000015000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "cache_read_price", "label": "Cache read", "native_amount_usd_per_unit": "0.000000015", "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": "mistralai/ministral-8b-2512:batch", "nativeProvenance": { "input_facts_canonical_sha256": "7e635e203aace9cb560033c2682aa6846b640ef85cc4279db46434d57a12d119", "input_html_sha256": "36ff7a6a428f590a3be24f9809c0b3b606d3a2a14f3921947bda4e53a7beca56", "private_audit_sha256": "955014b3953610664d8deee2e2c2c36a646b1925ae272f295578d18d003fa1e2", "role": "historical-normalized-input-audit-hashes", "schema": "ailoot-native-model-provenance-v2" }, "page": { "canonical": "https://ailoot.ai/models/zh-hant-tw/mistralai-ministral-8b-2512-u003a-batch/", "description": "Ministral 3 8B Instruct 2512 是多語言文字與影像指令模型，具備 84 億參數語言元件與 4 億參數視覺編碼器。它支援原廠提供的 256k 上下文、系統指令、JSON 及原生函式呼叫，適用於助理與文件工作流程。", "locale": "zh-hant-tw", "md_url": "https://ailoot.ai/models/zh-hant-tw/mistralai-ministral-8b-2512-u003a-batch/index.md", "title": "Mistral: Ministral 3 8B 2512 (batch) — Ailoot", "url": "https://ailoot.ai/models/zh-hant-tw/mistralai-ministral-8b-2512-u003a-batch/" }, "rawModel": { "about": "Ministral 3 8B Instruct 2512 是 Mistral AI 的 Ministral 3 系列中，規模居中的指令微調模型。發布的檢查點以 FP8 精度針對聊天與指令任務進行後訓練。它結合語言元件與視覺編碼器，接受文字與影像並回傳文字，而非影像或音訊成品。\n\n架構與主要功能\n\n原廠列出 84 億參數語言模型及 4 億參數視覺編碼器。其上下文視窗描述為 256k，公開使用說明中的預設設定長度為 262,144。這些描述屬於此 8B 規模版本；較小的 3B 及較大的 14B 系列成員，仍有各自的元件規模與設定。\n\n視覺能力讓模型輸入不限於書面對話。文件影像可搭配關於特定欄位、段落或可見關係的問題。截圖可搭配使用者目標，要求辨識相關控制項。回答依賴視覺細節時，請要求列出支持每項結論的觀察，並保留解讀裁切影像所需的標題、標籤及單位。\n\n模型卡描述涵蓋數十種語言的多語言工作，包括英語、法語、西班牙語、德語、義大利語、葡萄牙語、荷蘭語、中文、日語、韓語及阿拉伯語，也指出對系統指令的遵循、原生函式呼叫及 JSON 輸出。請明確定義最終語言、角色與輸出需求，而非讓模型從大量輸入自行推測預期成品。\n\n文件、對話與代理任務\n\n原廠的使用案例包括聊天介面、日常助理、影像與文件描述、翻譯、內容生成及專用代理。對文件助理，請提供頁面並指定要回傳的資訊。擷取請求可以列出欄位標籤、預期型別及缺漏值的處理方式。實用回答可包含文件識別碼、擷取值，以及對應可見來源的簡短說明。\n\n對持續中的對話，請保留相關的先前回答，並提出聚焦的追問。使用者可以先要求文件摘要，再詢問哪項陳述支持某個結論。這會將所需輸出從一般概覽改為連結來源的說明，同時保留原始材料與對話目的。\n\n進行多語言編輯時，請提供原始段落、目標讀者與術語表。要求修訂版本保留名稱、條件與單位，再視需要附上簡短的變更說明。生成內容時，先指定讀者及應出現的事實，再要求短篇草稿或替代措辭。\n\n在代理任務中，應用程式提供工具及其參數。模型可以選擇函式並準備引數，而應用程式執行並回傳結果。模型卡的函式範例將影像問題與計算工具結合。請將工具結果與建議呼叫分開，讓後續書面回答使用操作實際回傳的資訊。\n\n建議的準備與設定\n\n原廠建議透過系統指令描述環境、使用案例及工具的使用方式。工具集合應定義清楚，並限於任務所需的最低數量。小型查詢工作流程可以提供與當前問題相關的函式，清楚命名必要引數，而非呈現大量無關操作。\n\n對日常與正式環境型用途，模型卡建議 temperature 低於 0.1，創意探索則可使用較高溫度。請將此視為指令工作流程的建議，而非獨立的推理模式控制。此系列具有不同的 Base、Instruct 及 Reasoning 檢查點；本條目是 Instruct 2512 版本，並非同規模的獨立 Reasoning 發布版本。\n\n對影像，原廠建議長寬比接近 1:1，避免過於狹長或寬扁的輸入。必要時裁切，同時保留問題所需的標籤與上下文。如果頁面包含數個無關區域，請指出要檢查的部分及要回傳的結果。清晰、聚焦的影像，比要求模型猜測寬廣頁面中的哪個小細節重要，更有幫助。\n\n上下文與版本界線\n\n請依設定的上下文規劃文字、影像、對話及期望回答。使用說明明確允許在不需要那麼多上下文時，減少設定的模型長度，因此完整視窗並非要求每次請求都填入所有可用材料。模型卡的 512 個 token 生成範例只是範例設定，已讀來源並未確立獨立的硬性最大回答長度。\n\nFP8 Instruct 檢查點、預訓練 Base 版本及 Reasoning 版本是不同版本。原廠也將專門化與微調描述為使用案例。準備對話時，請保留具名檢查點及其 tokenizer，並將文字生成與儲存庫存取、函式執行或周邊應用程式提供的其他動作區分。", "alias_of": null, "aliases": [], "author": "Mistral", "capabilities": { "context_length": 262144, "manufacturer_input": [ "text", "image" ], "manufacturer_output": [ "text" ] }, "card_routes": [ { "label": "Ultra", "rates": [ { "amount": "0.00015000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "input_price", "label": "Input tokens", "native_amount_usd_per_unit": "0.00000015", "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": "0.00015000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "output_price", "label": "Output tokens", "native_amount_usd_per_unit": "0.00000015", "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": "完整的設定價格資訊請見詳細資料。" } ], "ctx": null, "formats": [ "batches" ], "id": "mistralai/ministral-8b-2512:batch", "input": [ "text" ], "kind": "text", "max_out": null, "methods": [ { "available": null, "cache_read": 