For accounts without a purchase: runs above 2 credits need a top-up.
New here?
10 free credits (US$0.10) when you sign up with Google
Usable 24 hours after sign-up, up to 5 runs per day and at most 2 credits per run. Other sign-in methods start without credits.
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
Overlapping geometric shapes, pulsing to upbeat electronic music with SFX of shifting patterns
Length: 0:08
Settings
aspect_ratio
16:9
resolution
720p
duration
8
Input
Prompt
the seed slowly starts to spin, faster and faster as it morphs into a whole watermelon
Length: 0:08
Settings
aspect_ratio
16:9
resolution
720p
duration
8
Prompt
a cat steals a fish from a supermarket and escapes
Length: 0:08
Settings
aspect_ratio
16:9
resolution
720p
duration
8
Example prompts
Examples from the Railwail catalog. They were not generated live on this page.
Rain
Length: 0:04
Rain on window with city lights blurred
03
About Google Veo 3.1 Fast
TL;DRAs of 23 September 2026
Google Veo 3.1 Fast is a model by Google DeepMind in the Video generation category. On Railwail, Google Veo 3.1 Fast costs US$0.18 per second of video. Depending on the settings, the price ranges from US$0.12/s to US$0.18/s. A default run of 4 seconds costs US$0.72. Supported aspect ratios: 16:9 and 9:16. Possible lengths: 4, 6 or 8 s.
Background
About Google DeepMind
Founded 2010 · London, United Kingdom
Google DeepMind, formed in 2023 from Google Brain and DeepMind under Demis Hassabis, runs the Veo video-generation programme. Veo 3.1 Fast is the speed and cost tier of Veo 3.1, designed for high-volume creative iteration on Vertex AI, the Gemini API and consumer surfaces like VideoFX and YouTube Dream Screen. Like Veo 3 Fast before it, the Fast variant trades a small amount of fidelity for substantially faster generation and lower per-clip pricing, while keeping the joint audio-video diffusion stack and SynthID provenance from the full Veo 3.1.
Distilled latent video diffusion / DiT speed tier with joint audio-video diffusion
Veo 3.1 Fast is a distilled, low-step variant of Veo 3.1 that uses consistency-style sampler distillation and quantization to compress the diffusion process into far fewer denoising steps. The architecture is identical to Veo 3.1 -- a latent video diffusion model with a transformer denoiser plus a coupled audio diffusion module -- but parameters are tuned and the sampler shortened for substantially faster inference. Generation produces up to 8-second 1080p clips with synchronized audio (music, ambient sound, dialogue with lip-sync) at noticeably lower cost than the full Veo 3.1. Conditioning uses Gemini-family text encoders plus optional image and reference-frame inputs. Training is partly a distillation of Veo 3.1 with auxiliary supervision to preserve audio-video sync and prompt adherence under the shortened sampler.
Parameters
Undisclosed
Capabilities
Speed-tier Veo 3.1 with native synchronized audio retained
Up to 8-second 1080p clips at substantially lower latency and cost
Text-to-video and image-to-video
Reference-frame conditioning for consistency
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
Best for: high-volume creative iteration, ad A/B testing, social shorts with audio.
Training & license
Distilled from Veo 3.1 over the same curated multilingual audio-video corpus; 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 watermark.
Safety testing: Google Responsible AI framework with the same filters as Veo 3.1; SynthID-based provenance on all outputs.
Known limitations
Slight quality regression vs full Veo 3.1 on fine detail and complex audio
8-second clip limit
Audio short-form and English-leaning
Closed model with no 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-3-1-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-3-1-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-3-1-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 watermark.
Catalog entry updated
23 September 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 3.1 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 3.1 Fast cost on Railwail?
On Railwail, Google Veo 3.1 Fast costs US$0.18 per second of video. Depending on the settings, the price ranges from US$0.12/s to US$0.18/s. A default run of 4 seconds costs US$0.72. The price is known before the run starts. Usage is paid from prepaid credits; 1 credit equals US$0.01.
Which settings does Google Veo 3.1 Fast support?
According to its input schema, Google Veo 3.1 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 3.1 Fast?
There are not enough measured runs of Google Veo 3.1 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 3.1 Fast better than Google Veo 3.1?
That depends on the task. Google Veo 3.1 Fast (Google DeepMind) and Google Veo 3.1 (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-3-1-fast. Code examples for curl, Python and JavaScript are in the API section of this page.
