Gradium vs Smallest Pulse
Smallest Pulse 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
Smallest Pulse is the better pick over Gradium on every measure that separates them: accuracy on clean, scripted audio (2.82 points lower), showing words while the caller is still talking (648ms sooner) and quick turn-taking once the caller stops (11ms 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
- Gradium
- 6.48%17th
- Smallest Pulse
- 3.66%13th
Smallest Pulse, 2.82 points lower
- Gradium
- 4.45%12th
- Smallest Pulse
- 3.46%3rd
Too close to call: inside the margin of error
- Gradium
- 1.71s12th
- Smallest Pulse
- 1.06s5th
Smallest Pulse, 648ms sooner
- Gradium
- 212ms11th
- Smallest Pulse
- 201ms10th
Smallest Pulse, 11ms 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
Gradium shows first text after 7.32s and final text after 280ms, and Smallest Pulse shows first text after 3.03s and final text after 773ms, 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 |
| Smallest Pulse | 1.06s | 2.25s | 3.03s | |
| Final-text delay | Gradium | 212ms | 266ms | 280ms |
| Smallest Pulse | 201ms | 356ms | 773ms |
- 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 | Gradium | Pulse |
|---|---|---|
| Pipecat Dataset WER | 6.48%17th of 17 | 3.66%13th of 17 |
| Ocular Dataset WER | 4.45%12th of 17 | 3.46%3rd of 17 |
| Time to first text | 1.71s12th of 15 | 1.06s5th of 15 |
| Final-text delay | 212ms11th of 17 | 201ms10th of 17 |
How much audio each model was tested on
| Model | Pipecat clips | Ocular recordings | Turns timed | Failed |
|---|---|---|---|---|
| Gradium | 1,000 | 8 | 198 | 0 |
| Smallest Pulse | 1,000 | 8 | 206 | 0 |
Only clips with usable text count, so the two totals can differ. How WER is scored.
Related comparisons
- Gradium vs Deepgram Flux Multilingual
- Gradium vs Deepgram Flux English
- Gradium vs GPT-4o Transcribe
- 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
- Gradium vs AssemblyAI Universal 3.6 Pro
- Smallest Pulse vs Deepgram Nova-3
- Smallest Pulse vs GPT-4o Transcribe
- Smallest Pulse vs Deepgram Flux English
- Smallest Pulse vs GPT-4o Mini Transcribe
- Smallest Pulse vs Inworld STT-1
- Smallest Pulse vs Soniox STT-RT v5
- Smallest Pulse vs Speechmatics Linden
- Smallest Pulse vs Cartesia Ink 2
- Smallest Pulse vs Deepgram Flux Multilingual
- Smallest Pulse vs GPT Realtime Whisper
- Smallest Pulse vs Reson8
- Smallest Pulse vs Google Chirp 3
- Smallest Pulse vs AssemblyAI Universal 3.6 Pro
Frequently asked questions
Which is more accurate, Gradium or Smallest Pulse?
Smallest Pulse is more accurate on the public clips. On the 1,000 public Pipecat clips, Gradium scores 6.48% and Smallest Pulse 3.66%, so Smallest Pulse makes fewer errors by 2.82 points. On the eight licensed Ocular recordings, Gradium scores 4.45% and Smallest Pulse 3.46%, with likely ranges of 3.17 to 5.90% and 2.66 to 4.22%. 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 Gradium faster than Smallest Pulse?
No. Smallest Pulse finishes the transcript 11ms sooner. Gradium has the final transcript 212ms after the speaker stops and Smallest Pulse 201ms, at the median. Both are measured on the same 206 streamed turns.
Is Gradium or Smallest Pulse better for voice agents?
Smallest Pulse finishes the transcript 11ms 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 Gradium and Smallest Pulse stream text while the speaker is talking?
Yes, both return partial text before the speaker stops. Gradium shows first text after 1.71s and Smallest Pulse after 1.06s, at the median, so Smallest Pulse is 648ms sooner.