Deepgram vs Whisper large-v3

Pick two tools from the same category to compare side-by-side.

	Deepgram Voice AI platform providing speech-to-text, text-to-speech, and a unified voice agent API.	Whisper large-v3 Open-weights automatic speech recognition (STT) model.
Category	voice	voice
Vendor type	commercial	open source
Pricing	usage	free
Strengths	+ Low-latency streaming STT widely used in realtime voice agent stacks + Unified Voice Agent API combining STT, LLM orchestration, and TTS + Cloud and self-hosted deployment options + Usage-based pricing with free credits to start	+ Open weights; self-host to keep audio in-environment + Strong multilingual transcription accuracy
Tradeoffs	− Proprietary models create vendor lock-in compared with open-weight options − Accuracy on niche accents, domains, and lower-resource languages can require model tuning or keyword boosting	− Needs a GPU for low-latency, high-volume transcription − Diarization (who said what) requires a separate component
Used in stacks	0	1