{ "aboutHtml": "

Nano Banana Pro 是 Google 以推理驅動圖像生成及編輯的 Gemini 3 Pro Image 模型。製造商將複雜平面設計、高保真產品樣稿及事實資料視覺化置於預定用途核心。它接收文字與圖像，產生圖像與文字。此具名 Pro 圖像版本以 Gemini 3 Pro 為基礎，同時保有自身圖像任務的輸入及能力設定。

模型支援 1K、2K、4K 圖像。文件中的形狀包括 1:1、2:3、3:2、3:4、4:3、4:5、5:4、9:16、16:9、21:9。正方形 4K 圖像為 4096 × 4096；16:9 4K 圖像為 5504 × 3072。無論需要直式海報、產品場景或寬幅解說圖，均應依成果選擇解析度及長寬比。Gemini 3.1 Flash Image 的 0.5K 選項及額外極端比例不在此 Pro 表內。

文字呈現支援海報、圖解及其他設計素材的清楚字樣。複雜資訊圖表應提供基礎事實、確切文字、閱讀順序，以及標籤與視覺元素關係。請將要傳達的資訊與所需藝術風格分開。Google 建議先準備文字，再生成包含文字的圖像。構圖結合標題、圖解及數段簡短說明時，這尤其實用。

多圖輸入支援最多 14 張參考。Google 功能表描述最多六張物件參考用於忠實呈現、最多五張角色參考用於一致性，以及最多三張風格參考。這些角色有助於準備合成視覺：產品照片定義外觀、另一張圖建立環境，風格圖像則影響處理方式。請告訴模型哪些細節具權威性、哪些參考提供靈感，而非要求它不加區分地結合每個可見特徵。

Google Search grounding 可為事實視覺化或反映當前狀況的場景提供現實資訊。Pro 圖像流程記載網頁 grounding；Image Search 擴充則專門記載於 Nano Banana 2.1 及 Gemini 3.1 Flash Image。資料圖像應提供預期呈現值，或在原始模型流程要求 grounding 資訊，再明確說明關係、標籤及版面。搜尋輔助生成的結果仍是需要檢查的圖像，不能取代核對描繪事實。

推理支援在最終渲染前組織複雜提示。圖像指南描述用於測試構圖與邏輯的中間圖像，與最終成果不同。請勿將 Nano Banana 2 的 minimal/high 控制表，或 Nano Banana 2.1 的 medium 預設表，套用至此 Pro 版本。高難度設計應提供完整需求，包含視覺層級、必要物件關係，以及後續編輯中必須保留的元素。

模型資訊卡描述了仍存在的重要限制：極小文字及長段落可能呈現不佳，角色外觀可能在參考與結果間改變，遮罩或塗鴉編輯可能僅部分遵循指令或留下痕跡。它也可能混淆左右，或將來源元素複製到新構圖。產品修訂應明確說明要保留的幾何形狀與標籤，並檢查編輯區域；圖解應比較箭頭方向及物件相對位置。

目前 API 表列出輸入上限 65,536 token、輸出上限 32,768 token。支援圖像生成、thinking、搜尋 grounding 及批次處理；不支援音訊生成、函式呼叫、程式碼執行、快取、結構化輸出、檔案搜尋、URL context 及 Live API。此設定的圖像任務不接受音訊或影片輸入。生成圖像包含 SynthID，且不一定精確遵循所需輸出圖像數量。

實用產品需求可結合產品圖像、光線參考及確切標題：「保留產品比例與字樣，將它呈現在柔和側光下的淺色石材表面，上方三分之一留白，以放置提供的標題。」事實圖解應指明每個實體及連結，並提供定稿標籤。可透過對話指出一項修改及要保留的特徵來完善結果，將選定圖像與解說文字一起保留為設計成果。

", "aboutText": "Nano Banana Pro 是 Google 以推理驅動圖像生成及編輯的 Gemini 3 Pro Image 模型。製造商將複雜平面設計、高保真產品樣稿及事實資料視覺化置於預定用途核心。它接收文字與圖像，產生圖像與文字。此具名 Pro 圖像版本以 Gemini 3 Pro 為基礎，同時保有自身圖像任務的輸入及能力設定。\n\n模型支援 1K、2K、4K 圖像。文件中的形狀包括 1:1、2:3、3:2、3:4、4:3、4:5、5:4、9:16、16:9、21:9。正方形 4K 圖像為 4096 × 4096；16:9 4K 圖像為 5504 × 3072。無論需要直式海報、產品場景或寬幅解說圖，均應依成果選擇解析度及長寬比。Gemini 3.1 Flash Image 的 0.5K 選項及額外極端比例不在此 Pro 表內。\n\n文字呈現支援海報、圖解及其他設計素材的清楚字樣。複雜資訊圖表應提供基礎事實、確切文字、閱讀順序，以及標籤與視覺元素關係。請將要傳達的資訊與所需藝術風格分開。Google 建議先準備文字，再生成包含文字的圖像。構圖結合標題、圖解及數段簡短說明時，這尤其實用。\n\n多圖輸入支援最多 14 張參考。Google 功能表描述最多六張物件參考用於忠實呈現、最多五張角色參考用於一致性，以及最多三張風格參考。這些角色有助於準備合成視覺：產品照片定義外觀、另一張圖建立環境，風格圖像則影響處理方式。請告訴模型哪些細節具權威性、哪些參考提供靈感，而非要求它不加區分地結合每個可見特徵。\n\nGoogle Search grounding 可為事實視覺化或反映當前狀況的場景提供現實資訊。Pro 圖像流程記載網頁 grounding；Image Search 擴充則專門記載於 Nano Banana 2.1 及 Gemini 3.1 Flash Image。資料圖像應提供預期呈現值，或在原始模型流程要求 grounding 資訊，再明確說明關係、標籤及版面。搜尋輔助生成的結果仍是需要檢查的圖像，不能取代核對描繪事實。\n\n推理支援在最終渲染前組織複雜提示。圖像指南描述用於測試構圖與邏輯的中間圖像，與最終成果不同。請勿將 Nano Banana 2 的 minimal/high 控制表，或 Nano Banana 2.1 的 medium 預設表，套用至此 Pro 版本。高難度設計應提供完整需求，包含視覺層級、必要物件關係，以及後續編輯中必須保留的元素。\n\n模型資訊卡描述了仍存在的重要限制：極小文字及長段落可能呈現不佳，角色外觀可能在參考與結果間改變，遮罩或塗鴉編輯可能僅部分遵循指令或留下痕跡。它也可能混淆左右，或將來源元素複製到新構圖。產品修訂應明確說明要保留的幾何形狀與標籤，並檢查編輯區域；圖解應比較箭頭方向及物件相對位置。\n\n目前 API 表列出輸入上限 65,536 token、輸出上限 32,768 token。支援圖像生成、thinking、搜尋 grounding 及批次處理；不支援音訊生成、函式呼叫、程式碼執行、快取、結構化輸出、檔案搜尋、URL context 及 Live API。此設定的圖像任務不接受音訊或影片輸入。生成圖像包含 SynthID，且不一定精確遵循所需輸出圖像數量。\n\n實用產品需求可結合產品圖像、光線參考及確切標題：「保留產品比例與字樣，將它呈現在柔和側光下的淺色石材表面，上方三分之一留白，以放置提供的標題。」事實圖解應指明每個實體及連結，並提供定稿標籤。可透過對話指出一項修改及要保留的特徵來完善結果，將選定圖像與解說文字一起保留為設計成果。", "editorialOverlay": { "copy_fields": { "practical_html": "

實用任務

英文技術範例

Visualize a supplied packaging cycle\n\nCreate one landscape explanatory graphic showing this packaging return cycle: customer returns an empty jar, store inspects it, accepted jars are washed, clean jars are refilled. Use four large illustrated stages connected clockwise. Add only these exact labels: 'RETURN', 'INSPECT', 'WASH', 'REFILL'. Make the arrow direction and stage order unmistakable.

預期結果

One landscape image with four labeled stages and arrows matching the supplied cycle.

檢查結果

Inspect that arrows connect RETURN to INSPECT to WASH to REFILL in that order, with exact labels.
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G

Google: Nano Banana Pro (Gemini 3 Pro Image)

Google /gemini-3-pro-image

入門

Nano Banana Pro（Gemini 3 Pro Image）是 Google 以推理驅動的圖像模型，適用複雜設計、產品樣稿及事實視覺化。它接收文字與圖像參考，生成圖像及文字，提供 1K–4K 輸出與詳細創意控制。

接受的輸入
文字
結果
圖片
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。

Nano Banana Pro 是 Google 以推理驅動圖像生成及編輯的 Gemini 3 Pro Image 模型。製造商將複雜平面設計、高保真產品樣稿及事實資料視覺化置於預定用途核心。它接收文字與圖像，產生圖像與文字。此具名 Pro 圖像版本以 Gemini 3 Pro 為基礎，同時保有自身圖像任務的輸入及能力設定。

模型支援 1K、2K、4K 圖像。文件中的形狀包括 1:1、2:3、3:2、3:4、4:3、4:5、5:4、9:16、16:9、21:9。正方形 4K 圖像為 4096 × 4096；16:9 4K 圖像為 5504 × 3072。無論需要直式海報、產品場景或寬幅解說圖，均應依成果選擇解析度及長寬比。Gemini 3.1 Flash Image 的 0.5K 選項及額外極端比例不在此 Pro 表內。

文字呈現支援海報、圖解及其他設計素材的清楚字樣。複雜資訊圖表應提供基礎事實、確切文字、閱讀順序，以及標籤與視覺元素關係。請將要傳達的資訊與所需藝術風格分開。Google 建議先準備文字，再生成包含文字的圖像。構圖結合標題、圖解及數段簡短說明時，這尤其實用。

多圖輸入支援最多 14 張參考。Google 功能表描述最多六張物件參考用於忠實呈現、最多五張角色參考用於一致性，以及最多三張風格參考。這些角色有助於準備合成視覺：產品照片定義外觀、另一張圖建立環境，風格圖像則影響處理方式。請告訴模型哪些細節具權威性、哪些參考提供靈感，而非要求它不加區分地結合每個可見特徵。

Google Search grounding 可為事實視覺化或反映當前狀況的場景提供現實資訊。Pro 圖像流程記載網頁 grounding；Image Search 擴充則專門記載於 Nano Banana 2.1 及 Gemini 3.1 Flash Image。資料圖像應提供預期呈現值，或在原始模型流程要求 grounding 資訊，再明確說明關係、標籤及版面。搜尋輔助生成的結果仍是需要檢查的圖像，不能取代核對描繪事實。

推理支援在最終渲染前組織複雜提示。圖像指南描述用於測試構圖與邏輯的中間圖像，與最終成果不同。請勿將 Nano Banana 2 的 minimal/high 控制表，或 Nano Banana 2.1 的 medium 預設表，套用至此 Pro 版本。高難度設計應提供完整需求，包含視覺層級、必要物件關係，以及後續編輯中必須保留的元素。

模型資訊卡描述了仍存在的重要限制：極小文字及長段落可能呈現不佳，角色外觀可能在參考與結果間改變，遮罩或塗鴉編輯可能僅部分遵循指令或留下痕跡。它也可能混淆左右，或將來源元素複製到新構圖。產品修訂應明確說明要保留的幾何形狀與標籤，並檢查編輯區域；圖解應比較箭頭方向及物件相對位置。

目前 API 表列出輸入上限 65,536 token、輸出上限 32,768 token。支援圖像生成、thinking、搜尋 grounding 及批次處理；不支援音訊生成、函式呼叫、程式碼執行、快取、結構化輸出、檔案搜尋、URL context 及 Live API。此設定的圖像任務不接受音訊或影片輸入。生成圖像包含 SynthID，且不一定精確遵循所需輸出圖像數量。

實用產品需求可結合產品圖像、光線參考及確切標題：「保留產品比例與字樣，將它呈現在柔和側光下的淺色石材表面，上方三分之一留白，以放置提供的標題。」事實圖解應指明每個實體及連結，並提供定稿標籤。可透過對話指出一項修改及要保留的特徵來完善結果，將選定圖像與解說文字一起保留為設計成果。

Ailoot 可用 · 輸入與方法

Ailoot · 圖片 POST /v1/images/generations
輸入
text
輸出
image
上下文
65,536 tokens
輸出上限
32,768 tokens
輸出格式
圖片檔案
欄位類型要求值與限制預設值
欄位model類型string要求必填值與限制
gemini-3-pro-image
預設值—
欄位prompt類型string要求必填值與限制
長度下限: 1
預設值—
欄位n類型integer要求選填值與限制
最小值: 1
預設值1
欄位response_format類型string要求選填值與限制
url, b64_json
預設值—
欄位stream類型boolean要求選填值與限制預設值false
欄位size類型string要求選填值與限制
依模型而定
預設值—
欄位quality類型string要求選填值與限制
依模型而定
預設值—
欄位background類型string要求選填值與限制
依模型而定
預設值—
欄位output_format類型string要求選填值與限制
依模型而定
預設值—
欄位output_compression類型integer要求選填值與限制
依模型而定
預設值—
欄位moderation類型string要求選填值與限制
依模型而定
預設值—
欄位input_fidelity類型string要求選填值與限制
依模型而定
預設值—
欄位style類型string要求選填值與限制
依模型而定
預設值—
欄位partial_images類型integer要求選填值與限制
依模型而定
預設值—
輸入素材組合

文字生成圖片 · 必填： prompt

方法參數與生命週期
參數規格
參數material_types規格text
參數required規格model, prompt
參數optional_controls規格null
參數content_type規格application/json

生命週期： synchronous_result_then_owned_library

GET /v1/media/tasks/{task_id} · 實際回傳的 task_id 或媒體庫紀錄

GET /v1/media/assets/{asset_id}/content

GET /v1/media/assets

GET /v1/media/assets/{asset_id}

方法結構與 ID 均為精確值；供應商能力與准入狀態分開。

方案

Ailoot 方法費率

Ailoot 圖片POST /v1/images/generations
輸入
US$0.002 / 1K 圖片 Token
輸出
US$0.134 每張 1K 圖片
輸出
US$0.134 每張 2K 圖片
輸出
US$0.24 每張 4K 圖片

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 →

參考費率詳情

模型層級的參考費率表不會變更方法選擇、報價或費用。實際計費採用所選 Ailoot 方法的費率。

模型參考費率表

各設定的價格

設定費率表費用
設定Ultra費率表基本費率費用
輸入 · 輸入 Token $0.004000 / 1K Token
輸出 · 輸出 Token $0.024000 / 1K Token
輸入 · 圖片 $0.004000 / 1K Token
輸出 · 圖片輸出 $0.24000 / 1K Token
輸入 · 音訊 $0.004000 / 1K Token
輸入 · 輸入音訊快取 $0.0004000 / 1K Token
輸出 · 網頁搜尋 $0.028 每次網頁搜尋
輸出 · 內部推理 $0.024000 / 1K Token
輸入 · 讀取快取 $0.0004000 / 1K Token
輸入 · 寫入快取 $0.000750000 / 1K Token

請求範例

Ailoot · 圖片

set -eu\n: "${AILOOT_API_KEY:?Set your Ailoot API key}"\nexport AILOOT_API_KEY\nexport AILOOT_API_KEY\n: "${AILOOT_PROMPT_FILE:?Set your actual UTF-8 image brief}"\nexport AILOOT_PROMPT_FILE\npython3 - <<'PY_REQUEST'\nimport json,os\nfrom pathlib import Path\np=json.loads('{"model": "gemini-3-pro-image", "prompt": ""}')\nf=Path(os.environ["AILOOT_PROMPT_FILE"])\nif not f.is_file():raise SystemExit("Choose your actual UTF-8 brief")\np['prompt']=f.read_text(encoding="utf-8")\nif not p['prompt'].strip():raise SystemExit("Brief must contain text")\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/images/generations \\\n  -H "Authorization: Bearer $AILOOT_API_KEY" -H 'Content-Type: application/json' \\\n  --data-binary @request.json -D response-headers.txt -o result.json\npython3 - <<'PY_RESULT'\nimport base64, json, os, subprocess\nfrom pathlib import Path\nfrom urllib.parse import urlsplit, urljoin\n\ndef save_images(items):\n    if not items: raise SystemExit("No completed images; retain the full response")\n    for index, item in enumerate(items):\n        encoded=item.get("b64_json")\n        uri=item.get("url", "")\n        if not encoded and uri.startswith("data:image/"):\n            header, separator, encoded=uri.partition(",")\n            if not separator or ";base64" not in header: raise SystemExit("Unsupported image data URI")\n        if encoded:\n            raw=base64.b64decode(encoded,validate=True)\n        elif uri:\n            uri=urljoin("https://api.ailoot.ai",uri)\n            parsed=urlsplit(uri)\n            if parsed.scheme!="https" or not parsed.netloc or parsed.username or parsed.password:\n                raise SystemExit("Invalid returned image URL")\n            owned=parsed.netloc=="api.ailoot.ai" and parsed.path.startswith("/v1/media/assets/") and parsed.path.endswith("/content")\n            args=["curl","--fail-with-body","--silent","--show-error",uri]\n            if owned: args += ["-H","Authorization: Bearer "+os.environ["AILOOT_API_KEY"]]\n            temporary=Path(f"image-{index}.bin")\n            subprocess.run(args+["-o",str(temporary)],check=True)\n            raw=temporary.read_bytes()\n            temporary.unlink()\n        else: raise SystemExit("Image has neither bytes nor URL")\n        if not raw: raise SystemExit("Empty image result")\n        ext="png" if raw.startswith(b"\\x89PNG") else "jpg" if raw.startswith(b"\\xff\\xd8") else "webp" if raw[:4]==b"RIFF" and raw[8:12]==b"WEBP" else "svg" if raw.lstrip().startswith((b"<svg",b"<?xml")) else "bin"\n        Path(f"image-{index}.{ext}").write_bytes(raw)\n    print("Every returned image saved; complete response metadata retained")\nsave_images(json.loads(Path("result.json").read_text())["data"])\nPY_RESULT\n

接收並儲存結果

Ailoot · 圖片

下載每張傳回的圖片，或儲存其 Base64 內容

保留所有已完成的結果

請儲存每張已完成的圖片；從每個傳回的 URL 取得圖片，或解碼其 Base64 內容。

儲存所有資料項目。解碼每個 b64_json，或透過每個回傳的已簽署 URL 取得內容。依實際 MIME 類型／位元組內容選擇副檔名。

需要檢查原始回應時

若圖片生成或編輯結果需要檢查，請保留原始 operation_id/X-Client-Request-ID 與回傳的結果資訊。使用實際的 task_id 或 asset_id 值，透過媒體庫取回自己擁有的既有結果。請勿重新提交生成／編輯請求，也請勿以 operation_id 組成輪詢 URL。

回應欄位
欄位類型
欄位created類型integer
欄位data[].url類型string
欄位data[].b64_json類型base64 string
欄位usage類型object
錯誤與後續步驟
回應條件下一步
回應400 · invalid_request_error條件必要欄位、素材表示方式或參數值無效下一步提出新的建立請求前，先修正指定欄位。
回應server_error條件回傳的回應表示該作業或結果需要檢查下一步保留原始回傳的作業／任務 ID、請求標頭與回應；繼續以支援的方式讀取該原始作業。請勿重新提交建立請求。

別名

模型別名

Ailoot gemini-3-pro-image, gemini-3-pro-image-preview, nano-banana-pro
Ailoot Ultra google/gemini-3-pro-image

方法路徑別名

/v1/images

相關呼叫用 ID

google/gemini-3-pro-image, gemini-3-pro-image-preview, nano-banana-pro, gemini-3-pro-image

