Deepgram vs Reson8
Reson8 is ahead of Deepgram 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
Who is better at what
Each row sets Deepgram's best model against Reson8's best on that measure.
- Overall WER3.78%Deepgram Nova-32.05%Reson8 Rumble-2
- Pipecat Dataset WER3.46%Deepgram Nova-31.69%Reson8 Rumble-2
- Ocular Dataset WER4.18%Deepgram Flux English2.75%Reson8 Rumble-2
- Time to first text791msDeepgram Flux English486msReson8 Rumble-2
- Final-text delay103msDeepgram Nova-318msReson8 Rumble-2
Deepgram vs Reson8 FAQ
Is Deepgram or Reson8 better for speech-to-text?
Reson8 is ahead, 1.77 points lower. The best Deepgram result is Deepgram Nova-3 at 3.46%, and the best Reson8 result is Reson8 Rumble-2 at 1.69%, on the Pipecat Dataset.
Reson8 is ahead, 1.77 points lower. The best Deepgram result is Deepgram Nova-3 at 3.46%, and the best Reson8 result is Reson8 Rumble-2 at 1.69%, on the Pipecat Dataset.
Reson8 is faster, 85ms sooner. The best Deepgram result is Deepgram Nova-3 at 103ms, and the best Reson8 result is Reson8 Rumble-2 at 18ms, on final-text delay.
Deepgram: Deepgram Flux English, Deepgram Flux Multilingual, Deepgram Nova-3. Reson8: Reson8 Resonant-1, Reson8 Rumble-2. Every model ran the same tests on Converse-STT.
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