GenAI PMGemini 3.1 Flash TTS
Google's expressive and steerable text-to-speech model with granular voice controls. It is available through Gemini API, Google AI Studio, and Vertex AI enterprise access.
Key Highlights
- Gemini 3.1 Flash TTS is Google’s expressive, steerable text-to-speech model with granular voice controls.
- The model supports director-style prompting, giving teams more control over tone, pacing, and delivery.
- It is available via the Gemini API and Google AI Studio, with enterprise access through Vertex AI.
- For AI PMs, it makes voice UX a controllable product surface rather than a generic output layer.
Gemini 3.1 Flash TTS
Overview
Gemini 3.1 Flash TTS is Google’s text-to-speech model focused on expressive, steerable voice generation. It is designed to turn text into audio while giving builders granular control over how the speech sounds, including support for director-style prompting and voice profile guidance. The model is available through the Gemini API and Google AI Studio, with enterprise access via Vertex AI.For AI Product Managers, this matters because text-to-speech is moving from a generic output layer to a controllable product surface. Instead of treating voice as a fixed utility, teams can shape tone, pacing, and delivery for specific use cases like assistants, customer support, education, accessibility, and content generation. Gemini 3.1 Flash TTS signals that voice UX can now be product-managed with more precision, making it relevant for differentiation, brand consistency, and multimodal experiences.
Key Developments
- 2026-04-16 — Google released Gemini 3.1 Flash TTS as a text-to-speech model accessible via the Gemini API. Coverage highlighted that it outputs audio files and supports director-style prompting; Simon Willison also experimented with prompts and built a UI showing how voice profile tags and directorial notes can shape generated speech.
- 2026-04-17 — Demis Hassabis publicly unveiled Gemini 3.1 Flash TTS as Google’s most expressive and steerable text-to-speech model, emphasizing granular control over AI-generated voice. It was announced as available in preview via the Gemini API and Google AI Studio, with enterprise access on Vertex AI.
Relevance to AI PMs
- Design more intentional voice experiences — PMs can specify voice behaviors, not just content output, which helps teams tune speech for onboarding flows, conversational agents, summaries, notifications, and accessibility features.
- Prototype and validate audio UX faster — Availability through Google AI Studio and the Gemini API makes it easier to test multiple voice directions quickly, compare prompt patterns, and gather user feedback before committing to production integrations.
- Create differentiated multimodal products — Granular control over speech delivery can become a product lever for brand voice, trust, localization strategy, and domain-specific experiences such as tutoring, healthcare guidance, or enterprise copilots.
Related
- Gemini — Gemini 3.1 Flash TTS sits within Google’s broader Gemini model family and extends it into controllable speech generation.
- Google — Google is the company behind the launch and distribution of the model across its AI platforms.
- Demis Hassabis — Hassabis publicly unveiled the model and framed it around expressiveness and steerability.
- Simon Willison — Willison provided early hands-on coverage, showing practical experimentation with prompts and a UI demo.
- Google AI Studio — One of the primary access points for trying the model in preview.
- Gemini API — The core developer interface for integrating Gemini 3.1 Flash TTS into products and workflows.
- Vertex AI — Google’s enterprise channel for accessing the model in production-oriented environments.
Newsletter Mentions (2)
“#4 𝕏 Demis Hassabis unveiled Gemini 3.1 Flash TTS, Google’s most expressive and steerable text-to-speech model offering granular control over AI-generated voice; it’s available in preview today via the Gemini API and Google AI Studio, with enterprise access on Vertex AI.”
GenAI PM Daily April 17, 2026 GenAI PM Daily 🎧 Listen to this brief 3 min listen Today's top 25 insights for PM Builders, ranked by relevance from Blogs, X, LinkedIn, and YouTube. OpenAI Launches Codex for (Almost) Everything #1 📝 OpenAI News Codex for (almost) everything - OpenAI announces Codex for a wide range of uses, positioning Codex as a versatile product for many tasks. The post highlights product-focused capabilities and availability. #2 𝕏 Mike Krieger directs PMs to Anthropic’s follow-up blog on Claude Opus 4.7, outlining performance boosts, enhanced safety guardrails, and expanded multimodal capabilities. Let us know what you think! Also covered by: @Simon Willison , @LlamaIndex 🦙 , @Cursor , @v0 , @Mike Krieger , @Dharmesh Shah #3 𝕏 Qwen launched the open-source Qwen3.6-35B-A3B, an Apache 2.0–licensed sparse MoE model with 35B total (3B active) parameters. It matches coding performance of models 10× its active size and offers strong multimodal perception, reasoning, and dual thinking modes. #4 𝕏 Demis Hassabis unveiled Gemini 3.1 Flash TTS, Google’s most expressive and steerable text-to-speech model offering granular control over AI-generated voice; it’s available in preview today via the Gemini API and Google AI Studio, with enterprise access on Vertex AI. #5 📝 OpenAI News Introducing GPT-Rosalind for life sciences research - OpenAI introduces GPT-Rosalind, a model tailored for life sciences research to support domain-specific scientific workflows. The announcement emphasizes research applications and potential benefits for scientific discovery. Also covered by: @Kevin Weil #6 in Guillermo Rauch launched Workflow SDK, a framework that brings SQS/Kafka-style durability to AI agent backends—automatically handling LLM downtime, rate limits and database hiccups without the ops complexity and with self-hosting plus