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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
Length: 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.
Length: 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
Length: 0:08
Example prompts
Examples from the Railwail catalog. They were not generated live on this page.
Quick
Length: 0:06
Timelapse of flower blooming
03
About Google Veo 3 Fast
TL;DRAs of September 23, 2026
Google Veo 3 Fast is a model by Google DeepMind in the Video generation category. On Railwail, Google Veo 3 Fast costs $0.18 per second of video. Depending on the settings, the price ranges from $0.12/s to $0.18/s. A default run of 4 seconds costs $0.72. Supported aspect ratios: 16:9 and 9:16. Possible lengths: 4, 6, or 8 s. Newer version: Google Veo 3.1 Fast.
Background
About Google DeepMind
Founded 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.
Parameters
Undisclosed
Capabilities
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.
Training & license
Distilled from Veo 3 over the same curated multilingual audio-video corpus, with auxiliary supervision tuned for sampler-step efficiency and audio-video synchronization.
License: Proprietary commercial licence via Google Cloud / Vertex AI and Gemini API; commercial use under Google's generative-AI terms; mandatory SynthID watermarking.
Safety testing: Google Responsible AI framework with safety filters, public-figure filters, child-safety classifiers and provenance via SynthID; same red-team programme as Veo 3.
Known limitations
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.
Catalog entry updated
September 23, 2026
Input parameters
Inputs and settings from the model's input schema. The example in the API section shows which of them the API accepts.
Google Veo 3 Fast is a model by Google DeepMind in the Video generation category. On Railwail you can call it with an API key through the Railwail API.
How much does Google Veo 3 Fast cost on Railwail?
On Railwail, Google Veo 3 Fast costs $0.18 per second of video. Depending on the settings, the price ranges from $0.12/s to $0.18/s. A default run of 4 seconds costs $0.72. The price is known before the run starts. Usage is paid from prepaid credits; 1 credit equals $0.01.
Which settings does Google Veo 3 Fast support?
According to its input schema, Google Veo 3 Fast knows these parameters: prompt, duration (4, 6, or 8), start_image, and aspect_ratio (16:9 or 9:16).
How fast is Google Veo 3 Fast?
There are not enough measured runs of Google Veo 3 Fast on Railwail yet to state a run time. It depends on the input, the settings and the load at the provider.
Is Google Veo 3 Fast better than Google Veo 3.1 Fast?
That depends on the task. Google Veo 3 Fast (Google DeepMind) and Google Veo 3.1 Fast (Google DeepMind) are both models in the Video generation category. The comparison page shows their prices and specifications side by side.
Create a Railwail API key and send your request with the model ID veo-3-fast. Code examples for curl, Python and JavaScript are in the API section of this page.
