Bytedance Seed V2 Mini
整合
模型 id
bytedance/seed/v2/mini
# Run the model; wait up to 20 s for the finished result in the same call
curl -X POST "https://api.doitong.ru/v1/run/bytedance/seed/v2/mini?wait=20" \
-H "Authorization: Bearer $DOITONG_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field"
}'
# Still "queued" or "running"? Poll with the id from the response:
curl "https://api.doitong.ru/v1/requests/REQUEST_ID?wait=20" \
-H "Authorization: Bearer $DOITONG_API_KEY"
const API = "https://api.doitong.ru/v1";
const headers = {
"Authorization": "Bearer " + process.env.DOITONG_API_KEY,
"Content-Type": "application/json",
};
// Run the model; wait up to 20 s for the finished result in the same call
let res = await fetch(API + "/run/bytedance/seed/v2/mini?wait=20", {
method: "POST",
headers,
body: JSON.stringify({
"prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field"
}),
});
let request = await res.json();
if (!res.ok) throw new Error(request.error.code + ": " + request.error.message);
// Not finished yet: long-poll until it is
while (request.status === "queued" || request.status === "running") {
res = await fetch(API + "/requests/" + request.id + "?wait=20", { headers });
request = await res.json();
}
if (request.status !== "succeeded") throw new Error(JSON.stringify(request.error));
console.log(request.outputs.map((o) => o.url), request.cost.credits + " API credits ($" + request.cost.usd + ")");
import os
import requests
API = "https://api.doitong.ru/v1"
headers = {"Authorization": "Bearer " + os.environ["DOITONG_API_KEY"]}
payload = {
"prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field",
}
# Run the model; wait up to 20 s for the finished result in the same call
r = requests.post(API + "/run/bytedance/seed/v2/mini", params={"wait": 20}, json=payload, headers=headers)
request = r.json()
if not r.ok:
raise RuntimeError(request["error"]["code"] + ": " + request["error"]["message"])
# Not finished yet: long-poll until it is
while request["status"] in ("queued", "running"):
request = requests.get(API + "/requests/" + request["id"], params={"wait": 20}, headers=headers).json()
if request["status"] != "succeeded":
raise RuntimeError(request["error"])
print([o["url"] for o in request["outputs"]], request["cost"]["credits"], "API credits", "$" + request["cost"]["usd"])
# 1. Connect once (Claude Code; Cursor, VS Code, Claude Desktop: https://doitong.com/zh-TW/developers/docs/mcp)
claude mcp add --transport http doitong-models https://api.doitong.ru/v1/mcp \
--header "Authorization: Bearer $DOITONG_API_KEY"
# 2. Your agent calls the "run" tool with:
{
"model_id": "bytedance/seed/v2/mini",
"input": {
"prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field"
}
}
透過 Doitong API 呼叫 Bytedance Seed V2 Mini 模型(bytedance/seed/v2/mini)。代理程式文件:https://doitong.com/zh-TW/developers/models/bytedance/seed/v2/mini.md
POST https://api.doitong.ru/v1/run/bytedance/seed/v2/mini?wait=20
Authorization: Bearer $DOITONG_API_KEY
Content-Type: application/json
{
"prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field"
