OPENAISPEECH-TO-TEXT114,208 SAMPLES / 30 DAYSLAST RUN SEP 15, 2026, 09:00 UTC
GPT Realtime Whisper speech-to-text benchmarks
GPT Realtime Whisper, hosted by OpenAI, measures mean 551 ms time to final segment (23rd of 28) and 5.1% word error rate (14th of 30) among STT systems. Results cover the last 30 days. Coval benchmarks hosted endpoints daily using a consistent evaluation methodology. Last measured .
GPT Realtime Whisper is Whisper transcription running inside an OpenAI Realtime session, rather than the standalone Audio API.
- Time to Final Segment#23 / 28
- 551ms
- Word Error Rate#14 / 30
- 5.1%
- Time to First Token#19 / 26
- 1814ms
Overview
The path runs within a persistent Realtime connection while still being scored against Coval's standard STT references.
GPT Realtime Whisper is tested every day on fixed public audio — clean, accented, noisy, reverberant, far-field, clipped and phone-codec speech — for transcription accuracy and streaming latency.
How GPT Realtime Whisper ranks
Full STT dashboard- #1Qwen3 ASR 1.7bDedicated inference. Shared endpoints serve many customers on the same infrastructure, while dedicated endpoints run on hardware reserved for a single customer.39 ms
- #11Whisper Large v3via BasetenDedicated inference. Shared endpoints serve many customers on the same infrastructure, while dedicated endpoints run on hardware reserved for a single customer.125 ms
- #15Defaultvia Speechmatics209 ms
- #17Defaultvia Gradium246 ms
Show all 28 modelsShow fewer
- #6Qwen3 ASR 1.7bDedicated inference. Shared endpoints serve many customers on the same infrastructure, while dedicated endpoints run on hardware reserved for a single customer.4.1%
Show all 30 modelsShow fewer
- #16Defaultvia Speechmatics5.4%
- #18Whisper Large v3via BasetenDedicated inference. Shared endpoints serve many customers on the same infrastructure, while dedicated endpoints run on hardware reserved for a single customer.5.6%
- #28Defaultvia Gradium10.0%
- #1Whisper Large v3via BasetenDedicated inference. Shared endpoints serve many customers on the same infrastructure, while dedicated endpoints run on hardware reserved for a single customer.912 ms
- #2Qwen3 ASR 1.7bDedicated inference. Shared endpoints serve many customers on the same infrastructure, while dedicated endpoints run on hardware reserved for a single customer.931 ms
- #11Defaultvia Speechmatics1428 ms
Show all 26 modelsShow fewer
- #22Defaultvia Gradium1980 ms
| # | Model | Host | TTFS | WER | TTFT | Samples |
|---|---|---|---|---|---|---|
| 1 | Qwen3 ASR 1.7b | Baseten | 39 ms | 931 ms | 1,256 | |
| 2 | Qwen3 ASR Fast | Nari | 46 ms | 1748 ms | 4,451 | |
| 3 | STT RT v5 | Soniox | 57 ms | 1529 ms | 22,468 | |
| 4 | STT 1 | Inworld AI | 65 ms | 1400 ms | 22,836 | |
| 5 | Parakeet TDT 0.6B v3 | Together AI | 81 ms | 1215 ms | 22,488 | |
| 6 | Nova 3 | Deepgram | 89 ms | 1419 ms | 22,855 | |
| 7 | Nova 2 | Deepgram | 92 ms | 1420 ms | 22,733 | |
| 8 | Flux Multilingual | Deepgram | 98 ms | 1164 ms | 12,251 | |
| 9 | Flux | Deepgram | 99 ms | 1076 ms | 12,243 | |
| 10 | Ink 2 | Cartesia | 122 ms | 1827 ms | 22,862 | |
| 11 | Whisper Large v3 | Baseten | 125 ms | 912 ms | 1,252 | |
| 12 | Scribe v2 Realtime | ElevenLabs | 133 ms | 2175 ms | 22,866 | |
| 13 | Universal 3.5 Pro | AssemblyAI | 173 ms | 1041 ms | 20,253 | |
| 14 | Grok STT | xAI | 207 ms | — | 22,853 | |
| 15 | Default | Speechmatics | 209 ms | 1428 ms | 22,876 | |
| 16 | Pulse | Smallest | 212 ms | 2011 ms | 22,856 | |
| 17 | Default | Gradium | 246 ms | 1980 ms | 22,839 | |
| 18 | resonant-1 | Reson8 | 264 ms | — | 22,860 | |
| 19 | Whisper Large v3 | Together AI | 295 ms | 1338 ms | 22,744 | |
| 20 | Enhanced | Speechmatics | 299 ms | 1492 ms | 22,876 | |
| 21 | Gemini 3.5 Transcribe Live | Gemini | 305 ms | 1679 ms | 16,403 | |
| 22 | Voxtral Mini Transcribe Realtime 2602 | Mistral | 401 ms | 1851 ms | 22,583 | |
| 23 | GPT Realtime Whisper | OpenAI | 551 ms | 1814 ms | 22,812 | |
| 24 | GPT-4o mini Transcribe | OpenAI | 690 ms | — | 22,830 | |
| 25 | GPT-4o Transcribe | OpenAI | 754 ms | — | 22,831 | |
| 26 | Chirp 3 | 776 ms | 5974 ms | 22,875 | ||
| 27 | Solaria 1 | Gladia | 805 ms | 1804 ms | 22,439 | |
| 28 | Chirp 2 | 873 ms | 6071 ms | 22,789 | ||
| — | Nemotron 3.5 ASR Streaming | Together AI | — | 1548 ms | 22,747 | |
| — | Universal Streaming | AssemblyAI | — | 1514 ms | 20,235 |
Highest relative placement: 14th of 30 on Word Error Rate.