", "method_identity": { "effective_request_model_id": "gemini-3-pro-image", "fmt": "images", "http": "POST", "path": "/v1/images/generations", "request_model_id": "gemini-3-pro-image", "route_label": "Core" }, "method_key": "Core|images|/v1/images/generations|gemini-3-pro-image", "ordinal": 0, "rawMethod": { "cache_read": null, "cache_write": null, "cache_write_1h": null, "cache_write_5m": null, "conditional_meter": null, "contract": { "data": { "all_results": "Save every data item. Decode each b64_json or fetch every returned signed URL. Select a filename extension from the actual MIME/bytes.", "errors": [ { "code": null, "condition": "必要欄位、素材表示方式或參數值無效", "http_status": 400, "recovery": "提出新的建立請求前，先修正指定欄位。", "type": "invalid_request_error" }, { "code": null, "condition": "回傳的回應表示該作業或結果需要檢查", "http_status": null, "recovery": "保留原始回傳的作業／任務 ID、請求標頭與回應；繼續以支援的方式讀取該原始作業。請勿重新提交建立請求。", "type": "server_error" } ], "hints": [], "ignored_fields": [], "lifecycle": { "all_results": "Follow everyactualreturnedoutputandownedasset; no result is discardedbecauseindex0orcontent_urlalreadyexists.", "assets": [ { "http": "GET", "path": "/v1/media/assets" }, { "http": "GET", "path": "/v1/media/assets/{asset_id}" } ], "content": [ { "http": "GET", "path": "/v1/media/assets/{asset_id}/content", "url_source": "exact returned signed URL; never construct token" } ], "mode": "synchronous_result_then_owned_library", "operation_id_is_not_task_id": true, "status": [ { "http": "GET", "id_source": "actual returned task_id or media library record", "path": "/v1/media/tasks/{task_id}" } ], "unknown": "若圖片生成或編輯結果需要檢查，請保留原始 operation_id/X-Client-Request-ID 與回傳的結果資訊。使用實際的 task_id 或 asset_id 值，透過媒體庫取回自己擁有的既有結果。請勿重新提交生成／編輯請求，也請勿以 operation_id 組成輪詢 URL。" }, "material_combinations": [ { "content_types": [ "application/json", "multipart/form-data" ], "file_id_supported": false, "mode": "text_to_image", "multipart_part_read_limit_bytes": 20971520, "optional_mask": { "json": "mask.image_url", "multipart": "mask" }, "reference_representations": { "json": "images[].image_url", "multipart": [ "image", "image[]", "image[index]" ] }, "required": [ "prompt" ] } ], "media_library": { "asset": { "fields": [ { "description": null, "name": "asset_id", "type": "string" }, { "description": null, "name": "task_id", "type": "string" }, { "description": null, "name": "output_key", "type": "string" }, { "description": null, "name": "family", "type": "string" }, { "description": null, "name": "model", "type": "string" }, { "description": null, "name": "method", "type": "string" }, { "description": null, "name": "status", "type": "string" }, { "description": null, "name": "content_type", "type": "string" }, { "description": null, "name": "sha256", "type": "string" }, { "description": null, "name": "size_bytes", "type": "integer" }, { "description": null, "name": "content_url", "type": "string" } ], "http": "GET", "id_source": "actual returned asset_id", "path": "/v1/media/assets/{asset_id}" }, "content": { "http": "GET", "path": "/v1/media/assets/{asset_id}/content", "range_header_supported": true, "url_source": "Use exact returned signed content_url including its token; do not construct a token." }, "expired_link": { "code": "link_expired", "http_status": 404, "recovery": "Read the asset again to obtain its refreshed signed content_url, then fetch that URL. Do not regenerate." }, "list": { "all_pages": "Follow every returned next_cursor, then select records by their actual task_id/output_key.", "http": "GET", "output_fields": [ { "description": null, "name": "object", "type": "string" }, { "description": null, "name": "data", "type": "asset[]" }, { "description": null, "name": "next_cursor", "type": "string|null" } ], "parameters": [ { "availability": "source_interface", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "family", "required": false, "type": "string" }, { "availability": "source_interface", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "cursor", "required": false, "type": "string" }, { "availability": "source_interface", "default": 20, "default_known": true, "enum": null, "enum_known": false, "maximum": 100, "minimum": 1, "name": "limit", "required": false, "type": "integer" } ], "path": "/v1/media/assets" }, "revoke": { "http": "DELETE", "meaning": "Revokes/deletes the existing owned file; this is not generation cancellation.", "path": "/v1/media/assets/{asset_id}", "pending_status": "revoking", "success_statuses": [ 202, 204 ] }, "task": { "http": "GET", "id_source": "actual returned task_id or media library record; operation_id is not task_id", "path": "/v1/media/tasks/{task_id}" } }, "operation_modes": [ "text_to_image" ], "outputs": { "all_results": "儲存所有資料項目。解碼每個 b64_json，或透過每個回傳的已簽署 URL 取得內容。依實際 MIME 類型／位元組內容選擇副檔名。", "family": "image", "fields": [ { "description": null, "name": "created", "type": "integer" }, { "description": null, "name": "data[].url", "type": "string" }, { "description": null, "name": "data[].b64_json", "type": "base64 string" }, { "description": null, "name": "usage", "type": "object" } ], "format": "actual validated raster MIME" }, "parameters": [ { "availability": "source_interface", "default": null, "default_known": false, "enum": [ "gemini-3-pro-image" ], "enum_known": true, "name": "model", "required": true, "type": "string" }, { "availability": "source_interface", "default": null, "default_known": false, "enum": null, "enum_known": false, "min_length": 1, "name": "prompt", "required": true, "type": "string" }, { "availability": "source_interface", "default": 1, "default_known": true, "enum": null, "enum_known": false, "minimum": 1, "name": "n", "required": false, "type": "integer" }, { "availability": "source_interface", "default": null, "default_known": false, "enum": [ "url", "b64_json" ], "enum_known": true, "name": "response_format", "required": false, "type": "string" }, { "availability": "source_interface", "default": false, "default_known": true, "enum": null, "enum_known": false, "name": "stream", "required": false, "type": "boolean" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "size", "required": false, "type": "string" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "quality", "required": false, "type": "string" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "background", "required": false, "type": "string" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "output_format", "required": false, "type": "string" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "output_compression", "required": false, "type": "integer" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "moderation", "required": false, "type": "string" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "input_fidelity", "required": false, "type": "string" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "style", "required": false, "type": "string" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "partial_images", "required": false, "type": "integer" } ], "profile_binding": "Exact existing Ailoot model and method; interface constraints below do not assert provider qualification.", "unsupported": [ "images[].file_id", "mask.file_id" ] }, "hints": [ "方法結構與 ID 均為精確值；供應商能力與准入狀態分開。" ], "input": { "content_type": "application/json", "material_types": [ "text" ], "optional_controls": null, "required": [ "model", "prompt" ] }, "lifecycle": { "assets": [ { "http": "GET", "path": "/v1/media/assets" }, { "http": "GET", "path": "/v1/media/assets/{asset_id}" } ], "content": [ { "http": "GET", "path": "/v1/media/assets/{asset_id}/content", "url_source": "exact returned signed URL; never construct token" } ], "mode": "synchronous_result_then_owned_library", "operation_id_is_not_task_id": true, "status": [ { "http": "GET", "id_source": "實際回傳的 task_id 或媒體庫紀錄", "path": "/v1/media/tasks/{task_id}" } ], "unknown": "If an image generation or edit result requires a check, keep the original operation_id/X-Client-Request-ID and returned result information. Recover existing owned results through the media library using actual task_id or asset_id values. Do not resubmit the generation/edit request or construct a polling URL from operation_id." }, "method": { "http": "POST", "path": "/v1/images/generations" }, "operation_modes": [ "images" ], "output": { "family": [ "image" ], "format": null, "multioutputs": "retain every actual response output" } }, "ctx": 65536, "examples": [ { "code": "set -eu\n: \"${AILOOT_API_KEY:?Set your Ailoot API key}\"\nexport AILOOT_API_KEY\nexport AILOOT_API_KEY\n: \"${AILOOT_PROMPT_FILE:?Set your actual UTF-8 image brief}\"\nexport AILOOT_PROMPT_FILE\npython3 - <<'PY_REQUEST'\nimport json,os\nfrom pathlib import Path\np=json.loads('{\"model\": \"gemini-3-pro-image\", \"prompt\": \"\"}')\nf=Path(os.environ[\"AILOOT_PROMPT_FILE\"])\nif not f.is_file():raise SystemExit(\"Choose your actual UTF-8 brief\")\np['prompt']=f.read_text(encoding=\"utf-8\")\nif not p['prompt'].strip():raise SystemExit(\"Brief must contain text\")\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/images/generations \\\n -H \"Authorization: Bearer $AILOOT_API_KEY\" -H 'Content-Type: application/json' \\\n --data-binary @request.json -D response-headers.txt -o result.json\npython3 - <<'PY_RESULT'\nimport base64, json, os, subprocess\nfrom pathlib import Path\nfrom urllib.parse import urlsplit, urljoin\n\ndef save_images(items):\n if not items: raise SystemExit(\"No completed images; retain the full response\")\n for index, item in enumerate(items):\n encoded=item.get(\"b64_json\")\n uri=item.get(\"url\", \"\")\n if not encoded and uri.startswith(\"data:image/\"):\n header, separator, encoded=uri.partition(\",\")\n if not separator or \";base64\" not in header: raise SystemExit(\"Unsupported image data URI\")\n if encoded:\n raw=base64.b64decode(encoded,validate=True)\n elif uri:\n uri=urljoin(\"https://api.ailoot.ai\",uri)\n parsed=urlsplit(uri)\n if parsed.scheme!=\"https\" or not parsed.netloc or parsed.username or parsed.password:\n raise SystemExit(\"Invalid returned image URL\")\n owned=parsed.netloc==\"api.ailoot.ai\" and parsed.path.startswith(\"/v1/media/assets/\") and parsed.path.endswith(\"/content\")\n args=[\"curl\",\"--fail-with-body\",\"--silent\",\"--show-error\",uri]\n if owned: args += [\"-H\",\"Authorization: Bearer \"+os.environ[\"AILOOT_API_KEY\"]]\n temporary=Path(f\"image-{index}.bin\")\n subprocess.run(args+[\"-o\",str(temporary)],check=True)\n raw=temporary.read_bytes()\n temporary.unlink()\n else: raise SystemExit(\"Image has neither bytes nor URL\")\n if not raw: raise SystemExit(\"Empty image result\")\n ext=\"png\" if raw.startswith(b\"\\x89PNG\") else \"jpg\" if raw.startswith(b\"\\xff\\xd8\") else \"webp\" if raw[:4]==b\"RIFF\" and raw[8:12]==b\"WEBP\" else \"svg\" if raw.lstrip().startswith((b\"G

Google: Nano Banana Pro (Gemini 3 Pro Image)

Google /gemini-3-pro-image-preview

入門

Nano Banana Pro（Gemini 3 Pro Image）是 Google 以推理驅動的圖像模型，適用複雜設計、產品樣稿及事實視覺化。它接收文字與圖像參考，生成圖像及文字，提供 1K–4K 輸出與詳細創意控制。

接受的輸入
文字
結果
圖片
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。

Nano Banana Pro 是 Google 以推理驅動圖像生成及編輯的 Gemini 3 Pro Image 模型。製造商將複雜平面設計、高保真產品樣稿及事實資料視覺化置於預定用途核心。它接收文字與圖像，產生圖像與文字。此具名 Pro 圖像版本以 Gemini 3 Pro 為基礎，同時保有自身圖像任務的輸入及能力設定。

模型支援 1K、2K、4K 圖像。文件中的形狀包括 1:1、2:3、3:2、3:4、4:3、4:5、5:4、9:16、16:9、21:9。正方形 4K 圖像為 4096 × 4096；16:9 4K 圖像為 5504 × 3072。無論需要直式海報、產品場景或寬幅解說圖，均應依成果選擇解析度及長寬比。Gemini 3.1 Flash Image 的 0.5K 選項及額外極端比例不在此 Pro 表內。

文字呈現支援海報、圖解及其他設計素材的清楚字樣。複雜資訊圖表應提供基礎事實、確切文字、閱讀順序，以及標籤與視覺元素關係。請將要傳達的資訊與所需藝術風格分開。Google 建議先準備文字，再生成包含文字的圖像。構圖結合標題、圖解及數段簡短說明時，這尤其實用。

多圖輸入支援最多 14 張參考。Google 功能表描述最多六張物件參考用於忠實呈現、最多五張角色參考用於一致性，以及最多三張風格參考。這些角色有助於準備合成視覺：產品照片定義外觀、另一張圖建立環境，風格圖像則影響處理方式。請告訴模型哪些細節具權威性、哪些參考提供靈感，而非要求它不加區分地結合每個可見特徵。

Google Search grounding 可為事實視覺化或反映當前狀況的場景提供現實資訊。Pro 圖像流程記載網頁 grounding；Image Search 擴充則專門記載於 Nano Banana 2.1 及 Gemini 3.1 Flash Image。資料圖像應提供預期呈現值，或在原始模型流程要求 grounding 資訊，再明確說明關係、標籤及版面。搜尋輔助生成的結果仍是需要檢查的圖像，不能取代核對描繪事實。

推理支援在最終渲染前組織複雜提示。圖像指南描述用於測試構圖與邏輯的中間圖像，與最終成果不同。請勿將 Nano Banana 2 的 minimal/high 控制表，或 Nano Banana 2.1 的 medium 預設表，套用至此 Pro 版本。高難度設計應提供完整需求，包含視覺層級、必要物件關係，以及後續編輯中必須保留的元素。

模型資訊卡描述了仍存在的重要限制：極小文字及長段落可能呈現不佳，角色外觀可能在參考與結果間改變，遮罩或塗鴉編輯可能僅部分遵循指令或留下痕跡。它也可能混淆左右，或將來源元素複製到新構圖。產品修訂應明確說明要保留的幾何形狀與標籤，並檢查編輯區域；圖解應比較箭頭方向及物件相對位置。

目前 API 表列出輸入上限 65,536 token、輸出上限 32,768 token。支援圖像生成、thinking、搜尋 grounding 及批次處理；不支援音訊生成、函式呼叫、程式碼執行、快取、結構化輸出、檔案搜尋、URL context 及 Live API。此設定的圖像任務不接受音訊或影片輸入。生成圖像包含 SynthID，且不一定精確遵循所需輸出圖像數量。

實用產品需求可結合產品圖像、光線參考及確切標題：「保留產品比例與字樣，將它呈現在柔和側光下的淺色石材表面，上方三分之一留白，以放置提供的標題。」事實圖解應指明每個實體及連結，並提供定稿標籤。可透過對話指出一項修改及要保留的特徵來完善結果，將選定圖像與解說文字一起保留為設計成果。

Ailoot 可用 · 輸入與方法

Ailoot · 圖片 POST /v1/images/generations
輸入
text
輸出
image
上下文
65,536 tokens
輸出上限
32,768 tokens
輸出格式
圖片檔案
欄位類型要求值與限制預設值
欄位model類型string要求必填值與限制
gemini-3-pro-image-preview
預設值—
欄位prompt類型string要求必填值與限制
長度下限: 1
預設值—
欄位n類型integer要求選填值與限制
最小值: 1
預設值1
欄位response_format類型string要求選填值與限制
url, b64_json
預設值—
欄位stream類型boolean要求選填值與限制預設值false
欄位size類型string要求選填值與限制
依模型而定
預設值—
欄位quality類型string要求選填值與限制
依模型而定
預設值—
欄位background類型string要求選填值與限制
依模型而定
預設值—
欄位output_format類型string要求選填值與限制
依模型而定
預設值—
欄位output_compression類型integer要求選填值與限制
依模型而定
預設值—
欄位moderation類型string要求選填值與限制
依模型而定
預設值—
欄位input_fidelity類型string要求選填值與限制
依模型而定
預設值—
欄位style類型string要求選填值與限制
依模型而定
預設值—
欄位partial_images類型integer要求選填值與限制
依模型而定
預設值—
輸入素材組合

文字生成圖片 · 必填： prompt

方法參數與生命週期
參數規格
參數material_types規格text
參數required規格model, prompt
參數optional_controls規格null
參數content_type規格application/json

生命週期： synchronous_result_then_owned_library

GET /v1/media/tasks/{task_id} · 實際回傳的 task_id 或媒體庫紀錄

GET /v1/media/assets/{asset_id}/content

GET /v1/media/assets

GET /v1/media/assets/{asset_id}

方法結構與 ID 均為精確值；供應商能力與准入狀態分開。

方案

Ailoot 方法費率

Ailoot 圖片POST /v1/images/generations
輸入
US$0.002 / 1K 圖片 Token
輸出
US$0.134 每張 1K 圖片
輸出
US$0.134 每張 2K 圖片
輸出
US$0.24 每張 4K 圖片

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 →

參考費率詳情

模型層級的參考費率表不會變更方法選擇、報價或費用。實際計費採用所選 Ailoot 方法的費率。

模型參考費率表

各設定的價格

設定費率表費用
設定Ultra費率表基本費率費用
輸入 · 輸入 Token $0.004000 / 1K Token
輸出 · 輸出 Token $0.024000 / 1K Token
輸入 · 圖片 $0.004000 / 1K Token
輸出 · 圖片輸出 $0.24000 / 1K Token
輸入 · 音訊 $0.004000 / 1K Token
輸入 · 輸入音訊快取 $0.0004000 / 1K Token
輸出 · 網頁搜尋 $0.028 每次網頁搜尋
輸出 · 內部推理 $0.024000 / 1K Token
輸入 · 讀取快取 $0.0004000 / 1K Token
輸入 · 寫入快取 $0.000750000 / 1K Token

請求範例

Ailoot · 圖片

set -eu\n: "${AILOOT_API_KEY:?Set your Ailoot API key}"\nexport AILOOT_API_KEY\nexport AILOOT_API_KEY\n: "${AILOOT_PROMPT_FILE:?Set your actual UTF-8 image brief}"\nexport AILOOT_PROMPT_FILE\npython3 - <<'PY_REQUEST'\nimport json,os\nfrom pathlib import Path\np=json.loads('{"model": "gemini-3-pro-image-preview", "prompt": ""}')\nf=Path(os.environ["AILOOT_PROMPT_FILE"])\nif not f.is_file():raise SystemExit("Choose your actual UTF-8 brief")\np['prompt']=f.read_text(encoding="utf-8")\nif not p['prompt'].strip():raise SystemExit("Brief must contain text")\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/images/generations \\\n  -H "Authorization: Bearer $AILOOT_API_KEY" -H 'Content-Type: application/json' \\\n  --data-binary @request.json -D response-headers.txt -o result.json\npython3 - <<'PY_RESULT'\nimport base64, json, os, subprocess\nfrom pathlib import Path\nfrom urllib.parse import urlsplit, urljoin\n\ndef save_images(items):\n    if not items: raise SystemExit("No completed images; retain the full response")\n    for index, item in enumerate(items):\n        encoded=item.get("b64_json")\n        uri=item.get("url", "")\n        if not encoded and uri.startswith("data:image/"):\n            header, separator, encoded=uri.partition(",")\n            if not separator or ";base64" not in header: raise SystemExit("Unsupported image data URI")\n        if encoded:\n            raw=base64.b64decode(encoded,validate=True)\n        elif uri:\n            uri=urljoin("https://api.ailoot.ai",uri)\n            parsed=urlsplit(uri)\n            if parsed.scheme!="https" or not parsed.netloc or parsed.username or parsed.password:\n                raise SystemExit("Invalid returned image URL")\n            owned=parsed.netloc=="api.ailoot.ai" and parsed.path.startswith("/v1/media/assets/") and parsed.path.endswith("/content")\n            args=["curl","--fail-with-body","--silent","--show-error",uri]\n            if owned: args += ["-H","Authorization: Bearer "+os.environ["AILOOT_API_KEY"]]\n            temporary=Path(f"image-{index}.bin")\n            subprocess.run(args+["-o",str(temporary)],check=True)\n            raw=temporary.read_bytes()\n            temporary.unlink()\n        else: raise SystemExit("Image has neither bytes nor URL")\n        if not raw: raise SystemExit("Empty image result")\n        ext="png" if raw.startswith(b"\\x89PNG") else "jpg" if raw.startswith(b"\\xff\\xd8") else "webp" if raw[:4]==b"RIFF" and raw[8:12]==b"WEBP" else "svg" if raw.lstrip().startswith((b"<svg",b"<?xml")) else "bin"\n        Path(f"image-{index}.{ext}").write_bytes(raw)\n    print("Every returned image saved; complete response metadata retained")\nsave_images(json.loads(Path("result.json").read_text())["data"])\nPY_RESULT\n

接收並儲存結果

Ailoot · 圖片

下載每張傳回的圖片，或儲存其 Base64 內容

  • GET /v1/media/tasks/{task_id}
  • GET /v1/media/assets/{asset_id}/content
  • GET /v1/media/assets
  • GET /v1/media/assets/{asset_id}
保留所有已完成的結果

請儲存每張已完成的圖片；從每個傳回的 URL 取得圖片，或解碼其 Base64 內容。

儲存所有資料項目。解碼每個 b64_json，或透過每個回傳的已簽署 URL 取得內容。依實際 MIME 類型／位元組內容選擇副檔名。

需要檢查原始回應時

若圖片生成或編輯結果需要檢查，請保留原始 operation_id/X-Client-Request-ID 與回傳的結果資訊。使用實際的 task_id 或 asset_id 值，透過媒體庫取回自己擁有的既有結果。請勿重新提交生成／編輯請求，也請勿以 operation_id 組成輪詢 URL。

回應欄位
欄位類型
欄位created類型integer
欄位data[].url類型string
欄位data[].b64_json類型base64 string
欄位usage類型object
錯誤與後續步驟
回應條件下一步
回應400 · invalid_request_error條件必要欄位、素材表示方式或參數值無效下一步提出新的建立請求前，先修正指定欄位。
回應server_error條件回傳的回應表示該作業或結果需要檢查下一步保留原始回傳的作業／任務 ID、請求標頭與回應；繼續以支援的方式讀取該原始作業。請勿重新提交建立請求。

別名

模型別名

Ailoot gemini-3-pro-image, gemini-3-pro-image-preview, nano-banana-pro
Ailoot Ultra google/gemini-3-pro-image

方法路徑別名

/v1/images

相關呼叫用 ID

google/gemini-3-pro-image, gemini-3-pro-image-preview, nano-banana-pro, gemini-3-pro-image

