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Home/Models/Google/Veo 3.1
G

Veo 3.1

Per Detik:$0.0625
Veo 3.1 is Google’s incremental-but-significant update to its Veo text-and-image→video family, adding richer native audio, longer and more controllable video outputs, and finer editing and scene-level controls.
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Core features

Veo 3.1 focuses on practical content creation features:

  • Native audio generation (dialogue, ambient sound, SFX) integrated in outputs. Veo 3.1 generates native audio (dialogue + ambience + SFX) aligned to the visual timeline; the model aims to preserve lip sync and audio–visual alignment for dialogue and scene cues.
  • Longer outputs (support for up to ~60 seconds / 1080p versus Veo 3’s very short clips,8s), and multi-prompt multi-shot sequences for narrative continuity.
  • Scene Extension and First/Last Frame modes that extend or interpolate footage between key frames.
  • Object insertion and (coming) object removal and editing primitives inside Flow.

Each bullet above is designed to reduce manual VFX work: audio and scene continuity are now first-class outputs rather than afterthoughts.

Technical details (model behavior & inputs)

Model family & variants: Veo belongs to Google’s Veo-3 family; the preview model ID is typically veo3.1-pro; veo3.1 (CometAPI doc). It accepts text prompts, image references (single frame or sequences), and structured multi-prompt layouts for multi-shot generation.

Resolution & duration: Preview documentation describes outputs at 720p/1080p with options for longer durations (up to ~60s in certain preview settings) and higher fidelity than earlier Veo variants.

Aspect ratios: 16:9 (supported) and 9:16 (supported except in some reference-image flows).

Prompt language: English (preview).

API limits: typical preview limits include max 10 API requests/min per project, max 4 videos per request, and video lengths selectable among 4, 6, or 8 seconds (reference-image flows support 8s).

Benchmark performance

Google’s internal and publicly summarized evaluations report strong preference for Veo 3.1 outputs across human rater comparisons on metrics such as text alignment, visual quality, and audio–visual coherence (text→video and image→video tasks).

Veo 3.1 achieved state-of-the-art results on internal human-rater comparisons across several objective axes — overall preference, prompt alignment (text→video and image→video), visual quality, audio-video alignment, and “visually realistic physics” on benchmark datasets such as MovieGenBench and VBench.

Limitations & safety considerations

Limitations:

  • Artifacts & inconsistency: despite improvements, certain lighting, fine-grained physics, and complex occlusions can still yield artifacts; image→video consistency (especially over long durations) is improved but not perfect.
  • Misinformation / deepfake risk: richer audio + object insertion/removal increases misuse risk (realistic fake audio and extended clips). Google notes mitigations (policy, safeguards) and earlier Veo launches referenced watermarking/SynthID to aid provenance; however technical safeguards do not eliminate misuse risk.
  • Cost & throughput constraints: high-resolution, long videos are computationally expensive and currently gated in a paid preview—expect higher latency and cost compared with image models. Community posts and Google forum threads discuss availability windows and fallback strategies.

Safety controls: Veo3.1 has integrated content policies, watermarking/synthID signaling in earlier Veo releases, and preview access controls; customers are advised to follow platform policy and implement human review for high-risk outputs.

Practical use cases

  • Rapid prototyping for creatives: storyboards → multi-shot clips and animatics with native dialogue for early creative review.
  • Marketing & short form content: 15–60s product spots, social clips, and concept teasers where speed matters more than perfect photorealism.
  • Image→video adaptation: turning illustrations, characters, or two frames into smooth transitions or animated scenes via First/Last Frame and Scene Extension.
  • Tooling augmentation: integrated into Flow for iterative editing (object insertion/removal, lighting presets) that reduces manual VFX passes.

Comparison with other leading models

Veo 3.1 vs Veo 3 (predecessor): Veo 3.1 focuses on improved prompt adherence, audio quality, and multi-shot consistency — incremental but impactful updates aimed at reducing artifacts and improving editability.

Veo 3.1 vs OpenAI Sora 2: tradeoffs reported in press: Veo 3.1 emphasizes longer-form narrative control, integrated audio, and Flow editing integration; Sora 2 (when compared in press) focuses on different strengths (speed, different editing pipelines). TechRadar and other outlets frame Veo 3.1 as Google’s targeted competitor to Sora 2 for narrative and longer video support. Independent side-by-side testing remains limited.

