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Google Veo 3.1 Lite Launch: How to Use It in Gemini API and AI Studio

Google announced Veo 3.1 Lite on March 31, 2026 as a lower-cost video generation model for developers. It supports Text-to-Video and Image-to-Video with multiple aspect ratios, resolutions, and short-duration controls for production-style iteration.

If you are deciding whether Veo 3.1 Lite is practical for your pipeline, this guide breaks down what actually launched, why pricing matters, and how to compare model behavior inside ChatBoost.

What launched

Google added Veo 3.1 Lite as a new option in the Veo 3.1 family, positioned for teams that need larger output volume without paying premium-tier cost on every generation. The launch focuses on practical throughput rather than headline-only quality claims.

According to the official announcement, the model is rolling out through the paid Gemini API tier and is available for testing in Google AI Studio. Feature-wise, Veo 3.1 Lite supports Text-to-Video and Image-to-Video, 16:9 and 9:16 framing, 720p and 1080p resolution, plus 4s/6s/8s duration controls.

Why it matters

The core search intent around this launch is straightforward: can developers cut cost while keeping enough quality and speed for real shipping workflows? Veo 3.1 Lite directly targets that question, which makes it more relevant than a generic model announcement.

Google also stated that Veo 3.1 Fast pricing will be reduced on April 7, 2026. In practice, that gives product teams a cleaner two-tier strategy: use Lite for broader experimentation and reserve Fast for higher-stakes outputs where quality margins matter most.

Where ChatBoost fits

Most users do not fail at discovering new models; they fail at comparing them consistently. ChatBoost helps by keeping prompts, test history, and cross-model evaluation in one mobile workflow, so launch news can be turned into repeatable decision-making.

A practical approach is to create a fixed prompt set, run variants across your preferred models, and log style consistency, instruction adherence, and iteration speed in ChatBoost. That converts trend traffic into a usable model selection process instead of one-off experimentation.

Try it in ChatBoost

Try the workflow in ChatBoost

If you want to compare new AI models on mobile without changing apps, ChatBoost lets you switch providers, keep local history, and test new workflows in one place.

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