multi-environment support. #7 𝕏 Google Research launched YouTube AI Search (YouTube Ask on TV), enabling users to ask complex questions and hold iterative conversations to refine video results; catch the live demo at the Google booth at 10:30 AM #CHI2026. #8 𝕏 Google DeepMind built a bridge between Gemini Robotics ER and Spot’s system, letting the AI use plain English to move the robot, take photos, and grab objects for more complex tasks. #9 𝕏 Teresa Torres highlights Doist’s new Ramble feature in Todoist: a pure-AI voice-to-task pipeline built on Gemini live audio, dynamic tool calls and automated evals, validated through user research in five languages and primed for future multimodal support. #10 in Hannah Stulberg walked through how her team at DoorDash uses a shared GitHub repo called Team OS to centralize customer call summaries, metric definitions, PRDs and research so any coding agent can assist across product, design, analytics and engineering. #11 𝕏 Philipp Schmid built a voice-enabled Telegram bot in ~400 lines of Python using the Gemini Interactions API—leveraging Gemini 3. #12 𝕏 LlamaIndex 🦙 added LiteParse—4.3K+ GitHub stars, zero-cloud parsing at 500 pages/2 s across 50+ formats—to its ecosystem, now powering agents like Claude Code and Cursor. #13 📝 Claude Code Blog Best practices for using Claude Opus 4.7 with Claude Code - Practical guidance for using the Claude Opus 4.7 model inside Claude Code, covering recommended patterns, configuration tips, and usage best practices to optimize developer workflows when coding with Claude. Also covered by: @Simon Willison , @LlamaIndex 🦙 , @Cursor , @v0 , @Mike Krieger , @Dharmesh Shah #14 ▶️ New course! Spec-Driven Development Deeplearning.ai The video announces a free spec-driven development course by Deeplearning.ai and JetBrains, taught by Paul Everitt, covering how to write markdown-based specifications for AI agents to generate code and build the Agent Clinic web application. The course is built in partnership with JetBrains, taught by Developer Advocate Paul Everitt, and available for free enrollment at https://bit.ly/4toWsIY. Spec-driven development begins with a markdown file or long prompt that precisely defines functionality for AI agents to implement, reducing hallucination and context rot. Participants will construct "Agent Clinic," a fully featured web application where AI agents can diagnose and address problems like hallucination and context rot. #15 𝕏 Google Research unveiled Simula, a framework that reframes synthetic data generation as dataset-level mechanism design, using reasoning from first principles to offer fine-grained control over coverage, complexity, and quality. #16 𝕏 Sam Altman announced major Codex improvements, including a macOS computer-use feature that lets the AI leverage all your Mac apps in parallel without disrupting your work. He also highlighted new plugin integrations to broaden its functionality. #17 📝 Simon Willison Qwen3.6-35B-A3B on my laptop drew me a better pelican than Claude Opus 4.7 - A comparison of pelican drawings produced by Qwen3.6-35B-A3B (Alibaba) and Claude Opus 4.7, with Qwen producing a markedly better pelican on the author's local machine. #18 𝕏 OpenAI launched GPT-Rosalind, its Life Sciences model series, as a research preview via ChatGPT, Codex, and the API for qualified partners including Amgen, Moderna, the Allen Institute, and Thermo Fisher Scientific. Also covered by: @Kevin Weil #19 𝕏 Kevin Weil clarifies that the Rosalind bio/drug discovery model’s enterprise and education partnerships strictly exclude their data from any training processes to ensure customer data protection. #20 𝕏 DeepLearning.AI previews AI Dev 26, where Andrew Ng outlines how AI is transforming software engineering workflows, skill sets, and future job roles. #21 𝕏 OpenAI notes that the US drug discovery-to-approval process takes 10–15 years on average. Advanced AI systems can accelerate this by boosting research efficiency, uncovering hidden connections, and helping scientists form stronger hypotheses faster. #22 𝕏 Cursor finds that as AI code generation improves, developers’ roles shift to managing that output—documentation (+62%), architecture (+52%) and...
“Google released Gemini 3.1 Flash TTS, a text-to-speech model accessible via the Gemini API that outputs audio files and supports director-style prompting.”
#10 📝 Simon Willison Gemini 3.1 Flash TTS - Google released Gemini 3.1 Flash TTS, a text-to-speech model accessible via the Gemini API that outputs audio files and supports director-style prompting. Simon experimented with prompts and built a UI to try it out, showing how voice profile tags and directorial notes can shape the generated speech.
Related
Developer and AI commentator known for hands-on experiments with new models and APIs. Here he is associated with Gemini 3.1 Flash TTS.
Google’s AI assistant/app ecosystem. In this newsletter it appears as a Mac desktop version and as the API/model family behind Flash TTS.
Technology company behind Gemini and related AI initiatives. Mentioned here through Jeff Dean's comments on personalized learning.
Google’s AI app-building environment used to prototype and generate software from prompts and sketches. In this newsletter it is highlighted for its doodle-to-code workflow and vibe coding features.
CEO and co-founder of Google DeepMind, mentioned here unveiling Gemini 3.1 Flash TTS and sharing a prompt guide. He is a prominent AI executive relevant to product strategy and model launches.
Google's API for accessing Gemini models, with a billing update noted in the newsletter. Relevant to AI PMs for pricing, onboarding, and product operations.
Google Cloud’s AI platform, mentioned as a distribution and deployment surface for MedGemma 1.5.
Stay updated on Gemini 3.1 Flash TTS
Get curated AI PM insights delivered daily — covering this and 1,000+ other sources.
Subscribe Free