", "method_identity": { "effective_request_model_id": "gemini-3-pro-image-preview", "fmt": "images", "http": "POST", "path": "/v1/images/generations", "request_model_id": "gemini-3-pro-image-preview", "route_label": "Core" }, "method_key": "Core|images|/v1/images/generations|gemini-3-pro-image-preview", "ordinal": 1, "rawMethod": { "cache_read": null, "cache_write": null, "cache_write_1h": null, "cache_write_5m": null, "conditional_meter": null, "contract": { "data": { "all_results": "Save every data item. Decode each b64_json or fetch every returned signed URL. Select a filename extension from the actual MIME/bytes.", "errors": [ { "code": null, "condition": "必要欄位、素材表示方式或參數值無效", "http_status": 400, "recovery": "提出新的建立請求前，先修正指定欄位。", "type": "invalid_request_error" }, { "code": null, "condition": "回傳的回應表示該作業或結果需要檢查", "http_status": null, "recovery": "保留原始回傳的作業／任務 ID、請求標頭與回應；繼續以支援的方式讀取該原始作業。請勿重新提交建立請求。", "type": "server_error" } ], "hints": [], "ignored_fields": [], "lifecycle": { "all_results": "Follow everyactualreturnedoutputandownedasset; no result is discardedbecauseindex0orcontent_urlalreadyexists.", "assets": [ { "http": "GET", "path": "/v1/media/assets" }, { "http": "GET", "path": "/v1/media/assets/{asset_id}" } ], "content": [ { "http": "GET", "path": "/v1/media/assets/{asset_id}/content", "url_source": "exact returned signed URL; never construct token" } ], "mode": "synchronous_result_then_owned_library", "operation_id_is_not_task_id": true, "status": [ { "http": "GET", "id_source": "actual returned task_id or media library record", "path": "/v1/media/tasks/{task_id}" } ], "unknown": "若圖片生成或編輯結果需要檢查，請保留原始 operation_id/X-Client-Request-ID 與回傳的結果資訊。使用實際的 task_id 或 asset_id 值，透過媒體庫取回自己擁有的既有結果。請勿重新提交生成／編輯請求，也請勿以 operation_id 組成輪詢 URL。" }, "material_combinations": [ { "content_types": [ "application/json", "multipart/form-data" ], "file_id_supported": false, "mode": "text_to_image", "multipart_part_read_limit_bytes": 20971520, "optional_mask": { "json": "mask.image_url", "multipart": "mask" }, "reference_representations": { "json": "images[].image_url", "multipart": [ "image", "image[]", "image[index]" ] }, "required": [ "prompt" ] } ], "media_library": { "asset": { "fields": [ { "description": null, "name": "asset_id", "type": "string" }, { "description": null, "name": "task_id", "type": "string" }, { "description": null, "name": "output_key", "type": "string" }, { "description": null, "name": "family", "type": "string" }, { "description": null, "name": "model", "type": "string" }, { "description": null, "name": "method", "type": "string" }, { "description": null, "name": "status", "type": "string" }, { "description": null, "name": "content_type", "type": "string" }, { "description": null, "name": "sha256", "type": "string" }, { "description": null, "name": "size_bytes", "type": "integer" }, { "description": null, "name": "content_url", "type": "string" } ], "http": "GET", "id_source": "actual returned asset_id", "path": "/v1/media/assets/{asset_id}" }, "content": { "http": "GET", "path": "/v1/media/assets/{asset_id}/content", "range_header_supported": true, "url_source": "Use exact returned signed content_url including its token; do not construct a token." }, "expired_link": { "code": "link_expired", "http_status": 404, "recovery": "Read the asset again to obtain its refreshed signed content_url, then fetch that URL. Do not regenerate." }, "list": { "all_pages": "Follow every returned next_cursor, then select records by their actual task_id/output_key.", "http": "GET", "output_fields": [ { "description": null, "name": "object", "type": "string" }, { "description": null, "name": "data", "type": "asset[]" }, { "description": null, "name": "next_cursor", "type": "string|null" } ], "parameters": [ { "availability": "source_interface", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "family", "required": false, "type": "string" }, { "availability": "source_interface", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "cursor", "required": false, "type": "string" }, { "availability": "source_interface", "default": 20, "default_known": true, "enum": null, "enum_known": false, "maximum": 100, "minimum": 1, "name": "limit", "required": false, "type": "integer" } ], "path": "/v1/media/assets" }, "revoke": { "http": "DELETE", "meaning": "Revokes/deletes the existing owned file; this is not generation cancellation.", "path": "/v1/media/assets/{asset_id}", "pending_status": "revoking", "success_statuses": [ 202, 204 ] }, "task": { "http": "GET", "id_source": "actual returned task_id or media library record; operation_id is not task_id", "path": "/v1/media/tasks/{task_id}" } }, "operation_modes": [ "text_to_image" ], "outputs": { "all_results": "儲存所有資料項目。解碼每個 b64_json，或透過每個回傳的已簽署 URL 取得內容。依實際 MIME 類型／位元組內容選擇副檔名。", "family": "image", "fields": [ { "description": null, "name": "created", "type": "integer" }, { "description": null, "name": "data[].url", "type": "string" }, { "description": null, "name": "data[].b64_json", "type": "base64 string" }, { "description": null, "name": "usage", "type": "object" } ], "format": "actual validated raster MIME" }, "parameters": [ { "availability": "source_interface", "default": null, "default_known": false, "enum": [ "gemini-3-pro-image-preview" ], "enum_known": true, "name": "model", "required": true, "type": "string" }, { "availability": "source_interface", "default": null, "default_known": false, "enum": null, "enum_known": false, "min_length": 1, "name": "prompt", "required": true, "type": "string" }, { "availability": "source_interface", "default": 1, "default_known": true, "enum": null, "enum_known": false, "minimum": 1, "name": "n", "required": false, "type": "integer" }, { "availability": "source_interface", "default": null, "default_known": false, "enum": [ "url", "b64_json" ], "enum_known": true, "name": "response_format", "required": false, "type": "string" }, { "availability": "source_interface", "default": false, "default_known": true, "enum": null, "enum_known": false, "name": "stream", "required": false, "type": "boolean" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "size", "required": false, "type": "string" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "quality", "required": false, "type": "string" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "background", "required": false, "type": "string" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "output_format", "required": false, "type": "string" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "output_compression", "required": false, "type": "integer" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "moderation", "required": false, "type": "string" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "input_fidelity", "required": false, "type": "string" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "style", "required": false, "type": "string" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "partial_images", "required": false, "type": "integer" } ], "profile_binding": "Exact existing Ailoot model and method; interface constraints below do not assert provider qualification.", "unsupported": [ "images[].file_id", "mask.file_id" ] }, "hints": [ "方法結構與 ID 均為精確值；供應商能力與准入狀態分開。" ], "input": { "content_type": "application/json", "material_types": [ "text" ], "optional_controls": null, "required": [ "model", "prompt" ] }, "lifecycle": { "assets": [ { "http": "GET", "path": "/v1/media/assets" }, { "http": "GET", "path": "/v1/media/assets/{asset_id}" } ], "content": [ { "http": "GET", "path": "/v1/media/assets/{asset_id}/content", "url_source": "exact returned signed URL; never construct token" } ], "mode": "synchronous_result_then_owned_library", "operation_id_is_not_task_id": true, "status": [ { "http": "GET", "id_source": "實際回傳的 task_id 或媒體庫紀錄", "path": "/v1/media/tasks/{task_id}" } ], "unknown": "If an image generation or edit result requires a check, keep the original operation_id/X-Client-Request-ID and returned result information. Recover existing owned results through the media library using actual task_id or asset_id values. Do not resubmit the generation/edit request or construct a polling URL from operation_id." }, "method": { "http": "POST", "path": "/v1/images/generations" }, "operation_modes": [ "images" ], "output": { "family": [ "image" ], "format": null, "multioutputs": "retain every actual response output" } }, "ctx": 65536, "examples": [ { "code": "set -eu\n: \"${AILOOT_API_KEY:?Set your Ailoot API key}\"\nexport AILOOT_API_KEY\nexport AILOOT_API_KEY\n: \"${AILOOT_PROMPT_FILE:?Set your actual UTF-8 image brief}\"\nexport AILOOT_PROMPT_FILE\npython3 - <<'PY_REQUEST'\nimport json,os\nfrom pathlib import Path\np=json.loads('{\"model\": \"gemini-3-pro-image-preview\", \"prompt\": \"\"}')\nf=Path(os.environ[\"AILOOT_PROMPT_FILE\"])\nif not f.is_file():raise SystemExit(\"Choose your actual UTF-8 brief\")\np['prompt']=f.read_text(encoding=\"utf-8\")\nif not p['prompt'].strip():raise SystemExit(\"Brief must contain text\")\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/images/generations \\\n -H \"Authorization: Bearer $AILOOT_API_KEY\" -H 'Content-Type: application/json' \\\n --data-binary @request.json -D response-headers.txt -o result.json\npython3 - <<'PY_RESULT'\nimport base64, json, os, subprocess\nfrom pathlib import Path\nfrom urllib.parse import urlsplit, urljoin\n\ndef save_images(items):\n if not items: raise SystemExit(\"No completed images; retain the full response\")\n for index, item in enumerate(items):\n encoded=item.get(\"b64_json\")\n uri=item.get(\"url\", \"\")\n if not encoded and uri.startswith(\"data:image/\"):\n header, separator, encoded=uri.partition(\",\")\n if not separator or \";base64\" not in header: raise SystemExit(\"Unsupported image data URI\")\n if encoded:\n raw=base64.b64decode(encoded,validate=True)\n elif uri:\n uri=urljoin(\"https://api.ailoot.ai\",uri)\n parsed=urlsplit(uri)\n if parsed.scheme!=\"https\" or not parsed.netloc or parsed.username or parsed.password:\n raise SystemExit(\"Invalid returned image URL\")\n owned=parsed.netloc==\"api.ailoot.ai\" and parsed.path.startswith(\"/v1/media/assets/\") and parsed.path.endswith(\"/content\")\n args=[\"curl\",\"--fail-with-body\",\"--silent\",\"--show-error\",uri]\n if owned: args += [\"-H\",\"Authorization: Bearer \"+os.environ[\"AILOOT_API_KEY\"]]\n temporary=Path(f\"image-{index}.bin\")\n subprocess.run(args+[\"-o\",str(temporary)],check=True)\n raw=temporary.read_bytes()\n temporary.unlink()\n else: raise SystemExit(\"Image has neither bytes nor URL\")\n if not raw: raise SystemExit(\"Empty image result\")\n ext=\"png\" if raw.startswith(b\"\\x89PNG\") else \"jpg\" if raw.startswith(b\"\\xff\\xd8\") else \"webp\" if raw[:4]==b\"RIFF\" and raw[8:12]==b\"WEBP\" else \"svg\" if raw.lstrip().startswith((b\"G

Google: Nano Banana Pro (Gemini 3 Pro Image)

Google /nano-banana-pro

入門

Nano Banana Pro（Gemini 3 Pro Image）是 Google 以推理驅動的圖像模型，適用複雜設計、產品樣稿及事實視覺化。它接收文字與圖像參考，生成圖像及文字，提供 1K–4K 輸出與詳細創意控制。

接受的輸入
文字
結果
圖片
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。

Nano Banana Pro 是 Google 以推理驅動圖像生成及編輯的 Gemini 3 Pro Image 模型。製造商將複雜平面設計、高保真產品樣稿及事實資料視覺化置於預定用途核心。它接收文字與圖像，產生圖像與文字。此具名 Pro 圖像版本以 Gemini 3 Pro 為基礎，同時保有自身圖像任務的輸入及能力設定。

模型支援 1K、2K、4K 圖像。文件中的形狀包括 1:1、2:3、3:2、3:4、4:3、4:5、5:4、9:16、16:9、21:9。正方形 4K 圖像為 4096 × 4096；16:9 4K 圖像為 5504 × 3072。無論需要直式海報、產品場景或寬幅解說圖，均應依成果選擇解析度及長寬比。Gemini 3.1 Flash Image 的 0.5K 選項及額外極端比例不在此 Pro 表內。

文字呈現支援海報、圖解及其他設計素材的清楚字樣。複雜資訊圖表應提供基礎事實、確切文字、閱讀順序，以及標籤與視覺元素關係。請將要傳達的資訊與所需藝術風格分開。Google 建議先準備文字，再生成包含文字的圖像。構圖結合標題、圖解及數段簡短說明時，這尤其實用。

多圖輸入支援最多 14 張參考。Google 功能表描述最多六張物件參考用於忠實呈現、最多五張角色參考用於一致性，以及最多三張風格參考。這些角色有助於準備合成視覺：產品照片定義外觀、另一張圖建立環境，風格圖像則影響處理方式。請告訴模型哪些細節具權威性、哪些參考提供靈感，而非要求它不加區分地結合每個可見特徵。

Google Search grounding 可為事實視覺化或反映當前狀況的場景提供現實資訊。Pro 圖像流程記載網頁 grounding；Image Search 擴充則專門記載於 Nano Banana 2.1 及 Gemini 3.1 Flash Image。資料圖像應提供預期呈現值，或在原始模型流程要求 grounding 資訊，再明確說明關係、標籤及版面。搜尋輔助生成的結果仍是需要檢查的圖像，不能取代核對描繪事實。

推理支援在最終渲染前組織複雜提示。圖像指南描述用於測試構圖與邏輯的中間圖像，與最終成果不同。請勿將 Nano Banana 2 的 minimal/high 控制表，或 Nano Banana 2.1 的 medium 預設表，套用至此 Pro 版本。高難度設計應提供完整需求，包含視覺層級、必要物件關係，以及後續編輯中必須保留的元素。

模型資訊卡描述了仍存在的重要限制：極小文字及長段落可能呈現不佳，角色外觀可能在參考與結果間改變，遮罩或塗鴉編輯可能僅部分遵循指令或留下痕跡。它也可能混淆左右，或將來源元素複製到新構圖。產品修訂應明確說明要保留的幾何形狀與標籤，並檢查編輯區域；圖解應比較箭頭方向及物件相對位置。

目前 API 表列出輸入上限 65,536 token、輸出上限 32,768 token。支援圖像生成、thinking、搜尋 grounding 及批次處理；不支援音訊生成、函式呼叫、程式碼執行、快取、結構化輸出、檔案搜尋、URL context 及 Live API。此設定的圖像任務不接受音訊或影片輸入。生成圖像包含 SynthID，且不一定精確遵循所需輸出圖像數量。

實用產品需求可結合產品圖像、光線參考及確切標題：「保留產品比例與字樣，將它呈現在柔和側光下的淺色石材表面，上方三分之一留白，以放置提供的標題。」事實圖解應指明每個實體及連結，並提供定稿標籤。可透過對話指出一項修改及要保留的特徵來完善結果，將選定圖像與解說文字一起保留為設計成果。

Ailoot 可用 · 輸入與方法

Ailoot · 圖片 POST /v1/images/generations
輸入
text
輸出
image
上下文
65,536 tokens
輸出上限
32,768 tokens
輸出格式
圖片檔案
欄位類型要求值與限制預設值
欄位model類型string要求必填值與限制
nano-banana-pro
預設值—
欄位prompt類型string要求必填值與限制
長度下限: 1
預設值—
欄位n類型integer要求選填值與限制
最小值: 1
預設值1
欄位response_format類型string要求選填值與限制
url, b64_json
預設值—
欄位stream類型boolean要求選填值與限制預設值false
欄位size類型string要求選填值與限制
依模型而定
預設值—
欄位quality類型string要求選填值與限制
依模型而定
預設值—
欄位background類型string要求選填值與限制
依模型而定
預設值—
欄位output_format類型string要求選填值與限制
依模型而定
預設值—
欄位output_compression類型integer要求選填值與限制
依模型而定
預設值—
欄位moderation類型string要求選填值與限制
依模型而定
預設值—
欄位input_fidelity類型string要求選填值與限制
依模型而定
預設值—
欄位style類型string要求選填值與限制
依模型而定
預設值—
欄位partial_images類型integer要求選填值與限制
依模型而定
預設值—
輸入素材組合

文字生成圖片 · 必填： prompt

方法參數與生命週期
參數規格
參數material_types規格text
參數required規格model, prompt
參數optional_controls規格null
參數content_type規格application/json

生命週期： synchronous_result_then_owned_library

GET /v1/media/tasks/{task_id} · 實際回傳的 task_id 或媒體庫紀錄

GET /v1/media/assets/{asset_id}/content

GET /v1/media/assets

GET /v1/media/assets/{asset_id}

方法結構與 ID 均為精確值；供應商能力與准入狀態分開。

方案

Ailoot 方法費率

Ailoot 圖片POST /v1/images/generations
輸入
US$0.002 / 1K 圖片 Token
輸出
US$0.134 每張 1K 圖片
輸出
US$0.134 每張 2K 圖片
輸出
US$0.24 每張 4K 圖片

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 →

參考費率詳情

模型層級的參考費率表不會變更方法選擇、報價或費用。實際計費採用所選 Ailoot 方法的費率。

模型參考費率表

各設定的價格

設定費率表費用
設定Ultra費率表基本費率費用
輸入 · 輸入 Token $0.004000 / 1K Token
輸出 · 輸出 Token $0.024000 / 1K Token
輸入 · 圖片 $0.004000 / 1K Token
輸出 · 圖片輸出 $0.24000 / 1K Token
輸入 · 音訊 $0.004000 / 1K Token
輸入 · 輸入音訊快取 $0.0004000 / 1K Token
輸出 · 網頁搜尋 $0.028 每次網頁搜尋
輸出 · 內部推理 $0.024000 / 1K Token
輸入 · 讀取快取 $0.0004000 / 1K Token
輸入 · 寫入快取 $0.000750000 / 1K Token

請求範例

Ailoot · 圖片

set -eu\n: "${AILOOT_API_KEY:?Set your Ailoot API key}"\nexport AILOOT_API_KEY\nexport AILOOT_API_KEY\n: "${AILOOT_PROMPT_FILE:?Set your actual UTF-8 image brief}"\nexport AILOOT_PROMPT_FILE\npython3 - <<'PY_REQUEST'\nimport json,os\nfrom pathlib import Path\np=json.loads('{"model": "nano-banana-pro", "prompt": ""}')\nf=Path(os.environ["AILOOT_PROMPT_FILE"])\nif not f.is_file():raise SystemExit("Choose your actual UTF-8 brief")\np['prompt']=f.read_text(encoding="utf-8")\nif not p['prompt'].strip():raise SystemExit("Brief must contain text")\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/images/generations \\\n  -H "Authorization: Bearer $AILOOT_API_KEY" -H 'Content-Type: application/json' \\\n  --data-binary @request.json -D response-headers.txt -o result.json\npython3 - <<'PY_RESULT'\nimport base64, json, os, subprocess\nfrom pathlib import Path\nfrom urllib.parse import urlsplit, urljoin\n\ndef save_images(items):\n    if not items: raise SystemExit("No completed images; retain the full response")\n    for index, item in enumerate(items):\n        encoded=item.get("b64_json")\n        uri=item.get("url", "")\n        if not encoded and uri.startswith("data:image/"):\n            header, separator, encoded=uri.partition(",")\n            if not separator or ";base64" not in header: raise SystemExit("Unsupported image data URI")\n        if encoded:\n            raw=base64.b64decode(encoded,validate=True)\n        elif uri:\n            uri=urljoin("https://api.ailoot.ai",uri)\n            parsed=urlsplit(uri)\n            if parsed.scheme!="https" or not parsed.netloc or parsed.username or parsed.password:\n                raise SystemExit("Invalid returned image URL")\n            owned=parsed.netloc=="api.ailoot.ai" and parsed.path.startswith("/v1/media/assets/") and parsed.path.endswith("/content")\n            args=["curl","--fail-with-body","--silent","--show-error",uri]\n            if owned: args += ["-H","Authorization: Bearer "+os.environ["AILOOT_API_KEY"]]\n            temporary=Path(f"image-{index}.bin")\n            subprocess.run(args+["-o",str(temporary)],check=True)\n            raw=temporary.read_bytes()\n            temporary.unlink()\n        else: raise SystemExit("Image has neither bytes nor URL")\n        if not raw: raise SystemExit("Empty image result")\n        ext="png" if raw.startswith(b"\\x89PNG") else "jpg" if raw.startswith(b"\\xff\\xd8") else "webp" if raw[:4]==b"RIFF" and raw[8:12]==b"WEBP" else "svg" if raw.lstrip().startswith((b"<svg",b"<?xml")) else "bin"\n        Path(f"image-{index}.{ext}").write_bytes(raw)\n    print("Every returned image saved; complete response metadata retained")\nsave_images(json.loads(Path("result.json").read_text())["data"])\nPY_RESULT\n

接收並儲存結果

Ailoot · 圖片

下載每張傳回的圖片，或儲存其 Base64 內容

  • GET /v1/media/tasks/{task_id}
  • GET /v1/media/assets/{asset_id}/content
  • GET /v1/media/assets
  • GET /v1/media/assets/{asset_id}
保留所有已完成的結果

請儲存每張已完成的圖片；從每個傳回的 URL 取得圖片，或解碼其 Base64 內容。

儲存所有資料項目。解碼每個 b64_json，或透過每個回傳的已簽署 URL 取得內容。依實際 MIME 類型／位元組內容選擇副檔名。

需要檢查原始回應時

若圖片生成或編輯結果需要檢查，請保留原始 operation_id/X-Client-Request-ID 與回傳的結果資訊。使用實際的 task_id 或 asset_id 值，透過媒體庫取回自己擁有的既有結果。請勿重新提交生成／編輯請求，也請勿以 operation_id 組成輪詢 URL。

回應欄位
欄位類型
欄位created類型integer
欄位data[].url類型string
欄位data[].b64_json類型base64 string
欄位usage類型object
錯誤與後續步驟
回應條件下一步
回應400 · invalid_request_error條件必要欄位、素材表示方式或參數值無效下一步提出新的建立請求前，先修正指定欄位。
回應server_error條件回傳的回應表示該作業或結果需要檢查下一步保留原始回傳的作業／任務 ID、請求標頭與回應；繼續以支援的方式讀取該原始作業。請勿重新提交建立請求。

