Sora 2 vs Sora 2 Pro
什麼情況選哪一個
sora-2-pro 每輸出秒貴 3 倍($0.3 對 $0.1),換來的是一檔解析度:720p 或 1024p,對比只有 720p。其餘完全一致——4–12 秒、24 fps、16:9 和 9:16、原生音訊,以及單張參考圖的圖生視訊。除非交付格式需要更高的畫幅,否則選 sora-2。
Benchmark 成績
Sora 2:供應商沒有公布 benchmark 成績。
Sora 2 Pro:公布了 6 項,但每一項都沒有夠多其他模型的成績,無法比較。
供應商公布: ByteDance
定價
| Sora 2 | Sora 2 Pro | Δ | |
|---|---|---|---|
| 每秒輸出(含音訊) | $0.1 | $0.3 | 0.33× |
費率取自網站建置時的即時目錄;各模型頁面都列有最新的價目。
兩者的相對位置:每秒輸出的價格,涵蓋同一計費單位下全部 7 個影片生成模型(對數尺度)
功能
| Sora 2 | Sora 2 Pro | |
|---|---|---|
| 原生音訊 | 是 | 是 |
規格
| Sora 2 | Sora 2 Pro | |
|---|---|---|
| 輸入模態 | 文字 圖像 | 文字 圖像 |
| 輸出模態 | 影片 | 影片 |
| 發布日期 | 2025-09 | 2025-09 |
| 解析度 | 720p | 720p / 1024p (固定選項) |
| 影片長度 | 4-12 s (範圍) | 4-12 s (範圍) |
| 影格率 | 24 fps | 24 fps |
| 長寬比 |
|
|
| 輸入方式 |
|
|
| 格式 | .mp4 | .mp4 |
規格摘錄自各供應商的文件;供應商沒有公布的項目就直接略過,不自行推測。 完整來源: Sora 2 · Sora 2 Pro
同一段提示詞,兩個模型,經閘道實測
模型回傳 720×1280 長度 4s 延遲 68 s
模型回傳 1280×720 長度 4s 延遲 130 s
同一段提示詞,每個模型只送一次請求,不重試,也不挑比較好的結果,看到的就是各模型回傳的第一個結果。尺寸和長度都沒有指定,各模型用的是自己的預設值;如果硬把請求調成每個模型都適用的規格,反而誰的長處都看不出來。這裡的檔案都為了網頁重新編碼過,所以請看構圖和有沒有照提示詞做,不要拿來評斷壓縮品質。
改一行程式碼就能在兩者之間切換
下面每個頁籤都列了這兩個模型 ID,要改的只有醒目標示的那兩行。端點、金鑰和請求格式都不變。
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": "sora-2",
# "model": "sora-2-pro", # 取消這一行的註解,並把上一行註解掉
"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: "sora-2",
// model: "sora-2-pro", // 取消這一行的註解,並把上一行註解掉
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": "sora-2",
# "model": "sora-2-pro", # 取消這一行的註解,並把上一行註解掉
"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": "sora-2",
// "model": "sora-2-pro", // 取消這一行的註解,並把上一行註解掉
"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": "sora-2",
// {"model": "sora-2-pro", // 取消這一行的註解,並把上一行註解掉
"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
Sora 2 和 Sora 2 Pro 哪個比較便宜?
以「每秒輸出(含音訊)」來看,Sora 2 比較便宜($0.1 對 $0.3,相差 3.0×)。其他項目的結果可能相反,完整價目請看上表;實際成本要看你的用量組合。
可以只串接一次,就對 Sora 2 和 Sora 2 Pro 做 A/B 測試嗎?
可以。兩個模型都走同一個 OpenAI 相容端點,用的也是同一把 API 金鑰,切換時只要改一行裡的模型名稱字串。你可以把一部分流量分別導到兩邊,再直接比較帳單。
它們支援哪些影片長度與解析度?
上方的規格表列出各模型公布的解析度與影片長度,並標明數值是固定選項還是連續範圍。兩種看起來很像,費用算起來卻不一樣,因為按秒計費時,金額會隨長度等比增加。