AssemblyAI Universal 3.6 Pro is ahead of GPT Realtime Whisper 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
Each dot is one model. Bottom-left is best: fewer errors and a faster final transcript.
AssemblyAI Universal 3.6 Pro is the better pick over GPT Realtime Whisper on every measure that separates them: showing words while the caller is still talking (894ms sooner) and quick turn-taking once the caller stops (452ms 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.
Too close to call: inside the margin of error
Too close to call: inside the margin of error
AssemblyAI Universal 3.6 Pro, 894ms sooner
AssemblyAI Universal 3.6 Pro, 452ms sooner
Lower is better on every metric. The small figure is each model's place in the whole field. What each metric measures.
AssemblyAI Universal 3.6 Pro shows first text after 967ms and final text after 232ms, and GPT Realtime Whisper shows first text after 2.86s and final text after 669ms, on a bad turn (P95) across the same streamed turns.
| Measure | Model | P50 | P90 | P95 |
|---|---|---|---|---|
| Time to first text | AssemblyAI Universal 3.6 Pro | 485ms | 966ms | 967ms |
| GPT Realtime Whisper | 1.38s | 1.84s | 2.86s | |
| Final-text delay | AssemblyAI Universal 3.6 Pro | 91ms | 210ms | 232ms |
| GPT Realtime Whisper | 543ms | 647ms | 669ms |
Place among the 17 models on each metric. Lower is better on all four.
| Metric | Universal 3.6 Pro | Realtime Whisper |
|---|---|---|
| Pipecat Dataset WER | 1.77%1st of 17 | 2.16%5th of 17 |
| Ocular Dataset WER | 4.50%14th of 17 | 3.53%4th of 17 |
| Time to first text | 485ms1st of 15 | 1.38s10th of 15 |
| Final-text delay | 91ms3rd of 17 | 543ms14th of 17 |
| Model | Pipecat clips | Ocular recordings | Turns timed | Failed |
|---|---|---|---|---|
| AssemblyAI Universal 3.6 Pro | 1,000 | 8 | 206 | 0 |
| GPT Realtime Whisper | 1,000 | 8 | 206 | 0 |
Only clips with usable text count, so the two totals can differ. How WER is scored.
Both providers, every model: AssemblyAI vs OpenAI
AssemblyAI Universal 3.6 Pro and GPT Realtime Whisper are too close to call on accuracy. On the 1,000 public Pipecat clips, AssemblyAI Universal 3.6 Pro scores 1.77% and GPT Realtime Whisper 2.16%, with likely ranges of 1.55 to 2.00% and 1.92 to 2.41%. The ranges overlap, so the difference is too close to call. On the eight licensed Ocular recordings, AssemblyAI Universal 3.6 Pro scores 4.50% and GPT Realtime Whisper 3.53%, with likely ranges of 3.66 to 5.34% and 2.58 to 4.51%. The ranges overlap, so the difference is too close to call. Word error rate counts incorrect, missing, and extra words, so lower is better.
Yes. AssemblyAI Universal 3.6 Pro finishes the transcript 452ms sooner. AssemblyAI Universal 3.6 Pro has the final transcript 91ms after the speaker stops and GPT Realtime Whisper 543ms, at the median. Both are measured on the same 206 streamed turns.
AssemblyAI Universal 3.6 Pro finishes the transcript 452ms 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.
Yes, both return partial text before the speaker stops. AssemblyAI Universal 3.6 Pro shows first text after 485ms and GPT Realtime Whisper after 1.38s, at the median, so AssemblyAI Universal 3.6 Pro is 894ms sooner.