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Gemini Transcribe

Gemini 3.5 Transcribe

Google's dedicated speech-to-text model family for accurate non-streaming and live transcription across 85+ languages.

Content updated today·Gemini 3.5 Transcribe released 3 days ago

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Pros & Cons

Pros

  • One Google API family for recorded files and low-latency live transcription
  • Automatic detection and code-switching across more than 85 languages
  • Useful controls for vocabulary, diarization, timestamps, and cleaned-up prose
  • Usage-based pricing with a free tier
  • Clear upgrade path from Google's Chirp speech models

Cons

  • API product rather than a complete recorder, meeting workspace, or transcription editor
  • Smart transcription is incompatible with diarization and word-level timestamps
  • Non-streaming limits drop from one hour to 30 minutes when detailed alignment features are enabled
  • Speaker diarization supports up to eight speakers, but Google explicitly marks attribution for three or more speakers as experimental.
  • Google Cloud enterprise endpoints may use preview identifiers even though the Gemini API models are GA

Overview

Gemini Transcribe is Google's dedicated speech-to-text model family for converting recorded and streaming audio into text. It is separate from the general Gemini chatbot and from conversational voice agents: the output is a transcript, not an AI-generated spoken response. The first Gemini-branded release, Gemini 3.5 Transcribe, became generally available in the Gemini API on August 26, 2026 with non-streaming and live model endpoints.

The family succeeds Google's Chirp speech-recognition models and brings two workflows under one product. The non-streaming model processes uploaded or inline audio with unary requests, while the live model returns partial and final transcripts over a persistent WebSocket connection. Both target developers building meeting notes, captions, call analytics, media indexing, and voice-input features.

For buyers comparing AI transcription tools, Gemini Transcribe is primarily an API rather than a finished meeting-notes app. Its advantages are multilingual coverage, code-switching, promptable vocabulary, and access to Google's current speech model; teams that need calendars, summaries, action items, and a user-facing workspace will still need to build those layers or use an AI meeting-notes product.

Key Features

  • Non-streaming and live endpoints — Use gemini-3.5-transcribe for standard unary file transcription or gemini-3.5-transcribe-live for continuous streaming transcription. Google's dedicated Gemini Batch API is not supported for Gemini 3.5 Transcribe.
  • 85+ languages with automatic detection — The model can identify supported languages and transcribe multilingual audio, including code-switching within a recording.
  • Custom vocabulary — Supply up to 1,000 words or phrases to improve recognition of product names, acronyms, technical terminology, and domain-specific entities; Google says lists of 100 or fewer usually work best.
  • Speaker diarization — Label speakers in multi-person non-streaming audio for interviews, meetings, podcasts, and support-call analysis. Google documents up to eight speakers, while attribution with three or more speakers remains experimental.
  • Word-level timestamps — Available for non-streaming gemini-3.5-transcribe, not gemini-3.5-transcribe-live. Enabling word-level timestamps reduces the documented file-processing limit to 30 minutes and may degrade overall transcription accuracy.
  • Smart transcription — Remove disfluencies, resolve self-corrections, and format spoken language into cleaner readable text when verbatim output is not required.

How to Get Started

  1. Create a Gemini API key in Google AI Studio and choose the non-streaming or live workflow.
  2. For a recording, send supported audio to the Interactions API with gemini-3.5-transcribe; add a language hint, vocabulary list, diarization, or timestamps only when needed.
  3. For a microphone or live call, open a Live API WebSocket session with gemini-3.5-transcribe-live, stream audio chunks, and consume partial and final transcript events.
  4. Store both the transcript and model configuration so quality issues can be reproduced during evaluation.
  5. Test real accents, background noise, domain terms, overlapping speech, and speaker counts before production rollout.

Start with clean representative recordings, then introduce the difficult audio conditions your application must handle. Smart transcription cannot be combined with diarization or word-level timestamps, so choose readable prose or detailed alignment per request rather than expecting every feature at once.

Pricing & Plans

The Gemini API offers a free tier and usage-based paid pricing. Google states that free-tier usage may be used to improve its products, while paid-tier usage is not; rate limits also vary by project and usage tier and should be checked in Google AI Studio.

Mode Input Output Approximate combined cost
Non-streaming transcription $2.00 / 1M audio tokens, about $0.003/min $12.00 / 1M text tokens, about $0.002/min About $0.005/audio minute
Live transcription $3.50 / 1M audio tokens, about $0.005/min $21.00 / 1M text tokens, about $0.004/min About $0.009/audio minute

Non-streaming requests support up to one hour of audio. Enabling speaker diarization or word-level timestamps reduces the documented maximum to 30 minutes. Live transcription sessions support continuous streaming for up to 10 minutes, so production applications should implement session rollover or reconnection handling. Enterprise access through Gemini Enterprise Agent Platform is a separate channel that Google's launch material describes as public preview; verify its pricing, quotas, regional availability, and endpoint identifiers separately.