0.015, "cache_write": null, "cache_write_1h": null, "contract": { "data": { "all_results": "Preserve full JSON and every result; provider real IDs are only read from actual returned responses.", "authentication": { "api_key_source": "AILOOT_API_KEY", "header": "Authorization: Bearer" }, "errors": [ { "code": null, "condition": "文件規定的內嵌封裝格式無效、索引鍵重複、項目識別有誤，或與已設定的模型能力衝突。", "http_status": 400, "recovery": "再次提交前，請先修正指出的欄位。", "type": "invalid_request_error" }, { "code": null, "condition": "API 金鑰無效。", "http_status": 401, "recovery": "使用已獲授權的 Ailoot 金鑰。", "type": "authentication_error" }, { "code": null, "condition": "批次處理群組無法使用。", "http_status": 403, "recovery": "檢查金鑰／群組的使用權限。", "type": "permission_error" }, { "code": null, "condition": "批次處理採用餘額計費；透過訂閱建立批次的請求會遭拒絕。", "http_status": 422, "recovery": "使用已獲授權、以餘額計費的群組。", "type": "invalid_request_error" }, { "code": null, "condition": "無法為批次輸入估價。", "http_status": 422, "recovery": "保留回應；使用文件規定的該 API 家族輸入格式。", "type": "price_unavailable" }, { "code": null, "condition": "批次處理的預留額度無法取得。", "http_status": 402, "recovery": "提交新請求前，請先解決請求受理問題。", "type": "billing_error" }, { "code": null, "condition": "批次處理方法的價格／原生費率無法取得。", "http_status": 503, "recovery": "保留回應；請勿替換價格。", "type": "price_unavailable" }, { "code": null, "condition": "指定的供應商路由無法使用。", "http_status": 503, "recovery": "保留回應，以供修復路由。", "type": "api_error" }, { "code": "result_pending_check", "condition": "原始結果需要檢查；X-Should-Retry:false。", "http_status": 503, "recovery": "保留原始 operation_id/id 並讀取其狀態；請勿重複原始 POST。", "type": null }, { "code": "not_found", "condition": "查詢批次狀態所需的作業不存在，或屬於其他身分。", "http_status": 404, "recovery": "使用完全相同的原始 id，以及相同的使用者／金鑰／群組。", "type": null } ], "example_body": { "endpoint": "/v1/chat/completions", "model": "mistralai/ministral-8b-2512:batch", "requests": [ { "body": { "max_tokens": 16, "messages": [ { "content": "Hello!", "role": "user" } ] }, "custom_id": "req-0001" } ] }, "input_constraints": [ "Use the exact shown :batch model ID.", "Each custom_id must be nonempty and unique within the batch.", "Keep requests last in the serialized body; duplicate JSON keys are rejected.", "Each body.model is omitted or equals the exact batch caller or its documented base ID.", "Per-item provider, service_tier and input_type are outside this batch profile.", "stream is omitted or false.", "Supply text messages for this Chat batch profile; image/audio/file/video objects, hosted tools and cache-control fields are outside this profile.", "If body.model is present, use only the exact caller or wire ID listed here; no suffix conversion is needed.", "For google/ wire IDs, all items use an identical response_format." ], "outputs": { "all_results": "保留完整的原始狀態 JSON、每個結果／custom_id，以及完整的回應或錯誤主體。將已完成的 results[] 儲存為 JSONL，不得篩除任何項目。", "enclosing_family": "batch", "family": "text", "fields": [ { "name": "results[].custom_id", "type": "string" }, { "name": "results[].response.body.choices[].message.content", "type": "string|null" }, { "name": "results[].error", "type": "object|null" }, { "name": "usage", "type": "object|null" }, { "description": null, "name": "id", "type": "string" }, { "description": null, "name": "model", "type": "string" }, { "description": null, "name": "endpoint", "type": "string" }, { "description": null, "name": "status", "type": "string" }, { "description": null, "name": "request_counts", "type": "object" }, { "description": null, "name": "results[].id", "type": "string" }, { "description": null, "name": "results[].response.status_code", "type": "integer" }, { "description": null, "name": "results[].response.request_id", "type": "string" } ], "format": "內嵌的 results[].response.body JSON" }, "parameters": [ { "availability": "source_interface", "default": null, "default_known": false, "enum": [ "/v1/chat/completions" ], "enum_known": true, "name": "endpoint", "required": true, "type": "string" }, { "availability": "source_interface", "default": null, "default_known": false, "enum": [ "mistralai/ministral-8b-2512:batch" ], "enum_known": true, "name": "model", "required": true, "type": "string" }, { "availability": "source_interface", "default": null, "default_known": false, "enum": null, "enum_known": false, "min_items": 1, "name": "requests", "required": true, "type": "batch_item[]" }, { "availability": "source_interface", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "requests[].custom_id", "required": true, "type": "string", "unique_within_batch": true }, { "availability": "source_interface", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "requests[].body.messages", "required": true, "type": "message[]" }, { "availability": "source_interface", "default": null, "default_known": false, "enum": [ "24h" ], "enum_known": true, "name": "completion_window", "required": false, "type": "string" }, { "availability": "source_interface", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "provider", "required": false, "type": "object|null" }, { "availability": "source_interface", "default": null, "default_known": false, "enum": [ "mistralai/ministral-8b-2512:batch", "mistralai/ministral-8b-2512" ], "enum_known": true, "name": "requests[].body.model", "required": false, "type": "string" }, { "availability": "source_interface", "default": null, "default_known": false, "enum": [ [ "mistral" ] ], "enum_known": true, "name": "provider.only", "required": false, "type": "string[]" }, { "availability": "source_interface", "default": null, "default_known": false, "enum": [ false, null ], "enum_known": true, "name": "provider.allow_fallbacks", "required": false, "type": "boolean|null" } ], "provider_policy": { "allow_fallbacks": false, "configured_only": [ "mistral" ], "per_item_override": false, "when_omitted": "Current Source injects the exact persisted declaration before fresh submission." }, "request_schema": { "additionalProperties": false, "properties": { "completion_window": { "enum": [ "24h" ], "type": "string" }, "endpoint": { "enum": [ "/v1/chat/completions" ], "type": "string" }, "model": { "enum": [ "mistralai/ministral-8b-2512:batch" ], "type": "string" }, "provider": { "additionalProperties": false, "properties": { "allow_fallbacks": { "enum": [ false, null ], "type": [ "boolean", "null" ] }, "only": { "enum": [ [ "mistral" ] ], "items": { "enum": [ "mistral" ], "type": "string" }, "maxItems": 1, "minItems": 1, "type": "array" } }, "type": [ "object", "null" ] }, "requests": { "items": { "additionalProperties": false, "properties": { "body": { "additionalProperties": true, "properties": { "max_tokens": { "minimum": 1, "type": "integer" }, "messages": { "items": { "properties": { "content": { "type": "string" }, "role": { "type": "string" } }, "required": [ "role", "content" ], "type": "object" }, "minItems": 1, "type": "array" }, "model": { "enum": [ "mistralai/ministral-8b-2512:batch", "mistralai/ministral-8b-2512" ], "type": "string" } }, "required": [ "messages" ], "type": "object" }, "custom_id": { "minLength": 1, "type": "string" } }, "required": [ "custom_id", "body" ], "type": "object" }, "minItems": 1, "type": "array" } }, "required": [ "endpoint", "model", "requests" ], "type": "object" }, "schema_template": { "endpoint": "/v1/chat/completions", "model": "mistralai/ministral-8b-2512:batch", "requests": [ { "body": { "max_tokens": 16, "messages": [ { "content": "Hello!", "role": "user" } ] }, "custom_id": "req-0001" } ] }, "unsupported": [ "Files/input_file_id batch upload workflow", "active cancel route", "public batch list/delete/result-download route", "model-name-derived capability or weights equivalence" ] }, "input": { "content_type": "application/json", "file_material": "呼叫端可在本機將實際的 UTF-8 JSONL 讀入 requests[]。