Fitur untuk Veo 3.1

Jelajahi fitur-fitur utama dari Veo 3.1, yang dirancang untuk meningkatkan performa dan kegunaan. Temukan bagaimana kemampuan-kemampuan ini dapat menguntungkan proyek Anda dan meningkatkan pengalaman pengguna.

Harga untuk Veo 3.1

Jelajahi harga kompetitif untuk Veo 3.1, dirancang untuk berbagai anggaran dan kebutuhan penggunaan. Paket fleksibel kami memastikan Anda hanya membayar untuk apa yang Anda gunakan, memudahkan untuk meningkatkan skala seiring berkembangnya kebutuhan Anda. Temukan bagaimana Veo 3.1 dapat meningkatkan proyek Anda sambil menjaga biaya tetap terkendali.
Harga Comet (USD / M Tokens)Harga Resmi (USD / M Tokens)Diskon
Per Detik:$0.0625
Per Detik:$0.078125
-20%

Kode contoh dan API untuk Veo 3.1

Akses kode sampel komprehensif dan sumber daya API untuk Veo 3.1 guna mempermudah proses integrasi Anda. Dokumentasi terperinci kami menyediakan panduan langkah demi langkah, membantu Anda memanfaatkan potensi penuh Veo 3.1 dalam proyek Anda.
Python
JavaScript
Curl
import os
import time
import requests

# Get your CometAPI key from https://api.cometapi.com/console/token, and paste it here
COMETAPI_KEY = os.environ.get("COMETAPI_KEY") or "<YOUR_COMETAPI_KEY>"
BASE_URL = "https://api.cometapi.com/veo/v1/video"

# Create video generation task
create_response = requests.post(
    f"{BASE_URL}/create",
    headers={
        "Authorization": COMETAPI_KEY,
        "Content-Type": "application/json",
    },
    json={
        "prompt": "An orange cat flying in the blue sky with white clouds, sunlight pouring onto its fur, creating a beautiful and dreamlike scene",
        "model": "veo3.1",
        "enhance_prompt": True,
    },
)

task = create_response.json()
task_id = task["id"]
print(f"Task created: {task_id}")
print(f"Status: {task['status']}")

# Poll until video is ready
while True:
    query_response = requests.get(
        f"{BASE_URL}/query/{task_id}",
        headers={
            "Authorization": f"Bearer {COMETAPI_KEY}",
        },
    )

    result = query_response.json()
    status = result["data"]["status"]
    progress = result["data"].get("progress", "")

    print(f"Checking status... {status} {progress}")

    if status == "SUCCESS" or result["data"]["data"]["status"] == "completed":
        video_url = result["data"]["data"]["video_url"]
        print(f"
Video URL: {video_url}")
        break
    elif status == "FAILED":
        print(f"Failed: {result['data'].get('fail_reason', 'Unknown error')}")
        break

    time.sleep(10)

Python Code Example

import os
import time
import requests

# Get your CometAPI key from https://api.cometapi.com/console/token, and paste it here
COMETAPI_KEY = os.environ.get("COMETAPI_KEY") or "<YOUR_COMETAPI_KEY>"
BASE_URL = "https://api.cometapi.com/veo/v1/video"

# Create video generation task
create_response = requests.post(
    f"{BASE_URL}/create",
    headers={
        "Authorization": COMETAPI_KEY,
        "Content-Type": "application/json",
    },
    json={
        "prompt": "An orange cat flying in the blue sky with white clouds, sunlight pouring onto its fur, creating a beautiful and dreamlike scene",
        "model": "veo3.1",
        "enhance_prompt": True,
    },
)

task = create_response.json()
task_id = task["id"]
print(f"Task created: {task_id}")
print(f"Status: {task['status']}")

# Poll until video is ready
while True:
    query_response = requests.get(
        f"{BASE_URL}/query/{task_id}",
        headers={
            "Authorization": f"Bearer {COMETAPI_KEY}",
        },
    )

    result = query_response.json()
    status = result["data"]["status"]
    progress = result["data"].get("progress", "")

    print(f"Checking status... {status} {progress}")

    if status == "SUCCESS" or result["data"]["data"]["status"] == "completed":
        video_url = result["data"]["data"]["video_url"]
        print(f"\nVideo URL: {video_url}")
        break
    elif status == "FAILED":
        print(f"Failed: {result['data'].get('fail_reason', 'Unknown error')}")
        break

    time.sleep(10)