How It Compares

Deepgram, AssemblyAI, and AWS Transcribe are alternative transcription APIs. Gemini Transcribe provides 85+ language detection, code-switching, custom vocabulary, and non-streaming and live transcription within the Gemini API.

Gemini Transcribe should not be evaluated like a general chatbot. A voice agent such as Vapi or Retell AI orchestrates turn-taking, language-model responses, telephony, and synthesized speech. Gemini Transcribe covers the recognition stage only, which gives developers more control but also leaves agent orchestration and end-user workflow design to the application.

Best For

  • Developers adding transcription to media, support, education, accessibility, or productivity products
  • Multilingual applications that encounter code-switching and changing accents
  • Meeting, interview, and podcast pipelines needing speaker labels or timestamps
  • Live captioning and voice-input experiences that need partial results over WebSockets
  • Existing Gemini API teams that want speech recognition without adding another AI vendor

FAQ

What is Gemini Transcribe?

Gemini Transcribe is Google's dedicated speech-to-text model family. It converts recorded or streaming audio to text and is distinct from the Gemini chatbot and from Live Agent models that generate conversational responses.

Is Gemini 3.5 Transcribe generally available?

Yes in the Gemini API. Google's August 26, 2026 changelog lists both gemini-3.5-transcribe and gemini-3.5-transcribe-live as generally available. The Gemini Enterprise Agent Platform currently documents separate -preview endpoints, so deployment stage depends on the access channel.

What languages does Gemini Transcribe support?

Google documents automatic detection and transcription for more than 85 languages, including code-switching. Quality still varies by language, accent, audio quality, domain vocabulary, and speaker overlap.

Does it support speaker diarization and timestamps?

The non-streaming model supports speaker diarization and word-level timestamps. Enabling either reduces the maximum audio length to 30 minutes, and smart transcription cannot be used in the same request.

How much does Gemini Transcribe cost?

Google estimates about $0.005 per audio minute for non-streaming transcription and $0.009 per audio minute for live transcription, combining input-audio and output-text charges. A free tier is available for evaluation.

Is Gemini Transcribe the same as Gemini Live?

No. Gemini Transcribe Live streams speech-to-text results. Gemini Live Agent models listen, reason, call tools, and generate responses for a two-way conversation.

What came before Gemini Transcribe?

Gemini Transcribe follows Google's Chirp speech-model line: Chirp, Chirp 2, and Chirp 3. The dedicated Gemini 3.5 Transcribe release is the next major generation and Google's official launch comparison uses Chirp 3 as its predecessor.

Sources

Version History

Gemini 3.5 Transcribe

Current Version

Released on August 26, 2026

View Update
+What's new
3 updates
  • Transcribe files with gemini-3.5-transcribe or stream partial and final text through gemini-3.5-transcribe-live, with both dedicated speech-to-text models GA in the Gemini API
  • Support 85+ languages, code-switching, custom vocabulary, smart transcription, speaker diarization, and word-level timestamps in a purpose-built transcription family
  • Compare with Chirp 3 using figures Google cites from Artificial Analysis: 4.0% streaming WER, 2.6% non-streaming WER, and 70% faster finalization, at ~$0.005/min file or ~$0.009/min live

Chirp 3 (GA)

Released on October 13, 2025

+What's new
2 updates
  • Move Chirp 3 workloads from public preview to general availability with a production lifecycle for Google Cloud Speech-to-Text V2 deployments
  • Transcribe multilingual and real-time speech with the generation Google later identified as the direct predecessor to Gemini 3.5 Transcribe

Chirp 3 (Public Preview)

Released on August 29, 2025

+What's new
2 updates
  • Evaluate the third Chirp generation in public preview for multilingual and streaming workloads before its October 2025 general-availability milestone
  • Use Chirp 3 in Cloud Speech-to-Text V2 for multilingual streaming and short-form transcription during public preview, with speaker diarization and language-agnostic transcription

Chirp 2 (Major GA Update)

Released on October 7, 2024

+What's new
2 updates
  • Adopt the major Chirp 2 general-availability update in Cloud Speech-to-Text V2 for improved multilingual automatic speech recognition
  • Use word-level timestamps, model adaptation, speech translation, and StreamingRecognize alongside synchronous and batch recognition in the updated Chirp 2 model

Chirp (GA)

Released on July 18, 2023

+What's new
2 updates
  • Deploy Google's universal speech model in production as a generally available Vertex AI foundation model after its May 2023 preview
  • Use a model trained across millions of hours of audio and more than 100 languages to improve multilingual transcription coverage

Chirp (Preview)

Released on May 10, 2023

+What's new
2 updates
  • Test Google's first Chirp universal speech model across early cloud transcription workflows in preview with support spanning more than 100 languages
  • Build early multilingual speech-recognition workflows on Google Cloud before the model's July 2023 general-availability release

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