Reson8 is ahead of Google Chirp 2 on time to first text and final-text delay. The Pipecat Dataset and The Ocular Dataset are too close to call.
Google Chirp 2 has a newer release. See Google Chirp 3 vs Reson8.
Last updated Methodology by Dileep Chagam
Each dot is one model. Bottom-left is best: fewer errors and a faster final transcript.
Reson8 is the better pick over Google Chirp 2 on every measure that separates them: showing words while the caller is still talking (2.10s sooner) and quick turn-taking once the caller stops (333ms 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.
Too close to call: inside the margin of error
Too close to call: inside the margin of error
Reson8, 2.10s sooner
Reson8, 333ms sooner
Lower is better on every metric. The small figure is each model's place in the whole field. What each metric measures.
Google Chirp 2 shows first text after 8.15s and final text after 1.22s, 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 2 | 4.50s | 6.40s | 8.15s |
| Reson8 | 2.40s | 7.97s | 10.20s | |
| Final-text delay | Google Chirp 2 | 568ms* | 1.04s* | 1.22s* |
| Reson8 | 235ms | 357ms | 398ms |
* 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.
Place among the 17 models on each metric. Lower is better on all four.
| Metric | Chirp 2 | Reson8 |
|---|---|---|
| Pipecat Dataset WER | 2.59%9th of 17 | 2.10%4th of 17 |
| Ocular Dataset WER | 3.80%5th of 17 | 2.93%1st of 17 |
| Time to first text | 4.50s15th of 15 | 2.40s13th of 15 |
| Final-text delay | 568ms15th of 17 | 235ms12th of 17 |
| Model | Pipecat clips | Ocular recordings | Turns timed | Failed |
|---|---|---|---|---|
| Google Chirp 2 | 1,000 | 8 | 205 | 1 |
| Reson8 | 1,000 | 8 | 201 | 0 |
Only clips with usable text count, so the two totals can differ. How WER is scored.
Google Chirp 2 and Reson8 are too close to call on accuracy. On the 1,000 public Pipecat clips, Google Chirp 2 scores 2.59% and Reson8 2.10%, with likely ranges of 2.31 to 2.89% 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 2 scores 3.80% and Reson8 2.93%, with likely ranges of 2.93 to 4.60% 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.
No. Reson8 finishes the transcript 333ms sooner. Google Chirp 2 has the final transcript 568ms after the speaker stops and Reson8 235ms, at the median. Both are measured on the same 206 streamed turns.
Reson8 finishes the transcript 333ms 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.
Yes, both return partial text before the speaker stops. Google Chirp 2 shows first text after 4.50s and Reson8 after 2.40s, at the median, so Reson8 is 2.10s sooner.