Veo 3.1
Google's Veo 3.1 video generation model, the stable production release succeeding the preview version for high-quality AI video creation.
Google's stable production video generation model
Veo 3.1 is Google's generally available video generation model, released under the identifier veo-3.1-generate-001 and accessible through Google's Vertex AI platform. It is the production-ready successor to the veo-3.1-generate-preview endpoint, making it the recommended migration target for developers who built on the preview version. The model generates video content from text prompts and supports image-based inputs, enabling a range of media creation workflows. It is part of Google's broader Veo model family, which includes multiple generation variants.
Veo 3.1 is designed for developers and businesses that need a reliable, supported API for AI video generation at scale. Its stable endpoint status means it carries production-grade support commitments, distinguishing it from preview or experimental releases. The model accepts text prompts, individual image URLs, and image arrays as inputs, and supports a seed parameter for reproducible outputs. It is well suited for applications such as marketing content pipelines, automated media production, and any workflow requiring consistent, repeatable video generation.
What Veo 3.1 supports
Text-to-Video Generation
Generates video content from natural language text prompts, supporting up to a 5000-token context window for detailed scene descriptions.
Image-to-Video
Accepts one or more image URLs as input to animate or extend still images into video sequences.
Multi-Image Input
Supports an array of image URLs as input, allowing multiple reference images to inform a single video generation request.
Reproducible Outputs
Accepts a seed parameter so developers can reproduce the same video output from identical inputs, useful for testing and iterative workflows.
Configurable Generation Options
Exposes multiple toggle groups and select controls, enabling configuration of generation parameters such as aspect ratio, duration, and resolution.
Stable Production API
Available as a generally available endpoint (veo-3.1-generate-001) on Vertex AI, providing production-grade support and stability for deployment at scale.
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Get Started FreeCommon questions about Veo 3.1
What is the context window for Veo 3.1?
Veo 3.1 supports a context window of 5000 tokens, which applies to the text prompt input for video generation requests.
What is the difference between veo-3.1-generate-001 and the preview version?
The veo-3.1-generate-001 endpoint is the stable, generally available release, while veo-3.1-generate-preview was an earlier experimental endpoint. Google designates veo-3.1-generate-001 as the recommended migration target for production use.
What input types does Veo 3.1 accept?
Veo 3.1 accepts text prompts, individual image URLs, and arrays of image URLs. It also supports a seed value for reproducible outputs and several configurable toggle and select parameters.
Where is Veo 3.1 hosted and how is it accessed?
Veo 3.1 is available through Google's Vertex AI platform. It is also accessible via unified AI SDKs and gateways, including Vercel's AI Gateway.
What is the training data cutoff for Veo 3.1?
According to the available metadata, Veo 3.1 has a training date of July 2025.
What people think about Veo 3.1
Community discussion around Veo 3.1 is limited but positive, with a well-received Reddit post in r/midjourney showcasing it alongside Midjourney and Runway in an animated short that earned over 1,300 upvotes. Users in that thread responded favorably to the visual quality of the AI-generated animation.
The thread focused primarily on the creative workflow of combining multiple AI tools rather than on Veo 3.1 in isolation, making it difficult to draw specific conclusions about the model's perceived strengths or limitations from community feedback alone.
Parameters & options
Optional URL of an input image to animate.
Optional URL of the last frame of the video.
Provide up to 10 references images of the scene, subject, objects, or anything else in the image.
Description of what to exclude from an image.
A specific value that is used to guide the 'randomness' of the generation.
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