Google AI Unveils Gemini 3.5 Transcribe: A New Era for Speech-to-Text Technology

Introducing Gemini 3.5 Transcribe: Google’s Latest Innovation

The bigger takeaway is simple: Google AI has officially launched Gemini 3.5 Transcribe, a cutting-edge speech-to-text model designed to revolutionize how we interact with voice interfaces and process recorded audio. This new offering significantly advances transcription accuracy and speed, building on Google’s expertise in artificial intelligence.

Meanwhile, Unlike previous models, Gemini 3.5 Transcribe is delivered through two distinct API endpoints, each tailored for specific use cases: one for pre-recorded files and another for real-time, bidirectional streaming. This dual approach provides developers with specialized tools to meet diverse application requirements.

Two Powerful APIs for Diverse Needs

Understanding the unique demands of different transcription scenarios, Google has engineered Gemini 3.5 Transcribe with two separate API surfaces, each with its own feature set, limitations, and pricing structure.

1. The Interactions API: For Pre-Recorded Audio

In practical terms, The gemini-3.5-transcribe endpoint, accessed via the Interactions API, is optimized for processing pre-recorded audio files. This API excels in situations where sub-second latency is not the primary concern, but detailed analysis and comprehensive transcription features are paramount.

• Speaker Diarization: Identify and separate individual speakers in a conversation.
• Word-Level Timestamps: Obtain precise start and end times for each word, crucial for detailed analysis and editing.
• Custom Vocabulary Biasing: Improve accuracy for domain-specific terms by providing a list of up to 1,000 custom words (with best results under 100).
• Audio Length: Supports up to one hour of audio for standard requests, reducing to 30 minutes when diarization or word timestamps are enabled.

2. The Live API: For Real-time Streaming

The gemini-3.5-transcribe-live endpoint, utilizing the Live API, is engineered for real-time voice interfaces and live transcription. It delivers sub-second, continuous transcription, making it ideal for interactive applications.

• Continuous Transcription: Provides interim transcriptions while a speaker is still talking, finalizing them once a turn is complete.
• Low Latency: Designed for responsiveness, crucial for live agents and interactive systems.
• Audio Format: Accepts raw 16-bit PCM audio at 16kHz mono, processed in 100ms chunks.
• Voice Activity Detection: Supports automatic, hybrid, and manual detection.
• Ephemeral Tokens: Enables secure streaming from mobile and web clients without exposing API keys.
• Session Limits: Live sessions are capped at 10 minutes of continuous streaming.
• Feature Trade-offs: Notably, the Live API currently does not support speaker diarization or word-level timestamps, a key distinction from the Interactions API.

Verbatim vs. Smart Mode: Precision or Readability?

For example, Both API endpoints offer two distinct transcription modes, allowing developers to choose between a raw, comprehensive transcript and a refined, readable summary.

• Verbatim Mode: This is the default setting, returning everything spoken, including filler words (like “um,” “uh”), repetitions, and false starts. It provides an auditable, unedited record of the speech.
• Smart Mode: Designed for readability, Smart mode intelligently removes disfluencies, resolves spoken self-corrections inline, and applies structured formatting. For example, a phrase like “Um, so for the meeting, I think we should, uh, invite Alice and, wait no, Bob and Carol.” would become “For the meeting, I think we should invite Bob and Carol.”

It’s important to note the trade-off: Smart mode cannot be combined with word timestamps or diarization. Developers must decide whether their application prioritizes a readable summary or a detailed, auditable transcript.

Performance That Sets a New Standard

That said, Gemini 3.5 Transcribe boasts impressive performance metrics, showcasing Google’s commitment to accuracy and efficiency:

• Word Error Rate (WER): According to Artificial Analysis, the model achieves an average WER of 4.0% for streaming and an exceptional 2.6% for non-streaming applications. On the multilingual FLEURS benchmark, it reports 5.50% streaming and 5.04% non-streaming across top languages.
• Speed Improvement: Time to final transcription has improved by a remarkable 70% compared to Google’s previous model, Chirp 3.
• Multilingual Support: The model offers automatic detection and robust support for over 85 languages, including seamless handling of mid-sentence code-switching without additional configuration.

Deployment, Accessibility, and Target Industries

Gemini 3.5 Transcribe is an API-only service; there are no open weights or self-hosted paths, reflecting Google’s managed-service approach.

• Accessibility: Solo developers and startups can begin with the Gemini API free tier via Google AI Studio. Mid-market teams can transition to the paid tier for higher rate limits and a guarantee that their content won’t be used to improve Google’s products. Regulated enterprises can leverage the Gemini Enterprise Agent Platform, which offers provisioned throughput, compliance controls, and volume discounts.
• Key Industries: This technology is poised to transform various sectors, including:
  • Contact centers and customer experience (CX) platforms
  • Clinical documentation and healthcare
  • Media captioning, localization, and accessibility
  • Legal and insurance intake processes
  • Meeting tooling and collaboration platforms
  • Voice-driven developer tools and applications
• Applications: Specific use cases range from real-time voice agents and live captioning to post-call analytics pipelines, meeting transcription with speaker attribution, dictation, and advanced voice-controlled interfaces.

Key Takeaways for Developers and Businesses

• Dual Endpoints: Choose between the Live API for real-time, low-latency streaming (without diarization/word timestamps) and the Interactions API for recorded audio with advanced features.
• Exceptional Accuracy: Achieve industry-leading WERs, particularly for non-streaming applications.
• Smart vs. Verbatim: Decide between a clean, readable summary and a complete, auditable transcript, understanding the feature trade-offs.
• Scalable Deployment: From free tiers for startups to enterprise-grade solutions for regulated industries.
• Broad Language Support: Automatic detection across 85+ languages, including robust code-switching.

Interestingly, Google’s Gemini 3.5 Transcribe represents a significant leap forward in speech-to-text technology, offering unparalleled flexibility, accuracy, and speed for a wide array of applications.

Expert Perspective

From an industry angle, the clearest signal around Gemini 3.5 Transcribe is how it may influence gemini. The story reads less like a one-day spike and more like a marker of broader movement.

The next phase will depend on how quickly teams, regulators, or customers react. In practice, that gives Gemini 3.5 Transcribe room to reshape expectations across google over the near term.

For readers focused on practical impact, the best next step is to watch what changes around transcribe once attention turns into execution.

Frequently Asked Questions

Why does Gemini 3.5 Transcribe matter right now?

Introducing Gemini 3.5 Transcribe: Google’s Latest InnovationThe bigger takeaway is simple: Google AI has officially launched Gemini 3.5 Transcribe, a cutting-edge speech-to-text model designed to revolutionize how we interact with voice interfaces and process recorded audio.

What broader change could Gemini 3.5 Transcribe signal?

This new offering significantly advances transcription accuracy and speed, building on Google’s expertise in artificial intelligence.Meanwhile, Unlike previous models, Gemini 3.5 Transcribe is delivered through two distinct API endpoints, each tailored for specific use cases: one for pre-recorded files and another for real-time, bidirectional streaming.

What should the market watch next around Gemini 3.5 Transcribe?

This dual approach provides developers with specialized tools to meet diverse application requirements.Two Powerful APIs for Diverse NeedsUnderstanding the unique demands of different transcription scenarios, Google has engineered Gemini 3.5 Transcribe with two separate API surfaces, each with its own feature set, limitations, and pricing structure.1.

Source: https://www.marktechpost.com/2026/08/27/google-ai-releases-gemini-3-5-transcribe-a-speech-to-text-model-reporting-2-6-average-wer-across-85-languages/