Left gets fewer words wrong. Lower has the final text ready sooner.
Reson8 Rumble-2 is ahead of Deepgram Flux English 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.
Reson8 Rumble-2 is more accurate on both datasets. On the 1,000 public Pipecat clips, Deepgram Flux English scores 4.00% and Reson8 Rumble-2 2.05%, so Reson8 Rumble-2 makes fewer errors by 1.94 points. On the 300 licensed Ocular turns, Deepgram Flux English scores 3.90% and Reson8 Rumble-2 1.69%, so Reson8 Rumble-2 makes fewer errors by 2.21 points. Word error rate counts incorrect, missing, and extra words, so lower is better.
Reson8 Rumble-2 is more accurate on both datasets. On the 1,000 public Pipecat clips, Deepgram Flux English scores 4.00% and Reson8 Rumble-2 2.05%, so Reson8 Rumble-2 makes fewer errors by 1.94 points. On the 300 licensed Ocular turns, Deepgram Flux English scores 3.90% and Reson8 Rumble-2 1.69%, so Reson8 Rumble-2 makes fewer errors by 2.21 points. Word error rate counts incorrect, missing, and extra words, so lower is better.
No. Reson8 Rumble-2 finishes the transcript 305ms sooner. Deepgram Flux English has the final transcript 791ms after the speaker stops and Reson8 Rumble-2 486ms, at the median. Both are measured on the same 206 streamed turns.
Reson8 Rumble-2 is the stronger pick for voice agents: it makes fewer errors on real conversations and finishes the transcript 305ms 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 Flux English shows first text after 4.18% and Reson8 Rumble-2 after 2.75%, at the median.
Cekura runs these simulated calls on your agent and scores every one.