Voice AI BenchmarksBy

GOOGLESPEECH-TO-TEXT133,250 SAMPLES / 30 DAYSLAST RUN OCT 14, 2026, 11:00 UTC

official resource

Chirp 2 speech-to-text benchmarks

Chirp 2, hosted by Google, measures mean 908 ms time to final segment (29th of 29) and 3.9% word error rate (10th of 31) among STT systems. Results cover the last 30 days. Coval benchmarks hosted endpoints daily using a consistent evaluation methodology. Last measured .

Chirp 2 is a Google Cloud Speech-to-Text model in the Chirp family.

Time to Final Segment#29 / 29
908ms
Word Error Rate#10 / 31
3.9%
Time to First Token#27 / 27
6099ms

Overview

Chirp 2 is a multilingual recognizer served through Cloud Speech-to-Text V2; the tested endpoint includes voice-activity and phrase-biasing controls.

Chirp 2 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
Google
Hosted by
Google
Source
Official API
Licensing
Proprietary
Deployment
On-prem
Region
US
Features
Keyterm biasing, Multilingual, VAD

How Chirp 2 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 Chirp 2 highlighted.
  1. #1Qwen3 ASR 1.7b39 ms
  2. #2STT RT v545 ms
  3. #3Qwen3 ASR Fast47 ms
  4. #4STT 167 ms
  5. #5Nova 385 ms
  6. #6Nova 287 ms
  7. #7Parakeet TDT 0.6B v397 ms
  8. #8Flux Multilingual98 ms
  9. #9Flux99 ms
  10. #10Scribe v2 Realtime122 ms
  11. #11Whisper Large v3via Baseten131 ms
  12. #12Universal 3.6 Pro135 ms
  13. #13Ink 2149 ms
  14. #14Universal 3.5 Pro168 ms
  15. #15Whisper Large v3via Together AI199 ms
  16. #16Pulse205 ms
  17. #17Grok STT223 ms
  18. #18resonant-1252 ms
  19. #19Default258 ms
  20. #20Linden 1271 ms
  21. #21Gemini 3.5 Transcribe Live317 ms
  22. #22Daytona STT399 ms
  23. #23Voxtral Mini Transcribe Realtime 2602411 ms
  24. #24GPT Realtime Whisper599 ms
  25. #25Solaria 1626 ms
  26. #26GPT-4o mini Transcribe708 ms
  27. #27Chirp 3768 ms
  28. #28GPT-4o Transcribe783 ms
  29. #29Chirp 2908 ms
median of all models · 199 ms
STT models over the last 30 days, ranked on Time to Final Segment.
#ModelHostTTFSWERTTFTSamples
1Qwen3 ASR 1.7bBaseten39 ms946 ms13,669
2STT RT v5Soniox45 ms1518 ms23,533
3Qwen3 ASR FastNari Labs47 ms1752 ms26,653
4STT 1Inworld AI67 ms1208 ms24,749
5Nova 3Deepgram85 ms1432 ms26,002
6Nova 2Deepgram87 ms1417 ms25,960
7Parakeet TDT 0.6B v3Together AI97 ms1228 ms26,462
8Flux MultilingualDeepgram98 ms1165 ms26,007
9FluxDeepgram99 ms1091 ms26,005
10Scribe v2 RealtimeElevenLabs122 ms2157 ms26,640
11Whisper Large v3Baseten131 ms924 ms13,663
12Universal 3.6 ProAssemblyAI135 ms1072 ms24,394
13Ink 2Cartesia149 ms1967 ms26,653
14Universal 3.5 ProAssemblyAI168 ms1026 ms26,654
15Whisper Large v3Together AI199 ms1260 ms26,447
16PulseSmallest205 ms1976 ms26,654
17Grok STTSpaceXAI223 ms—26,576
18resonant-1Reson8252 ms—26,654
19DefaultGradium258 ms1986 ms26,632
20Linden 1Speechmatics271 ms1537 ms26,595
21Gemini 3.5 Transcribe LiveGemini317 ms1606 ms26,567
22Daytona STTGuava399 ms5695 ms5,225
23Voxtral Mini Transcribe Realtime 2602Mistral411 ms1851 ms26,158
24GPT Realtime WhisperOpenAI599 ms1824 ms26,622
25Solaria 1Gladia626 ms1775 ms26,215
26GPT-4o mini TranscribeOpenAI708 ms—26,621
27Chirp 3Google768 ms5956 ms26,638
28GPT-4o TranscribeOpenAI783 ms—26,625
29Chirp 2Google908 ms6099 ms26,650
—Nemotron 3.5 ASR StreamingTogether AI—1544 ms26,550
—Universal StreamingAssemblyAI—1509 ms26,625
Under-sampled models are excluded; tied models share a place. Dotted WER values split into substitutions, deletions and insertions on hover or tap.

