Left gets fewer words wrong. Lower has the final text ready sooner.
Deepgram Nova-3 is ahead of Gradium on both datasets together, the Pipecat Dataset, time to first text and final-text delay. The Ocular Dataset is too close to call.
Last updated Methodology by Dileep Chagam
Lower is better on every measure. Too close to call means the likely ranges overlap. For costs, see our breakdown of Deepgram pricing.
Deepgram Nova-3 is more accurate on both datasets. On the 1,000 public Pipecat clips, Deepgram Nova-3 scores 3.78% and Gradium 5.78%, so Deepgram Nova-3 makes fewer errors by 1.99 points. On the eight licensed Ocular recordings, Deepgram Nova-3 scores 3.46% and Gradium 6.48%, so Deepgram Nova-3 makes fewer errors by 3.01 points. Word error rate counts incorrect, missing, and extra words, so lower is better.
Deepgram Nova-3 is more accurate on both datasets. On the 1,000 public Pipecat clips, Deepgram Nova-3 scores 3.78% and Gradium 5.78%, so Deepgram Nova-3 makes fewer errors by 1.99 points. On the eight licensed Ocular recordings, Deepgram Nova-3 scores 3.46% and Gradium 6.48%, so Deepgram Nova-3 makes fewer errors by 3.01 points. Word error rate counts incorrect, missing, and extra words, so lower is better.
Yes. Deepgram Nova-3 finishes the transcript 641ms sooner. Deepgram Nova-3 has the final transcript 1.06s after the speaker stops and Gradium 1.71s, at the median. Both are measured on the same 206 streamed turns.
Deepgram Nova-3 is the stronger pick for voice agents: it makes fewer errors on real conversations and finishes the transcript 641ms sooner. A voice agent cannot reply until the final transcript arrives, and the Ocular recordings are real conversations.
Yes, both return partial text before the speaker stops. Deepgram Nova-3 shows first text after 4.39% and Gradium after 4.45%, at the median.
Cekura runs these simulated calls on your agent and scores every one.