Gradium vs GPT-4o Transcribe
Accuracy and speed
Left gets fewer words wrong. Lower has the final text ready sooner.
- Gradium6.48% · 212ms
- 4o Transcribe3.90% · 652ms
Gradium is ahead on both datasets together, the Ocular Dataset and final-text delay, and GPT-4o Transcribe on the Pipecat Dataset.
Last updated Methodology by Dileep Chagam
Who is better at what
- Overall WER5.78%6.85%
- Pipecat Dataset WER6.48%3.90%
- Ocular Dataset WER4.45%12.45%
- Time to first text1.71sn/a
- Final-text delay212ms652ms
Lower is better on every measure. Too close to call means the likely ranges overlap. Our guide explains how word error rate is measured.
Gradium vs 4o Transcribe FAQ
Which is more accurate, Gradium or GPT-4o Transcribe?
Gradium is more accurate on clean public clips and GPT-4o Transcribe on real conversations. On the 1,000 public Pipecat clips, Gradium scores 5.78% and GPT-4o Transcribe 6.85%, so Gradium makes fewer errors by 1.07 points. On the eight licensed Ocular recordings, Gradium scores 6.48% and GPT-4o Transcribe 3.90%, so GPT-4o Transcribe makes fewer errors by 2.57 points. Word error rate counts incorrect, missing, and extra words, so lower is better.
Gradium is more accurate on clean public clips and GPT-4o Transcribe on real conversations. On the 1,000 public Pipecat clips, Gradium scores 5.78% and GPT-4o Transcribe 6.85%, so Gradium makes fewer errors by 1.07 points. On the eight licensed Ocular recordings, Gradium scores 6.48% and GPT-4o Transcribe 3.90%, so GPT-4o Transcribe makes fewer errors by 2.57 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.
GPT-4o Transcribe 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 Gradium. GPT-4o 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.