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02
Examples
Real outputs from the public examples of this model on Replicate, with the prompt and settings that produced them. They were not generated live on this page.
Prompt
a dog riding a skateboard
Längd: 0:05
Settings
aspect_ratio
16:9
duration
5
Exempelprompts
Exempel från Railwail-katalogen. De genererades inte live på denna sida.
Nature Scene
Längd: 0:08
Aerial drone shot slowly rising above a misty old-growth forest at dawn, revealing a winding river cutting through the valley below, golden sunlight breaking through clouds
Cinematic Portrait
Längd: 0:05
Close-up of a woman's face as she opens her eyes and looks into the camera, shallow depth of field, soft golden backlight, hair gently moving in the breeze, cinematic 24fps
03
Om Google Veo 2
Kort sagtFrån och med 23 september 2026
Google Veo 2 är en modell av Google DeepMind i kategorin Videogenerering. På Railwail kostar Google Veo 2 0,60 US$ per videosekund. En standardkörning på 8 sekunder kostar 4,80 US$. Bildförhållanden som stöds: 16:9 och 9:16. Möjliga längder: 5, 6, 7 eller 8 s. Nyare version: Google Veo 3.1.
Bakgrund
Om Google DeepMind
Grundat 2010 · London, United Kingdom
Google DeepMind is the merged AI research organisation formed in April 2023 when Google Brain and DeepMind (acquired by Google in 2014) were combined into a single unit led by Demis Hassabis (CEO). DeepMind was founded in 2010 by Hassabis, Shane Legg and Mustafa Suleyman, and is famous for AlphaGo, AlphaFold and the Gemini language-model family. On the video side, DeepMind shipped Imagen Video (2022), Lumiere (2024), Veo (May 2024, Google I/O), Veo 2 (December 2024), Veo 3 with native audio (May 2025) and Veo 3.1 (late 2025). Veo is exposed via Vertex AI, the Gemini API, Google Labs (VideoFX, Whisk) and YouTube's Dream Screen.
Latent video diffusion / Diffusion Transformer hybrid with cascaded super-resolution
Veo 2 is a closed text-to-video and image-to-video model that builds on DeepMind's Imagen and Lumiere research. It uses a spatio-temporal latent diffusion architecture with a transformer-based denoiser conditioned on rich text embeddings from Gemini-family encoders and optional image embeddings. Veo 2 generates clips up to 8 seconds at up to 4K resolution (extended versions reach minutes), with strong understanding of camera language ('dolly', 'aerial', '35mm anamorphic') and real-world physics. DeepMind report substantial gains over Veo 1 on motion realism, prompt adherence and detail. The pipeline combines a base diffusion model with cascaded spatial and temporal super-resolution and an upscaler. Veo 2 was trained on a curated YouTube-and-partner video corpus with synthetic captioning at multiple granularities, and post-trained with reward models for prompt adherence and aesthetic quality.
Parameter
Undisclosed
Funktioner
Text-to-video and image-to-video generation
Up to 8-second clips, up to 4K resolution
Rich cinematographic prompt vocabulary (lenses, lighting, camera moves)
Strong real-world physics and object permanence
Available via Vertex AI, Gemini API, VideoFX and YouTube Dream Screen
SynthID watermarking embedded in every frame
Multilingual prompts via Gemini text encoders
Lower hallucination of artefacts than Veo 1
Best for: high-quality marketing, film previs, broadcast inserts, enterprise creative.
Träning & licens
Curated mix of licensed video, public web video (including YouTube under Google's terms) and synthetic data, with multi-granularity captioning produced by Gemini vision models. Exact dataset size undisclosed.
Licens: Proprietary commercial licence via Google Cloud / Vertex AI and the Gemini API; commercial usage permitted under Google's generative AI terms; SynthID watermark required on all output.
Säkerhetstestning: Subject to Google's responsible AI framework with safety filters, public-figure filters, child-safety classifiers and provenance via SynthID; covered by Google's Responsible AI Progress Reports.