別名

模型別名

Ailoot gemini-3-pro-image, gemini-3-pro-image-preview, nano-banana-pro
Ailoot Ultra google/gemini-3-pro-image

方法路徑別名

/v1/images

相關呼叫用 ID

google/gemini-3-pro-image, gemini-3-pro-image-preview, nano-banana-pro, gemini-3-pro-image

", "method_identity": { "effective_request_model_id": "nano-banana-pro", "fmt": "images", "http": "POST", "path": "/v1/images/generations", "request_model_id": "nano-banana-pro", "route_label": "Core" }, "method_key": "Core|images|/v1/images/generations|nano-banana-pro", "ordinal": 2, "rawMethod": { "cache_read": null, "cache_write": null, "cache_write_1h": null, "cache_write_5m": null, "conditional_meter": null, "contract": { "data": { "all_results": "Save every data item. Decode each b64_json or fetch every returned signed URL. Select a filename extension from the actual MIME/bytes.", "errors": [ { "code": null, "condition": "必要欄位、素材表示方式或參數值無效", "http_status": 400, "recovery": "提出新的建立請求前，先修正指定欄位。", "type": "invalid_request_error" }, { "code": null, "condition": "回傳的回應表示該作業或結果需要檢查", "http_status": null, "recovery": "保留原始回傳的作業／任務 ID、請求標頭與回應；繼續以支援的方式讀取該原始作業。請勿重新提交建立請求。", "type": "server_error" } ], "hints": [], "ignored_fields": [], "lifecycle": { "all_results": "Follow everyactualreturnedoutputandownedasset; no result is discardedbecauseindex0orcontent_urlalreadyexists.", "assets": [ { "http": "GET", "path": "/v1/media/assets" }, { "http": "GET", "path": "/v1/media/assets/{asset_id}" } ], "content": [ { "http": "GET", "path": "/v1/media/assets/{asset_id}/content", "url_source": "exact returned signed URL; never construct token" } ], "mode": "synchronous_result_then_owned_library", "operation_id_is_not_task_id": true, "status": [ { "http": "GET", "id_source": "actual returned task_id or media library record", "path": "/v1/media/tasks/{task_id}" } ], "unknown": "若圖片生成或編輯結果需要檢查，請保留原始 operation_id/X-Client-Request-ID 與回傳的結果資訊。使用實際的 task_id 或 asset_id 值，透過媒體庫取回自己擁有的既有結果。請勿重新提交生成／編輯請求，也請勿以 operation_id 組成輪詢 URL。" }, "material_combinations": [ { "content_types": [ "application/json", "multipart/form-data" ], "file_id_supported": false, "mode": "text_to_image", "multipart_part_read_limit_bytes": 20971520, "optional_mask": { "json": "mask.image_url", "multipart": "mask" }, "reference_representations": { "json": "images[].image_url", "multipart": [ "image", "image[]", "image[index]" ] }, "required": [ "prompt" ] } ], "media_library": { "asset": { "fields": [ { "description": null, "name": "asset_id", "type": "string" }, { "description": null, "name": "task_id", "type": "string" }, { "description": null, "name": "output_key", "type": "string" }, { "description": null, "name": "family", "type": "string" }, { "description": null, "name": "model", "type": "string" }, { "description": null, "name": "method", "type": "string" }, { "description": null, "name": "status", "type": "string" }, { "description": null, "name": "content_type", "type": "string" }, { "description": null, "name": "sha256", "type": "string" }, { "description": null, "name": "size_bytes", "type": "integer" }, { "description": null, "name": "content_url", "type": "string" } ], "http": "GET", "id_source": "actual returned asset_id", "path": "/v1/media/assets/{asset_id}" }, "content": { "http": "GET", "path": "/v1/media/assets/{asset_id}/content", "range_header_supported": true, "url_source": "Use exact returned signed content_url including its token; do not construct a token." }, "expired_link": { "code": "link_expired", "http_status": 404, "recovery": "Read the asset again to obtain its refreshed signed content_url, then fetch that URL. Do not regenerate." }, "list": { "all_pages": "Follow every returned next_cursor, then select records by their actual task_id/output_key.", "http": "GET", "output_fields": [ { "description": null, "name": "object", "type": "string" }, { "description": null, "name": "data", "type": "asset[]" }, { "description": null, "name": "next_cursor", "type": "string|null" } ], "parameters": [ { "availability": "source_interface", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "family", "required": false, "type": "string" }, { "availability": "source_interface", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "cursor", "required": false, "type": "string" }, { "availability": "source_interface", "default": 20, "default_known": true, "enum": null, "enum_known": false, "maximum": 100, "minimum": 1, "name": "limit", "required": false, "type": "integer" } ], "path": "/v1/media/assets" }, "revoke": { "http": "DELETE", "meaning": "Revokes/deletes the existing owned file; this is not generation cancellation.", "path": "/v1/media/assets/{asset_id}", "pending_status": "revoking", "success_statuses": [ 202, 204 ] }, "task": { "http": "GET", "id_source": "actual returned task_id or media library record; operation_id is not task_id", "path": "/v1/media/tasks/{task_id}" } }, "operation_modes": [ "text_to_image" ], "outputs": { "all_results": "儲存所有資料項目。解碼每個 b64_json，或透過每個回傳的已簽署 URL 取得內容。依實際 MIME 類型／位元組內容選擇副檔名。", "family": "image", "fields": [ { "description": null, "name": "created", "type": "integer" }, { "description": null, "name": "data[].url", "type": "string" }, { "description": null, "name": "data[].b64_json", "type": "base64 string" }, { "description": null, "name": "usage", "type": "object" } ], "format": "actual validated raster MIME" }, "parameters": [ { "availability": "source_interface", "default": null, "default_known": false, "enum": [ "nano-banana-pro" ], "enum_known": true, "name": "model", "required": true, "type": "string" }, { "availability": "source_interface", "default": null, "default_known": false, "enum": null, "enum_known": false, "min_length": 1, "name": "prompt", "required": true, "type": "string" }, { "availability": "source_interface", "default": 1, "default_known": true, "enum": null, "enum_known": false, "minimum": 1, "name": "n", "required": false, "type": "integer" }, { "availability": "source_interface", "default": null, "default_known": false, "enum": [ "url", "b64_json" ], "enum_known": true, "name": "response_format", "required": false, "type": "string" }, { "availability": "source_interface", "default": false, "default_known": true, "enum": null, "enum_known": false, "name": "stream", "required": false, "type": "boolean" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "size", "required": false, "type": "string" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "quality", "required": false, "type": "string" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "background", "required": false, "type": "string" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "output_format", "required": false, "type": "string" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "output_compression", "required": false, "type": "integer" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "moderation", "required": false, "type": "string" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "input_fidelity", "required": false, "type": "string" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "style", "required": false, "type": "string" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "partial_images", "required": false, "type": "integer" } ], "profile_binding": "Exact existing Ailoot model and method; interface constraints below do not assert provider qualification.", "unsupported": [ "images[].file_id", "mask.file_id" ] }, "hints": [ "方法結構與 ID 均為精確值；供應商能力與准入狀態分開。" ], "input": { "content_type": "application/json", "material_types": [ "text" ], "optional_controls": null, "required": [ "model", "prompt" ] }, "lifecycle": { "assets": [ { "http": "GET", "path": "/v1/media/assets" }, { "http": "GET", "path": "/v1/media/assets/{asset_id}" } ], "content": [ { "http": "GET", "path": "/v1/media/assets/{asset_id}/content", "url_source": "exact returned signed URL; never construct token" } ], "mode": "synchronous_result_then_owned_library", "operation_id_is_not_task_id": true, "status": [ { "http": "GET", "id_source": "實際回傳的 task_id 或媒體庫紀錄", "path": "/v1/media/tasks/{task_id}" } ], "unknown": "If an image generation or edit result requires a check, keep the original operation_id/X-Client-Request-ID and returned result information. Recover existing owned results through the media library using actual task_id or asset_id values. Do not resubmit the generation/edit request or construct a polling URL from operation_id." }, "method": { "http": "POST", "path": "/v1/images/generations" }, "operation_modes": [ "images" ], "output": { "family": [ "image" ], "format": null, "multioutputs": "retain every actual response output" } }, "ctx": 65536, "examples": [ { "code": "set -eu\n: \"${AILOOT_API_KEY:?Set your Ailoot API key}\"\nexport AILOOT_API_KEY\nexport AILOOT_API_KEY\n: \"${AILOOT_PROMPT_FILE:?Set your actual UTF-8 image brief}\"\nexport AILOOT_PROMPT_FILE\npython3 - <<'PY_REQUEST'\nimport json,os\nfrom pathlib import Path\np=json.loads('{\"model\": \"nano-banana-pro\", \"prompt\": \"\"}')\nf=Path(os.environ[\"AILOOT_PROMPT_FILE\"])\nif not f.is_file():raise SystemExit(\"Choose your actual UTF-8 brief\")\np['prompt']=f.read_text(encoding=\"utf-8\")\nif not p['prompt'].strip():raise SystemExit(\"Brief must contain text\")\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/images/generations \\\n -H \"Authorization: Bearer $AILOOT_API_KEY\" -H 'Content-Type: application/json' \\\n --data-binary @request.json -D response-headers.txt -o result.json\npython3 - <<'PY_RESULT'\nimport base64, json, os, subprocess\nfrom pathlib import Path\nfrom urllib.parse import urlsplit, urljoin\n\ndef save_images(items):\n if not items: raise SystemExit(\"No completed images; retain the full response\")\n for index, item in enumerate(items):\n encoded=item.get(\"b64_json\")\n uri=item.get(\"url\", \"\")\n if not encoded and uri.startswith(\"data:image/\"):\n header, separator, encoded=uri.partition(\",\")\n if not separator or \";base64\" not in header: raise SystemExit(\"Unsupported image data URI\")\n if encoded:\n raw=base64.b64decode(encoded,validate=True)\n elif uri:\n uri=urljoin(\"https://api.ailoot.ai\",uri)\n parsed=urlsplit(uri)\n if parsed.scheme!=\"https\" or not parsed.netloc or parsed.username or parsed.password:\n raise SystemExit(\"Invalid returned image URL\")\n owned=parsed.netloc==\"api.ailoot.ai\" and parsed.path.startswith(\"/v1/media/assets/\") and parsed.path.endswith(\"/content\")\n args=[\"curl\",\"--fail-with-body\",\"--silent\",\"--show-error\",uri]\n if owned: args += [\"-H\",\"Authorization: Bearer \"+os.environ[\"AILOOT_API_KEY\"]]\n temporary=Path(f\"image-{index}.bin\")\n subprocess.run(args+[\"-o\",str(temporary)],check=True)\n raw=temporary.read_bytes()\n temporary.unlink()\n else: raise SystemExit(\"Image has neither bytes nor URL\")\n if not raw: raise SystemExit(\"Empty image result\")\n ext=\"png\" if raw.startswith(b\"\\x89PNG\") else \"jpg\" if raw.startswith(b\"\\xff\\xd8\") else \"webp\" if raw[:4]==b\"RIFF\" and raw[8:12]==b\"WEBP\" else \"svg\" if raw.lstrip().startswith((b\"G

Google: Nano Banana Pro (Gemini 3 Pro Image)

Google /google/gemini-3-pro-image

入門

Nano Banana Pro（Gemini 3 Pro Image）是 Google 以推理驅動的圖像模型，適用複雜設計、產品樣稿及事實視覺化。它接收文字與圖像參考，生成圖像及文字，提供 1K–4K 輸出與詳細創意控制。

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。

Nano Banana Pro 是 Google 以推理驅動圖像生成及編輯的 Gemini 3 Pro Image 模型。製造商將複雜平面設計、高保真產品樣稿及事實資料視覺化置於預定用途核心。它接收文字與圖像，產生圖像與文字。此具名 Pro 圖像版本以 Gemini 3 Pro 為基礎，同時保有自身圖像任務的輸入及能力設定。

模型支援 1K、2K、4K 圖像。文件中的形狀包括 1:1、2:3、3:2、3:4、4:3、4:5、5:4、9:16、16:9、21:9。正方形 4K 圖像為 4096 × 4096；16:9 4K 圖像為 5504 × 3072。無論需要直式海報、產品場景或寬幅解說圖，均應依成果選擇解析度及長寬比。Gemini 3.1 Flash Image 的 0.5K 選項及額外極端比例不在此 Pro 表內。

文字呈現支援海報、圖解及其他設計素材的清楚字樣。複雜資訊圖表應提供基礎事實、確切文字、閱讀順序，以及標籤與視覺元素關係。請將要傳達的資訊與所需藝術風格分開。Google 建議先準備文字，再生成包含文字的圖像。構圖結合標題、圖解及數段簡短說明時，這尤其實用。

多圖輸入支援最多 14 張參考。Google 功能表描述最多六張物件參考用於忠實呈現、最多五張角色參考用於一致性，以及最多三張風格參考。這些角色有助於準備合成視覺：產品照片定義外觀、另一張圖建立環境，風格圖像則影響處理方式。請告訴模型哪些細節具權威性、哪些參考提供靈感，而非要求它不加區分地結合每個可見特徵。

Google Search grounding 可為事實視覺化或反映當前狀況的場景提供現實資訊。Pro 圖像流程記載網頁 grounding；Image Search 擴充則專門記載於 Nano Banana 2.1 及 Gemini 3.1 Flash Image。資料圖像應提供預期呈現值，或在原始模型流程要求 grounding 資訊，再明確說明關係、標籤及版面。搜尋輔助生成的結果仍是需要檢查的圖像，不能取代核對描繪事實。

推理支援在最終渲染前組織複雜提示。圖像指南描述用於測試構圖與邏輯的中間圖像，與最終成果不同。請勿將 Nano Banana 2 的 minimal/high 控制表，或 Nano Banana 2.1 的 medium 預設表，套用至此 Pro 版本。高難度設計應提供完整需求，包含視覺層級、必要物件關係，以及後續編輯中必須保留的元素。

模型資訊卡描述了仍存在的重要限制：極小文字及長段落可能呈現不佳，角色外觀可能在參考與結果間改變，遮罩或塗鴉編輯可能僅部分遵循指令或留下痕跡。它也可能混淆左右，或將來源元素複製到新構圖。產品修訂應明確說明要保留的幾何形狀與標籤，並檢查編輯區域；圖解應比較箭頭方向及物件相對位置。

目前 API 表列出輸入上限 65,536 token、輸出上限 32,768 token。支援圖像生成、thinking、搜尋 grounding 及批次處理；不支援音訊生成、函式呼叫、程式碼執行、快取、結構化輸出、檔案搜尋、URL context 及 Live API。此設定的圖像任務不接受音訊或影片輸入。生成圖像包含 SynthID，且不一定精確遵循所需輸出圖像數量。

實用產品需求可結合產品圖像、光線參考及確切標題：「保留產品比例與字樣，將它呈現在柔和側光下的淺色石材表面，上方三分之一留白，以放置提供的標題。」事實圖解應指明每個實體及連結，並提供定稿標籤。可透過對話指出一項修改及要保留的特徵來完善結果，將選定圖像與解說文字一起保留為設計成果。

Ailoot 可用 · 輸入與方法

Ailoot Ultra · OpenAI Chat POST /v1/chat/completions
輸入
text
輸出
text
輸出格式
json 或 SSE
欄位類型要求值與限制預設值
欄位model類型string要求必填值與限制
google/gemini-3-pro-image
預設值—
欄位messages類型message[]要求必填值與限制
項目數下限: 1
預設值—
欄位messages[].role類型string要求必填值與限制
範例：system, user, assistant, tool, function
條件: 這些角色由 原始碼中的相容型別明確表示；確切角色集合仍依模型而定。
依模型而定
預設值—
欄位messages[].content類型string|content_part[]|null要求選填值與限制預設值—
欄位messages[].tool_calls類型tool_call[]要求選填值與限制預設值—
欄位messages[].tool_call_id類型string要求選填值與限制
適用條件: role=tool；使用實際回傳的 ID
預設值—
欄位messages[].name類型string要求選填值與限制預設值—
欄位messages[].reasoning_content類型string要求選填值與限制
適用條件: 此模型使用推理內容時，將實際回傳的推理內容帶回後續請求
預設值—
欄位messages[].reasoning_details類型object|array要求選填值與限制
依模型而定
預設值—
欄位max_tokens類型integer要求選填值與限制
最小值: 1
依模型而定
預設值—
欄位max_completion_tokens類型integer要求選填值與限制
最小值: 1
依模型而定
預設值—
欄位stream類型boolean要求選填值與限制預設值false
欄位stream_options.include_usage類型boolean要求選填值與限制
依模型而定
預設值—
欄位temperature類型number要求選填值與限制
依模型而定
預設值—
欄位top_p類型number要求選填值與限制
依模型而定
預設值—
欄位stop類型string|string[]要求選填值與限制
依模型而定
預設值—
欄位tools類型function_tool[]要求選填值與限制
依模型而定
預設值—
欄位tools[].type類型string要求選填值與限制
function
依模型而定
預設值—
欄位tools[].function.name類型string要求必填值與限制
適用條件: 已提供函式工具
預設值—
欄位tools[].function.description類型string要求選填值與限制預設值—
欄位tools[].function.parameters類型JSON_schema要求選填值與限制預設值—
欄位tool_choice類型string|object要求選填值與限制
依模型而定
預設值—
欄位parallel_tool_calls類型boolean要求選填值與限制
依模型而定
預設值—
欄位response_format類型object要求選填值與限制
依模型而定
預設值—
欄位reasoning_effort類型string要求選填值與限制
依模型而定
預設值—
欄位reasoning類型object要求選填值與限制
依模型而定
預設值—
欄位service_tier類型string要求選填值與限制
依模型而定
預設值—
欄位instructions類型string要求選填值與限制
相容性欄位
預設值—
欄位functions類型function[]要求選填值與限制
依模型而定
預設值—
欄位function_call類型string|object要求選填值與限制
依模型而定
預設值—
欄位prompt_cache_options類型object要求選填值與限制
依模型而定
預設值—
欄位modalities類型string[]要求選填值與限制
text
預設值—
欄位provider類型object要求選填值與限制
條件: 此 Ultra 文字路由拒絕 provider.options
預設值—
欄位cache_control.ttl類型string要求選填值與限制
條件: 實際提示詞快取位置拒絕 1h
預設值—
輸入素材組合

文字 · UTF8 文字

messages[].content

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model, messages
參數material_types規格text
參數messages規格具有 role/content 結構的訊息陣列
參數file_material規格實際 UTF-8 文件以原文文字插入；不推定檔案 ID
參數optional_controls規格stream, temperature, top_p, stop, max_tokens, max_completion_tokens, reasoning, response_format, tools, tool_choice
參數control_scope規格依模型而定；使用者函式工具與託管工具不同
參數output_modalities規格text
參數hosted_operations規格false
參數multimodal_input_binding規格null

生命週期： synchronous_or_streamed

將確切模型 ID 與 messages 一併送出。

上下文長度不是輸出上限。

文字檔案可提供原文文字；圖片／音訊／檔案物件輸入需要精確綁定。

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
標準費率 選取快速模式時
flex 模式
標準費率 選取 flex 模式時
最高推理強度
標準費率 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 $0.004 / 1K Token
輸出 · 輸出 Token $0.024 / 1K Token
輸入 · 讀取快取 $0.0004 / 1K Token
輸入 · 寫入快取 $0.00075 / 1K Token
輸入 · 寫入快取，1 小時 — / 1K Token
輸出 · 圖片輸出詞元 $0.24 / 1K 圖片 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 $0.004 / 1K Token
輸出 · 輸出 Token $0.024 / 1K Token
輸入 · 讀取快取 $0.0004 / 1K Token
輸入 · 寫入快取 $0.00075 / 1K Token
輸入 · 寫入快取，1 小時 — / 1K Token

參考費率詳情

模型層級的參考費率表不會變更方法選擇、報價或費用。實際計費採用所選 Ailoot 方法的費率。

Google: Nano Banana Pro (Gemini 3 Pro Image)

各設定的價格

設定計費條件費用
設定Google: Nano Banana Pro (Gemini 3 Pro Image) · 預設設定計費條件預設設定費用
輸入 · 輸入 Token US$0.004 / 1K Token
輸出 · 輸出 Token US$0.024 / 1K Token
輸入 · 輸入圖片 US$0.004 / 1K Token
輸出 · 輸出圖片 US$0.24 / 1K Token
輸入 · 輸入音訊 US$0.004 / 1K Token
輸入 · 讀取音訊快取 US$0.0004 / 1K Token
輸出 · 網頁搜尋 US$0.028 每次搜尋
輸出 · 推理詞元 US$0.024 / 1K Token
輸入 · 讀取快取 US$0.0004 / 1K Token
輸入 · 寫入快取 · 5 分鐘 US$0.00075 / 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 · OpenAI Chat

set -eu\n: "${AILOOT_API_KEY:?Set your Ailoot API key}"\npython3 - <<'PY_REQUEST'\nimport json,os\nfrom pathlib import Path\np=json.loads('{"model": "google/gemini-3-pro-image", "messages": [{"role": "user", "content": "Explain the difference between an observation and a hypothesis in three sentences."}]}')\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\npython3 - <<'PY_RESULT'\nimport json\nfrom pathlib import Path\nr=json.loads(Path("result.json").read_text())\nfor x in r.get("choices",[]):\n    if x.get("message",{}).get("content"): print(x["message"]["content"])\nPY_RESULT\n

