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Your choice of model determines which audio formats are accepted, what language values are valid, and what response fields are available. deepgram/nova-2 and deepgram/nova-2-medical are also accepted and behave the same way, with a smaller language set (~33 languages plus multi for nova-2). Prefer the nova-3 models unless you have a specific reason.

openai/whisper-large-v3-turbo

Default model. Multilingual. Auto-detected if language omitted. See Whisper docs for the full language list. Returns text only — no timestamps regardless of response_format.

openai/whisper-tiny

Lightweight, lowest resource usage. Multilingual (50+ languages, auto-detected). Returns text only — no timestamps.

deepgram/nova-3

Highest accuracy for English. Advanced features (diarization, word timestamps, smart formatting, numerals, punctuation) available via model_config. Defaults language to en if omitted. Can also set language inside model_config — top-level field takes precedence. See Deepgram language docs for details.

deepgram/nova-3-medical

Nova-3 tuned for clinical speech — medication names, dosages, and medical terminology. Same feature set and model_config pass-through as deepgram/nova-3. English only. language accepts en and its regional variants (en-US, en-GB, en-AU, en-IN, en-NZ); any other value, including multi, returns a 400 with language_not_found.

deepgram/nova-2 and deepgram/nova-2-medical

Previous generation. Same request shape and model_config pass-through as the nova-3 models; deepgram/nova-2 covers ~33 languages plus multi, and deepgram/nova-2-medical is English only. Prefer nova-3 unless you have a specific reason.