Google Chirp 3 vs GPT-4o Transcribe
Google Chirp 3 is ahead of GPT-4o Transcribe on the Pipecat Dataset, the Ocular Dataset and final-text delay.
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
Google Chirp 3 is the better pick over GPT-4o Transcribe on every measure that separates them: accuracy on clean, scripted audio (1.90 points lower), accuracy on real phone conversations (8.26 points lower) and quick turn-taking once the caller stops (177ms sooner).
The four metrics, side by side
- Google Chirp 3
- 2.00%3rd
- GPT-4o Transcribe
- 3.90%14th
Google Chirp 3, 1.90 points lower
- Google Chirp 3
- 4.19%9th
- GPT-4o Transcribe
- 12.45%17th
Google Chirp 3, 8.26 points lower
- Google Chirp 3
- 4.48s14th
- GPT-4o Transcribe
- No text until the speaker stops
Not comparable
- Google Chirp 3
- 475ms13th
- GPT-4o Transcribe
- 652ms17th
Google Chirp 3, 177ms 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 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 3 | 4.48s | 6.21s | 7.97s |
| GPT-4o Transcribe | No text until the speaker stops | |||
| Final-text delay | Google Chirp 3 | 475ms* | 941ms* | 1.41s* |
| GPT-4o Transcribe | 652ms | 1.73s | 1.97s | |
- 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 | 4o Transcribe |
|---|---|---|
| Pipecat Dataset WER | 2.00%3rd of 17 | 3.90%14th of 17 |
| Ocular Dataset WER | 4.19%9th of 17 | 12.45%17th of 17 |
| Time to first text | 4.48s14th of 15 | Not comparable |
| Final-text delay | 475ms13th of 17 | 652ms17th 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 |
| GPT-4o Transcribe | 1,000 | 8 | 206 | 0 |
Only clips with usable text count, so the two totals can differ. How WER is scored.
Related comparisons
Both providers, every model: Google vs OpenAI
- Google Chirp 3 vs Reson8
- Google Chirp 3 vs GPT Realtime Whisper
- 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 Deepgram Flux English
- Google Chirp 3 vs Deepgram Flux Multilingual
- Google Chirp 3 vs Gradium
- GPT-4o Transcribe vs Deepgram Flux English
- GPT-4o Transcribe vs Smallest Pulse
- GPT-4o Transcribe vs Deepgram Nova-3
- GPT-4o Transcribe vs GPT-4o Mini Transcribe
- GPT-4o Transcribe vs Deepgram Flux Multilingual
- GPT-4o Transcribe vs Inworld STT-1
- GPT-4o Transcribe vs Soniox STT-RT v5
- GPT-4o Transcribe vs Speechmatics Linden
- GPT-4o Transcribe vs Cartesia Ink 2
- GPT-4o Transcribe vs GPT Realtime Whisper
- GPT-4o Transcribe vs Reson8
- GPT-4o Transcribe vs AssemblyAI Universal 3.6 Pro
- GPT-4o Transcribe vs Gradium
Frequently asked questions
Which is more accurate, Google Chirp 3 or GPT-4o Transcribe?
Google Chirp 3 is more accurate on both datasets. On the 1,000 public Pipecat clips, Google Chirp 3 scores 2.00% and GPT-4o Transcribe 3.90%, so Google Chirp 3 makes fewer errors by 1.90 points. On the eight licensed Ocular recordings, Google Chirp 3 scores 4.19% and GPT-4o Transcribe 12.45%, so Google Chirp 3 makes fewer errors by 8.26 points. Word error rate counts incorrect, missing, and extra words, so lower is better.
Is Google Chirp 3 faster than GPT-4o Transcribe?
Yes. Google Chirp 3 finishes the transcript 177ms sooner. Google Chirp 3 has the final transcript 475ms after the speaker stops and GPT-4o Transcribe 652ms, at the median. Both are measured on the same 206 streamed turns.
Is Google Chirp 3 or GPT-4o Transcribe better for voice agents?
Google Chirp 3 is the stronger pick for voice agents: it makes fewer errors on real conversations and finishes the transcript 177ms sooner. A voice agent cannot reply until the final transcript arrives, and the Ocular recordings are real conversations.
Do Google Chirp 3 and GPT-4o Transcribe stream text while the speaker is talking?
Only Google Chirp 3. GPT-4o Transcribe returns no text until the speaker stops, which matters if your agent reacts to partial transcripts.