接收並儲存結果

Ailoot Ultra · OpenAI Chat

json 或 SSE

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。

保留每個候選項及其內容／工具呼叫／推理。SSE 中依候選項／工具索引組合增量，保留最終完成原因與用量。

需要檢查原始回應時

保留請求／回應 ID 與標頭。未提供通用的文字工作擷取 URL。

回應欄位
欄位類型
欄位choices[].index類型integer
欄位choices[].message.content類型string|null
欄位choices[].message.tool_calls類型tool_call[]
欄位choices[].message.reasoning_content類型string
欄位choices[].message.reasoning_details類型object|array
欄位choices[].finish_reason類型string|null
欄位usage類型object
錯誤與後續步驟
回應條件下一步
回應400 · invalid_request_error條件必要欄位、素材表示方式或參數值無效下一步提出新的建立請求前，先修正指定欄位。

別名

模型別名

Ailoot gemini-3-pro-image, gemini-3-pro-image-preview, nano-banana-pro
Ailoot Ultra google/gemini-3-pro-image

方法路徑別名

/v1/images

相關呼叫用 ID

google/gemini-3-pro-image, gemini-3-pro-image-preview, nano-banana-pro, gemini-3-pro-image

", "method_identity": { "effective_request_model_id": "google/gemini-3-pro-image", "fmt": "chat", "http": "POST", "path": "/v1/chat/completions", "request_model_id": "google/gemini-3-pro-image", "route_label": "Ultra" }, "method_key": "Ultra|chat|/v1/chat/completions|google%2Fgemini-3-pro-image", "ordinal": 3, "rawMethod": { "available": null, "cache_read": 0.4, "cache_write": 0.75, "cache_write_1h": null, "contract": { "data": { "all_results": "Keep every choice and its content/tool calls/reasoning. In SSE assemble deltas by choice/tool index, retain the final finish reason and usage.", "authentication": { "api_key_source": "AILOOT_API_KEY", "header": "Authorization: Bearer" }, "errors": [ { "code": null, "condition": "必要欄位、素材表示方式或參數值無效", "http_status": 400, "recovery": "提出新的建立請求前，先修正指定欄位。", "type": "invalid_request_error" } ], "hints": [ "Model context is not an output cap.", "A model-dependent field needs the exact published model profile; unspecified defaults/enums are not guessed.", "Tool calls propose actions; the client application returns actual observations with the returned call ID.", "Guarded canonical keys must occur once; duplicate or case-varied model/tools/cap fields are rejected." ], "ignored_fields": [], "lifecycle": { "create": { "http": "POST", "path": "/v1/chat/completions" }, "job_read": null, "mode": "synchronous_or_streamed", "unknown": "保留請求／回應 ID 與標頭。未提供通用的文字工作擷取 URL。" }, "material_combinations": [ { "mode": "text", "representation": "messages[].content", "required_material": "UTF8 文字" } ], "operation_modes": [ "conversation", "function_tool_continuation", "streaming" ], "outputs": { "all_results": "保留每個候選項及其內容／工具呼叫／推理。SSE 中依候選項／工具索引組合增量，保留最終完成原因與用量。", "family": "text", "fields": [ { "description": null, "name": "choices[].index", "type": "integer" }, { "description": null, "name": "choices[].message.content", "type": "string|null" }, { "description": null, "name": "choices[].message.tool_calls", "type": "tool_call[]" }, { "description": null, "name": "choices[].message.reasoning_content", "type": "string" }, { "description": null, "name": "choices[].message.reasoning_details", "type": "object|array" }, { "description": null, "name": "choices[].finish_reason", "type": "string|null" }, { "description": null, "name": "usage", "type": "object" } ], "format": "json 或 SSE" }, "parameters": [ { "availability": "source_interface", "default": null, "default_known": false, "enum": [ "google/gemini-3-pro-image" ], "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": "messages", "required": true, "type": "message[]" }, { "availability": "model_dependent", "conditions": "這些角色由 原始碼中的相容型別明確表示；確切角色集合仍依模型而定。", "default": null, "default_known": false, "enum": [ "system", "user", "assistant", "tool", "function" ], "enum_exhaustive": false, "enum_known": true, "name": "messages[].role", "required": true, "type": "string" }, { "availability": "source_interface", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "messages[].content", "required": false, "type": "string|content_part[]|null" }, { "availability": "source_interface", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "messages[].tool_calls", "required": false, "type": "tool_call[]" }, { "availability": "source_interface", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "messages[].tool_call_id", "required": false, "type": "string", "when": "role=tool；使用實際回傳的 ID" }, { "availability": "source_interface", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "messages[].name", "required": false, "type": "string" }, { "availability": "source_interface", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "messages[].reasoning_content", "required": false, "type": "string", "when": "此模型使用推理內容時，將實際回傳的推理內容帶回後續請求" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "messages[].reasoning_details", "required": false, "type": "object|array" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "minimum": 1, "name": "max_tokens", "required": false, "type": "integer" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "minimum": 1, "name": "max_completion_tokens", "required": false, "type": "integer" }, { "availability": "source_interface", "default": false, "default_known": true, "enum": null, "enum_known": false, "name": "stream", "required": false, "type": "boolean" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "stream_options.include_usage", "required": false, "type": "boolean" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "temperature", "required": false, "type": "number" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "top_p", "required": false, "type": "number" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "stop", "required": false, "type": "string|string[]" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "tools", "required": false, "type": "function_tool[]" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": [ "function" ], "enum_known": true, "name": "tools[].type", "required": false, "type": "string" }, { "availability": "source_interface", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "tools[].function.name", "required": true, "type": "string", "when": "已提供函式工具" }, { "availability": "source_interface", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "tools[].function.description", "required": false, "type": "string" }, { "availability": "source_interface", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "tools[].function.parameters", "required": false, "type": "JSON_schema" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "tool_choice", "required": false, "type": "string|object" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "parallel_tool_calls", "required": false, "type": "boolean" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "response_format", "required": false, "type": "object" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "reasoning_effort", "required": false, "type": "string" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "reasoning", "required": false, "type": "object" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "service_tier", "required": false, "type": "string" }, { "availability": "source_compatibility", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "instructions", "required": false, "type": "string" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "functions", "required": false, "type": "function[]" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "function_call", "required": false, "type": "string|object" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "prompt_cache_options", "required": false, "type": "object" }, { "availability": "source_interface", "default": null, "default_known": false, "enum": [ "text" ], "enum_known": true, "name": "modalities", "required": false, "type": "string[]" }, { "availability": "source_interface", "conditions": "此 Ultra 文字路由拒絕 provider.options", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "provider", "required": false, "type": "object" }, { "availability": "source_interface", "conditions": "實際提示詞快取位置拒絕 1h", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "cache_control.ttl", "required": false, "type": "string" } ], "profile_binding": "Exact existing Ailoot model and method; interface constraints below do not assert provider qualification.", "unsupported": [ "additional models/models list", "plugins", "route", "hosted tools; ordinary client function tools remain separate", "non-text output modalities", "provider.options overrides", "one-hour prompt-cache TTL" ] }, "hints": [ "將確切模型 ID 與 messages 一併送出。", "上下文長度不是輸出上限。", "文字檔案可提供原文文字；圖片／音訊／檔案物件輸入需要精確綁定。" ], "input": { "content_type": "application/json", "control_scope": "依模型而定；使用者函式工具與託管工具不同", "file_material": "實際 UTF-8 文件以原文文字插入；不推定檔案 ID", "hosted_operations": false, "material_types": [ "text" ], "messages": "具有 role/content 結構的訊息陣列", "multimodal_input_binding": null, "optional_controls": [ "stream", "temperature", "top_p", "stop", "max_tokens", "max_completion_tokens", "reasoning", "response_format", "tools", "tool_choice" ], "output_modalities": [ "text" ], "required": [ "model", "messages" ] }, "lifecycle": { "mode": "synchronous_or_streamed", "unknown": "preserve original request id; no generic chat job retrieval path" }, "manufacturer_capability": null, "method": { "http": "POST", "path": "/v1/chat/completions" }, "method_aliases": [], "operation_modes": [ "text_chat" ], "output": { "content": "choices[].message.content or stream delta", "family": "text", "format": "json or supported SSE", "tool_calls": "retain actual returned function calls" } }, "ctx": null, "declared_pricing_profiles": [ { "dimensions": { "regime": "base" }, "label": "詞元基本費率", "units": [ { "amount": "0.004000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "input_price", "label": "Input tokens", "native_amount_usd_per_unit": "0.000004", "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": "0.024000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "output_price", "label": "Output tokens", "native_amount_usd_per_unit": "0.000024", "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": "0.0004000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "cache_read_price", "label": "Cache read", "native_amount_usd_per_unit": "0.0000004", "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": "0.00075000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "cache_write_price", "label": "Cache write", "native_amount_usd_per_unit": "0.00000075", "native_quantity": 1, "native_unit": "generic_cache_creation_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "generic_cache_creation_token" }, { "amount": null, "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "cache_write_1h_price", "label": "Cache write, 1 hour", "native_amount_usd_per_unit": null, "native_quantity": 1, "native_unit": "one_hour_cache_creation_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "one_hour_cache_creation_token" }, { "amount": "0.24000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "image_output_price", "label": "Image output tokens", "native_amount_usd_per_unit": "0.00024", "native_quantity": 1, "native_unit": "image_output_token", "public_unit_label": "/ 1K image tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "out", "unit": "image_output_token" } ] }, { "dimensions": { "max_context_tokens_inclusive": null, "min_context_tokens_exclusive": 0 }, "label": "請求長度級距 1", "units": [ { "amount": "0.004000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "input_price", "label": "Input tokens", "native_amount_usd_per_unit": "0.000004", "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": "0.024000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "output_price", "label": "Output tokens", "native_amount_usd_per_unit": "0.000024", "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": "0.0004000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "cache_read_price", "label": "Cache read", "native_amount_usd_per_unit": "0.0000004", "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": "0.00075000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "cache_write_price", "label": "Cache write", "native_amount_usd_per_unit": "0.00000075", "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" } ] } ], "declared_tariff_references": [ { "client_selectable": false, "key": "337a7b9c613ce8361e5a", "label": "Google: Nano Banana Pro (Gemini 3 Pro Image)", "profiles": [ { "basis": "", "dimensions": { "conditions": "預設設定" }, "label": "Google: Nano Banana Pro (Gemini 3 Pro Image) · 預設設定", "units": [ { "amount": "0.004000", "amount_unit": "usd_per_thousand_tokens", "billing_input": false, "key": "ecef187a88e448a7d3462365", "label": "Input tokens", "public_unit_label": "/ 1K tokens", "quantity": 1000, "rate_role": "declared_tariff_rate", "side": "in", "unit": "input_token" }, { "amount": "0.024000", "amount_unit": "usd_per_thousand_tokens", "billing_input": false, "key": "d2d88fe2ad422a7d383fa621", "label": "Output tokens", "public_unit_label": "/ 1K tokens", "quantity": 1000, "rate_role": "declared_tariff_rate", "side": "out", "unit": "output_token" }, { "amount": "0.004000", "amount_unit": "usd_per_thousand_tokens", "billing_input": false, "key": "6e3b452557375456f40688b4", "label": "Input image", "public_unit_label": "/ 1K tokens", "quantity": 1000, "rate_role": "declared_tariff_rate", "side": "in", "unit": "input_image_token" }, { "amount": "0.24000", "amount_unit": "usd_per_thousand_tokens", "billing_input": false, "key": "2c580e7a4cc14a9bd642fb4c", "label": "Output image", "public_unit_label": "/ 1K tokens", "quantity": 1000, "rate_role": "declared_tariff_rate", "side": "out", "unit": "output_image_token" }, { "amount": "0.004000", "amount_unit": "usd_per_thousand_tokens", "billing_input": false, "key": "efc34a7dfe8001f04c757788", "label": "Audio input", "public_unit_label": "/ 1K tokens", "quantity": 1000, "rate_role": "declared_tariff_rate", "side": "in", "unit": "input_audio_token" }, { "amount": "0.0004000", "amount_unit": "usd_per_thousand_tokens", "billing_input": false, "key": "64cd47a86fbdece16eee82b4", "label": "Audio cache read", "public_unit_label": "/ 1K tokens", "quantity": 1000, "rate_role": "declared_tariff_rate", "side": "in", "unit": "cached_audio_input_token" }, { "amount": "0.028", "amount_unit": "usd_per_exact_physical_unit", "billing_input": false, "key": "b5c0d83e66832bfef08e9755", "label": "Web search", "public_unit_label": "per search", "quantity": "1", "rate_role": "declared_tariff_rate", "side": "out", "unit": "web_search" }, { "amount": "0.024000", "amount_unit": "usd_per_thousand_tokens", "billing_input": false, "key": "cb4eaac7889580c43365e8b4", "label": "Reasoning tokens", "public_unit_label": "/ 1K tokens", "quantity": 1000, "rate_role": "declared_tariff_rate", "side": "out", "unit": "internal_reasoning_token" }, { "amount": "0.0004000", "amount_unit": "usd_per_thousand_tokens", "billing_input": false, "key": "d9abdd5ecc7712d6486db3f5", "label": "Cache read", "public_unit_label": "/ 1K tokens", "quantity": 1000, "rate_role": "declared_tariff_rate", "side": "in", "unit": "cached_input_token" }, { "amount": "0.000750000", "amount_unit": "usd_per_thousand_tokens", "billing_input": false, "key": "55ff0879ecf30ca79c061816", "label": "Cache write · 5 minutes", "public_unit_label": "/ 1K tokens", "quantity": 1000, "rate_role": "declared_tariff_rate", "side": "in", "unit": "cache_write_token" } ] } ] } ], "examples": [ { "code": "set -eu\n: \"${AILOOT_API_KEY:?Set your Ailoot API key}\"\npython3 - <<'PY_REQUEST'\nimport json,os\nfrom pathlib import Path\np=json.loads('{\"model\": \"google/gemini-3-pro-image\", \"messages\": [{\"role\": \"user\", \"content\": \"Explain the difference between an observation and a hypothesis in three sentences.\"}]}')\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\npython3 - <<'PY_RESULT'\nimport json\nfrom pathlib import Path\nr=json.loads(Path(\"result.json\").read_text())\nfor x in r.get(\"choices\",[]):\n if x.get(\"message\",{}).get(\"content\"): print(x[\"message\"][\"content\"])\nPY_RESULT\n", "label": "curl · retained exact creation", "language": "bash" }, { "code": "from openai import OpenAI\nimport os\n\nif not os.environ.get(\"AILOOT_API_KEY\", \"\").strip(): raise SystemExit(\"Set AILOOT_API_KEY before making a request\")\nclient=OpenAI(base_url=\"https://api.ailoot.ai/v1\",api_key=os.environ[\"AILOOT_API_KEY\"],max_retries=0)\nresult=client.chat.completions.create(model='google/gemini-3-pro-image',messages=[{\"role\":\"user\",\"content\":\"Explain observations and hypotheses in three sentences.\"}])\nimport base64, json\nfrom pathlib import Path\n\ndef save_result(data, stem=\"result\"):\n # Keep every field, including usage, IDs, reasoning and tool requests.\n Path(stem + \".json\").write_text(json.dumps(data, ensure_ascii=False, indent=2), encoding=\"utf-8\")\n print(json.dumps(data, ensure_ascii=False, indent=2))\n def save_blob(encoded, suffix, label):\n raw = base64.b64decode(encoded, altchars=b\"-_\", validate=True)\n ext = \"png\" if raw.startswith(b\"\\x89PNG\\r\\n\\x1a\\n\") else \"jpg\" if raw.startswith(b\"\\xff\\xd8\") else \"webp\" if raw[:4] == b\"RIFF\" and raw[8:12] == b\"WEBP\" else suffix\n file = Path(stem + \"-\" + label + \".\" + ext)\n file.write_bytes(raw)\n print(\"Saved\", file)\n for index, block in enumerate(data.get(\"content\") or []):\n print(\"Content\", index, json.dumps(block, ensure_ascii=False))\n for choice in data.get(\"choices\") or []:\n print(\"Choice\", choice.get(\"index\"), json.dumps(choice.get(\"message\", choice.get(\"delta\", {})), ensure_ascii=False))\n for index, item in enumerate(data.get(\"output\") or []):\n print(\"Output\", index, json.dumps(item, ensure_ascii=False))\n if item.get(\"type\") == \"image_generation_call\" and item.get(\"result\"):\n save_blob(item[\"result\"], item.get(\"output_format\") or \"bin\", \"output-\" + str(index))\n for ci, candidate in enumerate(data.get(\"candidates\") or []):\n for pi, part in enumerate((candidate.get(\"content\") or {}).get(\"parts\") or []):\n print(\"Candidate/part\", ci, pi, json.dumps(part, ensure_ascii=False))\n blob = part.get(\"inlineData\") or part.get(\"inline_data\")\n if blob and blob.get(\"data\"):\n mime = blob.get(\"mimeType\") or blob.get(\"mime_type\")\n suffix = {\"image/png\":\"png\", \"image/jpeg\":\"jpg\", \"image/webp\":\"webp\", \"audio/wav\":\"wav\", \"audio/mpeg\":\"mp3\", \"video/mp4\":\"mp4\"}.get(mime, \"bin\")\n save_blob(blob[\"data\"], suffix, \"candidate-\" + str(ci) + \"-part-\" + str(pi))\n\nsave_result(result.to_dict(mode=\"json\"))\n", "label": "Python SDK · all choices", "language": "python" }, { "code": "from openai import OpenAI\nimport os\nfrom pathlib import Path\n\nif not os.environ.get(\"AILOOT_API_KEY\", \"\").strip(): raise SystemExit(\"Set AILOOT_API_KEY before making a request\")\nclient=OpenAI(base_url=\"https://api.ailoot.ai/v1\",api_key=os.environ[\"AILOOT_API_KEY\"],max_retries=0)\nimport base64, json\nfrom pathlib import Path\n\ndef save_result(data, stem=\"result\"):\n # Keep every field, including usage, IDs, reasoning and tool requests.\n Path(stem + \".json\").write_text(json.dumps(data, ensure_ascii=False, indent=2), encoding=\"utf-8\")\n print(json.dumps(data, ensure_ascii=False, indent=2))\n def save_blob(encoded, suffix, label):\n raw = base64.b64decode(encoded, altchars=b\"-_\", validate=True)\n ext = \"png\" if raw.startswith(b\"\\x89PNG\\r\\n\\x1a\\n\") else \"jpg\" if raw.startswith(b\"\\xff\\xd8\") else \"webp\" if raw[:4] == b\"RIFF\" and raw[8:12] == b\"WEBP\" else suffix\n file = Path(stem + \"-\" + label + \".\" + ext)\n file.write_bytes(raw)\n print(\"Saved\", file)\n for index, block in enumerate(data.get(\"content\") or []):\n print(\"Content\", index, json.dumps(block, ensure_ascii=False))\n for choice in data.get(\"choices\") or []:\n print(\"Choice\", choice.get(\"index\"), json.dumps(choice.get(\"message\", choice.get(\"delta\", {})), ensure_ascii=False))\n for index, item in enumerate(data.get(\"output\") or []):\n print(\"Output\", index, json.dumps(item, ensure_ascii=False))\n if item.get(\"type\") == \"image_generation_call\" and item.get(\"result\"):\n save_blob(item[\"result\"], item.get(\"output_format\") or \"bin\", \"output-\" + str(index))\n for ci, candidate in enumerate(data.get(\"candidates\") or []):\n for pi, part in enumerate((candidate.get(\"content\") or {}).get(\"parts\") or []):\n print(\"Candidate/part\", ci, pi, json.dumps(part, ensure_ascii=False))\n blob = part.get(\"inlineData\") or part.get(\"inline_data\")\n if blob and blob.get(\"data\"):\n mime = blob.get(\"mimeType\") or blob.get(\"mime_type\")\n suffix = {\"image/png\":\"png\", \"image/jpeg\":\"jpg\", \"image/webp\":\"webp\", \"audio/wav\":\"wav\", \"audio/mpeg\":\"mp3\", \"video/mp4\":\"mp4\"}.get(mime, \"bin\")\n save_blob(blob[\"data\"], suffix, \"candidate-\" + str(ci) + \"-part-\" + str(pi))\n\nwith client.chat.completions.stream(model='google/gemini-3-pro-image',messages=[{\"role\":\"user\",\"content\":\"Explain observations and hypotheses in three sentences.\"}]) as stream:\n with Path(\"stream-events.jsonl\").open(\"w\",encoding=\"utf-8\") as log:\n for event in stream:\n payload=event.to_dict(mode=\"json\")\n log.write(json.dumps(payload,ensure_ascii=False)+\"\\n\"); log.flush()\n print(json.dumps(payload,ensure_ascii=False))\n final=stream.get_final_completion()\n save_result(final.to_dict(mode=\"json\"),\"stream-result\")\n", "label": "Python SDK streaming · all events", "language": "python" } ], "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", "in": 4, "input": [ "text" ], "label": "OpenAI Chat", "max_out": null, "max_reasoning_effort_multiplier": 1, "method_aliases": [], "out": 24, "output": [ "text" ], "path": "/v1/chat/completions", "price_conditions": [ { "label": "快速模式", "value": "標準費率", "when": "選取快速模式時" }, { "label": "flex 模式", "value": "標準費率", "when": "選取 flex 模式時" }, { "label": "最高推理強度", "value": "標準費率", "when": "最高推理強度採用 default 調整值時" }, { "label": "顯式快取計價", "value": "未啟用", "when": "請求顯式快取時" } ], "pricing": { "billing_mode": "token", "image_input_price": null, "image_output_price": 0.00024, "per_request_price": null }, "pricing_profiles": [ { "dimensions": { "regime": "base" }, "label": "Base token rates", "units": [ { "amount": "0.004000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "input_price", "label": "Input tokens", "native_amount_usd_per_unit": "0.000004", "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": "0.024000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "output_price", "label": "Output tokens", "native_amount_usd_per_unit": "0.000024", "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": "0.0004000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "cache_read_price", "label": "Cache read", "native_amount_usd_per_unit": "0.0000004", "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": "0.00075000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "cache_write_price", "label": "Cache write", "native_amount_usd_per_unit": "0.00000075", "native_quantity": 1, "native_unit": "generic_cache_creation_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "generic_cache_creation_token" }, { "amount": null, "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "cache_write_1h_price", "label": "Cache write, 1 hour", "native_amount_usd_per_unit": null, "native_quantity": 1, "native_unit": "one_hour_cache_creation_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "one_hour_cache_creation_token" }, { "amount": "0.24000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "image_output_price", "label": "Image output tokens", "native_amount_usd_per_unit": "0.00024", "native_quantity": 1, "native_unit": "image_output_token", "public_unit_label": "/ 1K image tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "out", "unit": "image_output_token" } ] }, { "dimensions": { "max_context_tokens_inclusive": null, "min_context_tokens_exclusive": 0 }, "label": "Request-length tier 1", "units": [ { "amount": "0.004000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "input_price", "label": "Input tokens", "native_amount_usd_per_unit": "0.000004", "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": "0.024000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "output_price", "label": "Output tokens", "native_amount_usd_per_unit": "0.000024", "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": "0.0004000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "cache_read_price", "label": "Cache read", "native_amount_usd_per_unit": "0.0000004", "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": "0.00075000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "cache_write_price", "label": "Cache write", "native_amount_usd_per_unit": "0.00000075", "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": "google/gemini-3-pro-image", "route_label": "Ultra", "status_reads": [], "tiers": [ { "cache_read": 0.4, "cache_read_multiplier": null, "cache_write": 0.75, "cache_write_1h": null, "cache_write_multiplier": null, "created_at": "0001-01-01T00:00:00Z", "in": 4, "input_multiplier": null, "interval_boundary": "min_exclusive_max_inclusive", "max": null, "max_tokens": null, "min": 0, "min_tokens": 0, "null_rate_policy": "unknown or inherited; never zero", "out": 24, "output_multiplier": null, "per_request_price": null, "sort_order": 0, "tier_label": "", "updated_at": "0001-01-01T00:00:00Z" } ], "units": [ { "amount": "0.004000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "input_price", "label": "Input tokens", "native_amount_usd_per_unit": "0.000004", "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": "0.024000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "output_price", "label": "Output tokens", "native_amount_usd_per_unit": "0.000024", "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": "0.0004000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "cache_read_price", "label": "Cache read", "native_amount_usd_per_unit": "0.0000004", "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": "0.00075000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "cache_write_price", "label": "Cache write", "native_amount_usd_per_unit": "0.00000075", "native_quantity": 1, "native_unit": "generic_cache_creation_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "generic_cache_creation_token" }, { "amount": null, "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "cache_write_1h_price", "label": "Cache write, 1 hour", "native_amount_usd_per_unit": null, "native_quantity": 1, "native_unit": "one_hour_cache_creation_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "one_hour_cache_creation_token" }, { "amount": "0.24000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "image_output_price", "label": "Image output tokens", "native_amount_usd_per_unit": "0.00024", "native_quantity": 1, "native_unit": "image_output_token", "public_unit_label": "/ 1K image tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "out", "unit": "image_output_token" } ] } }, { "html": "
G

