AssemblyAI Universal 3.5 ProvsGPT-4o Mini Transcribe

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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)
  • Universal 3.5 Pro1.93% · 180ms
  • 4o Mini Transcribe3.35% · 630ms

AssemblyAI Universal 3.5 Pro is ahead of GPT-4o Mini Transcribe on the Pipecat Dataset and final-text delay. The Ocular Dataset is too close to call. AssemblyAI Universal 3.5 Pro has a newer release: AssemblyAI Universal 3.6 Pro vs GPT-4o Mini Transcribe.

Last updated Methodology by Dileep Chagam

Who is better at what

Universal 3.5 Pro4o Mini Transcribe
  • Pipecat Dataset WER1.93%3.35%
  • Ocular Dataset WER4.23%4.45%
  • Time to first text489msn/a
  • Final-text delay180ms630ms

Lower is better on every measure. Too close to call means the likely ranges overlap.

Universal 3.5 Pro vs 4o Mini Transcribe FAQ

  • AssemblyAI Universal 3.5 Pro is more accurate on the public clips. On the 1,000 public Pipecat clips, AssemblyAI Universal 3.5 Pro scores 1.93% and GPT-4o Mini Transcribe 3.35%, so AssemblyAI Universal 3.5 Pro makes fewer errors by 1.43 points. On the eight licensed Ocular recordings, AssemblyAI Universal 3.5 Pro scores 4.23% and GPT-4o Mini Transcribe 4.45%, with likely ranges of 3.57 to 4.68% and 3.22 to 5.55%. 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 3.5 Pro finishes the transcript 450ms sooner. AssemblyAI Universal 3.5 Pro has the final transcript 180ms after the speaker stops and GPT-4o Mini Transcribe 630ms, at the median. Both are measured on the same 206 streamed turns.

  • AssemblyAI Universal 3.5 Pro finishes the transcript 450ms 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.

  • Only AssemblyAI Universal 3.5 Pro. GPT-4o Mini Transcribe returns no text until the speaker stops, which matters if your agent reacts to partial transcripts.