Google Chirp 2 vs Smallest Pulse
Smallest Pulse is ahead on time to first text and final-text delay, and Google Chirp 2 on the Pipecat Dataset. The Ocular Dataset is too close to call.
Google Chirp 2 has a newer release. See Google Chirp 3 vs Smallest Pulse.
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
Pick Google Chirp 2 for accuracy on clean, scripted audio (1.06 points lower). Pick Smallest Pulse for showing words while the caller is still talking (3.44s sooner) and quick turn-taking once the caller stops (367ms sooner). For 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 2
- 2.59%9th
- Smallest Pulse
- 3.66%13th
Google Chirp 2, 1.06 points lower
- Google Chirp 2
- 3.80%5th
- Smallest Pulse
- 3.46%3rd
Too close to call: inside the margin of error
- Google Chirp 2
- 4.50s15th
- Smallest Pulse
- 1.06s5th
Smallest Pulse, 3.44s sooner
- Google Chirp 2
- 568ms15th
- Smallest Pulse
- 201ms10th
Smallest Pulse, 367ms 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 2 shows first text after 8.15s and final text after 1.22s, and Smallest Pulse shows first text after 3.03s and final text after 773ms, 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 |
| Smallest Pulse | 1.06s | 2.25s | 3.03s | |
| Final-text delay | Google Chirp 2 | 568ms* | 1.04s* | 1.22s* |
| Smallest Pulse | 201ms | 356ms | 773ms |
- 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 2 | Pulse |
|---|---|---|
| Pipecat Dataset WER | 2.59%9th of 17 | 3.66%13th of 17 |
| Ocular Dataset WER | 3.80%5th of 17 | 3.46%3rd of 17 |
| Time to first text | 4.50s15th of 15 | 1.06s5th of 15 |
| Final-text delay | 568ms15th of 17 | 201ms10th of 17 |
How much audio each model was tested on
| Model | Pipecat clips | Ocular recordings | Turns timed | Failed |
|---|---|---|---|---|
| Google Chirp 2 | 1,000 | 8 | 205 | 1 |
| Smallest Pulse | 1,000 | 8 | 206 | 0 |
Only clips with usable text count, so the two totals can differ. How WER is scored.
Related comparisons
- Google Chirp 2 vs Google Chirp 3
- Smallest Pulse vs Deepgram Nova-3
- Smallest Pulse vs GPT-4o Transcribe
- Smallest Pulse vs Deepgram Flux English
- Smallest Pulse vs GPT-4o Mini Transcribe
- Smallest Pulse vs Inworld STT-1
- Smallest Pulse vs Soniox STT-RT v5
- Smallest Pulse vs Speechmatics Linden
- Smallest Pulse vs Cartesia Ink 2
- Smallest Pulse vs Deepgram Flux Multilingual
- Smallest Pulse vs GPT Realtime Whisper
- Smallest Pulse vs Reson8
- Smallest Pulse vs Google Chirp 3
- Smallest Pulse vs AssemblyAI Universal 3.6 Pro
- Smallest Pulse vs Gradium
Frequently asked questions
Which is more accurate, Google Chirp 2 or Smallest Pulse?
Google Chirp 2 is more accurate on the public clips. On the 1,000 public Pipecat clips, Google Chirp 2 scores 2.59% and Smallest Pulse 3.66%, so Google Chirp 2 makes fewer errors by 1.06 points. On the eight licensed Ocular recordings, Google Chirp 2 scores 3.80% and Smallest Pulse 3.46%, with likely ranges of 2.93 to 4.60% and 2.66 to 4.22%. 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 2 faster than Smallest Pulse?
No. Smallest Pulse finishes the transcript 367ms sooner. Google Chirp 2 has the final transcript 568ms after the speaker stops and Smallest Pulse 201ms, at the median. Both are measured on the same 206 streamed turns.
Is Google Chirp 2 or Smallest Pulse better for voice agents?
Smallest Pulse finishes the transcript 367ms 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 2 and Smallest Pulse stream text while the speaker is talking?
Yes, both return partial text before the speaker stops. Google Chirp 2 shows first text after 4.50s and Smallest Pulse after 1.06s, at the median, so Smallest Pulse is 3.44s sooner.