Google: Nano Banana Pro (Gemini 3 Pro Image)

Google /google/gemini-3-pro-image

入門

Nano Banana Pro（Gemini 3 Pro Image）是 Google 以推理驅動的圖像模型，適用複雜設計、產品樣稿及事實視覺化。它接收文字與圖像參考，生成圖像及文字，提供 1K–4K 輸出與詳細創意控制。

接受的輸入
文字 · 圖片
結果
圖片
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。

Nano Banana Pro 是 Google 以推理驅動圖像生成及編輯的 Gemini 3 Pro Image 模型。製造商將複雜平面設計、高保真產品樣稿及事實資料視覺化置於預定用途核心。它接收文字與圖像，產生圖像與文字。此具名 Pro 圖像版本以 Gemini 3 Pro 為基礎，同時保有自身圖像任務的輸入及能力設定。

模型支援 1K、2K、4K 圖像。文件中的形狀包括 1:1、2:3、3:2、3:4、4:3、4:5、5:4、9:16、16:9、21:9。正方形 4K 圖像為 4096 × 4096；16:9 4K 圖像為 5504 × 3072。無論需要直式海報、產品場景或寬幅解說圖，均應依成果選擇解析度及長寬比。Gemini 3.1 Flash Image 的 0.5K 選項及額外極端比例不在此 Pro 表內。

文字呈現支援海報、圖解及其他設計素材的清楚字樣。複雜資訊圖表應提供基礎事實、確切文字、閱讀順序，以及標籤與視覺元素關係。請將要傳達的資訊與所需藝術風格分開。Google 建議先準備文字，再生成包含文字的圖像。構圖結合標題、圖解及數段簡短說明時，這尤其實用。

多圖輸入支援最多 14 張參考。Google 功能表描述最多六張物件參考用於忠實呈現、最多五張角色參考用於一致性，以及最多三張風格參考。這些角色有助於準備合成視覺：產品照片定義外觀、另一張圖建立環境，風格圖像則影響處理方式。請告訴模型哪些細節具權威性、哪些參考提供靈感，而非要求它不加區分地結合每個可見特徵。

Google Search grounding 可為事實視覺化或反映當前狀況的場景提供現實資訊。Pro 圖像流程記載網頁 grounding；Image Search 擴充則專門記載於 Nano Banana 2.1 及 Gemini 3.1 Flash Image。資料圖像應提供預期呈現值，或在原始模型流程要求 grounding 資訊，再明確說明關係、標籤及版面。搜尋輔助生成的結果仍是需要檢查的圖像，不能取代核對描繪事實。

推理支援在最終渲染前組織複雜提示。圖像指南描述用於測試構圖與邏輯的中間圖像，與最終成果不同。請勿將 Nano Banana 2 的 minimal/high 控制表，或 Nano Banana 2.1 的 medium 預設表，套用至此 Pro 版本。高難度設計應提供完整需求，包含視覺層級、必要物件關係，以及後續編輯中必須保留的元素。

模型資訊卡描述了仍存在的重要限制：極小文字及長段落可能呈現不佳，角色外觀可能在參考與結果間改變，遮罩或塗鴉編輯可能僅部分遵循指令或留下痕跡。它也可能混淆左右，或將來源元素複製到新構圖。產品修訂應明確說明要保留的幾何形狀與標籤，並檢查編輯區域；圖解應比較箭頭方向及物件相對位置。

目前 API 表列出輸入上限 65,536 token、輸出上限 32,768 token。支援圖像生成、thinking、搜尋 grounding 及批次處理；不支援音訊生成、函式呼叫、程式碼執行、快取、結構化輸出、檔案搜尋、URL context 及 Live API。此設定的圖像任務不接受音訊或影片輸入。生成圖像包含 SynthID，且不一定精確遵循所需輸出圖像數量。

實用產品需求可結合產品圖像、光線參考及確切標題：「保留產品比例與字樣，將它呈現在柔和側光下的淺色石材表面，上方三分之一留白，以放置提供的標題。」事實圖解應指明每個實體及連結，並提供定稿標籤。可透過對話指出一項修改及要保留的特徵來完善結果，將選定圖像與解說文字一起保留為設計成果。

Ailoot 可用 · 輸入與方法

Ailoot Ultra · 圖片 POST /v1/images/generations
輸入
text, image
輸出
image
欄位類型要求值與限制預設值
欄位model類型string要求必填值與限制
google/gemini-3-pro-image
預設值—
欄位prompt類型string要求必填值與限制
長度下限: 1
預設值—
欄位resolution類型string要求選填值與限制
1K, 2K, 4K
預設值—
欄位aspect_ratio類型string要求選填值與限制
1:1, 2:3, 3:2, 3:4, 4:3, 4:5, 5:4, 9:16, 16:9, 21:9
預設值—
欄位n類型integer要求選填值與限制
最小值: 1
最大值: 1
預設值—
欄位input_references類型array要求選填值與限制
項目數下限: 0
項目數上限: 14
預設值—
欄位provider類型object要求選填值與限制預設值—
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model, prompt
參數material_types規格text, image

生命週期： synchronous_result_then_owned_library

GET /v1/media/tasks/{task_id} · 實際回傳的 task_id 或媒體庫紀錄

GET /v1/media/assets/{asset_id}/content

GET /v1/media/assets

GET /v1/media/assets/{asset_id}

方案

最終費用的計算方式

顯示的費率用於在生成前估算費用。最終費用依原始生成作業記錄的成本計算。實測的輸出時間長度與預估數量並非最終計費數量。

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

供比較的預估費率

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。

設定費率表預估數量費用
設定基礎 token 費率費率表基本費率預估數量—費用
輸入 · 輸入 Token · 僅供比較的估算 — / 1K Token
輸出 · 輸出 Token · 僅供比較的估算 — / 1K Token
輸入 · 讀取快取 · 僅供比較的估算 — / 1K Token
輸入 · 寫入快取 · 僅供比較的估算 — / 1K Token
輸入 · 寫入快取，1 小時 · 僅供比較的估算 — / 1K Token
設定預估生成費用費率表—預估數量單次生成估算值費用
輸出 · 預估生成費用 · 僅供比較的估算 $0.98304 生成前估算

此估算並非額外費用，也不是本次生成完成後的固定費率。

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 · 圖片

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={'model': 'google/gemini-3-pro-image', 'prompt': 'a red panda astronaut floating in space, studio lighting'}\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/images/generations \\\n  -H "Authorization: Bearer $AILOOT_API_KEY" -H 'Content-Type: application/json' \\\n  --data-binary @request.json -D response-headers.txt -o result.json\npython3 - <<'PY_RESULT'\nimport base64, json, os, subprocess\nfrom pathlib import Path\nfrom urllib.parse import urlsplit, urljoin\n\ndef save_images(items):\n    if not items: raise SystemExit("No completed images; retain the full response")\n    for index, item in enumerate(items):\n        encoded=item.get("b64_json")\n        uri=item.get("url", "")\n        if not encoded and uri.startswith("data:image/"):\n            header, separator, encoded=uri.partition(",")\n            if not separator or ";base64" not in header: raise SystemExit("Unsupported image data URI")\n        if encoded:\n            raw=base64.b64decode(encoded,validate=True)\n        elif uri:\n            uri=urljoin("https://api.ailoot.ai",uri)\n            parsed=urlsplit(uri)\n            if parsed.scheme!="https" or not parsed.netloc or parsed.username or parsed.password:\n                raise SystemExit("Invalid returned image URL")\n            owned=parsed.netloc=="api.ailoot.ai" and parsed.path.startswith("/v1/media/assets/") and parsed.path.endswith("/content")\n            args=["curl","--fail-with-body","--silent","--show-error",uri]\n            if owned: args += ["-H","Authorization: Bearer "+os.environ["AILOOT_API_KEY"]]\n            temporary=Path(f"image-{index}.bin")\n            subprocess.run(args+["-o",str(temporary)],check=True)\n            raw=temporary.read_bytes()\n            temporary.unlink()\n        else: raise SystemExit("Image has neither bytes nor URL")\n        if not raw: raise SystemExit("Empty image result")\n        ext="png" if raw.startswith(b"\\x89PNG") else "jpg" if raw.startswith(b"\\xff\\xd8") else "webp" if raw[:4]==b"RIFF" and raw[8:12]==b"WEBP" else "svg" if raw.lstrip().startswith((b"<svg",b"<?xml")) else "bin"\n        Path(f"image-{index}.{ext}").write_bytes(raw)\n    print("Every returned image saved; complete response metadata retained")\nsave_images(json.loads(Path("result.json").read_text())["data"])\nPY_RESULT\n

接收並儲存結果

Ailoot Ultra · 圖片

下載每張傳回的圖片，或儲存其 Base64 內容

  • GET /v1/media/tasks/{task_id}
  • GET /v1/media/assets/{asset_id}/content
  • GET /v1/media/assets
  • GET /v1/media/assets/{asset_id}
其他內容讀取方式
set -eu\n: "${AILOOT_API_KEY:?Set your Ailoot API key}"\ncurl --fail-with-body --silent --show-error https://api.ailoot.ai/v1/media/assets \\\n  -H "Authorization: Bearer $AILOOT_API_KEY" -o owned-assets.json\n# Preserve every returned asset and follow its exact signed content URL. Do not construct a signed token.\n
保留所有已完成的結果

請儲存每張已完成的圖片；從每個傳回的 URL 取得圖片，或解碼其 Base64 內容。

保留完整回應與標頭、所有實際輸出、原始回傳的識別碼，以及所有用量欄位。恢復原始作業時，請勿再次提交建立請求。

需要檢查原始回應時

保留回傳的 X-Client-Request-ID，以供核對。僅讀取實際回傳的 task_id/asset_id 值或自己擁有的媒體庫；請勿以作業 ID 組成任務 URL，也請勿重新提交建立請求。

回應欄位
欄位類型
欄位created類型
欄位data[].url類型
欄位data[].b64_json類型
欄位usage類型

別名

模型別名

Ailoot gemini-3-pro-image, gemini-3-pro-image-preview, nano-banana-pro
Ailoot Ultra google/gemini-3-pro-image

方法路徑別名

/v1/images

相關呼叫用 ID

google/gemini-3-pro-image, gemini-3-pro-image-preview, nano-banana-pro, gemini-3-pro-image

", "method_identity": { "effective_request_model_id": "google/gemini-3-pro-image", "fmt": "images", "http": "POST", "path": "/v1/images/generations", "request_model_id": "google/gemini-3-pro-image", "route_label": "Ultra" }, "method_key": "Ultra|images|/v1/images/generations|google%2Fgemini-3-pro-image", "ordinal": 4, "rawMethod": { "available": null, "billing_basis": { "basis": "original_invoice_usd", "description": "顯示的費率用於在生成前估算費用。最終費用依原始生成作業記錄的成本計算。實測的輸出時間長度與預估數量並非最終計費數量。", "forecast_quantity_is_estimate": true, "physical_output_is_billable_quantity": false, "version": "original_invoice_usd_v1" }, "cache_read": null, "cache_write": null, "cache_write_1h": null, "contract": { "data": { "all_results": "Retain the complete response and headers, every actual output, original returned identifiers and all usage fields. Recover the original operation without submitting creation again.", "lifecycle": { "assets": [ { "http": "GET", "path": "/v1/media/assets" }, { "http": "GET", "path": "/v1/media/assets/{asset_id}" } ], "content": [ { "http": "GET", "path": "/v1/media/assets/{asset_id}/content", "url_source": "exact returned signed URL; never construct token" } ], "mode": "synchronous_result_then_owned_library", "operation_id_is_not_task_id": true, "status": [ { "http": "GET", "id_source": "actual returned task_id or media library record", "path": "/v1/media/tasks/{task_id}" } ], "unknown": "保留回傳的 X-Client-Request-ID，以供核對。僅讀取實際回傳的 task_id/asset_id 值或自己擁有的媒體庫；請勿以作業 ID 組成任務 URL，也請勿重新提交建立請求。" }, "outputs": { "all_results": "保留完整回應與標頭、所有實際輸出、原始回傳的識別碼，以及所有用量欄位。恢復原始作業時，請勿再次提交建立請求。", "family": "image", "fields": [ { "description": null, "name": "created", "type": null }, { "description": null, "name": "data[].url", "type": null }, { "description": null, "name": "data[].b64_json", "type": null }, { "description": null, "name": "usage", "type": null } ] }, "parameters": [ { "enum": [ "google/gemini-3-pro-image" ], "enum_known": true, "name": "model", "required": true, "type": "string" }, { "min_length": 1, "name": "prompt", "required": true, "type": "string" }, { "enum": [ "1K", "2K", "4K" ], "enum_known": true, "name": "resolution", "required": false, "type": "string" }, { "enum": [ "1:1", "2:3", "3:2", "3:4", "4:3", "4:5", "5:4", "9:16", "16:9", "21:9" ], "enum_known": true, "name": "aspect_ratio", "required": false, "type": "string" }, { "maximum": 1, "minimum": 1, "name": "n", "required": false, "type": "integer" }, { "items": { "properties": { "image_url": { "properties": { "url": { "type": "string" } }, "required": [ "url" ], "type": "object" }, "type": { "const": "image_url" } }, "required": [ "type", "image_url" ], "type": "object" }, "maximum_items": 14, "minimum_items": 0, "name": "input_references", "required": false, "type": "array" }, { "name": "provider", "required": false, "type": "object" } ], "request_schema": { "properties": { "aspect_ratio": { "enum": [ "1:1", "2:3", "3:2", "3:4", "4:3", "4:5", "5:4", "9:16", "16:9", "21:9" ], "type": "string" }, "input_references": { "items": { "properties": { "image_url": { "properties": { "url": { "type": "string" } }, "required": [ "url" ], "type": "object" }, "type": { "const": "image_url" } }, "required": [ "type", "image_url" ], "type": "object" }, "maxItems": 14, "minItems": 0, "type": "array" }, "model": { "enum": [ "google/gemini-3-pro-image" ], "type": "string" }, "n": { "maximum": 1, "minimum": 1, "type": "integer" }, "prompt": { "minLength": 1, "type": "string" }, "provider": { "description": "Exact image provider preferences from the documented image request schema.", "type": "object" }, "resolution": { "enum": [ "1K", "2K", "4K" ], "type": "string" } }, "required": [ "model", "prompt" ], "type": "object" }, "schema_template": { "actual_file_preparation_required": false, "body": { "model": "google/gemini-3-pro-image", "prompt": "a red panda astronaut floating in space, studio lighting" }, "content_type": "application/json" } }, "input": { "content_type": "application/json", "material_types": [ "text", "image" ], "required": [ "model", "prompt" ] }, "lifecycle": { "assets": [ { "http": "GET", "path": "/v1/media/assets" }, { "http": "GET", "path": "/v1/media/assets/{asset_id}" } ], "content": [ { "http": "GET", "path": "/v1/media/assets/{asset_id}/content", "url_source": "exact returned signed URL; never construct token" } ], "mode": "synchronous_result_then_owned_library", "operation_id_is_not_task_id": true, "status": [ { "http": "GET", "id_source": "實際回傳的 task_id 或媒體庫紀錄", "path": "/v1/media/tasks/{task_id}" } ], "unknown": "Keep the returned X-Client-Request-ID for reconciliation. Read only actual returned task_id/asset_id values or the owned media library; never build a task URL from the operation ID and never resubmit creation." }, "method": { "http": "POST", "path": "/v1/images/generations" }, "output": { "all_results": "Retain the complete response and headers, every actual output, original returned identifiers and all usage fields. Recover the original operation without submitting creation again.", "family": "image", "fields": [ { "description": null, "name": "created", "type": null }, { "description": null, "name": "data[].url", "type": null }, { "description": null, "name": "data[].b64_json", "type": null }, { "description": null, "name": "usage", "type": null } ] } }, "ctx": null, "declared_pricing_profiles": [ { "dimensions": { "regime": "base" }, "label": "Base token rates", "units": [ { "amount": null, "amount_unit": "usd_per_thousand_tokens", "billing_input": false, "estimate_only": true, "key": "input_price", "label": "Input tokens", "native_amount_usd_per_unit": null, "native_quantity": 1, "native_unit": "input_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": true, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "input_token" }, { "amount": null, "amount_unit": "usd_per_thousand_tokens", "billing_input": false, "estimate_only": true, "key": "output_price", "label": "Output tokens", "native_amount_usd_per_unit": null, "native_quantity": 1, "native_unit": "output_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": true, "rate_role": "typed_native_retail_rate", "side": "out", "unit": "output_token" }, { "amount": null, "amount_unit": "usd_per_thousand_tokens", "billing_input": false, "estimate_only": true, "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": true, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "cached_input_token" }, { "amount": null, "amount_unit": "usd_per_thousand_tokens", "billing_input": false, "estimate_only": true, "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": true, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "generic_cache_creation_token" }, { "amount": null, "amount_unit": "usd_per_thousand_tokens", "billing_input": false, "estimate_only": true, "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": true, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "one_hour_cache_creation_token" } ] }, { "basis": "此估算並非額外費用，也不是本次生成完成後的固定費率。", "dimensions": { "forecast_quantity": "one generation estimate" }, "label": "預估生成費用", "units": [ { "amount": "0.98304", "amount_unit": "usd_per_exact_native_unit", "billing_input": false, "estimate_only": true, "key": "forecast_usd", "label": "Estimated generation cost", "native_amount_usd_per_unit": "0.98304", "native_quantity": 1, "public_unit_label": "estimate before generation", "quantity": 1, "quantity_is_estimate": true, "rate_role": "typed_native_retail_rate", "side": "out", "unit": "request_estimate" } ] } ], "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={'model': 'google/gemini-3-pro-image', 'prompt': 'a red panda astronaut floating in space, studio lighting'}\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/images/generations \\\n -H \"Authorization: Bearer $AILOOT_API_KEY\" -H 'Content-Type: application/json' \\\n --data-binary @request.json -D response-headers.txt -o result.json\npython3 - <<'PY_RESULT'\nimport base64, json, os, subprocess\nfrom pathlib import Path\nfrom urllib.parse import urlsplit, urljoin\n\ndef save_images(items):\n if not items: raise SystemExit(\"No completed images; retain the full response\")\n for index, item in enumerate(items):\n encoded=item.get(\"b64_json\")\n uri=item.get(\"url\", \"\")\n if not encoded and uri.startswith(\"data:image/\"):\n header, separator, encoded=uri.partition(\",\")\n if not separator or \";base64\" not in header: raise SystemExit(\"Unsupported image data URI\")\n if encoded:\n raw=base64.b64decode(encoded,validate=True)\n elif uri:\n uri=urljoin(\"https://api.ailoot.ai\",uri)\n parsed=urlsplit(uri)\n if parsed.scheme!=\"https\" or not parsed.netloc or parsed.username or parsed.password:\n raise SystemExit(\"Invalid returned image URL\")\n owned=parsed.netloc==\"api.ailoot.ai\" and parsed.path.startswith(\"/v1/media/assets/\") and parsed.path.endswith(\"/content\")\n args=[\"curl\",\"--fail-with-body\",\"--silent\",\"--show-error\",uri]\n if owned: args += [\"-H\",\"Authorization: Bearer \"+os.environ[\"AILOOT_API_KEY\"]]\n temporary=Path(f\"image-{index}.bin\")\n subprocess.run(args+[\"-o\",str(temporary)],check=True)\n raw=temporary.read_bytes()\n temporary.unlink()\n else: raise SystemExit(\"Image has neither bytes nor URL\")\n if not raw: raise SystemExit(\"Empty image result\")\n ext=\"png\" if raw.startswith(b\"\\x89PNG\") else \"jpg\" if raw.startswith(b\"\\xff\\xd8\") else \"webp\" if raw[:4]==b\"RIFF\" and raw[8:12]==b\"WEBP\" else \"svg\" if raw.lstrip().startswith((b\"G

