Google AI Releases Gemini 3.5 Transcribe: A Speech-to-Text Model Reporting 2.6% Average WER Across 85+ Languages

Google has released Gemini 3.5 Transcribe, a speech-to-text model for real-time voice interfaces and recorded audio. It ships as two endpoints, not one. gemini-3.5-transcribe handles pre-recorded files through the Interactions API. gemini-3.5-transcribe-live handles bidirectional streaming through the Live API. Google reports average word error rates of 4.0% streaming and 2.6% non-streaming, as measured by Artificial Analysis. Time to final transcription improves 70% over Chirp 3, the previous model. Automatic detection covers more than 85 languages, including mid-sentence code-switching. The split between the two endpoints is the part worth planning around. They do not share the same feature set, limits, or price.

Is it deployable?

Yes, but API-only. There are no open weights and no self-hosted path. This is a managed-service decision, not an infrastructure one.

Company level: Any. Solo developers and startups can start on the Gemini API free tier via Google AI Studio. Mid-market teams move to the paid tier for higher rate limits. The paid tier also guarantees content is not used to improve Google’s products. Regulated enterprises route through the Gemini Enterprise Agent Platform, which adds provisioned throughput, compliance controls, and volume discounts. Both developer and enterprise tracks are in public preview, so treat production commitments accordingly.

Industries: Contact centers and CX platforms, clinical documentation, media captioning and localization, legal and insurance intake, meeting tooling, and voice-driven developer tools.

Applications: Real-time voice agents, live captioning, post-call analytics pipelines, meeting transcription with speaker attribution, dictation, and voice-controlled interfaces.