JavaScript Code Example

// Get your CometAPI key from https://api.cometapi.com/console/token, and paste it here
const COMETAPI_KEY = process.env.COMETAPI_KEY || "<YOUR_COMETAPI_KEY>";
const BASE_URL = "https://api.cometapi.com/veo/v1/video";

async function sleep(ms) {
  return new Promise((resolve) => setTimeout(resolve, ms));
}

async function main() {
  // Create video generation task
  const createResponse = await fetch(`${BASE_URL}/create`, {
    method: "POST",
    headers: {
      Authorization: COMETAPI_KEY,
      "Content-Type": "application/json",
    },
    body: JSON.stringify({
      prompt:
        "An orange cat flying in the blue sky with white clouds, sunlight pouring onto its fur, creating a beautiful and dreamlike scene",
      model: "veo3.1",
      enhance_prompt: true,
    }),
  });

  const task = await createResponse.json();
  const taskId = task.id;
  console.log(`Task created: ${taskId}`);
  console.log(`Status: ${task.status}`);

  // Poll until video is ready
  while (true) {
    const queryResponse = await fetch(`${BASE_URL}/query/${taskId}`, {
      headers: {
        Authorization: `Bearer ${COMETAPI_KEY}`,
      },
    });

    const result = await queryResponse.json();
    const status = result.data.status;
    const progress = result.data.progress || "";

    console.log(`Checking status... ${status} ${progress}`);

    if (status === "SUCCESS" || result.data.data.status === "completed") {
      const videoUrl = result.data.data.video_url;
      console.log(`\nVideo URL: ${videoUrl}`);
      break;
    } else if (status === "FAILED") {
      console.log(`Failed: ${result.data.fail_reason || "Unknown error"}`);
      break;
    }

    await sleep(10000);
  }
}

main();

Curl Code Example

#!/bin/bash
# Get your CometAPI key from https://api.cometapi.com/console/token, and paste it here

BASE_URL="https://api.cometapi.com/veo/v1/video"

# Create video generation task
response=$(curl -s -X POST "${BASE_URL}/create" \
  -H "Authorization: $COMETAPI_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "prompt": "An orange cat flying in the blue sky with white clouds, sunlight pouring onto its fur, creating a beautiful and dreamlike scene",
    "model": "veo3.1",
    "enhance_prompt": true
  }')

task_id=$(echo "$response" | jq -r '.id')
status=$(echo "$response" | jq -r '.status')

echo "Task created: ${task_id}"
echo "Status: ${status}"

# Poll until video is ready
while true; do
  query_response=$(curl -s -X GET "${BASE_URL}/query/${task_id}" \
    -H "Authorization: Bearer $COMETAPI_KEY")

  status=$(echo "$query_response" | jq -r '.data.status')
  progress=$(echo "$query_response" | jq -r '.data.progress // ""')
  completed=$(echo "$query_response" | jq -r '.data.data.status')

  echo "Checking status... ${status} ${progress}"

  if [ "$status" = "SUCCESS" ] || [ "$completed" = "completed" ]; then
    video_url=$(echo "$query_response" | jq -r '.data.data.video_url')
    echo ""
    echo "Video URL: ${video_url}"
    break
  elif [ "$status" = "FAILED" ]; then
    fail_reason=$(echo "$query_response" | jq -r '.data.fail_reason // "Unknown error"')
    echo "Failed: ${fail_reason}"
    break
  fi

  sleep 10
done

Versi Veo 3.1

Alasan Veo 3.1 memiliki beberapa _snapshot_ mungkin mencakup faktor-faktor potensial seperti variasi keluaran setelah pembaruan yang memerlukan _snapshot_ lama untuk konsistensi, memberikan masa transisi bagi pengembang untuk beradaptasi dan bermigrasi, serta _snapshot_ berbeda yang sesuai dengan _endpoint_ global atau regional untuk mengoptimalkan pengalaman pengguna. Untuk perbedaan detail antar versi, silakan merujuk ke dokumentasi resmi.
version
veo3.1
veo3.1-pro

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