Google: Nano Banana Pro (Gemini 3 Pro Image)

Google /google/gemini-3-pro-image

入門

Nano Banana Pro（Gemini 3 Pro Image）是 Google 以推理驅動的圖像模型，適用複雜設計、產品樣稿及事實視覺化。它接收文字與圖像參考，生成圖像及文字，提供 1K–4K 輸出與詳細創意控制。

接受的輸入
文字
結果
json · sse
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。

Nano Banana Pro 是 Google 以推理驅動圖像生成及編輯的 Gemini 3 Pro Image 模型。製造商將複雜平面設計、高保真產品樣稿及事實資料視覺化置於預定用途核心。它接收文字與圖像，產生圖像與文字。此具名 Pro 圖像版本以 Gemini 3 Pro 為基礎，同時保有自身圖像任務的輸入及能力設定。

模型支援 1K、2K、4K 圖像。文件中的形狀包括 1:1、2:3、3:2、3:4、4:3、4:5、5:4、9:16、16:9、21:9。正方形 4K 圖像為 4096 × 4096；16:9 4K 圖像為 5504 × 3072。無論需要直式海報、產品場景或寬幅解說圖，均應依成果選擇解析度及長寬比。Gemini 3.1 Flash Image 的 0.5K 選項及額外極端比例不在此 Pro 表內。

文字呈現支援海報、圖解及其他設計素材的清楚字樣。複雜資訊圖表應提供基礎事實、確切文字、閱讀順序，以及標籤與視覺元素關係。請將要傳達的資訊與所需藝術風格分開。Google 建議先準備文字，再生成包含文字的圖像。構圖結合標題、圖解及數段簡短說明時，這尤其實用。

多圖輸入支援最多 14 張參考。Google 功能表描述最多六張物件參考用於忠實呈現、最多五張角色參考用於一致性，以及最多三張風格參考。這些角色有助於準備合成視覺：產品照片定義外觀、另一張圖建立環境，風格圖像則影響處理方式。請告訴模型哪些細節具權威性、哪些參考提供靈感，而非要求它不加區分地結合每個可見特徵。

Google Search grounding 可為事實視覺化或反映當前狀況的場景提供現實資訊。Pro 圖像流程記載網頁 grounding；Image Search 擴充則專門記載於 Nano Banana 2.1 及 Gemini 3.1 Flash Image。資料圖像應提供預期呈現值，或在原始模型流程要求 grounding 資訊，再明確說明關係、標籤及版面。搜尋輔助生成的結果仍是需要檢查的圖像，不能取代核對描繪事實。

推理支援在最終渲染前組織複雜提示。圖像指南描述用於測試構圖與邏輯的中間圖像，與最終成果不同。請勿將 Nano Banana 2 的 minimal/high 控制表，或 Nano Banana 2.1 的 medium 預設表，套用至此 Pro 版本。高難度設計應提供完整需求，包含視覺層級、必要物件關係，以及後續編輯中必須保留的元素。

模型資訊卡描述了仍存在的重要限制：極小文字及長段落可能呈現不佳，角色外觀可能在參考與結果間改變，遮罩或塗鴉編輯可能僅部分遵循指令或留下痕跡。它也可能混淆左右，或將來源元素複製到新構圖。產品修訂應明確說明要保留的幾何形狀與標籤，並檢查編輯區域；圖解應比較箭頭方向及物件相對位置。

目前 API 表列出輸入上限 65,536 token、輸出上限 32,768 token。支援圖像生成、thinking、搜尋 grounding 及批次處理；不支援音訊生成、函式呼叫、程式碼執行、快取、結構化輸出、檔案搜尋、URL context 及 Live API。此設定的圖像任務不接受音訊或影片輸入。生成圖像包含 SynthID，且不一定精確遵循所需輸出圖像數量。

實用產品需求可結合產品圖像、光線參考及確切標題：「保留產品比例與字樣，將它呈現在柔和側光下的淺色石材表面，上方三分之一留白，以放置提供的標題。」事實圖解應指明每個實體及連結，並提供定稿標籤。可透過對話指出一項修改及要保留的特徵來完善結果，將選定圖像與解說文字一起保留為設計成果。

Ailoot 可用 · 輸入與方法

Ailoot Ultra · Anthropic Messages POST /v1/messages
輸入
text
輸出
json, sse
輸出格式
JSON 或 SSE
欄位類型要求值與限制預設值
欄位model類型string要求必填值與限制
google/gemini-3-pro-image
預設值—
欄位messages類型message[]要求必填值與限制預設值—
欄位messages[].role類型string要求必填值與限制
user, assistant
預設值—
欄位messages[].content類型string要求必填值與限制預設值—
欄位max_tokens類型integer要求必填值與限制預設值—
欄位stream類型boolean要求選填值與限制預設值false
輸入素材組合

文字 · UTF-8 文字

messages[].content 字串

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model, messages, max_tokens
參數optional_controls規格stream
參數material_types規格text
參數text_file_material規格讀取實際 UTF-8 文件，將文字放入指定的 input 或訊息內容字串。

生命週期： synchronous_or_streamed

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
標準費率 選取快速模式時
flex 模式
標準費率 選取 flex 模式時
最高推理強度
標準費率 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 $0.004 / 1K Token
輸出 · 輸出 Token $0.024 / 1K Token
輸入 · 讀取快取 $0.0004 / 1K Token
輸入 · 寫入快取 $0.00075 / 1K Token
輸入 · 寫入快取，1 小時 — / 1K Token
輸出 · 圖片輸出詞元 $0.24 / 1K 圖片 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 $0.004 / 1K Token
輸出 · 輸出 Token $0.024 / 1K Token
輸入 · 讀取快取 $0.0004 / 1K Token
輸入 · 寫入快取 $0.00075 / 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 · Anthropic Messages

{\n  "model": "google/gemini-3-pro-image",\n  "max_tokens": 128,\n  "messages": [\n    {\n      "role": "user",\n      "content": "Summarize the incident report."\n    }\n  ],\n  "stream": false\n}

接收並儲存結果

Ailoot Ultra · Anthropic Messages

JSON 或 SSE

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。

保留所有內容區塊、思考簽章與實際工具使用 ID。組合所有 SSE 區塊增量；第一個文字區塊不是完整輸出。

需要檢查原始回應時

保留請求／回應 ID 與標頭。未提供通用的文字工作擷取 URL。

回應欄位
欄位類型
欄位id類型string
欄位model類型string
欄位content[]類型text|thinking|tool_use|other content block
欄位stop_reason類型string|null
欄位usage類型object
錯誤與後續步驟
回應條件下一步
回應400 · invalid_request_error條件必要欄位、素材表示方式或參數值無效下一步提出新的建立請求前，先修正指定欄位。

別名

模型別名

Ailoot gemini-3-pro-image, gemini-3-pro-image-preview, nano-banana-pro
Ailoot Ultra google/gemini-3-pro-image

方法路徑別名

/v1/images

相關呼叫用 ID

google/gemini-3-pro-image, gemini-3-pro-image-preview, nano-banana-pro, gemini-3-pro-image

", "method_identity": { "effective_request_model_id": "google/gemini-3-pro-image", "fmt": "messages", "http": "POST", "path": "/v1/messages", "request_model_id": "google/gemini-3-pro-image", "route_label": "Ultra" }, "method_key": "Ultra|messages|/v1/messages|google%2Fgemini-3-pro-image", "ordinal": 5, "rawMethod": { "available": null, "cache_read": 0.4, "cache_write": 0.75, "cache_write_1h": null, "contract": { "data": { "authentication": { "api_key_source": "AILOOT_API_KEY", "headers": [ "Authorization: Bearer", "x-api-key", "anthropic-version" ], "version_example": "2023-06-01" }, "errors": [ { "code": null, "condition": "必要欄位、素材表示方式或參數值無效", "http_status": 400, "recovery": "提出新的建立請求前，先修正指定欄位。", "type": "invalid_request_error" } ], "example_body": { "max_tokens": 128, "messages": [ { "content": "Summarize the incident report.", "role": "user" } ], "model": "google/gemini-3-pro-image", "stream": false }, "lifecycle": { "create": { "http": "POST", "path": "/v1/messages" }, "job_read": null, "mode": "synchronous_or_streamed", "unknown": "保留請求／回應 ID 與標頭。未提供通用的文字工作擷取 URL。" }, "material_combinations": [ { "mode": "text", "representation": "messages[].content 字串", "required_material": "UTF-8 文字" } ], "operation_modes": [ "synchronous_json", "streamed_SSE" ], "outputs": { "all_results": "保留所有內容區塊、思考簽章與實際工具使用 ID。組合所有 SSE 區塊增量；第一個文字區塊不是完整輸出。", "family": "protocol", "fields": [ { "description": null, "name": "id", "type": "string" }, { "description": null, "name": "model", "type": "string" }, { "description": null, "name": "content[]", "type": "text|thinking|tool_use|other content block" }, { "description": null, "name": "stop_reason", "type": "string|null" }, { "description": null, "name": "usage", "type": "object" } ], "format": "JSON 或 SSE" }, "parameters": [ { "availability": "source_interface", "default": null, "default_known": false, "enum": [ "google/gemini-3-pro-image" ], "enum_known": true, "name": "model", "required": true, "type": "string" }, { "availability": "source_interface", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "messages", "required": true, "type": "message[]" }, { "availability": "source_interface", "default": null, "default_known": false, "enum": [ "user", "assistant" ], "enum_known": true, "name": "messages[].role", "required": true, "type": "string" }, { "availability": "source_interface", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "messages[].content", "required": true, "type": "string" }, { "availability": "source_interface", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "max_tokens", "required": true, "type": "integer" }, { "availability": "source_interface", "default": false, "default_known": true, "enum": null, "enum_known": false, "name": "stream", "required": false, "type": "boolean" } ], "profile_binding": "Documented current stock Messages bridge; optional model capabilities are separate from this minimal text request.", "request_schema": { "additionalProperties": false, "properties": { "max_tokens": { "minimum": 1, "type": "integer" }, "messages": { "items": { "additionalProperties": false, "properties": { "content": { "oneOf": [ { "type": "string" }, { "items": { "oneOf": [ { "properties": { "text": { "type": "string" }, "type": { "const": "text" } }, "required": [ "type", "text" ], "type": "object" }, { "properties": { "source": { "oneOf": [ { "properties": { "type": { "const": "url" }, "url": { "type": "string" } }, "required": [ "type", "url" ], "type": "object" }, { "properties": { "data": { "type": "string" }, "media_type": { "type": "string" }, "type": { "const": "base64" } }, "required": [ "type", "media_type", "data" ], "type": "object" } ] }, "type": { "const": "image" } }, "required": [ "type", "source" ], "type": "object" } ] }, "type": "array" } ] }, "role": { "enum": [ "user", "assistant" ], "type": "string" } }, "required": [ "role", "content" ], "type": "object" }, "minItems": 1, "type": "array" }, "model": { "enum": [ "google/gemini-3-pro-image" ], "type": "string" }, "stream": { "default": false, "type": "boolean" } }, "required": [ "model", "messages", "max_tokens" ], "type": "object" }, "schema_template": { "max_tokens": 128, "messages": [ { "content": "Summarize the incident report.", "role": "user" } ], "model": "google/gemini-3-pro-image", "stream": false }, "unsupported": [ "No query API key.", "Hosted/server-side tools and model-specific optional controls are not part of this minimal family example." ] }, "input": { "content_type": "application/json", "material_types": [ "text" ], "optional_controls": [ "stream" ], "required": [ "model", "messages", "max_tokens" ], "text_file_material": "讀取實際 UTF-8 文件，將文字放入指定的 input 或訊息內容字串。" }, "lifecycle": { "create": { "http": "POST", "path": "/v1/messages" }, "job_read": null, "mode": "synchronous_or_streamed", "unknown": "Keep request/response IDs and headers. No generic text job retrieval URL is supplied." }, "manufacturer_capability": null, "method": { "http": "POST", "path": "/v1/messages" }, "output": { "all_results": "Keep all content blocks, thinking signatures and actual tool-use IDs. Assemble all SSE block deltas; a first text block is not the complete output.", "family": "protocol", "format": "JSON or SSE" } }, "ctx": null, "declared_pricing_profiles": [ { "dimensions": { "regime": "base" }, "label": "詞元基本費率", "units": [ { "amount": "0.004000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "input_price", "label": "Input tokens", "native_amount_usd_per_unit": "0.000004", "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": "0.024000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "output_price", "label": "Output tokens", "native_amount_usd_per_unit": "0.000024", "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": "0.0004000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "cache_read_price", "label": "Cache read", "native_amount_usd_per_unit": "0.0000004", "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": "0.00075000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "cache_write_price", "label": "Cache write", "native_amount_usd_per_unit": "0.00000075", "native_quantity": 1, "native_unit": "generic_cache_creation_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "generic_cache_creation_token" }, { "amount": null, "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "cache_write_1h_price", "label": "Cache write, 1 hour", "native_amount_usd_per_unit": null, "native_quantity": 1, "native_unit": "one_hour_cache_creation_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "one_hour_cache_creation_token" }, { "amount": "0.24000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "image_output_price", "label": "Image output tokens", "native_amount_usd_per_unit": "0.00024", "native_quantity": 1, "native_unit": "image_output_token", "public_unit_label": "/ 1K image tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "out", "unit": "image_output_token" } ] }, { "dimensions": { "max_context_tokens_inclusive": null, "min_context_tokens_exclusive": 0 }, "label": "請求長度級距 1", "units": [ { "amount": "0.004000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "input_price", "label": "Input tokens", "native_amount_usd_per_unit": "0.000004", "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": "0.024000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "output_price", "label": "Output tokens", "native_amount_usd_per_unit": "0.000024", "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": "0.0004000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "cache_read_price", "label": "Cache read", "native_amount_usd_per_unit": "0.0000004", "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": "0.00075000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "cache_write_price", "label": "Cache write", "native_amount_usd_per_unit": "0.00000075", "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": "{\n \"model\": \"google/gemini-3-pro-image\",\n \"max_tokens\": 128,\n \"messages\": [\n {\n \"role\": \"user\",\n \"content\": \"Summarize the incident report.\"\n }\n ],\n \"stream\": false\n}", "label": "Complete minimal JSON body", "language": "json" }, { "code": "set -eu\n: \"${AILOOT_API_KEY:?Set your Ailoot API key}\"\n: \"${AILOOT_TEXT_FILE:?Set your actual UTF-8 document}\"\nexport AILOOT_TEXT_FILE\npython3 - <<'PY_REQUEST'\nimport json, os\nfrom pathlib import Path\n\nsource_file = Path(os.environ['AILOOT_TEXT_FILE'])\nif not source_file.is_file():\n raise SystemExit('Set AILOOT_TEXT_FILE to your actual UTF-8 document')\ntext = source_file.read_text(encoding='utf-8')\nif not text.strip():\n raise SystemExit('Choose a document containing text')\npayload = {'model': 'google/gemini-3-pro-image', 'max_tokens': 128, 'messages': [{'role': 'user', 'content': 'Summarize the incident report.'}]}\npayload['messages'][0]['content'] = 'Summarize this material and quote supporting source passages.\\n\\n' + text\nPath('request.json').write_text(json.dumps(payload, ensure_ascii=False), encoding='utf-8')\nPY_REQUEST\ncurl --fail-with-body --silent --show-error https://api.ailoot.ai/v1/messages \\\n -H \"x-api-key: $AILOOT_API_KEY\" -H 'anthropic-version: 2023-06-01' -H 'Content-Type: application/json' \\\n --data-binary @request.json -D response-headers.txt -o result.json\npython3 - <<'PY_RESULT'\nimport json\nfrom pathlib import Path\n\nresult = json.loads(Path('result.json').read_text(encoding='utf-8'))\nprint(json.dumps(result, ensure_ascii=False, indent=2))\nPY_RESULT\n", "label": "curl · use your UTF-8 document", "language": "bash" }, { "code": "import json, os\nfrom pathlib import Path\n\nsource_file = Path(os.environ['AILOOT_TEXT_FILE'])\nif not source_file.is_file():\n raise SystemExit('Set AILOOT_TEXT_FILE to your actual UTF-8 document')\ntext = source_file.read_text(encoding='utf-8')\nif not text.strip():\n raise SystemExit('Choose a document containing text')\npayload = {'model': 'google/gemini-3-pro-image', 'max_tokens': 128, 'messages': [{'role': 'user', 'content': 'Summarize the incident report.'}]}\npayload['messages'][0]['content'] = 'Summarize this material and quote supporting source passages.\\n\\n' + text\nfrom urllib.request import Request, urlopen\nfrom urllib.error import HTTPError\n\napi_key = os.environ['AILOOT_API_KEY']\nif not api_key.strip():\n raise SystemExit('Set AILOOT_API_KEY before making a request')\nheaders = {'x-api-key': 'PLACEHOLDER_KEY', 'anthropic-version': '2023-06-01', 'Content-Type': 'application/json'}\nheaders['x-api-key'] = api_key\nrequest = Request('https://api.ailoot.ai/v1/messages', data=json.dumps(payload, ensure_ascii=False).encode('utf-8'), headers=headers, method='POST')\ntry:\n with urlopen(request, timeout=120) as response:\n raw = response.read()\n Path('response-headers.txt').write_text(str(response.headers), encoding='utf-8')\nexcept HTTPError as error:\n Path('result.json').write_bytes(error.read())\n Path('response-headers.txt').write_text(str(error.headers), encoding='utf-8')\n raise\nPath('result.json').write_bytes(raw)\nimport json\nfrom pathlib import Path\n\nresult = json.loads(Path('result.json').read_text(encoding='utf-8'))\nprint(json.dumps(result, ensure_ascii=False, indent=2))\n", "label": "Python · save the complete result", "language": "python" } ], "family": "anthropic", "fast_multiplier": 1, "flex_multiplier": 1, "fmt": "messages", "http": "POST", "in": 4, "input": [ "text" ], "label": "Anthropic Messages", "max_out": null, "max_reasoning_effort_multiplier": 1, "method_aliases": [], "out": 24, "output": [ "json", "sse" ], "path": "/v1/messages", "price_conditions": [ { "label": "快速模式", "value": "標準費率", "when": "選取快速模式時" }, { "label": "flex 模式", "value": "標準費率", "when": "選取 flex 模式時" }, { "label": "最高推理強度", "value": "標準費率", "when": "最高推理強度採用 default 調整值時" }, { "label": "顯式快取計價", "value": "未啟用", "when": "請求顯式快取時" } ], "pricing": { "billing_mode": "token", "image_input_price": null, "image_output_price": 0.00024, "per_request_price": null }, "pricing_profiles": [ { "dimensions": { "regime": "base" }, "label": "Base token rates", "units": [ { "amount": "0.004000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "input_price", "label": "Input tokens", "native_amount_usd_per_unit": "0.000004", "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": "0.024000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "output_price", "label": "Output tokens", "native_amount_usd_per_unit": "0.000024", "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": "0.0004000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "cache_read_price", "label": "Cache read", "native_amount_usd_per_unit": "0.0000004", "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": "0.00075000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "cache_write_price", "label": "Cache write", "native_amount_usd_per_unit": "0.00000075", "native_quantity": 1, "native_unit": "generic_cache_creation_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "generic_cache_creation_token" }, { "amount": null, "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "cache_write_1h_price", "label": "Cache write, 1 hour", "native_amount_usd_per_unit": null, "native_quantity": 1, "native_unit": "one_hour_cache_creation_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "one_hour_cache_creation_token" }, { "amount": "0.24000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "image_output_price", "label": "Image output tokens", "native_amount_usd_per_unit": "0.00024", "native_quantity": 1, "native_unit": "image_output_token", "public_unit_label": "/ 1K image tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "out", "unit": "image_output_token" } ] }, { "dimensions": { "max_context_tokens_inclusive": null, "min_context_tokens_exclusive": 0 }, "label": "Request-length tier 1", "units": [ { "amount": "0.004000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "input_price", "label": "Input tokens", "native_amount_usd_per_unit": "0.000004", "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": "0.024000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "output_price", "label": "Output tokens", "native_amount_usd_per_unit": "0.000024", "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": "0.0004000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "cache_read_price", "label": "Cache read", "native_amount_usd_per_unit": "0.0000004", "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": "0.00075000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "cache_write_price", "label": "Cache write", "native_amount_usd_per_unit": "0.00000075", "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": "google/gemini-3-pro-image", "route_label": "Ultra", "status_reads": [], "tiers": [ { "cache_read": 0.4, "cache_read_multiplier": null, "cache_write": 0.75, "cache_write_1h": null, "cache_write_multiplier": null, "created_at": "0001-01-01T00:00:00Z", "in": 4, "input_multiplier": null, "max": null, "max_tokens": null, "min": 0, "min_tokens": 0, "out": 24, "output_multiplier": null, "per_request_price": null, "sort_order": 0, "tier_label": "", "updated_at": "0001-01-01T00:00:00Z" } ], "units": [ { "amount": "0.004000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "input_price", "label": "Input tokens", "native_amount_usd_per_unit": "0.000004", "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": "0.024000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "output_price", "label": "Output tokens", "native_amount_usd_per_unit": "0.000024", "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": "0.0004000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "cache_read_price", "label": "Cache read", "native_amount_usd_per_unit": "0.0000004", "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": "0.00075000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "cache_write_price", "label": "Cache write", "native_amount_usd_per_unit": "0.00000075", "native_quantity": 1, "native_unit": "generic_cache_creation_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "generic_cache_creation_token" }, { "amount": null, "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "cache_write_1h_price", "label": "Cache write, 1 hour", "native_amount_usd_per_unit": null, "native_quantity": 1, "native_unit": "one_hour_cache_creation_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "one_hour_cache_creation_token" }, { "amount": "0.24000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "image_output_price", "label": "Image output tokens", "native_amount_usd_per_unit": "0.00024", "native_quantity": 1, "native_unit": "image_output_token", "public_unit_label": "/ 1K image tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "out", "unit": "image_output_token" } ] } } ], "model_id": "google/gemini-3-pro-image", "nativeProvenance": { "input_facts_canonical_sha256": "0eb0dce6653dc79650af40348128d2d55397743ffeb609ec2ed917f1f304c942", "input_html_sha256": "4d57789955490e156076453a82a4eb5b06ec71aef3b66dfbb6e847d942c51fae", "private_audit_sha256": "e1fef979a5529155e54615d459c6dbe1b5a4569cacb909873f17526fb1ff1690", "role": "historical-normalized-input-audit-hashes", "schema": "ailoot-native-model-provenance-v2" }, "page": { "canonical": "https://ailoot.ai/models/zh-hant-tw/gemini-3-pro-image/", "description": "Nano Banana Pro（Gemini 3 Pro Image）是 Google 以推理驅動的圖像模型，適用複雜設計、產品樣稿及事實視覺化。它接收文字與圖像參考，生成圖像及文字，提供 1K–4K 輸出與詳細創意控制。", "locale": "zh-hant-tw", "md_url": "https://ailoot.ai/models/zh-hant-tw/gemini-3-pro-image/index.md", "title": "Google: Nano Banana Pro (Gemini 3 Pro Image) — Ailoot", "url": "https://ailoot.ai/models/zh-hant-tw/gemini-3-pro-image/" }, "practicalHtml": "