此流程不使用上傳用途、input_file_id 或檔案參照。若缺少客戶素材或素材為空，應在 POST 前停止準備。", "material_types": [ "text" ], "optional_controls": [ "provider.only", "provider.allow_fallbacks", "completion_window" ], "representation": "內嵌的 requests[]；每個項目皆含 custom_id 與 body", "request_endpoint_profile": "/v1/chat/completions", "required": [ "endpoint", "model", "requests" ], "schema_scope": "依文件規定的內嵌 Batch 封裝格式提供文字 Chat Completions 請求主體。", "serialization_order": [ "endpoint", "model", "provider（如有提供）", "completion_window（如有提供）", "requests 放在最後" ] }, "lifecycle": { "cancel": null, "create": { "accepted_status": 202, "http": "POST", "path": "/v1/batches" }, "delete": null, "file_upload": null, "mode": "asynchronous", "observed_status_values": [ "validating", "in_progress", "finalizing", "completed", "failed", "expired", "cancelling", "cancelled" ], "owned_results": { "behavior": "Completed results are saved as owned JSONL, read back byte-for-byte and registered in the existing media library before publication after settlement. Status returns inline results; no separate Batch download route is added.", "format": "application/x-ndjson", "public_url_field_in_status": null }, "status": { "http": "GET", "id_source": "原始建立回應中實際回傳的 response.id；使用相同使用者／金鑰／群組", "path": "/v1/batches/{operation_id}" }, "terminal": [ "completed", "failed", "expired", "cancelled" ], "unknown": "保留原始作業 ID。503 result_pending_check 回應帶有 X-Should-Retry:false；請勿重新提交狀態不明的原始批次。" }, "manufacturer_capability": null, "method": { "http": "POST", "path": "/v1/batches" }, "output": { "all_results": "Preserve the full original status JSON, every result/custom_id and complete response or error body. Save completed results[] as JSONL without filtering.", "family": "batch", "format": "JSON; completed results[] are returned inline and can be saved as JSONL." } }, "ctx": null, "declared_pricing_profiles": [ { "dimensions": { "regime": "base" }, "label": "詞元基本費率", "units": [ { "amount": "0.00015000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "input_price", "label": "Input tokens", "native_amount_usd_per_unit": "0.00000015", "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": "0.00015000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "output_price", "label": "Output tokens", "native_amount_usd_per_unit": "0.00000015", "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": "0.000015000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "cache_read_price", "label": "Cache read", "native_amount_usd_per_unit": "0.000000015", "native_quantity": 1, "native_unit": "cached_input_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "cached_input_token" }, { "amount": null, "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "cache_write_price", "label": "Cache write", "native_amount_usd_per_unit": null, "native_quantity": 1, "native_unit": "generic_cache_creation_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "generic_cache_creation_token" }, { "amount": null, "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "cache_write_1h_price", "label": "Cache write, 1 hour", "native_amount_usd_per_unit": null, "native_quantity": 1, "native_unit": "one_hour_cache_creation_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "one_hour_cache_creation_token" } ] }, { "dimensions": { "max_context_tokens_inclusive": null, "min_context_tokens_exclusive": 0 }, "label": "請求長度級距 1", "units": [ { "amount": "0.00015000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "input_price", "label": "Input