Latency vs accuracy
Where the errors come from
- GPT Realtime Whisper5.1%
Averages and tail latency
Averages hide slow outliers — these are the distributions behind each figure.
- Time to Final Segmentp50 553 ms · p99 847 ms
- Time to First Tokenp50 1837 ms · p99 3538 ms
- GPT Realtime Whisperp50 0.0% · p99 53.6%
| Metric | Average | p25 | p50 | p75 | p90 | p95 | p99 | Samples |
|---|---|---|---|---|---|---|---|---|
| Time to Final Segment | 551 ms | 463 ms | 553 ms | 602 ms | 643 ms | 673 ms | 847 ms | 22,812 |
| Word Error Rate | 5.1% | 0.0% | 0.0% | 6.3% | 14.3% | 22.7% | 53.6% | 22,849 |
| Time to First Token | 1814 ms | 1530 ms | 1837 ms | 2033 ms | 2311 ms | 2541 ms | 3538 ms | 22,849 |
Last 30 days
Daily medians from the same measurement runs · gaps are days without qualifying runs.
Time to Final Segment by dataset
- WildASR clean543 ms
- PipeCat (production)549 ms
- WildASR noise gaps550 ms
- WildASR far-field551 ms
- WildASR phone codec556 ms
- WildASR reverb559 ms
- WildASR accents565 ms
- WildASR clipping568 ms
| Dataset | TTFS | Samples |
|---|---|---|
| LibriSpeech | 457 ms | 1 |
| ProductionPipeCat | 549 ms | 11,495 |
| AccentsWildASR | 565 ms | 1,115 |
| CleanWildASR | 543 ms | 4,570 |
| ClippingWildASR | 568 ms | 1,138 |
| Far-fieldWildASR | 551 ms | 1,141 |
| Noise gapsWildASR | 550 ms | 1,141 |
| Phone codecWildASR | 556 ms | 1,136 |
| ReverbWildASR | 559 ms | 1,075 |
Strongest condition: LibriSpeech at 457 ms · weakest: WildASR clipping at 568 ms.
How fast is GPT Realtime Whisper?
On OpenAI, GPT Realtime Whisper measures mean 551 ms time to final segment (23rd of 28) and mean 1814 ms time to first token (19th of 26). Last measured 2026-09-15.
How accurate is GPT Realtime Whisper?
On OpenAI, GPT Realtime Whisper measures 5.1% word error rate (14th of 30). Last measured 2026-09-15.
Who hosts GPT Realtime Whisper?
GPT Realtime Whisper is created by OpenAI and served by OpenAI. Coval measures each hosted endpoint separately.
Limits of this comparison
This path is reported separately because session events and integration behavior differ from standalone audio-transcription requests.
- The name describes Coval's integration path, and OpenAI can update Realtime defaults independently of standalone Whisper endpoints.
Official sources
Results are re-measured daily using fixed datasets and reported over a rolling 30-day window. Same datasets, prompts and metric definitions for every model, measured by Coval’s open-source runner. Full methodology on the overview.
Evaluate your own voice agent
Use Coval to test your production configuration, prompts and calls—not only the public benchmark endpoints.