GPT-4o Mini Transcribe vs Smallest Pulse
Smallest Pulse is ahead of GPT-4o Mini Transcribe on final-text delay. The Pipecat Dataset and The Ocular Dataset are 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 GPT-4o Mini Transcribe on every measure that separates them: quick turn-taking once the caller stops (429ms 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.
The four metrics, side by side
- GPT-4o Mini Transcribe
- 3.35%11th
- Smallest Pulse
- 3.66%13th
Too close to call: inside the margin of error
- GPT-4o Mini Transcribe
- 4.45%12th
- Smallest Pulse
- 3.46%3rd
Too close to call: inside the margin of error
- GPT-4o Mini Transcribe
- No text until the speaker stops
- Smallest Pulse
- 1.06s5th
Not comparable
- GPT-4o Mini Transcribe
- 630ms16th
- Smallest Pulse
- 201ms10th
Smallest Pulse, 429ms 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
GPT-4o Mini Transcribe shows first text after 40.84s and final text after 1.53s, 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 | GPT-4o Mini Transcribe | No text until the speaker stops | ||
| Smallest Pulse | 1.06s | 2.25s | 3.03s | |
| Final-text delay | GPT-4o Mini Transcribe | 630ms | 1.34s | 1.53s |
| 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 | 4o Mini Transcribe | Pulse |
|---|---|---|
| Pipecat Dataset WER | 3.35%11th of 17 | 3.66%13th of 17 |
| Ocular Dataset WER | 4.45%12th of 17 | 3.46%3rd of 17 |
| Time to first text | Not comparable | 1.06s5th of 15 |
| Final-text delay | 630ms16th of 17 | 201ms10th of 17 |
How much audio each model was tested on
| Model | Pipecat clips | Ocular recordings | Turns timed | Failed |
|---|---|---|---|---|
| GPT-4o Mini Transcribe | 1,000 | 8 | 206 | 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
- GPT-4o Mini Transcribe vs Deepgram Nova-3
- GPT-4o Mini Transcribe vs GPT-4o Transcribe
- GPT-4o Mini Transcribe vs Deepgram Flux English
- GPT-4o Mini Transcribe vs Inworld STT-1
- GPT-4o Mini Transcribe vs Soniox STT-RT v5
- GPT-4o Mini Transcribe vs Speechmatics Linden
- GPT-4o Mini Transcribe vs Cartesia Ink 2
- GPT-4o Mini Transcribe vs GPT Realtime Whisper
- GPT-4o Mini Transcribe vs Reson8
- GPT-4o Mini Transcribe vs Google Chirp 3
- GPT-4o Mini Transcribe vs AssemblyAI Universal 3.6 Pro
- GPT-4o Mini Transcribe vs Deepgram Flux Multilingual
- GPT-4o Mini Transcribe vs Gradium
- Smallest Pulse vs Deepgram Nova-3
- Smallest Pulse vs GPT-4o Transcribe
- Smallest Pulse vs Deepgram Flux English
- 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
- Smallest Pulse vs Gradium
Frequently asked questions
Which is more accurate, GPT-4o Mini Transcribe or Smallest Pulse?
GPT-4o Mini Transcribe and Smallest Pulse are too close to call on accuracy. On the 1,000 public Pipecat clips, GPT-4o Mini Transcribe scores 3.35% and Smallest Pulse 3.66%, with likely ranges of 3.08 to 3.65% and 3.34 to 3.99%. The ranges overlap, so the difference is too close to call. On the eight licensed Ocular recordings, GPT-4o Mini Transcribe scores 4.45% and Smallest Pulse 3.46%, with likely ranges of 3.22 to 5.55% 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 GPT-4o Mini Transcribe faster than Smallest Pulse?
No. Smallest Pulse finishes the transcript 429ms sooner. GPT-4o Mini Transcribe has the final transcript 630ms after the speaker stops and Smallest Pulse 201ms, at the median. Both are measured on the same 206 streamed turns.
Is GPT-4o Mini Transcribe or Smallest Pulse better for voice agents?
Smallest Pulse finishes the transcript 429ms 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 GPT-4o Mini Transcribe and Smallest Pulse stream text while the speaker is talking?
Only Smallest Pulse. GPT-4o Mini Transcribe returns no text until the speaker stops, which matters if your agent reacts to partial transcripts.