GPT-4o Mini Transcribe vs Smallest Pulse

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Accuracy and speed

Left gets fewer words wrong. Lower has the final text ready sooner.

Accurate and fast0ms200ms400ms600ms800ms0%2%4%6%8%Words wrong on clean audio (Pipecat WER)
  • 4o Mini Transcribe3.35% · 630ms
  • Pulse3.66% · 201ms

Smallest Pulse is ahead of GPT-4o Mini Transcribe on both datasets together and final-text delay. The Pipecat Dataset and The Ocular Dataset are too close to call.

Last updated Methodology by Dileep Chagam

Who is better at what

4o Mini TranscribePulse
  • Overall WER3.73%3.59%
  • Pipecat Dataset WER3.35%3.66%
  • Ocular Dataset WER4.45%3.46%
  • Time to first textn/a1.06s
  • Final-text delay630ms201ms

Lower is better on every measure. Too close to call means the likely ranges overlap. Our guide covers testing OpenAI Realtime API voice agents.

4o Mini Transcribe vs Pulse FAQ

  • Smallest Pulse is more accurate on the public clips. On the 1,000 public Pipecat clips, GPT-4o Mini Transcribe scores 3.73% and Smallest Pulse 3.59%, so Smallest Pulse makes fewer errors by 0.15 points. On the eight licensed Ocular recordings, 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. Word error rate counts incorrect, missing, and extra words, so lower is better.

  • Final-text delay was not measured for one or both, so speed cannot be compared. Both are measured on the same 206 streamed turns.

  • GPT-4o Mini Transcribe and Smallest Pulse are level on the two figures a voice agent depends on most. A voice agent cannot reply until the final transcript arrives, and the Ocular recordings are real conversations.

  • Only Smallest Pulse. GPT-4o Mini Transcribe returns no text until the speaker stops, which matters if your agent reacts to partial transcripts.

Test your voice agent the same way.

Cekura runs these simulated calls on your agent and scores every one.