Google Veo 3.1 Fast
Faster Veo 3.1 with image-to-video and audio
Google Veo 3.1 Fast is video generation AI model from Google DeepMind, priced at €0.000 per 1M input tokens with a unknown context window.
Image References
Examples
See what Google Veo 3.1 Fast can generate
Rain
"Rain on window with city lights blurred"
Pricing
API Integration
Use our OpenAI-compatible API to integrate Google Veo 3.1 Fast into your application.
npm install railwailimport railwail from "railwail";
const rw = railwail("YOUR_API_KEY");
// Simple — just pass a string
const reply = await rw.run("veo-3-1-fast", "Hello! What can you do?");
console.log(reply);
// With message history
const reply2 = await rw.run("veo-3-1-fast", [
{ role: "system", content: "You are a helpful assistant." },
{ role: "user", content: "Explain quantum computing simply." },
]);
console.log(reply2);
// Full response with usage info
const res = await rw.chat("veo-3-1-fast", [
{ role: "user", content: "Hello!" },
], { temperature: 0.7, max_tokens: 500 });
console.log(res.choices[0].message.content);
console.log(res.usage);Deep dive — Google DeepMind's Google Veo 3.1 Fast
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.
Visit Google DeepMind →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
- Context
- unknown
- 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.
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.
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
Research papers
Frequently asked questions
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