GenAI PMGemini 3.1 Flash TTS
A Google AI text-to-speech model with native multi-speaker dialogue support across many languages. It is positioned as part of the Gemini product family.
Key Highlights
- Gemini 3.1 Flash TTS is Google AI’s steerable text-to-speech model in the Gemini family.
- The model supports native multi-speaker dialogue and 70+ languages, expanding its use for conversational products.
- Google positioned it as its most expressive and controllable TTS model, with director-style prompting and granular voice control.
- It is available via the Gemini API and Google AI Studio, with enterprise access through Vertex AI.
- For AI PMs, it is especially relevant for branded voice experiences, multilingual launches, and more realistic voice UX prototyping.
Gemini 3.1 Flash TTS
Overview
Gemini 3.1 Flash TTS is Google AI’s text-to-speech model in the Gemini family, designed to generate expressive spoken audio from text with fine-grained controllability. It has been positioned as Google’s most steerable TTS offering, with support for director-style prompting, voice-shaping instructions, audio file output, and native multi-speaker dialogue generation across 70+ languages. Availability was announced through the Gemini API and Google AI Studio, with enterprise access via Vertex AI.For AI Product Managers, this matters because it pushes TTS from a generic voice layer into a product surface that can be designed, tuned, and differentiated. Instead of treating speech as a simple output format, teams can use Gemini 3.1 Flash TTS to prototype branded voices, conversational agents with multiple speakers, onboarding flows, accessibility features, narrated content, and multilingual customer experiences. Its placement inside the broader Gemini ecosystem also makes it relevant for teams already building on Google’s model stack.
Key Developments
- 2026-04-16: Google released Gemini 3.1 Flash TTS as a text-to-speech model accessible via the Gemini API. Early coverage highlighted that it outputs audio files and supports director-style prompting. Simon Willison experimented with the model and showed how voice profile tags and directorial notes could shape generated speech.
- 2026-04-17: Demis Hassabis unveiled Gemini 3.1 Flash TTS as Google’s most expressive and steerable text-to-speech model. The announcement emphasized granular control over AI-generated voice and preview availability via the Gemini API and Google AI Studio, with enterprise access on Vertex AI.
- 2026-04-18: Google AI highlighted Gemini 3.1 Flash TTS as shipping with native multi-speaker dialogue support in 70+ languages. This positioned the model not just as a voice generator, but as a stronger fit for multilingual conversational experiences and dialogue-heavy applications.
Relevance to AI PMs
- Designing better voice UX: AI PMs can use Gemini 3.1 Flash TTS to prototype more natural voice interfaces, including assistants, narrated workflows, support bots, and guided experiences. Native multi-speaker dialogue makes it easier to simulate realistic conversations without stitching together multiple tools.
- Controlling brand and tone: The model’s steerability and director-style prompting are useful for teams that need consistent voice personality, emotional tone, pacing, or delivery style. That makes it relevant for branded experiences, marketing narration, education products, and customer support automation.
- Expanding multilingual product reach: Support for 70+ languages gives PMs a more practical path to localized voice features. This can reduce the overhead of launching in new markets and help teams test international use cases such as onboarding, help content, or conversational commerce.
Related
- Google / Google AI / Google AI Studio: Gemini 3.1 Flash TTS is a Google AI product and was announced as available through Google AI Studio for preview and experimentation.
- Gemini API: The core access point for developers to integrate Gemini 3.1 Flash TTS into applications and generate audio programmatically.
- Vertex AI: Enterprise access channel for organizations that want to use the model within Google Cloud workflows and governance controls.
- Gemini: The model is part of the broader Gemini product family, which helps position it alongside other multimodal and developer-facing capabilities.
- Demis Hassabis: Publicly unveiled the model and framed it as Google’s most expressive and steerable TTS system.
- Simon Willison: Provided early hands-on coverage, noting practical capabilities like audio output, UI experimentation, and director-style prompting.
- Gemini Robotics-ER 1.6: Mentioned alongside Gemini 3.1 Flash TTS in Google AI updates, illustrating how Google is shipping voice, robotics, and assistant experiences as part of a broader Gemini roadmap.
- Gemini Mac app: Announced in the same update cycle, reinforcing the expansion of Gemini into end-user application surfaces as well as APIs and infrastructure.
Newsletter Mentions (3)
“Google AI shipped Gemini 3.1 Flash TTS with native multi-speaker dialogue in 70+ languages, Gemini Robotics-ER 1.6 for physical-world reasoning, and the new Gemini Mac app (Option + Space shortcut).”
#2 𝕏 Google AI shipped Gemini 3.1 Flash TTS with native multi-speaker dialogue in 70+ languages, Gemini Robotics-ER 1.6 for physical-world reasoning, and the new Gemini Mac app (Option + Space shortcut). #3 𝕏 DeepLearning.AI highlights Anthropic’s Claude Mythos Preview, an AI model that autonomously finds and exploits critical software vulnerabilities; it’s currently limited to industry partners to uncover and patch flaws before any public release.
“#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 writer known for his AI tooling commentary and the `llm` project. He is credited here with the 0.32a2 release note.
Google's AI assistant/model family mentioned as one of the systems that can answer category-level brand questions. It is presented alongside ChatGPT and Perplexity in the context of AI-driven visibility.
The company behind Gemini, referenced through a Gemini API quickstart guide. It is relevant for model access and developer onboarding.
Google’s environment for building and experimenting with Gemini-powered apps and prototypes. It appears here as the venue for interactive UI experiments and an intelligent mouse pointer prototype.
Co-founder and CEO of Google DeepMind. He is mentioned here in relation to new funding for Isomorphic Labs and a Gemini-powered UI prototype.
Google’s developer API for Gemini, mentioned via an interactions quickstart guide. It is relevant for PM builders who need to prototype and test model capabilities quickly.
Google’s AI organization, referenced for launching Gemini 3.1 TTS with controllable vocal style tags.
Google Cloud’s AI platform, mentioned as a distribution and deployment surface for MedGemma 1.5.
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