tokens", "native_amount_usd_per_unit": "0.00000015", "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": "0.00015000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "output_price", "label": "Output tokens", "native_amount_usd_per_unit": "0.00000015", "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": "0.000015000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "cache_read_price", "label": "Cache read", "native_amount_usd_per_unit": "0.000000015", "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}\"\npython3 - <<'PY_REQUEST'\nimport json\nfrom pathlib import Path\nbody=json.loads('{\"endpoint\":\"/v1/chat/completions\",\"model\":\"mistralai/ministral-8b-2512:batch\",\"requests\":[{\"custom_id\":\"req-0001\",\"body\":{\"messages\":[{\"role\":\"user\",\"content\":\"Hello!\"}],\"max_tokens\":16}}]}')\nPath(\"batch-request.json\").write_text(json.dumps(body,ensure_ascii=False),encoding=\"utf-8\")\nPY_REQUEST\ncurl --fail-with-body --silent --show-error https://api.ailoot.ai/v1/batches \\\n -H \"Authorization: Bearer $AILOOT_API_KEY\" -H 'Content-Type: application/json' \\\n --data-binary @batch-request.json -D batch-response-headers.txt -o batch-create-response.json\n", "label": "curl · retained fixture", "language": "bash" }, { "code": "import json, os\nfrom pathlib import Path\nfrom urllib.request import Request, urlopen\n\ndef prepare_requests(customer_path):\n path = Path(customer_path)\n if not path.is_file(): raise ValueError(\"Customer JSONL file is missing\")\n items = [json.loads(line) for line in path.read_text(encoding=\"utf-8\").splitlines() if line.strip()]\n if not items: raise ValueError(\"Customer JSONL contains no requests\")\n ids = set()\n for item in items:\n if set(item) != {\"custom_id\", \"body\"}: raise ValueError(\"Each item needs custom_id and body\")\n cid = item[\"custom_id\"]\n if not isinstance(cid, str) or not cid.strip() or cid in ids: raise ValueError(\"custom_id must be nonempty and unique\")\n ids.add(cid)\n if not isinstance(item[\"body\"], dict) or not item[\"body\"].get(\"messages\"): raise ValueError(\"Supply actual text messages\")\n supplied_model = item[\"body\"].get(\"model\")\n if supplied_model is not None and supplied_model not in ['mistralai/ministral-8b-2512:batch', 'mistralai/ministral-8b-2512']: raise ValueError(\"body.model must be an exact documented caller or wire ID\")\n return {\"endpoint\":\"/v1/chat/completions\", \"model\":\"mistralai/ministral-8b-2512:batch\", \"requests\":items}\n\nif __name__ == \"__main__\":\n material = os.environ.get(\"AILOOT_BATCH_REQUESTS_JSONL\", \"\")\n if not material: raise SystemExit(\"Set AILOOT_BATCH_REQUESTS_JSONL to your actual customer file\")\n body = prepare_requests(material)\n key = os.environ.get(\"AILOOT_API_KEY\", \"\")\n if not key: raise SystemExit(\"Set AILOOT_API_KEY\")\n request = Request(\"https://api.ailoot.ai/v1/batches\", data=json.dumps(body, ensure_ascii=False).encode(\"utf-8\"), headers={\"Authorization\":\"Bearer \" + key, \"Content-Type\":\"application/json\"}, method=\"POST\")\n with urlopen(request) as response:\n raw = response.read()\n Path(\"batch-create-response.json\").write_bytes(raw)\n print(raw.decode(\"utf-8\"))\n", "label": "Python HTTP · actual customer JSONL", "language": "python" }, { "code": "set -eu\n: \"${AILOOT_API_KEY:?Set your Ailoot API key}\"\nBATCH_OPERATION_ID=\"$(python3 - <<'PY_ID'\nimport json\nfrom pathlib import Path\nfrom urllib.parse import quote\nresponse = json.loads(Path(\"batch-create-response.json\").read_text(encoding=\"utf-8\"))\noperation = response.get(\"id\")\nif not isinstance(operation, str) or not operation: raise SystemExit(\"No actual original