GPT Realtime Whisper vs Speechmatics Linden
Speechmatics Linden is ahead of GPT Realtime Whisper on time to first text and 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
Speechmatics Linden is the better pick over GPT Realtime Whisper on every measure that separates them: showing words while the caller is still talking (189ms sooner) and quick turn-taking once the caller stops (396ms 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
- Speechmatics Linden
- 2.46%7th
Too close to call: inside the margin of error
- GPT Realtime Whisper
- 3.53%4th
- Speechmatics Linden
- 3.93%7th
Too close to call: inside the margin of error
- GPT Realtime Whisper
- 1.38s10th
- Speechmatics Linden
- 1.19s8th
Speechmatics Linden, 189ms sooner
- GPT Realtime Whisper
- 543ms14th
- Speechmatics Linden
- 147ms8th
Speechmatics Linden, 396ms 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 Speechmatics Linden shows first text after 2.52s and final text after 213ms, 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 |
| Speechmatics Linden | 1.19s | 1.56s | 2.52s | |
| Final-text delay | GPT Realtime Whisper | 543ms | 647ms | 669ms |
| Speechmatics Linden | 147ms | 192ms | 213ms |
- 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 | Linden |
|---|---|---|
| Pipecat Dataset WER | 2.16%5th of 17 | 2.46%7th of 17 |
| Ocular Dataset WER | 3.53%4th of 17 | 3.93%7th of 17 |
| Time to first text | 1.38s10th of 15 | 1.19s8th of 15 |
| Final-text delay | 543ms14th of 17 | 147ms8th 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 |
| Speechmatics Linden | 998 | 8 | 194 | 12 |
Only clips with usable text count, so the two totals can differ. How WER is scored.
Related comparisons
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- GPT Realtime Whisper vs Gradium
- Speechmatics Linden vs Cartesia Ink 2
- Speechmatics Linden vs Soniox STT-RT v5
- Speechmatics Linden vs Inworld STT-1
- Speechmatics Linden vs Reson8
- Speechmatics Linden vs Google Chirp 3
- Speechmatics Linden vs AssemblyAI Universal 3.6 Pro
- Speechmatics Linden vs GPT-4o Mini Transcribe
- Speechmatics Linden vs Deepgram Nova-3
- Speechmatics Linden vs Smallest Pulse
- Speechmatics Linden vs GPT-4o Transcribe
- Speechmatics Linden vs Deepgram Flux English
- Speechmatics Linden vs Deepgram Flux Multilingual
- Speechmatics Linden vs Gradium
Frequently asked questions
Which is more accurate, GPT Realtime Whisper or Speechmatics Linden?
GPT Realtime Whisper and Speechmatics Linden are too close to call on accuracy. On the 1,000 public Pipecat clips, GPT Realtime Whisper scores 2.16% and Speechmatics Linden 2.46%, with likely ranges of 1.92 to 2.41% and 2.19 to 2.73%. The ranges overlap, so the difference is too close to call. On the eight licensed Ocular recordings, GPT Realtime Whisper scores 3.53% and Speechmatics Linden 3.93%, with likely ranges of 2.58 to 4.51% and 2.94 to 5.19%. 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 Speechmatics Linden?
No. Speechmatics Linden finishes the transcript 396ms sooner. GPT Realtime Whisper has the final transcript 543ms after the speaker stops and Speechmatics Linden 147ms, at the median. Both are measured on the same 206 streamed turns.
Is GPT Realtime Whisper or Speechmatics Linden better for voice agents?
Speechmatics Linden finishes the transcript 396ms 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 Speechmatics Linden 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 Speechmatics Linden after 1.19s, at the median, so Speechmatics Linden is 189ms sooner.