Google Unveils Gemini 3.1 Flash-TTS: The Next Generation of Expressive AI Speech

Google has officially introduced Gemini 3.1 Flash-TTS, its latest and most advanced text-to-speech model. Designed for high-fidelity audio generation, the model focuses on providing developers and enterprises with unprecedented levels of controllability and expressiveness across more than 70 languages.

Audio Tags: The "Director's Chair" for Speech

The standout feature of Gemini 3.1 Flash-TTS is the introduction of audio tags. These are natural language commands embedded directly into the text input that allow users to steer the AI's delivery with granular precision.

Dynamic Style & Pacing: Use tags to adjust vocal style, tone, and delivery speed mid-sentence.
Scene Direction: Developers can set "Director's Notes" to world-build context, ensuring characters stay in character and react naturally during multi-speaker dialogues.
Speaker Specificity: Cast distinct characters using unique Audio Profiles and toggle accents or expressions for a more immersive experience.

Industry-Leading Performance

According to the Artificial Analysis TTS leaderboard, Gemini 3.1 Flash-TTS achieved an impressive Elo score of 1,211, placing it among the most natural-sounding models available. It is positioned in the "most attractive quadrant" of the market due to its high-quality output paired with low operational costs.

Enterprise and Developer Access

Gemini API & Google AI Studio: Currently available in preview for developers to experiment with voices and export configurations.
Vertex AI: Available in preview for enterprises looking to integrate expressive speech into applications.
Google Workspace: Integrated into Google Vids to help users create engaging video content with professional voiceovers.

Safety and Watermarking

To help prevent misinformation and clearly identify AI-generated content, every audio output from Gemini 3.1 Flash-TTS is imperceptibly watermarked with SynthID. This technology is woven directly into the audio data, allowing for reliable detection of AI speech without affecting the listening quality.

This model provides a powerful new toolset for building everything from accessible reading apps to immersive, multi-character gaming experiences and localized voice assistants.