}
如果回應狀態為 "queued" 或 "running",請輪詢 GET https://api.doitong.ru/v1/requests/REQUEST_ID?wait=20,直到狀態變為 "succeeded";檔案位於 outputs[].url。使用相同主體傳送 POST https://api.doitong.ru/v1/quote/bytedance/seed/v2/mini,可在執行前取得確切價格。
每次執行最多 $0.213 依實際用量收費,其餘金額會退款 在此頁面執行
您的新 API 金鑰。 僅會在此時顯示,且已填入下方的程式碼與 API 金鑰欄位。請妥善保密:切勿將其放入在瀏覽器中執行的程式碼。
建立請求
控制項是根據模型結構描述生成的。變更設定時,程式碼和價格會同步更新。
POST
/run/bytedance/seed/v2/mini?wait=20
報價 → $0.213
# Run the model; wait up to 20 s for the finished result in the same call
curl -X POST "https://api.doitong.ru/v1/run/bytedance/seed/v2/mini?wait=20" \
-H "Authorization: Bearer $DOITONG_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field"
}'
# Still "queued" or "running"? Poll with the id from the response:
curl "https://api.doitong.ru/v1/requests/REQUEST_ID?wait=20" \
-H "Authorization: Bearer $DOITONG_API_KEY"
const API = "https://api.doitong.ru/v1";
const headers = {
"Authorization": "Bearer " + process.env.DOITONG_API_KEY,
"Content-Type": "application/json",
};
// Run the model; wait up to 20 s for the finished result in the same call
let res = await fetch(API + "/run/bytedance/seed/v2/mini?wait=20", {
method: "POST",
headers,
body: JSON.stringify({
"prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field"
}),
});
let request = await res.json();
if (!res.ok) throw new Error(request.error.code + ": " + request.error.message);
// Not finished yet: long-poll until it is
while (request.status === "queued" || request.status === "running") {
res = await fetch(API + "/requests/" + request.id + "?wait=20", { headers });
request = await res.json();
}
if (request.status !== "succeeded") throw new Error(JSON.stringify(request.error));
console.log(request.outputs.map((o) => o.url), request.cost.credits + " API credits ($" + request.cost.usd + ")");
import os
import requests
API = "https://api.doitong.ru/v1"
headers = {"Authorization": "Bearer " + os.environ["DOITONG_API_KEY"]}
payload = {
"prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field",
}
# Run the model; wait up to 20 s for the finished result in the same call
r = requests.post(API + "/run/bytedance/seed/v2/mini", params={"wait": 20}, json=payload, headers=headers)
request = r.json()
if not r.ok:
raise RuntimeError(request["error"]["code"] + ": " + request["error"]["message"])
# Not finished yet: long-poll until it is
while request["status"] in ("queued", "running"):
request = requests.get(API + "/requests/" + request["id"], params={"wait": 20}, headers=headers).json()
if request["status"] != "succeeded":
raise RuntimeError(request["error"])
print([o["url"] for o in request["outputs"]], request["cost"]["credits"], "API credits", "$" + request["cost"]["usd"])
{
"jsonrpc": "2.0",
"id": 1,
"method": "tools/call",
"params": {
"name": "run",
"arguments": {
"model_id": "bytedance/seed/v2/mini",
"input": {
"prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field"
},
"wait_seconds": 20
}
}
}
關於 Bytedance Seed V2 Mini
