Model Comparison: When to Use Nova‑2 vs Nova‑3 (for Devs)

Deepgram’s reference guide compares its Nova-2 and Nova-3 speech-to-text models, framing Nova-2 as a lower-cost, high-throughput option for primarily English batch transcription and Nova-3 as a more capable but more expensive choice for real-time, noisy, multilingual, and domain-specific audio. It reports that Nova-2 offers fast batch processing, approximately 8.4% batch word error rate, and batch pricing of $0.0043 per minute, while Nova-3 supports live code-switching across 10 languages, keyterm prompting for up to 100 specialized terms, medical variants, real-time PII redaction, and reported word error rates of 5.26% for batch and 6.84% for streaming. The guide recommends selecting models based on required accuracy, latency, language coverage, customization, and volume-based costs, and suggests routing clean English segments to Nova-2 while directing noisy, multilingual, or high-stakes segments to Nova-3. It also outlines production practices including retries, latency monitoring, fallback logic, formatting and redaction settings, keyterm caching, and testing both models on representative audio before deployment.

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