Deepgram Flux Multilingual vs Reson8 Rumble-2

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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)
  • Flux Multilingual4.96% · 114ms
  • Rumble-21.69% · 18ms

Reson8 Rumble-2 is ahead of Deepgram Flux Multilingual 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

Flux MultilingualRumble-2
  • Overall WER4.81%2.05%
  • Pipecat Dataset WER4.96%1.69%
  • Ocular Dataset WER4.53%2.75%
  • Time to first text793ms486ms
  • Final-text delay114ms18ms

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

Flux Multilingual vs Rumble-2 FAQ

  • Reson8 Rumble-2 is more accurate on both datasets. On the 1,000 public Pipecat clips, Deepgram Flux Multilingual scores 4.81% and Reson8 Rumble-2 2.05%, so Reson8 Rumble-2 makes fewer errors by 2.76 points. On the 300 licensed Ocular turns, Deepgram Flux Multilingual scores 4.96% and Reson8 Rumble-2 1.69%, so Reson8 Rumble-2 makes fewer errors by 3.27 points. Word error rate counts incorrect, missing, and extra words, so lower is better.

  • No. Reson8 Rumble-2 finishes the transcript 307ms sooner. Deepgram Flux Multilingual has the final transcript 793ms 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 307ms 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 Multilingual shows first text after 4.53% and Reson8 Rumble-2 after 2.75%, at the median.

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