可回答文字 `prompt` 的語言模型,也能分析最多 6 張影像(`image_urls`)和最多 3 部影片(`video_urls`),但不理解音訊。`thinking` 可設為啟用、停用或 auto,`reasoning_effort` 範圍從 minimal 到 high。透過 `max_completion_tokens`,輸出長度最高可達 65536 個 token。支援 `system_prompt` 及先前的 `messages`,可進行多輪對話。
參數
請傳送標準名稱或原生名稱其中之一,不要同時傳送兩者。 標準名稱
名稱類型
預設值允許值
說明
prompt必填
類型string
包含傳送給模型之提示詞或問題的文字。
image_urls選填
images
類型url[] · image
透過指向 JPEG、PNG、WebP 檔案的 URL 提供用於視覺理解的圖像。最多處理 6 個圖像;超過上限的項目會被忽略。
video_urls選填
videos
類型url[] · video
提供 MP4 或 MOV 影片 URL 以理解其視覺內容,不處理音訊。最多處理 3 部影片;超過上限的項目會被忽略。
system_prompt選填
類型string | null
可選的系統層級提示詞,用於引導模型行為。
messages選填
類型object[]
可選的多輪上下文,可重用先前回應的 `messages` 值來提供。不論此歷史記錄為何,都會附加一個新的最新使用者回合,其中包含目前的 `prompt`、`image_urls`、`video_urls` 和 `system_prompt`。
messages[].role必填
類型enum
systemuserassistant
指派給訊息作者的角色。
messages[].content必填
類型string | array of object
訊息內容可接受任一表示方式:多模態內容使用部分清單,例如圖像;純文字訊息則使用字串。
thinking選填
類型enum
預設值enabled
enableddisabledauto
思維鏈推理模式:`enabled` 每次都包含推理,`disabled` 完全排除推理,`auto` 允許模型依查詢自行選擇。
reasoning_effort選填
類型enum
minimallowmediumhigh
選擇模型回覆前的推理深度:`high` 深入分析複雜問題,`medium` 平衡深度與速度,`low` 使用輕量推理以更快回覆,`minimal` 立即回覆。此設定僅在 `thinking` 值為 `enabled` 或 `auto` 時適用。
max_completion_tokens選填
類型integer
預設值4096
1 – 65,536
生成輸出的最大 Token 額度。回應 Token 和思維鏈 Token 都會計入此共用上限。
temperature選填
類型number
預設值1
0 – 2
回應隨機性設定:值越高,生成越偏向創意;值越低,越偏向集中且確定性的輸出。
top_p選填
類型number
預設值0.7
0 – 1
核心取樣控制項 `top_p`:值越低,Token 選擇限制越嚴格。模型候選 Token 的累積機率質量會涵蓋 `top_p`。
enable_safety_checker選填
類型boolean
預設值true
在呼叫端獲得授權的情況下,將此值設為 false 可放寬審核。
必填
標準名稱,也可使用
檔案參數接受公開的 https:// URL、最大 10 MB 的 data: URI,或上傳檔案的 file_url。 檔案
輸出
GET /requests/req_8k2m4q7x1z9c3v5b6n0p2r4t
{
"id": "req_8k2m4q7x1z9c3v5b6n0p2r4t",
"object": "request",
"model": "bytedance/seed/v2/mini",
"status": "succeeded",
"created_at": "2026-10-20T12:00:00Z",
"started_at": "2026-10-20T12:00:02Z",
"completed_at": "2026-10-20T12:00:09Z",
"queue_position": null,
"cost": {
"credits": 213,
"usd": "0.213",
"charged": 213,
"refunded": 0
},
"input": {
"prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field"
},
"output": {
"output": "string",
"reasoning_content": "string",
"messages": [
{
"role": "system",
"content": "string"
}
]
},
"outputs": [
{
"type": "file",
"url": "https://content.doitong.com/dev-api/2026/10/20/req_8k2m4q7x1z9c3v5b6n0p2r4t/0-output.jpeg",
"content_type": "image/jpeg",
"file_size": 1843200,
"stored": true
}
],
"error": null,
"metrics": {
"inference_seconds": 6.8
},
"urls": {
"self": "https://api.doitong.ru/v1/requests/req_8k2m4q7x1z9c3v5b6n0p2r4t",
"cancel": "https://api.doitong.ru/v1/requests/req_8k2m4q7x1z9c3v5b6n0p2r4t/cancel"
}
}
您的檔案,由您選擇每個 outputs[].url 都是儲存空間中的副本:可永久保留(按 GB-月計費),或免費保留 7 天;可透過帳戶設定或 ?storage= 設定。
所有模型使用相同結構圖片、影片和音訊皆包含 type、url、content_type、width、height 和 duration。output 是模型自己的結果物件。
輸出欄位
- output
- string模型回傳的文字。
- reasoning_content
- string | null當 `thinking` 設為 `enabled` 或 `auto` 時,此輸出可能包含模型的思維鏈推理;其他設定下不會包含。
- messages
- array of object {role, content}供下一個 `messages` 輸入重用的對話上下文:回傳的歷史記錄包含每個回合,包括模型最新的回覆。
更多模型:LLM
給 AI 代理程式:此頁面的 Markdown 位於 https://doitong.com/zh-TW/developers/models/bytedance/seed/v2/mini.md. 所有模型與指南: https://doitong.com/developers/llms.txt