Google: Veo 3.1 Fast
google/veo-3.1-fast
Access Veo 3.1 Fast AI video generation using Puter.js API.
Get Started
Model Card
Veo 3.1 Fast is the speed-optimized variant of Google DeepMind's Veo 3.1 video model, generating output roughly twice as fast as the standard version with only a minor quality trade-off. Independent testing shows quality differences of 1–8% depending on scene complexity — negligible for most use cases.
It retains the full feature set of the standard model: native audio generation, text-to-video, image-to-video, reference images, frame-to-frame generation, and support for 720p, 1080p, and 4K resolutions. An 8-second 720p clip typically completes in 30–45 seconds.
At roughly one-fifth the per-second cost of the standard model, Veo 3.1 Fast is well suited for rapid prototyping, iterative prompt testing, and production workflows where turnaround time and budget matter more than maximum fidelity.
Max Duration 8s
seconds
Frame Rate N/A
fps
Aspect Ratio 16:9, 9:16
supported
Release Date Oct 15, 2025
Code Example
Use Veo 3.1 Fast in your app with the Puter.js AI API — no API keys or setup required.
// npm install @heyputer/puter.js
import { puter } from '@heyputer/puter.js';
puter.ai.txt2vid("A cat playing with a ball of yarn", {
model: "google/veo-3.1-fast"
}).then(video => {
document.body.appendChild(video);
});
<html>
<body>
<script src="https://js.puter.com/v2/"></script>
<script>
puter.ai.txt2vid("A cat playing with a ball of yarn", {
model: "google/veo-3.1-fast"
}).then(video => {
document.body.appendChild(video);
});
</script>
</body>
</html>
More AI Models From Google
Gemini 3.1 Flash Lite Image
Gemini 3.1 Flash Lite Image is Google DeepMind's fastest and lowest-cost image generation and editing model in the Gemini 3.1 family, also known as Nano Banana 2 Lite. It generates a 1K-resolution image in about 4 seconds, roughly 2.7x faster than Gemini 3.1 Flash Image, at $0.0336 per image. It keeps the character consistency, precise natural-language editing, and real-world knowledge of the Nano Banana family while trading some peak quality for speed. It supports text-to-image generation, image editing, and multi-image composition through the same API used by other Gemini image models, with a discrete set of 14 aspect ratios at 1K resolution. It's built for high-volume, latency-sensitive use cases such as rapid prototyping, interactive applications, and batch image generation, where cost and turnaround time matter more than maximum fidelity.
ChatGemini 3.5 Flash
Gemini 3.5 Flash is Google DeepMind's frontier-speed model that combines Flash-tier latency and cost with near-Pro-level reasoning, announced at Google I/O 2026. It processes output 4x faster than comparable frontier models while outperforming Gemini 3.1 Pro on coding and agentic benchmarks — 76.2% on Terminal-Bench 2.1, 83.6% on MCP Atlas, and 84.2% on CharXiv Reasoning. It's purpose-built for agentic workflows: orchestrating multi-step tool use, long-context document analysis, and iterative code generation. With a 1M token context window and full multimodal input support (text, image, audio, video, PDF), it handles complex real-world tasks at scale. At $1.50 per million input tokens and $9.00 per million output tokens, it's the best choice for developers who need frontier intelligence without frontier latency or cost.
ChatGemma 4 26B A4B
Gemma 4 26B A4B is a Mixture-of-Experts (MoE) open model from Google DeepMind, built from the same research as Gemini 3. It has 26B total parameters but activates only 3.8B per forward pass, delivering near-31B-dense quality at a fraction of the compute cost. The model supports a 256K token context window, multimodal image and text input, built-in step-by-step reasoning (thinking mode), and native function calling for agentic workflows. It currently ranks #6 among open models on the Arena AI text leaderboard with an estimated LMArena score of 1441 — competitive with models many times its active size. It excels at reasoning, coding, long-context tasks, and structured tool use. It's a strong pick for developers who need high throughput and low latency without sacrificing capability.
Frequently Asked Questions
You can access Veo 3.1 Fast by Google through Puter.js AI API. Include the library in your web app or Node.js project and start making calls with just a few lines of JavaScript — no backend and no configuration required.
Yes, it is free if you're using it through Puter.js. With the User-Pays Model, you can add Veo 3.1 Fast to your app at no cost — your users pay for their own AI usage directly, making it completely free for you as a developer.
Veo 3.1 Fast was created by Google and released on Oct 15, 2025.
Yes — the Veo 3.1 Fast API works with any JavaScript framework, Node.js, or plain HTML through Puter.js. Just include the library and start building. See the documentation for more details.
Get started with Puter.js
Add Veo 3.1 Fast video generation to your app without worrying about API keys or setup.
Read the Docs View Tutorials