Google Chirp 2 is ahead of GPT-4o Transcribe on the Pipecat Dataset, the Ocular Dataset and final-text delay.
Google Chirp 2 has a newer release. See Google Chirp 3 vs GPT-4o Transcribe.
Last updated Methodology by Dileep Chagam
Each dot is one model. Bottom-left is best: fewer errors and a faster final transcript.
Google Chirp 2 is the better pick over GPT-4o Transcribe on every measure that separates them: accuracy on clean, scripted audio (1.31 points lower), accuracy on real phone conversations (8.65 points lower) and quick turn-taking once the caller stops (84ms sooner).
Google Chirp 2, 1.31 points lower
Google Chirp 2, 8.65 points lower
Not comparable
Google Chirp 2, 84ms 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 GPT-4o Transcribe shows first text after 40.63s and final text after 1.97s, 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 |
| GPT-4o Transcribe | No text until the speaker stops | |||
| Final-text delay | Google Chirp 2 | 568ms* | 1.04s* | 1.22s* |
| GPT-4o Transcribe | 652ms | 1.73s | 1.97s | |
* 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 | 4o Transcribe |
|---|---|---|
| Pipecat Dataset WER | 2.59%9th of 17 | 3.90%14th of 17 |
| Ocular Dataset WER | 3.80%5th of 17 | 12.45%17th of 17 |
| Time to first text | 4.50s15th of 15 | Not comparable |
| Final-text delay | 568ms15th of 17 | 652ms17th of 17 |
| Model | Pipecat clips | Ocular recordings | Turns timed | Failed |
|---|---|---|---|---|
| Google Chirp 2 | 1,000 | 8 | 205 | 1 |
| GPT-4o Transcribe | 1,000 | 8 | 206 | 0 |
Only clips with usable text count, so the two totals can differ. How WER is scored.
Both providers, every model: Google vs OpenAI
Google Chirp 2 is more accurate on both datasets. On the 1,000 public Pipecat clips, Google Chirp 2 scores 2.59% and GPT-4o Transcribe 3.90%, so Google Chirp 2 makes fewer errors by 1.31 points. On the eight licensed Ocular recordings, Google Chirp 2 scores 3.80% and GPT-4o Transcribe 12.45%, so Google Chirp 2 makes fewer errors by 8.65 points. Word error rate counts incorrect, missing, and extra words, so lower is better.
Yes. Google Chirp 2 finishes the transcript 84ms sooner. Google Chirp 2 has the final transcript 568ms after the speaker stops and GPT-4o Transcribe 652ms, at the median. Both are measured on the same 206 streamed turns.
Google Chirp 2 is the stronger pick for voice agents: it makes fewer errors on real conversations and finishes the transcript 84ms sooner. A voice agent cannot reply until the final transcript arrives, and the Ocular recordings are real conversations.
Only Google Chirp 2. GPT-4o Transcribe returns no text until the speaker stops, which matters if your agent reacts to partial transcripts.