Voice AI BenchmarksBy

SONIOXSPEECH-TO-TEXT146,774 SAMPLES / 30 DAYSLAST RUN AUG 28, 2026, 21:30 UTC

official resource

STT RT v5 speech-to-text benchmarks

STT RT v5 is Soniox's fifth-generation real-time transcription model.

Time to Final Segment#1 / 24
64ms
Word Error Rate#16 / 28
5.8%
Time to First Token#11 / 24
1533ms

Overview

The Soniox endpoint supports multilingual transcription with diarization, translation, code switching and keyterm controls.

STT RT v5 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.

Technical specifications

Made by
Soniox
Hosted by
Soniox
Source
Official API
Licensing
Proprietary
Deployment
Cloud
Region
US
Features
Multilingual, VAD, Diarization, Translation, Code switching, Keyterm biasing

How STT RT v5 ranks

Full STT dashboard
Time to Final Segment — every measured STT modelMilliseconds · lower is better · 30-day averageEvery STT model ranked on Time to Final Segment, with STT RT v5 highlighted.
  1. #1STT RT v564 ms
  2. #2Parakeet TDT 0.6B v370 ms
  3. #3STT 183 ms
  4. #4Nova 399 ms
  5. #5Nova 2101 ms
  6. #6Ink 2108 ms
  7. #7Scribe v2 Realtime120 ms
  8. #8Universal 3.5 Pro146 ms
  9. #9Defaultvia Azure155 ms
  10. #10Whisper Large v3180 ms
  11. #11Velma 2 STT Streaming191 ms
  12. #12Grok STT199 ms
Show all 24 models
  1. #13Pulse205 ms
  2. #14Defaultvia Speechmatics223 ms
  3. #15Defaultvia Gradium249 ms
  4. #16resonant-1288 ms
  5. #17Enhanced341 ms
  6. #18Voxtral Mini Transcribe Realtime 2602356 ms
  7. #19GPT Realtime Whisper559 ms
  8. #20GPT-4o mini Transcribe623 ms
  9. #21Solaria 1680 ms
  10. #22GPT-4o Transcribe742 ms
  11. #23Chirp 2811 ms
  12. #24Chirp 3813 ms
median of all models · 202 ms
STT models over the last 30 days, ranked on Time to Final Segment.
#ModelHostTTFSWERTTFTSamples
1STT RT v5Soniox64 ms1533 ms29,322
2Parakeet TDT 0.6B v3Together AI70 ms1210 ms29,161
3STT 1Inworld AI83 ms1468 ms29,280
4Nova 3Deepgram99 ms1434 ms29,290
5Nova 2Deepgram101 ms1436 ms29,145
6Ink 2Cartesia108 ms1812 ms29,288
7Scribe v2 RealtimeElevenLabs120 ms2157 ms29,313
8Universal 3.5 ProAssemblyAI146 ms1030 ms29,280
9DefaultAzure155 ms1792 ms6,682
10Whisper Large v3Together AI180 ms1241 ms29,171
11Velma 2 STT StreamingModulate191 ms1576 ms17,895
12Grok STTxAI199 ms—29,322
13PulseSmallest205 ms2072 ms29,313
14DefaultSpeechmatics223 ms1473 ms29,323
15DefaultGradium249 ms1979 ms28,235
16resonant-1Reson8288 ms—17,066
17EnhancedSpeechmatics341 ms1536 ms29,322
18Voxtral Mini Transcribe Realtime 2602Mistral356 ms1828 ms29,175
19GPT Realtime WhisperOpenAI559 ms1823 ms29,286
20GPT-4o mini TranscribeOpenAI623 ms—29,318
21Solaria 1Gladia680 ms1703 ms26,356
22GPT-4o TranscribeOpenAI742 ms—29,318
23Chirp 2Google811 ms6000 ms29,237
24Chirp 3Google813 ms5999 ms29,319
—FluxDeepgram—1089 ms29,354
—Flux MultilingualDeepgram—1175 ms29,344
—Nemotron 3.5 ASR StreamingTogether AI—1540 ms29,193
—Universal StreamingAssemblyAI—1510 ms29,297
Under-sampled models are excluded; tied models share a place. Dotted WER values split into substitutions, deletions and insertions on hover or tap.

Latency vs accuracy

TTFS vs WEREach point is one measured model · STT RT v5 highlighted · 30-day averagesTime to Final Segment against Word Error Rate for every measured STT model, with STT RT v5 highlighted.
Parakeet TDT 0.6B v3 — 70 ms, 11.0%STT 1 — 83 ms, 4.8%Nova 3 — 99 ms, 6.3%Nova 2 — 101 ms, 7.9%Ink 2 — 108 ms, 4.9%Scribe v2 Realtime — 120 ms, 5.5%Universal 3.5 Pro — 146 ms, 3.2%Default via Azure — 155 ms, 5.3%Whisper Large v3 — 180 ms, 8.2%Velma 2 STT Streaming — 191 ms, 6.4%Grok STT — 199 ms, 4.8%Pulse — 205 ms, 5.3%Default via Speechmatics — 223 ms, 5.5%Default via Gradium — 249 ms, 10.0%resonant-1 — 288 ms, 3.4%Enhanced — 341 ms, 4.3%Voxtral Mini Transcribe Realtime 2602 — 356 ms, 6.2%GPT Realtime Whisper — 559 ms, 5.2%GPT-4o mini Transcribe — 623 ms, 5.1%Solaria 1 — 680 ms, 7.1%GPT-4o Transcribe — 742 ms, 4.7%Chirp 2 — 811 ms, 5.0%Chirp 3 — 813 ms, 4.1%STT RT v5 — 64 ms, 5.8%

Where the errors come from

WER compositionSTT RT v5's Word Error Rate split by error type · 30-day averageSTT RT v5's WER split into substitutions, deletions and insertions.
  • STT RT v55.8%
SubstitutionsDeletionsInsertions

Averages and tail latency

Averages hide slow outliers — these are the distributions behind each figure.