實用任務

英文技術範例

Visualize a supplied packaging cycle\n\nCreate one landscape explanatory graphic showing this packaging return cycle: customer returns an empty jar, store inspects it, accepted jars are washed, clean jars are refilled. Use four large illustrated stages connected clockwise. Add only these exact labels: 'RETURN', 'INSPECT', 'WASH', 'REFILL'. Make the arrow direction and stage order unmistakable.

預期結果

One landscape image with four labeled stages and arrows matching the supplied cycle.

檢查結果

Inspect that arrows connect RETURN to INSPECT to WASH to REFILL in that order, with exact labels.
", "practicalText": "實用任務 英文技術範例 Visualize a supplied packaging cycle Create one landscape explanatory graphic showing this packaging return cycle: customer returns an empty jar, store inspects it, accepted jars are washed, clean jars are refilled. Use four large illustrated stages connected clockwise. Add only these exact labels: 'RETURN', 'INSPECT', 'WASH', 'REFILL'. Make the arrow direction and stage order unmistakable. 預期結果 One landscape image with four labeled stages and arrows matching the supplied cycle. 檢查結果 Inspect that arrows connect RETURN to INSPECT to WASH to REFILL in that order, with exact labels.", "rawModel": { "about": "Nano Banana Pro 是 Google 以推理驅動圖像生成及編輯的 Gemini 3 Pro Image 模型。製造商將複雜平面設計、高保真產品樣稿及事實資料視覺化置於預定用途核心。它接收文字與圖像，產生圖像與文字。此具名 Pro 圖像版本以 Gemini 3 Pro 為基礎，同時保有自身圖像任務的輸入及能力設定。\n\n模型支援 1K、2K、4K 圖像。文件中的形狀包括 1:1、2:3、3:2、3:4、4:3、4:5、5:4、9:16、16:9、21:9。正方形 4K 圖像為 4096 × 4096；16:9 4K 圖像為 5504 × 3072。無論需要直式海報、產品場景或寬幅解說圖，均應依成果選擇解析度及長寬比。Gemini 3.1 Flash Image 的 0.5K 選項及額外極端比例不在此 Pro 表內。\n\n文字呈現支援海報、圖解及其他設計素材的清楚字樣。複雜資訊圖表應提供基礎事實、確切文字、閱讀順序，以及標籤與視覺元素關係。請將要傳達的資訊與所需藝術風格分開。Google 建議先準備文字，再生成包含文字的圖像。構圖結合標題、圖解及數段簡短說明時，這尤其實用。\n\n多圖輸入支援最多 14 張參考。Google 功能表描述最多六張物件參考用於忠實呈現、最多五張角色參考用於一致性，以及最多三張風格參考。這些角色有助於準備合成視覺：產品照片定義外觀、另一張圖建立環境，風格圖像則影響處理方式。請告訴模型哪些細節具權威性、哪些參考提供靈感，而非要求它不加區分地結合每個可見特徵。\n\nGoogle Search grounding 可為事實視覺化或反映當前狀況的場景提供現實資訊。Pro 圖像流程記載網頁 grounding；Image Search 擴充則專門記載於 Nano Banana 2.1 及 Gemini 3.1 Flash Image。資料圖像應提供預期呈現值，或在原始模型流程要求 grounding 資訊，再明確說明關係、標籤及版面。搜尋輔助生成的結果仍是需要檢查的圖像，不能取代核對描繪事實。\n\n推理支援在最終渲染前組織複雜提示。圖像指南描述用於測試構圖與邏輯的中間圖像，與最終成果不同。請勿將 Nano Banana 2 的 minimal/high 控制表，或 Nano Banana 2.1 的 medium 預設表，套用至此 Pro 版本。高難度設計應提供完整需求，包含視覺層級、必要物件關係，以及後續編輯中必須保留的元素。\n\n模型資訊卡描述了仍存在的重要限制：極小文字及長段落可能呈現不佳，角色外觀可能在參考與結果間改變，遮罩或塗鴉編輯可能僅部分遵循指令或留下痕跡。它也可能混淆左右，或將來源元素複製到新構圖。產品修訂應明確說明要保留的幾何形狀與標籤，並檢查編輯區域；圖解應比較箭頭方向及物件相對位置。\n\n目前 API 表列出輸入上限 65,536 token、輸出上限 32,768 token。支援圖像生成、thinking、搜尋 grounding 及批次處理；不支援音訊生成、函式呼叫、程式碼執行、快取、結構化輸出、檔案搜尋、URL context 及 Live API。此設定的圖像任務不接受音訊或影片輸入。生成圖像包含 SynthID，且不一定精確遵循所需輸出圖像數量。\n\n實用產品需求可結合產品圖像、光線參考及確切標題：「保留產品比例與字樣，將它呈現在柔和側光下的淺色石材表面，上方三分之一留白，以放置提供的標題。」事實圖解應指明每個實體及連結，並提供定稿標籤。可透過對話指出一項修改及要保留的特徵來完善結果，將選定圖像與解說文字一起保留為設計成果。", "alias_of": null, "aliases": [ "gemini-3-pro-image-preview", "nano-banana-pro", "gemini-3-pro-image" ], "author": "Google", "available": null, "canonical_model": "google/gemini-3-pro-image", "capabilities": { "context_length": 131072, "manufacturer_input": [ "image", "text" ], "manufacturer_output": [ "image", "text" ] }, "card_routes": [ { "label": "Ultra", "rates": [ { "amount": "0.004000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "configuration": "OpenAI Chat", "estimate_only": false, "key": "input_price", "label": "Input tokens", "native_amount_usd_per_unit": "0.000004", "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": "0.024000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "configuration": "OpenAI Chat", "estimate_only": false, "key": "output_price", "label": "Output tokens", "native_amount_usd_per_unit": "0.000024", "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": "0.98304", "amount_unit": "usd_per_exact_native_unit", "billing_input": false, "configuration": "Images", "estimate_only": true, "key": "forecast_usd", "label": "Estimated generation cost", "native_amount_usd_per_unit": "0.98304", "native_quantity": 1, "public_unit_label": "estimate before generation", "quantity": 1, "quantity_is_estimate": true, "rate_role": "typed_native_retail_rate", "side": "out", "unit": "request_estimate" }, { "amount": "0.004000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "configuration": "Anthropic Messages", "estimate_only": false, "key": "input_price", "label": "Input tokens", "native_amount_usd_per_unit": "0.000004", "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": "0.024000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "configuration": "Anthropic Messages", "estimate_only": false, "key": "output_price", "label": "Output tokens", "native_amount_usd_per_unit": "0.000024", "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, "entity_type": "model", "formats": [ "images", "chat", "messages" ], "id": "google/gemini-3-pro-image", "input": [ "text", "image" ], "kind": "text", "max_out": null, "methods": [ { "cache_read": null, "cache_write": null, "cache_write_1h": null, "cache_write_5m": null, "conditional_meter": null, "contract": { "data": { "all_results": "Save every data item. Decode each b64_json or fetch every returned signed URL. Select a filename extension from the actual MIME/bytes.", "errors": [ { "code": null, "condition": "必要欄位、素材表示方式或參數值無效", "http_status": 400, "recovery": "提出新的建立請求前，先修正指定欄位。", "type": "invalid_request_error" }, { "code": null, "condition": "回傳的回應表示該作業或結果需要檢查", "http_status": null, "recovery": "保留原始回傳的作業／任務 ID、請求標頭與回應；繼續以支援的方式讀取該原始作業。請勿重新提交建立請求。", "type": "server_error" } ], "hints": [], "ignored_fields": [], "lifecycle": { "all_results": "Follow everyactualreturnedoutputandownedasset; no result is discardedbecauseindex0orcontent_urlalreadyexists.", "assets": [ { "http": "GET", "path": "/v1/media/assets" }, { "http": "GET", "path": "/v1/media/assets/{asset_id}" } ], "content": [ { "http": "GET", "path": "/v1/media/assets/{asset_id}/content", "url_source": "exact returned signed URL; never construct token" } ], "mode": "synchronous_result_then_owned_library", "operation_id_is_not_task_id": true, "status": [ { "http": "GET", "id_source": "actual returned task_id or media library record", "path": "/v1/media/tasks/{task_id}" } ], "unknown": "若圖片生成或編輯結果需要檢查，請保留原始 operation_id/X-Client-Request-ID 與回傳的結果資訊。使用實際的 task_id 或 asset_id 值，透過媒體庫取回自己擁有的既有結果。請勿重新提交生成／編輯請求，也請勿以 operation_id 組成輪詢 URL。" }, "material_combinations": [ { "content_types": [ "application/json", "multipart/form-data" ], "file_id_supported": false, "mode": "text_to_image", "multipart_part_read_limit_bytes": 20971520, "optional_mask": { "json": "mask.image_url", "multipart": "mask" }, "reference_representations": { "json": "images[].image_url", "multipart": [ "image", "image[]", "image[index]" ] }, "required": [ "prompt" ] } ], "media_library": { "asset": { "fields": [ { "description": null, "name": "asset_id", "type": "string" }, { "description": null, "name": "task_id", "type": "string" }, { "description": null, "name": "output_key", "type": "string" }, { "description": null, "name": "family", "type": "string" }, { "description": null, "name": "model", "type": "string" }, { "description": null, "name": "method", "type": "string" }, { "description": null, "name": "status", "type": "string" }, { "description": null, "name": "content_type", "type": "string" }, { "description": null, "name": "sha256", "type": "string" }, { "description": null, "name": "size_bytes", "type": "integer" }, { "description": null, "name": "content_url", "type": "string" } ], "http": "GET", "id_source": "actual returned asset_id", "path": "/v1/media/assets/{asset_id}" }, "content": { "http": "GET", "path": "/v1/media/assets/{asset_id}/content", "range_header_supported": true, "url_source": "Use exact returned signed content_url including its token; do not construct a token." }, "expired_link": { "code": "link_expired", "http_status": 404, "recovery": "Read the asset again to obtain its refreshed signed content_url, then fetch that URL. Do not regenerate." }, "list": { "all_pages": "Follow every returned next_cursor, then select records by their actual task_id/output_key.", "http": "GET", "output_fields": [ { "description": null, "name": "object", "type": "string" }, { "description": null, "name": "data", "type": "asset[]" }, { "description": null, "name": "next_cursor", "type": "string|null" } ], "parameters": [ { "availability": "source_interface", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "family", "required": false, "type": "string" }, { "availability": "source_interface", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "cursor", "required": false, "type": "string" }, { "availability": "source_interface", "default": 20, "default_known": true, "enum": null, "enum_known": false, "maximum": 100, "minimum": 1, "name": "limit", "required": false, "type": "integer" } ], "path": "/v1/media/assets" }, "revoke": { "http": "DELETE", "meaning": "Revokes/deletes the existing owned file; this is not generation cancellation.", "path": "/v1/media/assets/{asset_id}", "pending_status": "revoking", "success_statuses": [ 202, 204 ] }, "task": { "http": "GET", "id_source": "actual returned task_id or media library record; operation_id is not task_id", "path": "/v1/media/tasks/{task_id}" } }, "operation_modes": [ "text_to_image" ], "outputs": { "all_results": "儲存所有資料項目。解碼每個 b64_json，或透過每個回傳的已簽署 URL 取得內容。依實際 MIME 類型／位元組內容選擇副檔名。", "family": "image", "fields": [ { "description": null, "name": "created", "type": "integer" }, { "description": null, "name": "data[].url", "type": "string" }, { "description": null, "name": "data[].b64_json", "type": "base64 string" }, { "description": null, "name": "usage", "type": "object" } ], "format": "actual validated raster MIME" }, "parameters": [ { "availability": "source_interface", "default": null, "default_known": false, "enum": [ "gemini-3-pro-image" ], "enum_known": true, "name": "model", "required": true, "type": "string" }, { "availability": "source_interface", "default": null, "default_known": false, "enum": null, "enum_known": false, "min_length": 1, "name": "prompt", "required": true, "type": "string" }, { "availability": "source_interface", "default": 1, "default_known": true, "enum": null, "enum_known": false, "minimum": 1, "name": "n", "required": false, "type": "integer" }, { "availability": "source_interface", "default": null, "default_known": false, "enum": [ "url", "b64_json" ], "enum_known": true, "name": "response_format", "required": false, "type": "string" }, { "availability": "source_interface", "default": false, "default_known": true, "enum": null, "enum_known": false, "name": "stream", "required": false, "type": "boolean" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "size", "required": false, "type": "string" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "quality", "required": false, "type": "string" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "background", "required": false, "type": "string" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "output_format", "required": false, "type": "string" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "output_compression", "required": false, "type": "integer" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "moderation", "required": false, "type": "string" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "input_fidelity", "required": false, "type": "string" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "style", "required": false, "type": "string" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "partial_images", "required": false, "type": "integer" } ], "profile_binding": "Exact existing Ailoot model and method; interface constraints below do not assert provider qualification.", "unsupported": [ "images[].file_id", "mask.file_id" ] }, "hints": [ "方法結構與 ID 均為精確值；供應商能力與准入狀態分開。" ], "input": { "content_type": "application/json", "material_types": [ "text" ], "optional_controls": null, "required": [ "model", "prompt" ] }, "lifecycle": { "assets": [ { "http": "GET", "path": "/v1/media/assets" }, { "http": "GET", "path": "/v1/media/assets/{asset_id}" } ], "content": [ { "http": "GET", "path": "/v1/media/assets/{asset_id}/content", "url_source": "exact returned signed URL; never construct token" } ], "mode": "synchronous_result_then_owned_library", "operation_id_is_not_task_id": true, "status": [ { "http": "GET", "id_source": "實際回傳的 task_id 或媒體庫紀錄", "path": "/v1/media/tasks/{task_id}" } ], "unknown": "If an image generation or edit result requires a check, keep the original operation_id/X-Client-Request-ID and returned result information. Recover existing owned results through the media library using actual task_id or asset_id values. Do not resubmit the generation/edit request or construct a polling URL from operation_id." }, "method": { "http": "POST", "path": "/v1/images/generations" }, "operation_modes": [ "images" ], "output": { "family": [ "image" ], "format": null, "multioutputs": "retain every actual response output" } }, "ctx": 65536, "examples": [ { "code": "set -eu\n: \"${AILOOT_API_KEY:?Set your Ailoot API key}\"\nexport AILOOT_API_KEY\nexport AILOOT_API_KEY\n: \"${AILOOT_PROMPT_FILE:?Set your actual UTF-8 image brief}\"\nexport AILOOT_PROMPT_FILE\npython3 - <<'PY_REQUEST'\nimport json,os\nfrom pathlib import Path\np=json.loads('{\"model\": \"gemini-3-pro-image\", \"prompt\": \"\"}')\nf=Path(os.environ[\"AILOOT_PROMPT_FILE\"])\nif not f.is_file():raise SystemExit(\"Choose your actual UTF-8 brief\")\np['prompt']=f.read_text(encoding=\"utf-8\")\nif not p['prompt'].strip():raise SystemExit(\"Brief must contain text\")\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/images/generations \\\n -H \"Authorization: Bearer $AILOOT_API_KEY\" -H 'Content-Type: application/json' \\\n --data-binary @request.json -D response-headers.txt -o result.json\npython3 - <<'PY_RESULT'\nimport base64, json, os, subprocess\nfrom pathlib import Path\nfrom urllib.parse import urlsplit, urljoin\n\ndef save_images(items):\n if not items: raise SystemExit(\"No completed images; retain the full response\")\n for index, item in enumerate(items):\n encoded=item.get(\"b64_json\")\n uri=item.get(\"url\", \"\")\n if not encoded and uri.startswith(\"data:image/\"):\n header, separator, encoded=uri.partition(\",\")\n if not separator or \";base64\" not in header: raise SystemExit(\"Unsupported image data URI\")\n if encoded:\n raw=base64.b64decode(encoded,validate=True)\n elif uri:\n uri=urljoin(\"https://api.ailoot.ai\",uri)\n parsed=urlsplit(uri)\n if parsed.scheme!=\"https\" or not parsed.netloc or parsed.username or parsed.password:\n raise SystemExit(\"Invalid returned image URL\")\n owned=parsed.netloc==\"api.ailoot.ai\" and parsed.path.startswith(\"/v1/media/assets/\") and parsed.path.endswith(\"/content\")\n args=[\"curl\",\"--fail-with-body\",\"--silent\",\"--show-error\",uri]\n if owned: args += [\"-H\",\"Authorization: Bearer \"+os.environ[\"AILOOT_API_KEY\"]]\n temporary=Path(f\"image-{index}.bin\")\n subprocess.run(args+[\"-o\",str(temporary)],check=True)\n raw=temporary.read_bytes()\n temporary.unlink()\n else: raise SystemExit(\"Image has neither bytes nor URL\")\n if not raw: raise SystemExit(\"Empty image result\")\n ext=\"png\" if raw.startswith(b\"\\x89PNG\") else \"jpg\" if raw.startswith(b\"\\xff\\xd8\") else \"webp\" if raw[:4]==b\"RIFF\" and raw[8:12]==b\"WEBP\" else \"svg\" if raw.lstrip().startswith((b\"