operation ID; preserve the response and do not resubmit\")\nprint(quote(operation, safe=\"\"))\nPY_ID\n)\"\ncurl --fail-with-body --silent --show-error \"https://api.ailoot.ai/v1/batches/$BATCH_OPERATION_ID\" \\\n -H \"Authorization: Bearer $AILOOT_API_KEY\" -o batch-status-response.json\n", "label": "curl · original operation status", "language": "bash" }, { "code": "import json\nfrom pathlib import Path\nraw = Path(\"batch-status-response.json\").read_bytes()\nresponse = json.loads(raw)\nif response.get(\"status\") != \"completed\":\n raise SystemExit(\"Keep the original operation; read its status without resubmitting\")\nresults = response.get(\"results\")\nif not isinstance(results, list) or not results:\n raise SystemExit(\"Preserve the original response; completed results are missing\")\nPath(\"batch-results.jsonl\").write_text(\"\".join(json.dumps(item, ensure_ascii=False) + \"\\n\" for item in results), encoding=\"utf-8\")\n# Preserve batch-status-response.json with aggregate usage and every result/error.\n", "label": "Python · save every completed result", "language": "python" } ], "family": "batch", "fast_multiplier": null, "flex_multiplier": null, "fmt": "batches", "hints": [ "Read your actual request items before submission; inline requests are required.", "Keep the returned operation ID and every result. Never replay an unknown submission." ], "http": "POST", "in": 0.15, "input": [ "text" ], "label": "批次處理（Batch）", "max_out": null, "max_reasoning_effort_multiplier": null, "out": 0.15, "output": [ "text" ], "path": "/v1/batches", "price_conditions": [ { "label": "Fast mode", "value": "Not specified", "when": "When fast mode is selected" }, { "label": "Flex mode", "value": "Not specified", "when": "When flex mode is selected" }, { "label": "Maximum reasoning effort", "value": "Not specified", "when": "When maximum reasoning effort uses the default adjustment" }, { "label": "Explicit cache pricing", "value": "Not enabled", "when": "When explicit cache is requested" } ], "pricing": { "billing_mode": "token", "image_input_price": null, "image_output_price": null, "per_request_price": null }, "pricing_profiles": [ { "dimensions": { "regime": "base" }, "label": "Base token rates", "units": [ { "amount": "0.00015000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "input_price", "label": "Input tokens", "native_amount_usd_per_unit": "0.00000015", "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": "0.00015000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "output_price", "label": "Output tokens", "native_amount_usd_per_unit": "0.00000015", "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": "0.000015000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "cache_read_price", "label": "Cache read", "native_amount_usd_per_unit": "0.000000015", "native_quantity": 1, "native_unit": "cached_input_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "cached_input_token" }, { "amount": null, "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "cache_write_price", "label": "Cache write", "native_amount_usd_per_unit": null, "native_quantity": 1, "native_unit": "generic_cache_creation_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "generic_cache_creation_token" }, { "amount": null, "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "cache_write_1h_price", "label": "Cache write, 1 hour", "native_amount_usd_per_unit": null, "native_quantity": 1, "native_unit": "one_hour_cache_creation_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "one_hour_cache_creation_token" } ] }, { "dimensions": { "max_context_tokens_inclusive": null, "min_context_tokens_exclusive": 0 }, "label": "Request-length tier 1", "units": [ { "amount": "0.00015000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "input_price", "label": "Input tokens", "native_amount_usd_per_unit": "0.00000015", "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": "0.00015000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "output_price", "label": "Output tokens", "native_amount_usd_per_unit": "0.00000015", "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": "0.000015000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "cache_read_price", "label": "Cache read", "native_amount_usd_per_unit": "0.000000015", "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": "mistralai/ministral-8b-2512:batch", "route_label": "Ultra", "status_reads": [ "GET /v1/batches/{operation_id}" ], "tiers": [ { "cache_read": 0.015, "cache_read_multiplier": null, "cache_write": null, "cache_write_1h": null, "cache_write_multiplier": null, "created_at": "0001-01-01T00:00:00Z", "in": 0.15, "input_multiplier": null, "max": null, "max_tokens": null, "min": 0, "min_tokens": 0, "out": 0.15, "output_multiplier": null, "per_request_price": null, "sort_order": 0, "tier_label": "", "updated_at": "0001-01-01T00:00:00Z" } ], "units": [ { "amount": "0.00015000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "input_price", "label": "Input tokens", "native_amount_usd_per_unit": "0.00000015", "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": "0.00015000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "output_price", "label": "Output tokens", "native_amount_usd_per_unit": "0.00000015", "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": "0.000015000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "cache_read_price", "label": "Cache read", "native_amount_usd_per_unit": "0.000000015", "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": "mistralai/ministral-8b-2512:batch", "request_model_id": "mistralai/ministral-8b-2512:batch", "route_label": "Ultra" } ], "name": "Mistral: Ministral 3 8B 2512 (batch)", "price": { "in": 0.15, "in_label": null, "out": 0.15, "out_label": null, "scope_label": "Token rates", "sort_in": 0.15, "sort_out": 0.15, "varies": true }, "short": "Ministral 3 8B Instruct 2512 是多語言文字與影像指令模型，具備 84 億參數語言元件與 4 億參數視覺編碼器。它支援原廠提供的 256k 上下文、系統指令、JSON 及原生函式呼叫，適用於助理與文件工作流程。" }, "renderer_schema": { "method_order": "Original DTO methods order; every exact route/format/path/caller survives.", "prices": "Original public DTO fields and original native display HTML; no flattened or normalized offers." }, "representation": "exact-public-dto-and-native-renderer-html", "representationNotes": { "current_reference": { "about_json_pointer": "/aboutHtml", "methods": [ { "contract_json_pointer": "/methods/0/rawMethod/contract", "html_json_pointer": "/methods/0/html", "method_ordinal": 0 } ], "role": "current-semantic-reference" }, "raw_input": { "examples_role": "historical-input-not-current-ready-examples", "json_pointers": [ "/rawModel", "/methods/0/rawMethod" ], "role": "historical-owner-input" }, "schema": "ailoot-native-model-representations-v1" }, "schema": "ailoot-static-model-facts-v1", "schema_version": 1, "shortText": "Ministral 3 8B Instruct 2512 是多語言文字與影像指令模型，具備 84 億參數語言元件與 4 億參數視覺編碼器。它支援原廠提供的 256k 上下文、系統指令、JSON 及原生函式呼叫，適用於助理與文件工作流程。", "source": { "audit_sha256": "2e00086bcbfc28e64d0cebe97aa47c17d8d5618963027f8ffb9dc6123d7d25b1", "bridge_map_sha256": "1125275768b9636fc8461bc7da5061239a81ddfe508e2557843ca42c58ab0036", "raw_model_json_sha256": "1682c42a4c4248a9e899fc9e16f7a9aac6ea85fb7d7749713950a42342adc206", "renderer_sha256": "13a3fc1b22d07359278e2249d630bfc9bb9e6416c71ba53def933fb5a903660b" }, "sourceRevision": "13cbc3e424e32f892993af18a38e1efafe4d2f8528d9c93fb0c381c521271621" }