Dreamina Seedance 2.0 vs Veo 3.1
Which one, when — curated verdict, not a benchmark table
Both take text or image input and return 24 fps .mp4 video with native audio and first-frame or first/last-frame guidance, so the real split is reach versus predictability: dreamina-seedance-2-0-260128 (2026-01) spans 480p to 4K with any duration from 4–15 s and 6 aspect ratios, while veo-3.1-generate-001 (2025-10) is fixed to 720p/1080p, 4/6/8 s and 16:9 or 9:16, with up to 2 guide images. Note the two bill in different units — $7 per million output tokens versus $0.2 per second without audio and $0.4 with — so no single conversion is honest; price per clip must be checked against your own shot lengths.
Pricing
| Dreamina Seedance 2.0 | Veo 3.1 | Δ | |
|---|---|---|---|
| Per output second (with audio) | — | $0.4 | — |
| Per output second (silent) | — | $0.2 | — |
| Per 1M video tokens | $7 | — | — |
These two models bill in different units, so no Δ is shown — converting between them would require an assumption we have not measured. Each card is listed in its own unit above.
Capabilities
| Dreamina Seedance 2.0 | Veo 3.1 | |
|---|---|---|
| Native audio | yes | yes |
Specs
| Dreamina Seedance 2.0 | Veo 3.1 | |
|---|---|---|
| Input modalities | text image | text image |
| Output modalities | video | video |
| Released | 2026-01 | 2025-10 |
| Resolution | 480p – 4K (10-bit at 4K) (range) | 720p / 1080p (fixed set) |
| Clip length | 4–15 s (range) | 4 / 6 / 8 s (fixed set) |
| Frame rate | 24 fps | 24 fps |
| Aspect ratios | 6 (incl. 16:9, 9:16, 1:1) |
|
| Input modes |
|
|
| Format | .mp4 | .mp4 |
Specs are transcribed from each vendor’s documentation; a row a vendor does not publish is left out rather than inferred. Full sources: Dreamina Seedance 2.0 · Veo 3.1
One prompt, both models — measured through the gateway
Model returned 1280×720 Length 5s latency 133 s
Model returned 1280×720 Length 8s latency 63 s
One prompt, one request per model, no retries and no cherry-picking — the first result each model returned. Neither size nor duration was pinned: each model used its own default, because a request shaped to fit all of them would flatter none. Files here are re-encoded for the web, so judge composition and prompt adherence, not compression.
Switch between them with one line
Both ids are in every tab below — the highlighted pair of lines is the only edit. Same endpoint, same key, same request shape.
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": "veo-3.1-generate-001", # uncomment this line, comment the one above
"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: "veo-3.1-generate-001", // uncomment this line, comment the one above
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": "veo-3.1-generate-001", # uncomment this line, comment the one above
"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": "veo-3.1-generate-001", // uncomment this line, comment the one above
"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": "veo-3.1-generate-001", // uncomment this line, comment the one above
"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).FAQ
Which is cheaper, Dreamina Seedance 2.0 or Veo 3.1?
They bill in different units, so there is no single honest number: Dreamina Seedance 2.0 and Veo 3.1 each appear in their own unit in the table above. Compare them on your own workload — the practical trade-off is described in the verdict at the top of this page.
Can I A/B test Dreamina Seedance 2.0 against Veo 3.1 without two integrations?
Yes. Both are served through the same OpenAI-compatible endpoint with one API key — switching is a one-line model-string change, so you can route a fraction of traffic to each and compare bills directly.
What clip lengths and resolutions do they support?
The spec table above lists each model’s published resolutions and clip lengths, and marks whether a value is a fixed set of options or a continuous range — the two look alike and price differently, since per-second billing multiplies with length.