Cartesia Ink 2 vs GPT-4o Mini Transcribe
Accuracy and speed
Left gets fewer words wrong. Lower has the final text ready sooner.
- Ink 22.39% · 123ms
- 4o Mini Transcribe3.35% · 630ms
Cartesia Ink 2 is ahead of GPT-4o Mini Transcribe on both datasets together, the Pipecat Dataset and final-text delay. The Ocular Dataset is too close to call.
Last updated Methodology by Dileep Chagam
Who is better at what
- Overall WER2.63%3.73%
- Pipecat Dataset WER2.39%3.35%
- Ocular Dataset WER3.09%4.45%
- Time to first text1.51sn/a
- Final-text delay123ms630ms
Lower is better on every measure. Too close to call means the likely ranges overlap. For its voices, see our notes on Cartesia text to speech.
Ink 2 vs 4o Mini Transcribe FAQ
Which is more accurate, Cartesia Ink 2 or GPT-4o Mini Transcribe?
Cartesia Ink 2 is more accurate on both datasets. On the 1,000 public Pipecat clips, Cartesia Ink 2 scores 2.63% and GPT-4o Mini Transcribe 3.73%, so Cartesia Ink 2 makes fewer errors by 1.10 points. On the eight licensed Ocular recordings, Cartesia Ink 2 scores 2.39% and GPT-4o Mini Transcribe 3.35%, so Cartesia Ink 2 makes fewer errors by 0.97 points. Word error rate counts incorrect, missing, and extra words, so lower is better.
Cartesia Ink 2 is more accurate on both datasets. On the 1,000 public Pipecat clips, Cartesia Ink 2 scores 2.63% and GPT-4o Mini Transcribe 3.73%, so Cartesia Ink 2 makes fewer errors by 1.10 points. On the eight licensed Ocular recordings, Cartesia Ink 2 scores 2.39% and GPT-4o Mini Transcribe 3.35%, so Cartesia Ink 2 makes fewer errors by 0.97 points. Word error rate counts incorrect, missing, and extra words, so lower is better.
Final-text delay was not measured for one or both, so speed cannot be compared. Both are measured on the same 206 streamed turns.
Cartesia Ink 2 makes fewer errors on real conversations, and the two are not separated on speed. A voice agent cannot reply until the final transcript arrives, and the Ocular recordings are real conversations.
Only Cartesia Ink 2. GPT-4o Mini Transcribe returns no text until the speaker stops, which matters if your agent reacts to partial transcripts.
Test your voice agent the same way.
Cekura runs these simulated calls on your agent and scores every one.