Deepgram Nova-3 vs Speechmatics Linden
Deepgram Nova-3 is ahead on time to first text and final-text delay, and Speechmatics Linden on the Pipecat Dataset. The Ocular Dataset is 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 Deepgram Nova-3 for showing words while the caller is still talking (126ms sooner) and quick turn-taking once the caller stops (44ms sooner). Pick Speechmatics Linden for accuracy on clean, scripted audio (1.01 points lower). For 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
- Speechmatics Linden
- 2.46%7th
Speechmatics Linden, 1.01 points lower
- Deepgram Nova-3
- 4.39%11th
- Speechmatics Linden
- 3.93%7th
Too close to call: inside the margin of error
- Deepgram Nova-3
- 1.06s7th
- Speechmatics Linden
- 1.19s8th
Deepgram Nova-3, 126ms sooner
- Deepgram Nova-3
- 103ms4th
- Speechmatics Linden
- 147ms8th
Deepgram Nova-3, 44ms 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 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 | Deepgram Nova-3 | 1.06s | 1.10s | 2.07s |
| Speechmatics Linden | 1.19s | 1.56s | 2.52s | |
| Final-text delay | Deepgram Nova-3 | 103ms | 143ms | 155ms |
| 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 | Nova-3 | Linden |
|---|---|---|
| Pipecat Dataset WER | 3.46%12th of 17 | 2.46%7th of 17 |
| Ocular Dataset WER | 4.39%11th of 17 | 3.93%7th of 17 |
| Time to first text | 1.06s7th of 15 | 1.19s8th of 15 |
| Final-text delay | 103ms4th of 17 | 147ms8th 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 |
| Speechmatics Linden | 998 | 8 | 194 | 12 |
Only clips with usable text count, so the two totals can differ. How WER is scored.
Related comparisons
- Deepgram Nova-3 vs GPT-4o Mini Transcribe
- 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 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
- Speechmatics Linden vs Cartesia Ink 2
- Speechmatics Linden vs Soniox STT-RT v5
- Speechmatics Linden vs Inworld STT-1
- Speechmatics Linden vs GPT Realtime Whisper
- 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 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, Deepgram Nova-3 or Speechmatics Linden?
Speechmatics Linden is more accurate on the public clips. On the 1,000 public Pipecat clips, Deepgram Nova-3 scores 3.46% and Speechmatics Linden 2.46%, so Speechmatics Linden makes fewer errors by 1.01 points. On the eight licensed Ocular recordings, Deepgram Nova-3 scores 4.39% and Speechmatics Linden 3.93%, with likely ranges of 3.42 to 5.25% 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 Deepgram Nova-3 faster than Speechmatics Linden?
Yes. Deepgram Nova-3 finishes the transcript 44ms sooner. Deepgram Nova-3 has the final transcript 103ms after the speaker stops and Speechmatics Linden 147ms, at the median. Both are measured on the same 206 streamed turns.
Is Deepgram Nova-3 or Speechmatics Linden better for voice agents?
Deepgram Nova-3 finishes the transcript 44ms 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 Speechmatics Linden stream text while the speaker is talking?
Yes, both return partial text before the speaker stops. Deepgram Nova-3 shows first text after 1.06s and Speechmatics Linden after 1.19s, at the median, so Deepgram Nova-3 is 126ms sooner.