Cartesia Ink 2 vs Google Chirp 3
Cartesia Ink 2 is ahead of Google Chirp 3 on time to first text and final-text delay. The Pipecat Dataset and The Ocular Dataset are too close to call.
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
Cartesia Ink 2 is the better pick over Google Chirp 3 on every measure that separates them: showing words while the caller is still talking (2.97s sooner) and quick turn-taking once the caller stops (352ms 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.
The four metrics, side by side
- Cartesia Ink 2
- 2.39%6th
- Google Chirp 3
- 2.00%3rd
Too close to call: inside the margin of error
- Cartesia Ink 2
- 3.09%2nd
- Google Chirp 3
- 4.19%9th
Too close to call: inside the margin of error
- Cartesia Ink 2
- 1.51s11th
- Google Chirp 3
- 4.48s14th
Cartesia Ink 2, 2.97s sooner
- Cartesia Ink 2
- 123ms7th
- Google Chirp 3
- 475ms13th
Cartesia Ink 2, 352ms 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
Cartesia Ink 2 shows first text after 3.23s and final text after 145ms, and Google Chirp 3 shows first text after 7.97s and final text after 1.41s, on a bad turn (P95) across the same streamed turns.
| Measure | Model | P50 | P90 | P95 |
|---|---|---|---|---|
| Time to first text | Cartesia Ink 2 | 1.51s | 2.04s | 3.23s |
| Google Chirp 3 | 4.48s | 6.21s | 7.97s | |
| Final-text delay | Cartesia Ink 2 | 123ms | 139ms | 145ms |
| Google Chirp 3 | 475ms* | 941ms* | 1.41s* |
- 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 | Ink 2 | Chirp 3 |
|---|---|---|
| Pipecat Dataset WER | 2.39%6th of 17 | 2.00%3rd of 17 |
| Ocular Dataset WER | 3.09%2nd of 17 | 4.19%9th of 17 |
| Time to first text | 1.51s11th of 15 | 4.48s14th of 15 |
| Final-text delay | 123ms7th of 17 | 475ms13th of 17 |
How much audio each model was tested on
| Model | Pipecat clips | Ocular recordings | Turns timed | Failed |
|---|---|---|---|---|
| Cartesia Ink 2 | 1,000 | 8 | 198 | 0 |
| Google Chirp 3 | 1,000 | 8 | 206 | 0 |
Only clips with usable text count, so the two totals can differ. How WER is scored.
Related comparisons
- Cartesia Ink 2 vs Speechmatics Linden
- Cartesia Ink 2 vs Soniox STT-RT v5
- Cartesia Ink 2 vs GPT Realtime Whisper
- Cartesia Ink 2 vs Reson8
- Cartesia Ink 2 vs Inworld STT-1
- Cartesia Ink 2 vs AssemblyAI Universal 3.6 Pro
- Cartesia Ink 2 vs GPT-4o Mini Transcribe
- Cartesia Ink 2 vs Deepgram Nova-3
- Cartesia Ink 2 vs Smallest Pulse
- Cartesia Ink 2 vs GPT-4o Transcribe
- Cartesia Ink 2 vs Deepgram Flux English
- Cartesia Ink 2 vs Deepgram Flux Multilingual
- Cartesia Ink 2 vs Gradium
- 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 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 GPT-4o Transcribe
- Google Chirp 3 vs Deepgram Flux English
- Google Chirp 3 vs Deepgram Flux Multilingual
- Google Chirp 3 vs Gradium
Frequently asked questions
Which is more accurate, Cartesia Ink 2 or Google Chirp 3?
Cartesia Ink 2 and Google Chirp 3 are too close to call on accuracy. On the 1,000 public Pipecat clips, Cartesia Ink 2 scores 2.39% and Google Chirp 3 2.00%, with likely ranges of 2.13 to 2.65% and 1.77 to 2.25%. The ranges overlap, so the difference is too close to call. On the eight licensed Ocular recordings, Cartesia Ink 2 scores 3.09% and Google Chirp 3 4.19%, with likely ranges of 2.43 to 3.84% and 2.97 to 5.27%. 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 Cartesia Ink 2 faster than Google Chirp 3?
Yes. Cartesia Ink 2 finishes the transcript 352ms sooner. Cartesia Ink 2 has the final transcript 123ms after the speaker stops and Google Chirp 3 475ms, at the median. Both are measured on the same 206 streamed turns.
Is Cartesia Ink 2 or Google Chirp 3 better for voice agents?
Cartesia Ink 2 finishes the transcript 352ms 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 Cartesia Ink 2 and Google Chirp 3 stream text while the speaker is talking?
Yes, both return partial text before the speaker stops. Cartesia Ink 2 shows first text after 1.51s and Google Chirp 3 after 4.48s, at the median, so Cartesia Ink 2 is 2.97s sooner.