Google Cloud Speech-to-Text

GCP-native teams who want Chirp 2 quality with managed scaling.

Google's Chirp 2 model, rolled out across Cloud Speech in 2025, finally closes the accuracy gap with Whisper and Deepgram on long-form audio. The Speech V2 API is cleaner than the legacy V1, and 125+ languages are supported. The pain point is still the GCP onboarding overhead.

Google Cloud Speech-to-Text became seriously competitive with the Chirp 2 launch in 2025. Prior to that, Google's ASR was respectable but consistently a step behind Deepgram and AssemblyAI on conversational and long-form content. Chirp 2 closed most of that gap and made Google a credible default for teams who already live in Google Cloud, which is the natural fit. The Speech V2 API is the version to use; it's cleaner, more consistent, and structurally easier to integrate than the legacy V1 endpoint that still lingers in the documentation. Language coverage is the broadest in the category, with 125+ languages and dialects supported, which makes Google the obvious choice for products serving genuinely global audiences. Multilingual transcription within a single audio file is supported, too, which is useful for code-switching content. The trade-offs are operational. Wiring up Cloud Speech requires GCS for input, Pub/Sub for orchestration, and IAM configuration that's noticeably more involved than Deepgram or AssemblyAI's API-key-and-go onboarding. The learning curve is real for non-GCP teams. Pricing is competitive: Chirp 2 batch costs less per minute than Deepgram Nova for many workloads, though diarisation and additional features add to the bill. For GCP-native teams with serious multilingual needs, this is the right choice.