Inworld STT-1 vs GPT Realtime Whisper
Inworld STT-1 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
Inworld STT-1 is the better pick over GPT Realtime Whisper on every measure that separates them: showing words while the caller is still talking (316ms sooner) and quick turn-taking once the caller stops (502ms 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
- Inworld STT-1
- 2.72%10th
- GPT Realtime Whisper
- 2.16%5th
Too close to call: inside the margin of error
- Inworld STT-1
- 10.60%16th
- GPT Realtime Whisper
- 3.53%4th
Too close to call: inside the margin of error
- Inworld STT-1
- 1.06s6th
- GPT Realtime Whisper
- 1.38s10th
Inworld STT-1, 316ms sooner
- Inworld STT-1
- 41ms2nd
- GPT Realtime Whisper
- 543ms14th
Inworld STT-1, 502ms 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
Inworld STT-1 shows first text after 1.07s and final text after 65ms, and GPT Realtime Whisper shows first text after 2.86s and final text after 669ms, on a bad turn (P95) across the same streamed turns.
| Measure | Model | P50 | P90 | P95 |
|---|---|---|---|---|
| Time to first text | Inworld STT-1 | 1.06s | 1.07s | 1.07s |
| GPT Realtime Whisper | 1.38s | 1.84s | 2.86s | |
| Final-text delay | Inworld STT-1 | 41ms | 60ms | 65ms |
| GPT Realtime Whisper | 543ms | 647ms | 669ms |
- 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 | STT-1 | Realtime Whisper |
|---|---|---|
| Pipecat Dataset WER | 2.72%10th of 17 | 2.16%5th of 17 |
| Ocular Dataset WER | 10.60%16th of 17 | 3.53%4th of 17 |
| Time to first text | 1.06s6th of 15 | 1.38s10th of 15 |
| Final-text delay | 41ms2nd of 17 | 543ms14th of 17 |
How much audio each model was tested on
| Model | Pipecat clips | Ocular recordings | Turns timed | Failed |
|---|---|---|---|---|
| Inworld STT-1 | 1,000 | 8 | 206 | 0 |
| GPT Realtime Whisper | 1,000 | 8 | 206 | 0 |
Only clips with usable text count, so the two totals can differ. How WER is scored.
Related comparisons
- Inworld STT-1 vs Soniox STT-RT v5
- Inworld STT-1 vs Speechmatics Linden
- Inworld STT-1 vs Cartesia Ink 2
- Inworld STT-1 vs Reson8
- Inworld STT-1 vs GPT-4o Mini Transcribe
- Inworld STT-1 vs Google Chirp 3
- Inworld STT-1 vs Deepgram Nova-3
- Inworld STT-1 vs Smallest Pulse
- Inworld STT-1 vs AssemblyAI Universal 3.6 Pro
- Inworld STT-1 vs GPT-4o Transcribe
- Inworld STT-1 vs Deepgram Flux English
- Inworld STT-1 vs Deepgram Flux Multilingual
- Inworld STT-1 vs Gradium
- GPT Realtime Whisper vs Reson8
- 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 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
Frequently asked questions
Which is more accurate, Inworld STT-1 or GPT Realtime Whisper?
Inworld STT-1 and GPT Realtime Whisper are too close to call on accuracy. On the 1,000 public Pipecat clips, Inworld STT-1 scores 2.72% and GPT Realtime Whisper 2.16%, with likely ranges of 1.67 to 4.68% and 1.92 to 2.41%. The ranges overlap, so the difference is too close to call. On the eight licensed Ocular recordings, Inworld STT-1 scores 10.60% and GPT Realtime Whisper 3.53%, with likely ranges of 3.85 to 22.76% and 2.58 to 4.51%. 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 Inworld STT-1 faster than GPT Realtime Whisper?
Yes. Inworld STT-1 finishes the transcript 502ms sooner. Inworld STT-1 has the final transcript 41ms after the speaker stops and GPT Realtime Whisper 543ms, at the median. Both are measured on the same 206 streamed turns.
Is Inworld STT-1 or GPT Realtime Whisper better for voice agents?
Inworld STT-1 finishes the transcript 502ms 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 Inworld STT-1 and GPT Realtime Whisper stream text while the speaker is talking?
Yes, both return partial text before the speaker stops. Inworld STT-1 shows first text after 1.06s and GPT Realtime Whisper after 1.38s, at the median, so Inworld STT-1 is 316ms sooner.