Inworld STT-1 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 Inworld STT-1.
Last updated Methodology by Dileep Chagam
Each dot is one model. Bottom-left is best: fewer errors and a faster final transcript.
Inworld STT-1 is the better pick over Google Chirp 2 on every measure that separates them: showing words while the caller is still talking (3.43s sooner) and quick turn-taking once the caller stops (527ms 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
Inworld STT-1, 3.43s sooner
Inworld STT-1, 527ms 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 Inworld STT-1 shows first text after 1.07s and final text after 65ms, 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 |
| Inworld STT-1 | 1.06s | 1.07s | 1.07s | |
| Final-text delay | Google Chirp 2 | 568ms* | 1.04s* | 1.22s* |
| Inworld STT-1 | 41ms | 60ms | 65ms |
* 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 | STT-1 |
|---|---|---|
| Pipecat Dataset WER | 2.59%9th of 17 | 2.72%10th of 17 |
| Ocular Dataset WER | 3.80%5th of 17 | 10.60%16th of 17 |
| Time to first text | 4.50s15th of 15 | 1.06s6th of 15 |
| Final-text delay | 568ms15th of 17 | 41ms2nd of 17 |
| Model | Pipecat clips | Ocular recordings | Turns timed | Failed |
|---|---|---|---|---|
| Google Chirp 2 | 1,000 | 8 | 205 | 1 |
| Inworld STT-1 | 1,000 | 8 | 206 | 0 |
Only clips with usable text count, so the two totals can differ. How WER is scored.
Google Chirp 2 and Inworld STT-1 are too close to call on accuracy. On the 1,000 public Pipecat clips, Google Chirp 2 scores 2.59% and Inworld STT-1 2.72%, with likely ranges of 2.31 to 2.89% and 1.67 to 4.68%. The ranges overlap, so the difference is too close to call. On the eight licensed Ocular recordings, Google Chirp 2 scores 3.80% and Inworld STT-1 10.60%, with likely ranges of 2.93 to 4.60% and 3.85 to 22.76%. 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. Inworld STT-1 finishes the transcript 527ms sooner. Google Chirp 2 has the final transcript 568ms after the speaker stops and Inworld STT-1 41ms, at the median. Both are measured on the same 206 streamed turns.
Inworld STT-1 finishes the transcript 527ms 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 Inworld STT-1 after 1.06s, at the median, so Inworld STT-1 is 3.43s sooner.