Dreamina Seedance 2.0 vs Sora 2 Pro
何時該用哪一個 — 綜合評斷,而非基準測試數據表
兩者都是文字和圖片轉影片模型,具備 24 fps、原生音訊和 .mp4 輸出,但它們的計費單位不同 — dreamina-seedance-2-0-260128 的定價為每百萬輸出 token $7,而 sora-2-pro 則依每秒影片收取 $0.3 — 因此兩者之間沒有單一的公允換算方式。當您需要高達 4K 的解析度、長達 15 s 的片段、6 種長寬比,或是首幀和首尾幀條件控制時,請選擇於 2026-01 發布、較新的 dreamina-seedance-2-0-260128。如果列舉的 720p/1024p 輸出、4-12 s 的片段、16:9 或 9:16 長寬比,以及單一參考圖片足以滿足您的需求,且按秒編列預算較易於評估,請選擇 sora-2-pro。
定價
| Dreamina Seedance 2.0 | Sora 2 Pro | Δ | |
|---|---|---|---|
| 每秒輸出(含音訊) | — | $0.3 | — |
| 每 1M 影片 tokens | $7 | — | — |
這兩個模型以不同的單位計費,因此未顯示 Δ — 在兩者之間進行換算需要基於我們未曾實測的假設。上方各費率卡均以其專屬的單位列出。
能力
| Dreamina Seedance 2.0 | Sora 2 Pro | |
|---|---|---|
| 原生音訊 | 是 | 是 |
規格
| Dreamina Seedance 2.0 | Sora 2 Pro | |
|---|---|---|
| 輸入模態 | 文字 影像 | 文字 影像 |
| 輸出模態 | 影片 | 影片 |
| 發布日期 | 2026-01 | 2025-09 |
| 解析度 | 480p – 4K (10-bit at 4K) (範圍) | 720p / 1024p (固定選項) |
| 片段長度 | 4–15 s (範圍) | 4-12 s (範圍) |
| 影格率 | 24 fps | 24 fps |
| 長寬比 | 6 (incl. 16:9, 9:16, 1:1) |
|
| 輸入模式 |
|
|
| 格式 | .mp4 | .mp4 |
規格摘錄自各供應商的文件;供應商未發布的資料列會直接省略,而非自行推測。 完整來源: Dreamina Seedance 2.0 · Sora 2 Pro
單一提示詞,兩款模型 — 經由閘道測量
模型回傳 1280×720 長度 5s 延遲 133 s
模型回傳 1280×720 長度 4s 延遲 130 s
單一提示詞,每個模型一次請求,不重試且不擇優挑選——皆為各模型回傳的第一個結果。尺寸與長度皆未強制指定:每個模型均使用其預設值,因為若將請求調整為迎合所有模型,反而無法展現任何一方的優勢。此處的檔案皆已針對網頁重新編碼,因此請評斷其構圖與提示詞遵循度,而非壓縮品質。
只需一行程式碼即可在兩者間切換
以下每個頁籤中都有這兩個 ID — 醒目提示的這兩行是唯一的修改處。相同的端點,相同的金鑰,相同的請求結構。
import time
import requests
BASE = "https://synthorai.io/v1"
HEADERS = {"Authorization": "Bearer sk-syn-..."}
# 1) create the video generation job (POST /v1/videos)
task = requests.post(
f"{BASE}/videos",
headers=HEADERS,
json={
"model": "dreamina-seedance-2-0-260128",
# "model": "sora-2-pro", # 取消註解此行,並註解上一行
"prompt": "a watercolor lighthouse at dawn, waves rolling in, camera pulling back",
"resolution": "720p",
"duration": 5,
},
).json()
# 2) poll the job until it reaches a terminal state
while task["status"] in ("queued", "in_progress"):
time.sleep(5)
task = requests.get(f"{BASE}/videos/{task['id']}", headers=HEADERS).json()
# 3) completed → signed video URL (valid ~24h — download and store it promptly)
if task["status"] == "completed":
print(task["data"][0]["url"])
else:
print(task["error"])const HEADERS = {
Authorization: "Bearer sk-syn-...",
"Content-Type": "application/json",
};
interface VideoTask {
id: string;
status: "queued" | "in_progress" | "completed" | "failed" | "cancelled";
data?: Array<{ url: string }>;
error?: { code: string; message: string };
}
// 1) create the video generation job (POST /v1/videos)
const created = await fetch("https://synthorai.io/v1/videos", {
method: "POST",
headers: HEADERS,
body: JSON.stringify({
model: "dreamina-seedance-2-0-260128",
// model: "sora-2-pro", // 取消註解此行,並註解上一行
prompt: "a watercolor lighthouse at dawn, waves rolling in, camera pulling back",
resolution: "720p",
duration: 5,
}),
});
let task = (await created.json()) as VideoTask;
// 2) poll the job until it reaches a terminal state
while (task.status === "queued" || task.status === "in_progress") {
await new Promise((r) => setTimeout(r, 5000));
const res = await fetch(`https://synthorai.io/v1/videos/${task.id}`, { headers: HEADERS });
task = (await res.json()) as VideoTask;
}
// 3) completed → signed video URL (valid ~24h — download and store it promptly)
if (task.status === "completed") console.log(task.data?.[0]?.url);
else console.error(task.error);# Create the job; "Prefer: wait" holds the request up to 60s and returns the
