Gradium is ahead on final-text delay, and GPT-4o Mini Transcribe on the Pipecat Dataset. The two tie on the Ocular Dataset.
Last updated Methodology by Dileep Chagam
Each dot is one model. Bottom-left is best: fewer errors and a faster final transcript.
Pick Gradium for quick turn-taking once the caller stops (418ms sooner). Pick GPT-4o Mini Transcribe for accuracy on clean, scripted audio (3.12 points lower). They are level on accuracy on real phone conversations.
GPT-4o Mini Transcribe, 3.12 points lower
Level
Not comparable
Gradium, 418ms sooner
Lower is better on every metric. The small figure is each model's place in the whole field. What each metric measures.
Gradium shows first text after 7.32s and final text after 280ms, and GPT-4o Mini Transcribe shows first text after 40.84s and final text after 1.53s, on a bad turn (P95) across the same streamed turns.
| Measure | Model | P50 | P90 | P95 |
|---|---|---|---|---|
| Time to first text | Gradium | 1.71s | 4.05s | 7.32s |
| GPT-4o Mini Transcribe | No text until the speaker stops | |||
| Final-text delay | Gradium | 212ms | 266ms | 280ms |
| GPT-4o Mini Transcribe | 630ms | 1.34s | 1.53s | |
Place among the 17 models on each metric. Lower is better on all four.
| Metric | Gradium | 4o Mini Transcribe |
|---|---|---|
| Pipecat Dataset WER | 6.48%17th of 17 | 3.35%11th of 17 |
| Ocular Dataset WER | 4.45%12th of 17 | 4.45%12th of 17 |
| Time to first text | 1.71s12th of 15 | Not comparable |
| Final-text delay | 212ms11th of 17 | 630ms16th of 17 |
| Model | Pipecat clips | Ocular recordings | Turns timed | Failed |
|---|---|---|---|---|
| Gradium | 1,000 | 8 | 198 | 0 |
| GPT-4o Mini Transcribe | 1,000 | 8 | 206 | 0 |
Only clips with usable text count, so the two totals can differ. How WER is scored.
GPT-4o Mini Transcribe is more accurate on the public clips. On the 1,000 public Pipecat clips, Gradium scores 6.48% and GPT-4o Mini Transcribe 3.35%, so GPT-4o Mini Transcribe makes fewer errors by 3.12 points. On the eight licensed Ocular recordings, Gradium scores 4.45% and GPT-4o Mini Transcribe 4.45%, which is a tie. Word error rate counts incorrect, missing, and extra words, so lower is better.
Yes. Gradium finishes the transcript 418ms sooner. Gradium has the final transcript 212ms after the speaker stops and GPT-4o Mini Transcribe 630ms, at the median. Both are measured on the same 206 streamed turns.
Gradium finishes the transcript 418ms sooner, and the two are level on real conversations. A voice agent cannot reply until the final transcript arrives, and the Ocular recordings are real conversations.
Only Gradium. GPT-4o Mini Transcribe returns no text until the speaker stops, which matters if your agent reacts to partial transcripts.