Deepgram Flux Multilingual vs GPT Realtime Whisper
Accuracy and speed
Left gets fewer words wrong. Lower has the final text ready sooner.
- Flux Multilingual4.96% · 114ms
- Realtime Whisper2.16% · 543ms
Deepgram Flux Multilingual is ahead on time to first text and final-text delay, and GPT Realtime Whisper 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
- Overall WER4.81%2.63%
- Pipecat Dataset WER4.96%2.16%
- Ocular Dataset WER4.53%3.53%
- Time to first text793ms1.38s
- Final-text delay114ms543ms
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 Realtime Whisper FAQ
Which is more accurate, Deepgram Flux Multilingual or GPT Realtime Whisper?
GPT Realtime Whisper is more accurate on both datasets. On the 1,000 public Pipecat clips, Deepgram Flux Multilingual scores 4.81% and GPT Realtime Whisper 2.63%, so GPT Realtime Whisper makes fewer errors by 2.18 points. On the eight licensed Ocular recordings, Deepgram Flux Multilingual scores 4.96% and GPT Realtime Whisper 2.16%, so GPT Realtime Whisper makes fewer errors by 2.80 points. Word error rate counts incorrect, missing, and extra words, so lower is better.
GPT Realtime Whisper is more accurate on both datasets. On the 1,000 public Pipecat clips, Deepgram Flux Multilingual scores 4.81% and GPT Realtime Whisper 2.63%, so GPT Realtime Whisper makes fewer errors by 2.18 points. On the eight licensed Ocular recordings, Deepgram Flux Multilingual scores 4.96% and GPT Realtime Whisper 2.16%, so GPT Realtime Whisper makes fewer errors by 2.80 points. Word error rate counts incorrect, missing, and extra words, so lower is better.
Yes. Deepgram Flux Multilingual finishes the transcript 586ms sooner. Deepgram Flux Multilingual has the final transcript 793ms after the speaker stops and GPT Realtime Whisper 1.38s, at the median. Both are measured on the same 206 streamed turns.
It is a trade-off. GPT Realtime Whisper makes fewer errors on real conversations, while Deepgram Flux Multilingual finishes the transcript 586ms 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 GPT Realtime Whisper after 3.53%, at the median.
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