# completed task when generation finishes in time (else the queued task).
curl https://synthorai.io/v1/videos \
-H "Authorization: Bearer sk-syn-..." \
-H "Content-Type: application/json" \
-H "Prefer: wait=60" \
-d '{
"model": "dreamina-seedance-2-0-260128",
# "model": "sora-2-pro", # 取消註解此行,並註解上一行
"prompt": "a watercolor lighthouse at dawn, waves rolling in, camera pulling back",
"resolution": "720p",
"duration": 5
}'
# Still queued / in_progress? Poll until completed → data[0].url (valid ~24h).
curl https://synthorai.io/v1/videos/vid_9f2e8c1a4b7d \
-H "Authorization: Bearer sk-syn-..."package main
import (
"bytes"
"encoding/json"
"fmt"
"net/http"
"time"
)
const base = "https://synthorai.io/v1"
type videoTask struct {
ID string `json:"id"`
Status string `json:"status"`
Data []struct {
URL string `json:"url"`
} `json:"data"`
}
func call(method, url string, body []byte) (t videoTask) {
req, _ := http.NewRequest(method, url, bytes.NewReader(body))
req.Header.Set("Authorization", "Bearer sk-syn-...")
req.Header.Set("Content-Type", "application/json")
resp, _ := http.DefaultClient.Do(req)
defer resp.Body.Close()
json.NewDecoder(resp.Body).Decode(&t)
return t
}
func main() {
// 1) create the video generation job (POST /v1/videos)
payload, _ := json.Marshal(map[string]any{
"model": "dreamina-seedance-2-0-260128",
// "model": "sora-2-pro", // 取消註解此行,並註解上一行
"prompt": "a watercolor lighthouse at dawn, waves rolling in, camera pulling back",
"resolution": "720p",
"duration": 5,
})
task := call("POST", base+"/videos", payload)
// 2) poll the job until it reaches a terminal state
for task.Status == "queued" || task.Status == "in_progress" {
time.Sleep(5 * time.Second)
task = call("GET", base+"/videos/"+task.ID, nil)
}
// 3) completed → signed video URL (valid ~24h — download and store promptly)
if task.Status == "completed" {
fmt.Println(task.Data[0].URL)
}
}import java.net.URI;
import java.net.http.HttpClient;
import java.net.http.HttpRequest;
import java.net.http.HttpResponse;
// JDK built-in HttpClient — no extra dependency needed.
HttpClient http = HttpClient.newHttpClient();
// 1) create the job; "Prefer: wait=60" holds the request up to 60s and
// returns the completed task when generation finishes in time
HttpRequest create = HttpRequest.newBuilder(URI.create("https://synthorai.io/v1/videos"))
.header("Authorization", "Bearer sk-syn-...")
.header("Content-Type", "application/json")
.header("Prefer", "wait=60")
.POST(HttpRequest.BodyPublishers.ofString("""
{"model": "dreamina-seedance-2-0-260128",
// {"model": "sora-2-pro", // 取消註解此行,並註解上一行
"prompt": "a watercolor lighthouse at dawn, waves rolling in, camera pulling back",
"resolution": "720p", "duration": 5}"""))
.build();
String task = http.send(create, HttpResponse.BodyHandlers.ofString()).body();
System.out.println(task); // {"id":"vid_…","status":…} — completed → data[0].url
// 2) still queued / in_progress? Poll GET https://synthorai.io/v1/videos/{id} until the
// status turns completed, then download data[0].url (valid ~24h).常見問題
Dreamina Seedance 2.0 和 Sora 2 Pro 哪個比較便宜?
兩者的計費單位不同,因此沒有單一絕對的數字:Dreamina Seedance 2.0 和 Sora 2 Pro 在上表中均以各自的單位呈現。請根據您自身的工作負載進行比較 — 本頁頂部的結論說明了實務上的取捨。
我可以在不進行兩次整合的情況下,對 Dreamina Seedance 2.0 和 Sora 2 Pro 進行 A/B 測試嗎?
可以。兩者皆透過同一個相容 OpenAI 的端點提供服務,並使用同一把 API 金鑰 — 切換只需更改一行的模型字串,因此您可以將部分流量分別導向兩者並直接比較帳單。
它們支援哪些片段長度與解析度?
上方的規格表列出了各模型公布的解析度與片段長度,並標示該數值是固定選項還是連續範圍 — 兩者看起來相似,但計費方式不同,因為按秒計費會與長度相乘。