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What is Gemini 3.8 Flash-Lite TTS?

Gemini 3.8 Flash-Lite TTS is Google’s efficiency-focused text-to-speech model for generating expressive audio at high volume. It is positioned for applications where scalability and cost efficiency are important, including dubbing, localization, automated content production, and conversational voice systems. The model gives users detailed control over speech characteristics such as tone, pacing, delivery, and expressive nuance. Creators and developers can direct individual lines using script instructions to produce performances ranging from straightforward narration to more expressive dialogue. Long-form generation is designed to maintain natural pacing, audio quality, and stable speaker characteristics over extended recordings such as podcasts and other continuous content. Gemini 3.8 Flash-Lite TTS also supports native two-speaker scene staging, allowing a single script to generate structured conversations with distinct speakers and natural turn-taking. Nonverbal performance cues including laughs, sighs, gasps, and conversational backchanneling can be incorporated to add realistic texture to generated speech. With support for more than 100 languages, the model can be used to create multilingual audio experiences and localized content for audiences across different regions. Google reports that Gemini 3.8 Flash-Lite TTS performs strongly in human preference evaluations across languages including Japanese, Brazilian Portuguese, Vietnamese, Modern Standard Arabic, Mexican Spanish, and Hindi. Generated audio from Gemini Audio models includes SynthID watermarking, providing an imperceptible signal that can help identify AI-generated speech. Gemini 3.8 Flash-Lite TTS is available through Google AI Studio and the Gemini API, is integrated into Google Vids, and is planned for enterprise API access through Gemini Enterprise.

What is Gemini 2.0 Flash-Lite?

Gemini 2.0 Flash-Lite is the latest AI model introduced by Google DeepMind, crafted to provide a cost-effective solution while upholding exceptional performance benchmarks. As the most economical choice within the Gemini 2.0 lineup, Flash-Lite is tailored for developers and businesses seeking effective AI functionalities without incurring significant expenses. This model supports multimodal inputs and features a remarkable context window of one million tokens, greatly enhancing its adaptability for a wide range of applications. Presently, Flash-Lite is available in public preview, allowing users to explore its functionalities to advance their AI-driven projects. This launch not only highlights cutting-edge technology but also invites user feedback to further enhance and polish its features, fostering a collaborative approach to development. With the ongoing feedback process, the model aims to evolve continuously to meet diverse user needs.

Media

Media

Integrations Supported

Gemini
Gemini Enterprise
Gemini Enterprise Agent Platform
Google AI Studio
Gemini 3.1 Pro
Gemini Notebook
Google Vids

Integrations Supported

Gemini
Gemini Enterprise
Gemini Enterprise Agent Platform
Google AI Studio
C++
Clojure
Elixir
F#
JavaScript
Kotlin
Ruby
Rust
SQL
Scala
TypeScript
Visual Basic
distil labs

API Availability

Has API

API Availability

Pricing Information

Pricing not provided

Pricing Information

Pricing not provided

Supported Platforms

SaaS

Supported Platforms

SaaS
Android
iPhone
iPad

Customer Service / Support

Web-Based Support

Customer Service / Support

Web-Based Support

Training Options

Documentation Hub

Training Options

Documentation Hub

Company Facts

Organization Name

Google

Date Founded

1998

Company Location

United States

Company Website

google.com

Company Facts

Organization Name

Google

Date Founded

1998

Company Location

United States

Company Website

deepmind.google/technologies/gemini/flash-lite/

Categories and Features

AI Models

Not specified

AI Voice Models

Not specified

Text to Speech

Not specified

Categories and Features

AI Models

Not specified

AI Reasoning Models

Not specified

Foundation Models

Not specified

Large Language Models

Not specified

Multimodal Models

Not specified

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