Deepgram Flux English vs GPT-4o Transcribe
Deepgram Flux English is ahead of GPT-4o Transcribe on the Ocular Dataset and final-text delay. The two tie on the Pipecat Dataset.
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 Flux English is the better pick over GPT-4o Transcribe on every measure that separates them: accuracy on real phone conversations (8.27 points lower) and quick turn-taking once the caller stops (544ms sooner). They are level on accuracy on clean, scripted audio.
The four metrics, side by side
- Deepgram Flux English
- 3.90%15th
- GPT-4o Transcribe
- 3.90%14th
Level
- Deepgram Flux English
- 4.18%8th
- GPT-4o Transcribe
- 12.45%17th
Deepgram Flux English, 8.27 points lower
- Deepgram Flux English
- 791ms3rd
- GPT-4o Transcribe
- No text until the speaker stops
Not comparable
- Deepgram Flux English
- 108ms5th
- GPT-4o Transcribe
- 652ms17th
Deepgram Flux English, 544ms 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 Flux English shows first text after 1.51s and final text after 141ms, and GPT-4o Transcribe shows first text after 40.63s and final text after 1.97s, on a bad turn (P95) across the same streamed turns.
| Measure | Model | P50 | P90 | P95 |
|---|---|---|---|---|
| Time to first text | Deepgram Flux English | 791ms | 1.23s | 1.51s |
| GPT-4o Transcribe | No text until the speaker stops | |||
| Final-text delay | Deepgram Flux English | 108ms | 132ms | 141ms |
| GPT-4o Transcribe | 652ms | 1.73s | 1.97s | |
- 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 | Flux English | 4o Transcribe |
|---|---|---|
| Pipecat Dataset WER | 3.90%15th of 17 | 3.90%14th of 17 |
| Ocular Dataset WER | 4.18%8th of 17 | 12.45%17th of 17 |
| Time to first text | 791ms3rd of 15 | Not comparable |
| Final-text delay | 108ms5th of 17 | 652ms17th of 17 |
How much audio each model was tested on
| Model | Pipecat clips | Ocular recordings | Turns timed | Failed |
|---|---|---|---|---|
| Deepgram Flux English | 999 | 8 | 199 | 7 |
| GPT-4o 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 Flux English vs Smallest Pulse
- Deepgram Flux English vs Deepgram Nova-3
- Deepgram Flux English vs GPT-4o Mini Transcribe
- Deepgram Flux English vs Deepgram Flux Multilingual
- Deepgram Flux English vs Inworld STT-1
- Deepgram Flux English vs Soniox STT-RT v5
- Deepgram Flux English vs Speechmatics Linden
- Deepgram Flux English vs Cartesia Ink 2
- Deepgram Flux English vs GPT Realtime Whisper
- Deepgram Flux English vs Reson8
- Deepgram Flux English vs Google Chirp 3
- Deepgram Flux English vs AssemblyAI Universal 3.6 Pro
- Deepgram Flux English vs Gradium
- GPT-4o Transcribe vs Smallest Pulse
- GPT-4o Transcribe vs Deepgram Nova-3
- GPT-4o Transcribe vs GPT-4o Mini Transcribe
- GPT-4o Transcribe vs Deepgram Flux Multilingual
- GPT-4o Transcribe vs Inworld STT-1
- GPT-4o Transcribe vs Soniox STT-RT v5
- GPT-4o Transcribe vs Speechmatics Linden
- GPT-4o Transcribe vs Cartesia Ink 2
- GPT-4o Transcribe vs GPT Realtime Whisper
- GPT-4o Transcribe vs Reson8
- GPT-4o Transcribe vs Google Chirp 3
- GPT-4o Transcribe vs AssemblyAI Universal 3.6 Pro
- GPT-4o Transcribe vs Gradium
Frequently asked questions
Which is more accurate, Deepgram Flux English or GPT-4o Transcribe?
Deepgram Flux English is more accurate on real conversations. On the 1,000 public Pipecat clips, Deepgram Flux English scores 3.90% and GPT-4o Transcribe 3.90%, which is a tie. On the eight licensed Ocular recordings, Deepgram Flux English scores 4.18% and GPT-4o Transcribe 12.45%, so Deepgram Flux English makes fewer errors by 8.27 points. Word error rate counts incorrect, missing, and extra words, so lower is better.
Is Deepgram Flux English faster than GPT-4o Transcribe?
Yes. Deepgram Flux English finishes the transcript 544ms sooner. Deepgram Flux English has the final transcript 108ms after the speaker stops and GPT-4o Transcribe 652ms, at the median. Both are measured on the same 206 streamed turns.
Is Deepgram Flux English or GPT-4o Transcribe better for voice agents?
Deepgram Flux English is the stronger pick for voice agents: it makes fewer errors on real conversations and finishes the transcript 544ms sooner. A voice agent cannot reply until the final transcript arrives, and the Ocular recordings are real conversations.
Do Deepgram Flux English and GPT-4o Transcribe stream text while the speaker is talking?
Only Deepgram Flux English. GPT-4o Transcribe returns no text until the speaker stops, which matters if your agent reacts to partial transcripts.