AssemblyAI Universal 3.6 Pro is ahead of Google Chirp 3 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 Google Chirp 3 on every measure that separates them: showing words while the caller is still talking (4.00s sooner) and quick turn-taking once the caller stops (384ms 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, 4.00s sooner
AssemblyAI Universal 3.6 Pro, 384ms 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 Google Chirp 3 shows first text after 7.97s and final text after 1.41s, 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 |
| Google Chirp 3 | 4.48s | 6.21s | 7.97s | |
| Final-text delay | AssemblyAI Universal 3.6 Pro | 91ms | 210ms | 232ms |
| Google Chirp 3 | 475ms* | 941ms* | 1.41s* |
* Final-text delay is the observed time after stream close, because controlled finalization is not available for this model. Compare it with care against models that finalize on request.
Place among the 17 models on each metric. Lower is better on all four.
| Metric | Universal 3.6 Pro | Chirp 3 |
|---|---|---|
| Pipecat Dataset WER | 1.77%1st of 17 | 2.00%3rd of 17 |
| Ocular Dataset WER | 4.50%14th of 17 | 4.19%9th of 17 |
| Time to first text | 485ms1st of 15 | 4.48s14th of 15 |
| Final-text delay | 91ms3rd of 17 | 475ms13th of 17 |
| Model | Pipecat clips | Ocular recordings | Turns timed | Failed |
|---|---|---|---|---|
| AssemblyAI Universal 3.6 Pro | 1,000 | 8 | 206 | 0 |
| Google Chirp 3 | 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 Google
AssemblyAI Universal 3.6 Pro and Google Chirp 3 are too close to call on accuracy. On the 1,000 public Pipecat clips, AssemblyAI Universal 3.6 Pro scores 1.77% and Google Chirp 3 2.00%, with likely ranges of 1.55 to 2.00% and 1.77 to 2.25%. 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 Google Chirp 3 4.19%, with likely ranges of 3.66 to 5.34% and 2.97 to 5.27%. 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 384ms sooner. AssemblyAI Universal 3.6 Pro has the final transcript 91ms after the speaker stops and Google Chirp 3 475ms, at the median. Both are measured on the same 206 streamed turns.
AssemblyAI Universal 3.6 Pro finishes the transcript 384ms 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 Google Chirp 3 after 4.48s, at the median, so AssemblyAI Universal 3.6 Pro is 4.00s sooner.