Deepgram Flux Multilingual vs Google Chirp 3

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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
  • Chirp 32.00% · 475ms

Deepgram Flux Multilingual is ahead on time to first text and final-text delay, and Google Chirp 3 on both datasets together and the Pipecat Dataset. The Ocular Dataset is too close to call.

Last updated Methodology by Dileep Chagam

Who is better at what

Flux MultilingualChirp 3
  • Overall WER4.81%2.76%
  • Pipecat Dataset WER4.96%2.00%
  • Ocular Dataset WER4.53%4.19%
  • Time to first text793ms4.48s
  • Final-text delay114ms475ms

Lower is better on every measure. Too close to call means the likely ranges overlap. For costs, see our breakdown of Deepgram pricing.

Flux Multilingual vs Chirp 3 FAQ

  • Google Chirp 3 is more accurate on both datasets. On the 1,000 public Pipecat clips, Deepgram Flux Multilingual scores 4.81% and Google Chirp 3 2.76%, so Google Chirp 3 makes fewer errors by 2.05 points. On the eight licensed Ocular recordings, Deepgram Flux Multilingual scores 4.96% and Google Chirp 3 2.00%, so Google Chirp 3 makes fewer errors by 2.96 points. Word error rate counts incorrect, missing, and extra words, so lower is better.

  • Yes. Deepgram Flux Multilingual finishes the transcript 3.69s sooner. Deepgram Flux Multilingual has the final transcript 793ms after the speaker stops and Google Chirp 3 4.48s, at the median. Both are measured on the same 206 streamed turns.

  • It is a trade-off. Google Chirp 3 makes fewer errors on real conversations, while Deepgram Flux Multilingual finishes the transcript 3.69s 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 Google Chirp 3 after 4.19%, at the median.

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