Google Chirp 3 vs Reson8
Reson8 is ahead of Google Chirp 3 on time to first text and final-text delay. The Pipecat Dataset and The Ocular Dataset are 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
Reson8 is the better pick over Google Chirp 3 on every measure that separates them: showing words while the caller is still talking (2.08s sooner) and quick turn-taking once the caller stops (240ms sooner). For accuracy on clean, scripted audio and accuracy on real phone conversations, the gap is inside the margin of error, so neither is ahead.
The four metrics, side by side
- Google Chirp 3
- 2.00%3rd
- Reson8
- 2.10%4th
Too close to call: inside the margin of error
- Google Chirp 3
- 4.19%9th
- Reson8
- 2.93%1st
Too close to call: inside the margin of error
- Google Chirp 3
- 4.48s14th
- Reson8
- 2.40s13th
Reson8, 2.08s sooner
- Google Chirp 3
- 475ms13th
- Reson8
- 235ms12th
Reson8, 240ms 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
Google Chirp 3 shows first text after 7.97s and final text after 1.41s, 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 | Google Chirp 3 | 4.48s | 6.21s | 7.97s |
| Reson8 | 2.40s | 7.97s | 10.20s | |
| Final-text delay | Google Chirp 3 | 475ms* | 941ms* | 1.41s* |
| 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.
* Final-text delay is the observed time after stream close, because controlled finalization is not available for this model. Compare it with care against models that finalize on request.
How each ranks among all 17 models
Place among the 17 models on each metric. Lower is better on all four.
| Metric | Chirp 3 | Reson8 |
|---|---|---|
| Pipecat Dataset WER | 2.00%3rd of 17 | 2.10%4th of 17 |
| Ocular Dataset WER | 4.19%9th of 17 | 2.93%1st of 17 |
| Time to first text | 4.48s14th of 15 | 2.40s13th of 15 |
| Final-text delay | 475ms13th of 17 | 235ms12th of 17 |
How much audio each model was tested on
| Model | Pipecat clips | Ocular recordings | Turns timed | Failed |
|---|---|---|---|---|
| Google Chirp 3 | 1,000 | 8 | 206 | 0 |
| Reson8 | 1,000 | 8 | 201 | 0 |
Only clips with usable text count, so the two totals can differ. How WER is scored.
Related comparisons
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- Google Chirp 3 vs AssemblyAI Universal 3.6 Pro
- Google Chirp 3 vs Cartesia Ink 2
- Google Chirp 3 vs Speechmatics Linden
- Google Chirp 3 vs Soniox STT-RT v5
- Google Chirp 3 vs Google Chirp 2
- Google Chirp 3 vs Inworld STT-1
- Google Chirp 3 vs GPT-4o Mini Transcribe
- Google Chirp 3 vs Deepgram Nova-3
- Google Chirp 3 vs Smallest Pulse
- Google Chirp 3 vs GPT-4o Transcribe
- Google Chirp 3 vs Deepgram Flux English
- Google Chirp 3 vs Deepgram Flux Multilingual
- Google Chirp 3 vs Gradium
- Reson8 vs GPT Realtime Whisper
- 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 English
- Reson8 vs Deepgram Flux Multilingual
- Reson8 vs Gradium
Frequently asked questions
Which is more accurate, Google Chirp 3 or Reson8?
Google Chirp 3 and Reson8 are too close to call on accuracy. On the 1,000 public Pipecat clips, Google Chirp 3 scores 2.00% and Reson8 2.10%, with likely ranges of 1.77 to 2.25% and 1.86 to 2.35%. The ranges overlap, so the difference is too close to call. On the eight licensed Ocular recordings, Google Chirp 3 scores 4.19% and Reson8 2.93%, with likely ranges of 2.97 to 5.27% 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 Google Chirp 3 faster than Reson8?
No. Reson8 finishes the transcript 240ms sooner. Google Chirp 3 has the final transcript 475ms after the speaker stops and Reson8 235ms, at the median. Both are measured on the same 206 streamed turns.
Is Google Chirp 3 or Reson8 better for voice agents?
Reson8 finishes the transcript 240ms 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 Google Chirp 3 and Reson8 stream text while the speaker is talking?
Yes, both return partial text before the speaker stops. Google Chirp 3 shows first text after 4.48s and Reson8 after 2.40s, at the median, so Reson8 is 2.08s sooner.