Deepgram Nova-3 vs GPT-4o Mini Transcribe
Deepgram Nova-3 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
Deepgram Nova-3 is the better pick over GPT-4o Mini Transcribe on every measure that separates them: quick turn-taking once the caller stops (527ms 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
- Deepgram Nova-3
- 3.46%12th
- GPT-4o Mini Transcribe
- 3.35%11th
Too close to call: inside the margin of error
- Deepgram Nova-3
- 4.39%11th
- GPT-4o Mini Transcribe
- 4.45%12th
Too close to call: inside the margin of error
- Deepgram Nova-3
- 1.06s7th
- GPT-4o Mini Transcribe
- No text until the speaker stops
Not comparable
- Deepgram Nova-3
- 103ms4th
- GPT-4o Mini Transcribe
- 630ms16th
Deepgram Nova-3, 527ms 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
Deepgram Nova-3 shows first text after 2.07s and final text after 155ms, and GPT-4o Mini Transcribe shows first text after 40.84s and final text after 1.53s, on a bad turn (P95) across the same streamed turns.
| Measure | Model | P50 | P90 | P95 |
|---|---|---|---|---|
| Time to first text | Deepgram Nova-3 | 1.06s | 1.10s | 2.07s |
| GPT-4o Mini Transcribe | No text until the speaker stops | |||
| Final-text delay | Deepgram Nova-3 | 103ms | 143ms | 155ms |
| GPT-4o Mini Transcribe | 630ms | 1.34s | 1.53s | |
- 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 | Nova-3 | 4o Mini Transcribe |
|---|---|---|
| Pipecat Dataset WER | 3.46%12th of 17 | 3.35%11th of 17 |
| Ocular Dataset WER | 4.39%11th of 17 | 4.45%12th of 17 |
| Time to first text | 1.06s7th of 15 | Not comparable |
| Final-text delay | 103ms4th of 17 | 630ms16th of 17 |
How much audio each model was tested on
| Model | Pipecat clips | Ocular recordings | Turns timed | Failed |
|---|---|---|---|---|
| Deepgram Nova-3 | 1,000 | 8 | 202 | 0 |
| GPT-4o Mini Transcribe | 1,000 | 8 | 206 | 0 |
Only clips with usable text count, so the two totals can differ. How WER is scored.
Related comparisons
Both providers, every model: Deepgram vs OpenAI
- Deepgram Nova-3 vs Smallest Pulse
- Deepgram Nova-3 vs GPT-4o Transcribe
- Deepgram Nova-3 vs Deepgram Flux English
- Deepgram Nova-3 vs Inworld STT-1
- Deepgram Nova-3 vs Soniox STT-RT v5
- Deepgram Nova-3 vs Speechmatics Linden
- Deepgram Nova-3 vs Cartesia Ink 2
- Deepgram Nova-3 vs GPT Realtime Whisper
- Deepgram Nova-3 vs Reson8
- Deepgram Nova-3 vs Google Chirp 3
- Deepgram Nova-3 vs Deepgram Flux Multilingual
- Deepgram Nova-3 vs AssemblyAI Universal 3.6 Pro
- Deepgram Nova-3 vs Gradium
- GPT-4o Mini Transcribe vs Smallest Pulse
- 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
Frequently asked questions
Which is more accurate, Deepgram Nova-3 or GPT-4o Mini Transcribe?
Deepgram Nova-3 and GPT-4o Mini Transcribe are too close to call on accuracy. On the 1,000 public Pipecat clips, Deepgram Nova-3 scores 3.46% and GPT-4o Mini Transcribe 3.35%, with likely ranges of 3.16 to 3.78% and 3.08 to 3.65%. The ranges overlap, so the difference is too close to call. On the eight licensed Ocular recordings, Deepgram Nova-3 scores 4.39% and GPT-4o Mini Transcribe 4.45%, with likely ranges of 3.42 to 5.25% 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.
Is Deepgram Nova-3 faster than GPT-4o Mini Transcribe?
Yes. Deepgram Nova-3 finishes the transcript 527ms sooner. Deepgram Nova-3 has the final transcript 103ms after the speaker stops and GPT-4o Mini Transcribe 630ms, at the median. Both are measured on the same 206 streamed turns.
Is Deepgram Nova-3 or GPT-4o Mini Transcribe better for voice agents?
Deepgram Nova-3 finishes the transcript 527ms 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 Deepgram Nova-3 and GPT-4o Mini Transcribe stream text while the speaker is talking?
Only Deepgram Nova-3. GPT-4o Mini Transcribe returns no text until the speaker stops, which matters if your agent reacts to partial transcripts.