Left gets fewer words wrong. Lower has the final text ready sooner.
Google Chirp 3 is ahead of GPT-4o Transcribe on both datasets together, the Pipecat Dataset, the Ocular Dataset and final-text delay.
Last updated Methodology by Dileep Chagam
Lower is better on every measure. Too close to call means the likely ranges overlap. For the wider field, see our pick of the best voice AI APIs for real-time audio.
Google Chirp 3 is more accurate on both datasets. On the 1,000 public Pipecat clips, Google Chirp 3 scores 2.76% and GPT-4o Transcribe 6.85%, so Google Chirp 3 makes fewer errors by 4.09 points. On the eight licensed Ocular recordings, Google Chirp 3 scores 2.00% and GPT-4o Transcribe 3.90%, so Google Chirp 3 makes fewer errors by 1.90 points. Word error rate counts incorrect, missing, and extra words, so lower is better.
Google Chirp 3 is more accurate on both datasets. On the 1,000 public Pipecat clips, Google Chirp 3 scores 2.76% and GPT-4o Transcribe 6.85%, so Google Chirp 3 makes fewer errors by 4.09 points. On the eight licensed Ocular recordings, Google Chirp 3 scores 2.00% and GPT-4o Transcribe 3.90%, so Google Chirp 3 makes fewer errors by 1.90 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.
Google Chirp 3 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 Google Chirp 3. GPT-4o Transcribe returns no text until the speaker stops, which matters if your agent reacts to partial transcripts.
Cekura runs these simulated calls on your agent and scores every one.