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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.
Input
Prompt
Rotate the shoe, keep everything else still
Lengde: 0:08
Settings
resolution
720p
Prompt
A hyper-speed superhero, resembling The Flash, is sprinting through a dense, dark forest at night. The trees blur into streaks of green and black as he moves. Fiery trails burst behind him with every stride, igniting parts of the underbrush in glowing embers. As he weaves between the trees, the blazing trail he leaves behind slowly forms the words 'VEO 3 FAST' in glowing, molten fire on the forest floor. The camera zooms up to show the entire text.
Lengde: 0:08
Prompt
A lion running fast through the savannah, dolly zoom into its face
The lion says in a deep voice: Veo 3 Fast is now on Replicate
Lengde: 0:08
Eksempelprompts
Eksempler fra Railwail-katalogen. De ble ikke generert live på denne siden.
Quick
Lengde: 0:06
Timelapse of flower blooming
03
Om Google Veo 3 Fast
Kort sagtPer 23. september 2026
Google Veo 3 Fast er en modell fra Google DeepMind i kategorien Videogenerering. På Railwail koster Google Veo 3 Fast 0,18 USD per videosekund. Avhengig av innstillingene varierer prisen fra 0,12 USD/s til 0,18 USD/s. En standardkjøring på 4 sekunder koster 0,72 USD. Støttede bildeformat: 16:9 og 9:16. Mulige lengder: 4, 6 eller 8 s. Nyere versjon: Google Veo 3.1 Fast.
Bakgrunn
Om Google DeepMind
Grunnlagt 2010 · London, United Kingdom
Google DeepMind is the merged AI research organisation formed in April 2023 from Google Brain and DeepMind under Demis Hassabis. The Veo video-generation programme delivered Veo 1 (May 2024), Veo 2 (December 2024) and Veo 3 (May 2025), the first major commercial video model with natively generated synchronized audio. Veo 3 Fast was launched alongside Veo 3 as the speed and cost tier: a distilled, low-step variant designed for high-volume creative iteration on Vertex AI, the Gemini API and consumer surfaces such as VideoFX and YouTube Dream Screen. It became the most widely-used Veo variant for high-throughput workflows because the cost difference versus full Veo 3 is significant while quality remains broadly cinematic.
Distilled latent video diffusion / DiT speed tier with joint audio-video diffusion
Veo 3 Fast is the distilled speed-tier variant of Veo 3. Like Veo 3 it is a latent video diffusion model with a transformer-based denoiser plus a coupled audio diffusion module that produces synchronized music, ambient sound and dialogue with lip-sync. Fast is produced via consistency-style sampler distillation and quantization, compressing the diffusion sampler into far fewer denoising steps while preserving most of Veo 3's prompt adherence, motion physics and audio-video sync. Conditioning uses Gemini-family text encoders and optional image embeddings. Native generation produces up to 8-second clips at 1080p with synchronized audio, at noticeably lower latency and per-clip cost than full Veo 3. Training is partly a distillation of Veo 3 over the same curated multilingual audio-video corpus, with auxiliary supervision tuned for sampler-step efficiency.
Parametere
Undisclosed
Evner
Speed-tier Veo 3 with native synchronized audio retained
Up to 8-second 1080p clips at substantially lower cost
Text-to-video and image-to-video
Rich cinematographic prompt vocabulary
Multilingual prompts via Gemini text encoders
Available via Vertex AI, Gemini API, VideoFX, Whisk and YouTube Dream Screen
SynthID audio + visual watermarking
Materially lower latency than full Veo 3
Best for: high-volume creative iteration, ad A/B testing, social shorts with sound.
Trening og lisens
Distilled from Veo 3 over the same curated multilingual audio-video corpus, with auxiliary supervision tuned for sampler-step efficiency and audio-video synchronization.
Lisens: Proprietary commercial licence via Google Cloud / Vertex AI and Gemini API; commercial use under Google's generative-AI terms; mandatory SynthID watermarking.
Sikkerhetstesting: Google Responsible AI framework with safety filters, public-figure filters, child-safety classifiers and provenance via SynthID; same red-team programme as Veo 3.
Kjente begrensninger
Slight quality regression vs full Veo 3 on fine detail
8-second native clip limit
Audio short-form and English-leaning
Closed model without peer-reviewed paper
Strict moderation on people, brands and political content
curl https://railwail.com/api/v1/videos/generations \
-H "Authorization: Bearer $RAILWAIL_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"model": "veo-3-fast",
"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": "veo-3-fast",
"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: "veo-3-fast",
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 Gemini API; commercial use under Google's generative-AI terms; mandatory SynthID watermarking.
Katalogoppføring oppdatert
23. september 2026
Inndataparametere
Inndataer og innstillinger fra modellens inndataskjema. Eksemplet i API-delen viser hvilke av dem APIen godtar.
Google Veo 3 Fast er en modell fra Google DeepMind i kategorien Videogenerering. På Railwail kan du kalle den med en API-nøkkel gjennom Railwail API.
Hvor mye koster Google Veo 3 Fast på Railwail?
På Railwail koster Google Veo 3 Fast 0,18 USD per videosekund. Avhengig av innstillingene varierer prisen fra 0,12 USD/s til 0,18 USD/s. En standardkjøring på 4 sekunder koster 0,72 USD. Prisen er kjent før kjøringen starter. Bruk betales fra forhåndskjøpte kreditter; 1 kreditt tilsvarer 0,01 USD.
Hvilke innstillinger støtter Google Veo 3 Fast?
I henhold til inndataskjemaet kjenner Google Veo 3 Fast disse parametrene: prompt, duration (4, 6 eller 8), start_image og aspect_ratio (16:9 eller 9:16).
Hvor rask er Google Veo 3 Fast?
Det finnes ennå ikke nok målte kjøringer av Google Veo 3 Fast på Railwail til å angi en kjøretid. Det avhenger av inndataene, innstillingene og belastningen hos leverandøren.
Er Google Veo 3 Fast bedre enn Google Veo 3.1 Fast?
Det avhenger av oppgaven. Google Veo 3 Fast (Google DeepMind) og Google Veo 3.1 Fast (Google DeepMind) er begge modeller i kategorien Videogenerering. Sammenligningssiden viser prisene og spesifikasjonene deres side ved side.
Hvordan bruker jeg Google Veo 3 Fast gjennom API-en?
Opprett en Railwail API-nøkkel og send forespørselen din med modell-ID-en veo-3-fast. Kodeeksempler for curl, Python og JavaScript finnes i API-delen av denne siden.
