Deepgram Flux English vs Reson8
Deepgram Flux English is ahead on time to first text and final-text delay, and Reson8 on the Pipecat Dataset. The Ocular Dataset is too close to call.
Last updated Methodology by Dileep Chagam
Accuracy vs speed
Each dot is one model. Bottom-left is best: fewer errors and a faster final transcript.
Which to pick
Pick Deepgram Flux English for showing words while the caller is still talking (1.61s sooner) and quick turn-taking once the caller stops (127ms sooner). Pick Reson8 for accuracy on clean, scripted audio (1.81 points lower). For accuracy on real phone conversations, the gap is inside the margin of error, so neither is ahead.
The four metrics, side by side
- Deepgram Flux English
- 3.90%15th
- Reson8
- 2.10%4th
Reson8, 1.81 points lower
- Deepgram Flux English
- 4.18%8th
- Reson8
- 2.93%1st
Too close to call: inside the margin of error
- Deepgram Flux English
- 791ms3rd
- Reson8
- 2.40s13th
Deepgram Flux English, 1.61s sooner
- Deepgram Flux English
- 108ms5th
- Reson8
- 235ms12th
Deepgram Flux English, 127ms sooner
Lower is better on every metric. The small figure is each model's place in the whole field. What each metric measures.
- WER · Word error rate
- Share of words the model got wrong: replaced, missing or added. Lower is better.
- Pipecat Dataset
- 1,000 short public clips from Pipecat's STT benchmark dataset.
- Ocular Dataset
- 8 recordings from 4 real phone conversations, licensed from Ocular.
- TTFT · Time to first text
- How long after the audio starts streaming until the first words appear.
- TTFS · Final-text delay
- How long after the caller stops until the full transcript arrives. A voice agent waits for this before it replies.
First text and final text, at three percentiles
Deepgram Flux English shows first text after 1.51s and final text after 141ms, and Reson8 shows first text after 10.20s and final text after 398ms, on a bad turn (P95) across the same streamed turns.
| Measure | Model | P50 | P90 | P95 |
|---|---|---|---|---|
| Time to first text | Deepgram Flux English | 791ms | 1.23s | 1.51s |
| Reson8 | 2.40s | 7.97s | 10.20s | |
| Final-text delay | Deepgram Flux English | 108ms | 132ms | 141ms |
| Reson8 | 235ms | 357ms | 398ms |
- P50 / P90 / P95 · Typical, slow and slowest turns
- Half of turns are faster than P50. Only 1 in 10 is slower than P90, and 1 in 20 slower than P95.
How each ranks among all 17 models
Place among the 17 models on each metric. Lower is better on all four.
| Metric | Flux English | Reson8 |
|---|---|---|
| Pipecat Dataset WER | 3.90%15th of 17 | 2.10%4th of 17 |
| Ocular Dataset WER | 4.18%8th of 17 | 2.93%1st of 17 |
| Time to first text | 791ms3rd of 15 | 2.40s13th of 15 |
| Final-text delay | 108ms5th of 17 | 235ms12th of 17 |
How much audio each model was tested on
| Model | Pipecat clips | Ocular recordings | Turns timed | Failed |
|---|---|---|---|---|
| Deepgram Flux English | 999 | 8 | 199 | 7 |
| Reson8 | 1,000 | 8 | 201 | 0 |
Only clips with usable text count, so the two totals can differ. How WER is scored.
Related comparisons
- Deepgram Flux English vs GPT-4o Transcribe
- Deepgram Flux English vs Smallest Pulse
- Deepgram Flux English vs Deepgram Nova-3
- Deepgram Flux English vs GPT-4o Mini Transcribe
- Deepgram Flux English vs Deepgram Flux Multilingual
- Deepgram Flux English vs Inworld STT-1
- Deepgram Flux English vs Soniox STT-RT v5
- Deepgram Flux English vs Speechmatics Linden
- Deepgram Flux English vs Cartesia Ink 2
- Deepgram Flux English vs GPT Realtime Whisper
- Deepgram Flux English vs Google Chirp 3
- Deepgram Flux English vs AssemblyAI Universal 3.6 Pro
- Deepgram Flux English vs Gradium
- Reson8 vs GPT Realtime Whisper
- Reson8 vs Google Chirp 3
- Reson8 vs Cartesia Ink 2
- Reson8 vs AssemblyAI Universal 3.6 Pro
- Reson8 vs Speechmatics Linden
- Reson8 vs Soniox STT-RT v5
- Reson8 vs Inworld STT-1
- Reson8 vs GPT-4o Mini Transcribe
- Reson8 vs Deepgram Nova-3
- Reson8 vs Smallest Pulse
- Reson8 vs GPT-4o Transcribe
- Reson8 vs Deepgram Flux Multilingual
- Reson8 vs Gradium
Frequently asked questions
Which is more accurate, Deepgram Flux English or Reson8?
Reson8 is more accurate on the public clips. On the 1,000 public Pipecat clips, Deepgram Flux English scores 3.90% and Reson8 2.10%, so Reson8 makes fewer errors by 1.81 points. On the eight licensed Ocular recordings, Deepgram Flux English scores 4.18% and Reson8 2.93%, with likely ranges of 3.08 to 5.23% and 2.29 to 3.68%. The ranges overlap, so the difference is too close to call. Word error rate counts incorrect, missing, and extra words, so lower is better.
Is Deepgram Flux English faster than Reson8?
Yes. Deepgram Flux English finishes the transcript 127ms sooner. Deepgram Flux English has the final transcript 108ms after the speaker stops and Reson8 235ms, at the median. Both are measured on the same 206 streamed turns.
Is Deepgram Flux English or Reson8 better for voice agents?
Deepgram Flux English finishes the transcript 127ms sooner, and the two are too close to call on real conversations. A voice agent cannot reply until the final transcript arrives, and the Ocular recordings are real conversations.
Do Deepgram Flux English and Reson8 stream text while the speaker is talking?
Yes, both return partial text before the speaker stops. Deepgram Flux English shows first text after 791ms and Reson8 after 2.40s, at the median, so Deepgram Flux English is 1.61s sooner.