GPT Realtime Whisper vs Reson8
GPT Realtime Whisper is ahead on time to first text, and Reson8 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
Pick GPT Realtime Whisper for showing words while the caller is still talking (1.02s sooner). Pick Reson8 for quick turn-taking once the caller stops (308ms 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 Realtime Whisper
- 2.16%5th
- Reson8
- 2.10%4th
Too close to call: inside the margin of error
- GPT Realtime Whisper
- 3.53%4th
- Reson8
- 2.93%1st
Too close to call: inside the margin of error
- GPT Realtime Whisper
- 1.38s10th
- Reson8
- 2.40s13th
GPT Realtime Whisper, 1.02s sooner
- GPT Realtime Whisper
- 543ms14th
- Reson8
- 235ms12th
Reson8, 308ms 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 Realtime Whisper shows first text after 2.86s and final text after 669ms, and Reson8 shows first text after 10.20s and final text after 398ms, on a bad turn (P95) across the same streamed turns.
| Measure | Model | P50 | P90 | P95 |
|---|---|---|---|---|
| Time to first text | GPT Realtime Whisper | 1.38s | 1.84s | 2.86s |
| Reson8 | 2.40s | 7.97s | 10.20s | |
| Final-text delay | GPT Realtime Whisper | 543ms | 647ms | 669ms |
| Reson8 | 235ms | 357ms | 398ms |
- 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 | Realtime Whisper | Reson8 |
|---|---|---|
| Pipecat Dataset WER | 2.16%5th of 17 | 2.10%4th of 17 |
| Ocular Dataset WER | 3.53%4th of 17 | 2.93%1st of 17 |
| Time to first text | 1.38s10th of 15 | 2.40s13th of 15 |
| Final-text delay | 543ms14th of 17 | 235ms12th of 17 |
How much audio each model was tested on
| Model | Pipecat clips | Ocular recordings | Turns timed | Failed |
|---|---|---|---|---|
| GPT Realtime Whisper | 1,000 | 8 | 206 | 0 |
| Reson8 | 1,000 | 8 | 201 | 0 |
Only clips with usable text count, so the two totals can differ. How WER is scored.
Related comparisons
- GPT Realtime Whisper vs Google Chirp 3
- GPT Realtime Whisper vs Cartesia Ink 2
- GPT Realtime Whisper vs Speechmatics Linden
- GPT Realtime Whisper vs AssemblyAI Universal 3.6 Pro
- GPT Realtime Whisper vs Soniox STT-RT v5
- GPT Realtime Whisper vs Inworld STT-1
- GPT Realtime Whisper vs GPT-4o Mini Transcribe
- GPT Realtime Whisper vs Deepgram Nova-3
- GPT Realtime Whisper vs Smallest Pulse
- GPT Realtime Whisper vs GPT-4o Transcribe
- GPT Realtime Whisper vs Deepgram Flux English
- GPT Realtime Whisper vs Deepgram Flux Multilingual
- GPT Realtime Whisper vs Gradium
- Reson8 vs Google Chirp 3
- Reson8 vs Cartesia Ink 2
- Reson8 vs AssemblyAI Universal 3.6 Pro
- Reson8 vs Speechmatics Linden
- Reson8 vs Soniox STT-RT v5
- Reson8 vs Inworld STT-1
- Reson8 vs GPT-4o Mini Transcribe
- Reson8 vs Deepgram Nova-3
- Reson8 vs Smallest Pulse
- Reson8 vs GPT-4o Transcribe
- Reson8 vs Deepgram Flux English
- Reson8 vs Deepgram Flux Multilingual
- Reson8 vs Gradium
Frequently asked questions
Which is more accurate, GPT Realtime Whisper or Reson8?
GPT Realtime Whisper and Reson8 are too close to call on accuracy. On the 1,000 public Pipecat clips, GPT Realtime Whisper scores 2.16% and Reson8 2.10%, with likely ranges of 1.92 to 2.41% and 1.86 to 2.35%. The ranges overlap, so the difference is too close to call. On the eight licensed Ocular recordings, GPT Realtime Whisper scores 3.53% and Reson8 2.93%, with likely ranges of 2.58 to 4.51% and 2.29 to 3.68%. 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 Realtime Whisper faster than Reson8?
No. Reson8 finishes the transcript 308ms sooner. GPT Realtime Whisper has the final transcript 543ms after the speaker stops and Reson8 235ms, at the median. Both are measured on the same 206 streamed turns.
Is GPT Realtime Whisper or Reson8 better for voice agents?
Reson8 finishes the transcript 308ms 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 Realtime Whisper and Reson8 stream text while the speaker is talking?
Yes, both return partial text before the speaker stops. GPT Realtime Whisper shows first text after 1.38s and Reson8 after 2.40s, at the median, so GPT Realtime Whisper is 1.02s sooner.