Kända begränsningar
No native audio in Veo 2 (audio first appears in Veo 3)
8-second clip limit per base generation
Closed access with gated waitlist on some surfaces
Strict moderation on people, brands and political content
Limited control over exact frame composition without seed images
curl https://railwail.com/api/v1/videos/generations \
-H "Authorization: Bearer $RAILWAIL_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"model": "google-veo-2",
"prompt": "A slow drone shot over a misty pine forest at sunrise"
}'
# Response: {"job_id": "...", "status": "queued", ...}
# Poll until status is completed, failed or cancelled:
curl https://railwail.com/api/v1/jobs/JOB_ID \
-H "Authorization: Bearer $RAILWAIL_API_KEY"
import os
import time
import requests
API = "https://railwail.com/api/v1"
headers = {"Authorization": f"Bearer {os.environ['RAILWAIL_API_KEY']}"}
job = requests.post(
f"{API}/videos/generations",
headers=headers,
json={
"model": "google-veo-2",
"prompt": "A slow drone shot over a misty pine forest at sunrise",
},
).json()
while True:
status = requests.get(f"{API}/jobs/{job['job_id']}", headers=headers).json()
if status["status"] in ("completed", "failed", "cancelled"):
break
time.sleep(5)
print(status["status"], status.get("output_url"))
const API = "https://railwail.com/api/v1";
const headers = {
Authorization: `Bearer ${process.env.RAILWAIL_API_KEY}`,
"Content-Type": "application/json",
};
const job = await fetch(`${API}/videos/generations`, {
method: "POST",
headers,
body: JSON.stringify({
model: "google-veo-2",
prompt: "A slow drone shot over a misty pine forest at sunrise"
}),
}).then((r) => r.json());
let status;
do {
await new Promise((r) => setTimeout(r, 5000));
status = await fetch(`${API}/jobs/${job.job_id}`, { headers }).then((r) => r.json());
} while (!["completed", "failed", "cancelled"].includes(status.status));
console.log(status.status, status.output_url);
Proprietary commercial licence via Google Cloud / Vertex AI and the Gemini API; commercial usage permitted under Google's generative AI terms; SynthID watermark required on all output.
Kataloginlägg uppdaterat
23 september 2026
Indataparametrar
Inmatningar och inställningar från modellens indataschema. Exemplet i API-avsnittet visar vilka som API:et accepterar.
Google Veo 2 är en modell av Google DeepMind i kategorin Videogenerering. På Railwail kan du anropa den med en API-nyckel via Railwail API.
Vad kostar Google Veo 2 på Railwail?
På Railwail kostar Google Veo 2 0,60 US$ per videosekund. En standardkörning på 8 sekunder kostar 4,80 US$. Priset är känt innan körningen startar. Användningen betalas från förbetald kredit; 1 kredit motsvarar 0,01 US$.
Vilka inställningar stöder Google Veo 2?
Enligt sitt inmatningsschema känner Google Veo 2 till dessa parametrar: prompt, duration (5, 6, 7 eller 8), start_image och aspect_ratio (16:9 eller 9:16).
Hur snabb är Google Veo 2?
Det finns ännu inte tillräckligt många uppmätta körningar av Google Veo 2 på Railwail för att ange en körningstid. Det beror på inmatningen, inställningarna och belastningen hos leverantören.
Är Google Veo 2 bättre än Google Veo 3.1?
Det beror på uppgiften. Google Veo 2 (Google DeepMind) och Google Veo 3.1 (Google DeepMind) är båda modeller i kategorin Videogenerering. Jämförelsesidan visar deras priser och specifikationer sida vid sida.
Skapa en Railwail API-nyckel och skicka din begäran med modell-ID:t google-veo-2. Kodexempel för curl, Python och JavaScript finns i API-avsnittet på denna sida.
Kuaishou's Kling v2.1, generating 5 and 10 second videos at 720p or 1080p from text or an image. Known for cinematic camera work and realistic physical motion, available on Replicate via the official KwaiVGI account.