STT RT v5 latency distributionMilliseconds · shared axis across metrics · last 30 daysSTT RT v5's latency percentiles per metric: p25–p75 band, p50 tick, whisker to p99.
  • Time to Final Segmentp50 62 ms · p99 115 ms
  • Time to First Tokenp50 1555 ms · p99 3259 ms
band p25–p75 · tick p50 · whisker to p99 with p90 and p95 stops
Average and percentile values per metric, with the number of samples behind each row.
MetricAveragep25p50p75p90p95p99Samples
Time to Final Segment64 ms51 ms62 ms72 ms83 ms92 ms115 ms29,322
Word Error Rate5.8%0.0%0.0%8.3%16.7%23.1%47.4%29,363
Time to First Token1533 ms1163 ms1555 ms1744 ms2060 ms2278 ms3259 ms29,363

Last 30 days

Daily medians from the same measurement runs · gaps are days without qualifying runs.

Time to Final Segment — daily p50Line p50 · band p25–p75 · UTC daysSTT RT v5's daily median Time to Final Segment over the last 30 days.
STT RT v5 · Jul 30: 57 msSTT RT v5 · Jul 31: 62 msSTT RT v5 · Aug 1: 60 msSTT RT v5 · Aug 2: 55 msSTT RT v5 · Aug 3: 64 msSTT RT v5 · Aug 4: 62 msSTT RT v5 · Aug 5: 67 msSTT RT v5 · Aug 6: 75 msSTT RT v5 · Aug 7: 75 msSTT RT v5 · Aug 8: 63 msSTT RT v5 · Aug 9: 65 msSTT RT v5 · Aug 10: 69 msSTT RT v5 · Aug 11: 73 msSTT RT v5 · Aug 12: 76 msSTT RT v5 · Aug 13: 74 msSTT RT v5 · Aug 14: 65 msSTT RT v5 · Aug 15: 62 msSTT RT v5 · Aug 16: 62 msSTT RT v5 · Aug 17: 68 msSTT RT v5 · Aug 18: 64 msSTT RT v5 · Aug 19: 50 msSTT RT v5 · Aug 20: 49 msSTT RT v5 · Aug 21: 49 msSTT RT v5 · Aug 22: 42 msSTT RT v5 · Aug 23: 46 msSTT RT v5 · Aug 24: 54 msSTT RT v5 · Aug 25: 58 msSTT RT v5 · Aug 26: 53 msSTT RT v5 · Aug 27: 51 msSTT RT v5 · Aug 28: 49 ms
Word Error Rate — daily averageDaily average · UTC daysSTT RT v5's daily Word Error Rate over the last 30 days.
STT RT v5 · Jul 30: 6.3%STT RT v5 · Jul 31: 7.2%STT RT v5 · Aug 1: 6.6%STT RT v5 · Aug 2: 7.3%STT RT v5 · Aug 3: 5.5%STT RT v5 · Aug 4: 7.6%STT RT v5 · Aug 5: 7.3%STT RT v5 · Aug 6: 6.3%STT RT v5 · Aug 7: 7.6%STT RT v5 · Aug 8: 8.7%STT RT v5 · Aug 9: 5.9%STT RT v5 · Aug 10: 7.9%STT RT v5 · Aug 11: 6.9%STT RT v5 · Aug 12: 5.8%STT RT v5 · Aug 13: 7.1%STT RT v5 · Aug 14: 6.3%STT RT v5 · Aug 15: 6.5%STT RT v5 · Aug 16: 7.0%STT RT v5 · Aug 17: 5.7%STT RT v5 · Aug 18: 7.5%STT RT v5 · Aug 19: 8.4%STT RT v5 · Aug 20: 6.0%STT RT v5 · Aug 21: 6.9%STT RT v5 · Aug 22: 7.9%STT RT v5 · Aug 23: 7.0%STT RT v5 · Aug 24: 5.9%STT RT v5 · Aug 25: 6.3%STT RT v5 · Aug 26: 6.1%STT RT v5 · Aug 27: 6.5%STT RT v5 · Aug 28: 8.0%

Time to Final Segment by dataset

STT RT v5 by test conditionMilliseconds · lower is better · best condition firstSTT RT v5's Time to Final Segment on each benchmark dataset.
  1. WildASR far-field61 ms
  2. WildASR phone codec61 ms
  3. WildASR noise gaps62 ms
  4. WildASR clipping62 ms
  5. WildASR reverb63 ms
  6. PipeCat (production)64 ms
  7. WildASR clean66 ms
  8. WildASR accents66 ms
Time to Final Segment per dataset, with the number of samples behind each figure.
DatasetTTFSSamples
LibriSpeech51 ms1
ProductionPipeCat64 ms14,938
AccentsWildASR66 ms1,438
CleanWildASR66 ms5,779
ClippingWildASR62 ms1,444
Far-fieldWildASR61 ms1,442
Noise gapsWildASR62 ms1,441
Phone codecWildASR61 ms1,441
ReverbWildASR63 ms1,398

Strongest condition: LibriSpeech at 51 ms · weakest: WildASR accents at 66 ms.

Limits of this comparison

Coval measures it alongside specialist and general-purpose recognizers with the same reference normalization and audio rotation.

  • The benchmark does not score translation or diarization quality, and English-heavy datasets do not establish performance for every supported language.

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.

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