AssemblyAI Universal 3.6 Pro vs Gradium
AssemblyAI Universal 3.6 Pro is ahead of Gradium on the Pipecat Dataset, time to first text and final-text delay. The Ocular Dataset is too close to call.
Last updated Methodology by Dileep Chagam
Accuracy vs speed
Each dot is one model. Bottom-left is best: fewer errors and a faster final transcript.
Which to pick
AssemblyAI Universal 3.6 Pro is the better pick over Gradium on every measure that separates them: accuracy on clean, scripted audio (4.71 points lower), showing words while the caller is still talking (1.22s sooner) and quick turn-taking once the caller stops (121ms sooner). For accuracy on real phone conversations, the gap is inside the margin of error, so neither is ahead.
The four metrics, side by side
- AssemblyAI Universal 3.6 Pro
- 1.77%1st
- Gradium
- 6.48%17th
AssemblyAI Universal 3.6 Pro, 4.71 points lower
- AssemblyAI Universal 3.6 Pro
- 4.50%14th
- Gradium
- 4.45%12th
Too close to call: inside the margin of error
- AssemblyAI Universal 3.6 Pro
- 485ms1st
- Gradium
- 1.71s12th
AssemblyAI Universal 3.6 Pro, 1.22s sooner
- AssemblyAI Universal 3.6 Pro
- 91ms3rd
- Gradium
- 212ms11th
AssemblyAI Universal 3.6 Pro, 121ms sooner
Lower is better on every metric. The small figure is each model's place in the whole field. What each metric measures.
- WER · Word error rate
- Share of words the model got wrong: replaced, missing or added. Lower is better.
- Pipecat Dataset
- 1,000 short public clips from Pipecat's STT benchmark dataset.
- Ocular Dataset
- 8 recordings from 4 real phone conversations, licensed from Ocular.
- TTFT · Time to first text
- How long after the audio starts streaming until the first words appear.
- TTFS · Final-text delay
- How long after the caller stops until the full transcript arrives. A voice agent waits for this before it replies.
First text and final text, at three percentiles
AssemblyAI Universal 3.6 Pro shows first text after 967ms and final text after 232ms, and Gradium shows first text after 7.32s and final text after 280ms, 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 |
| Gradium | 1.71s | 4.05s | 7.32s | |
| Final-text delay | AssemblyAI Universal 3.6 Pro | 91ms | 210ms | 232ms |
| Gradium | 212ms | 266ms | 280ms |
- P50 / P90 / P95 · Typical, slow and slowest turns
- Half of turns are faster than P50. Only 1 in 10 is slower than P90, and 1 in 20 slower than P95.
How each ranks among all 17 models
Place among the 17 models on each metric. Lower is better on all four.
| Metric | Universal 3.6 Pro | Gradium |
|---|---|---|
| Pipecat Dataset WER | 1.77%1st of 17 | 6.48%17th of 17 |
| Ocular Dataset WER | 4.50%14th of 17 | 4.45%12th of 17 |
| Time to first text | 485ms1st of 15 | 1.71s12th of 15 |
| Final-text delay | 91ms3rd of 17 | 212ms11th of 17 |
How much audio each model was tested on
| Model | Pipecat clips | Ocular recordings | Turns timed | Failed |
|---|---|---|---|---|
| AssemblyAI Universal 3.6 Pro | 1,000 | 8 | 206 | 0 |
| Gradium | 1,000 | 8 | 198 | 0 |
Only clips with usable text count, so the two totals can differ. How WER is scored.
Related comparisons
- AssemblyAI Universal 3.6 Pro vs AssemblyAI Universal 3.5 Pro
- AssemblyAI Universal 3.6 Pro vs Google Chirp 3
- AssemblyAI Universal 3.6 Pro vs Reson8
- AssemblyAI Universal 3.6 Pro vs GPT Realtime Whisper
- AssemblyAI Universal 3.6 Pro vs Cartesia Ink 2
- AssemblyAI Universal 3.6 Pro vs Speechmatics Linden
- AssemblyAI Universal 3.6 Pro vs Soniox STT-RT v5
- AssemblyAI Universal 3.6 Pro vs Inworld STT-1
- AssemblyAI Universal 3.6 Pro vs GPT-4o Mini Transcribe
- AssemblyAI Universal 3.6 Pro vs Deepgram Nova-3
- AssemblyAI Universal 3.6 Pro vs Smallest Pulse
- AssemblyAI Universal 3.6 Pro vs GPT-4o Transcribe
- AssemblyAI Universal 3.6 Pro vs Deepgram Flux English
- AssemblyAI Universal 3.6 Pro vs Deepgram Flux Multilingual
- Gradium vs Deepgram Flux Multilingual
- Gradium vs Deepgram Flux English
- Gradium vs GPT-4o Transcribe
- Gradium vs Smallest Pulse
- Gradium vs Deepgram Nova-3
- Gradium vs GPT-4o Mini Transcribe
- Gradium vs Inworld STT-1
- Gradium vs Soniox STT-RT v5
- Gradium vs Speechmatics Linden
- Gradium vs Cartesia Ink 2
- Gradium vs GPT Realtime Whisper
- Gradium vs Reson8
- Gradium vs Google Chirp 3
Frequently asked questions
Which is more accurate, AssemblyAI Universal 3.6 Pro or Gradium?
AssemblyAI Universal 3.6 Pro is more accurate on the public clips. On the 1,000 public Pipecat clips, AssemblyAI Universal 3.6 Pro scores 1.77% and Gradium 6.48%, so AssemblyAI Universal 3.6 Pro makes fewer errors by 4.71 points. On the eight licensed Ocular recordings, AssemblyAI Universal 3.6 Pro scores 4.50% and Gradium 4.45%, with likely ranges of 3.66 to 5.34% and 3.17 to 5.90%. The ranges overlap, so the difference is too close to call. Word error rate counts incorrect, missing, and extra words, so lower is better.
Is AssemblyAI Universal 3.6 Pro faster than Gradium?
Yes. AssemblyAI Universal 3.6 Pro finishes the transcript 121ms sooner. AssemblyAI Universal 3.6 Pro has the final transcript 91ms after the speaker stops and Gradium 212ms, at the median. Both are measured on the same 206 streamed turns.
Is AssemblyAI Universal 3.6 Pro or Gradium better for voice agents?
AssemblyAI Universal 3.6 Pro finishes the transcript 121ms 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.
Do AssemblyAI Universal 3.6 Pro and Gradium stream text while the speaker is talking?
Yes, both return partial text before the speaker stops. AssemblyAI Universal 3.6 Pro shows first text after 485ms and Gradium after 1.71s, at the median, so AssemblyAI Universal 3.6 Pro is 1.22s sooner.