Deepgram Nova-3vsGradium

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Accuracy and speed

Left gets fewer words wrong. Lower has the final text ready sooner.

Accurate and fast0ms200ms400ms600ms800ms0%2%4%6%8%Words wrong on clean audio (Pipecat WER)
  • Nova-33.46% · 103ms
  • Gradium6.48% · 212ms

Deepgram Nova-3 is ahead of Gradium on 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

Who is better at what

Nova-3Gradium
  • Pipecat Dataset WER3.46%6.48%
  • Ocular Dataset WER4.39%4.45%
  • Time to first text1.06s1.71s
  • Final-text delay103ms212ms

Lower is better on every measure. Too close to call means the likely ranges overlap.

Nova-3 vs Gradium FAQ

  • Deepgram Nova-3 is more accurate on the public clips. On the 1,000 public Pipecat clips, Deepgram Nova-3 scores 3.46% and Gradium 6.48%, so Deepgram Nova-3 makes fewer errors by 3.01 points. On the eight licensed Ocular recordings, Deepgram Nova-3 scores 4.39% and Gradium 4.45%, with likely ranges of 3.42 to 5.25% and 3.17 to 5.90%. The ranges overlap, so the difference is too close to call. Word error rate counts incorrect, missing, and extra words, so lower is better.

  • Yes. Deepgram Nova-3 finishes the transcript 109ms sooner. Deepgram Nova-3 has the final transcript 103ms after the speaker stops and Gradium 212ms, at the median. Both are measured on the same 206 streamed turns.

  • Deepgram Nova-3 finishes the transcript 109ms sooner, and the two are too close to call on real conversations. 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 1.06s and Gradium after 1.71s, at the median, so Deepgram Nova-3 is 641ms sooner.