Highest relative placement: 10th of 31 on Word Error Rate.

Latency vs accuracy

TTFS vs WEREach point is one measured model · Chirp 2 highlighted · 30-day averagesTime to Final Segment against Word Error Rate for every measured STT model, with Chirp 2 highlighted.
Qwen3 ASR 1.7b — 39 ms, 2.9%STT RT v5 — 45 ms, 4.8%Qwen3 ASR Fast — 47 ms, 2.6%STT 1 — 67 ms, 7.1%Nova 3 — 85 ms, 5.3%Nova 2 — 87 ms, 6.7%Parakeet TDT 0.6B v3 — 97 ms, 11.1%Flux Multilingual — 98 ms, 7.5%Flux — 99 ms, 5.8%Scribe v2 Realtime — 122 ms, 4.4%Whisper Large v3 via Baseten — 131 ms, 4.5%Universal 3.6 Pro — 135 ms, 2.1%Ink 2 — 149 ms, 3.6%Universal 3.5 Pro — 168 ms, 2.3%Whisper Large v3 via Together AI — 199 ms, 7.4%Pulse — 205 ms, 4.6%Grok STT — 223 ms, 4.1%resonant-1 — 252 ms, 2.6%Default — 258 ms, 8.8%Linden 1 — 271 ms, 3.9%Gemini 3.5 Transcribe Live — 317 ms, 3.0%Daytona STT — 399 ms, 4.9%Voxtral Mini Transcribe Realtime 2602 — 411 ms, 5.3%GPT Realtime Whisper — 599 ms, 4.0%Solaria 1 — 626 ms, 6.0%GPT-4o mini Transcribe — 708 ms, 3.9%Chirp 3 — 768 ms, 3.2%GPT-4o Transcribe — 783 ms, 3.7%Chirp 2 — 908 ms, 3.9%

Where the errors come from

WER compositionChirp 2's Word Error Rate split by error type · 30-day averageChirp 2's WER split into substitutions, deletions and insertions.
  • Chirp 23.9%
SubstitutionsDeletionsInsertions

Averages and tail latency

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

Chirp 2 latency distributionMilliseconds · shared axis across metrics · last 30 daysChirp 2's latency percentiles per metric: p25–p75 band, p50 tick, whisker to max.
  • Time to Final Segmentp50 803 ms · Max 19387 ms
  • Time to First Tokenp50 6445 ms · Max 24490 ms
band p25–p75 · tick p50 · whisker to max with p90 and p95 stops
Average and percentile values per metric, with the number of samples behind each row.
MetricAveragep25p50p75p90p95MaxSamples
Time to Final Segment908 ms706 ms803 ms965 ms1270 ms1556 ms19387 ms26,650
Word Error Rate3.9%0.0%0.0%6.7%13.3%20.0%100.0%26,650
Time to First Token6099 ms5714 ms6445 ms6713 ms7179 ms7586 ms24490 ms26,650

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 daysChirp 2's daily median Time to Final Segment over the last 30 days.
Chirp 2 · Sep 14: 825 msChirp 2 · Sep 15: 771 msChirp 2 · Sep 16: 809 msChirp 2 · Sep 17: 831 msChirp 2 · Sep 18: 787 msChirp 2 · Sep 19: 966 msChirp 2 · Sep 20: 811 msChirp 2 · Sep 21: 873 msChirp 2 · Sep 22: 767 msChirp 2 · Sep 23: 789 msChirp 2 · Sep 24: 785 msChirp 2 · Sep 25: 887 msChirp 2 · Sep 26: 970 msChirp 2 · Sep 27: 795 msChirp 2 · Sep 28: 689 msChirp 2 · Sep 29: 809 msChirp 2 · Sep 30: 818 msChirp 2 · Oct 1: 806 msChirp 2 · Oct 2: 896 msChirp 2 · Oct 3: 730 msChirp 2 · Oct 4: 945 msChirp 2 · Oct 5: 795 msChirp 2 · Oct 6: 786 msChirp 2 · Oct 7: 834 msChirp 2 · Oct 8: 740 msChirp 2 · Oct 9: 727 msChirp 2 · Oct 10: 768 msChirp 2 · Oct 11: 826 msChirp 2 · Oct 12: 768 msChirp 2 · Oct 13: 822 msChirp 2 · Oct 14: 829 ms
Word Error Rate — daily averageDaily average · UTC daysChirp 2's daily Word Error Rate over the last 30 days.
Chirp 2 · Sep 14: 3.8%Chirp 2 · Sep 15: 5.2%Chirp 2 · Sep 16: 5.5%Chirp 2 · Sep 17: 5.8%Chirp 2 · Sep 18: 4.6%Chirp 2 · Sep 19: 4.8%Chirp 2 · Sep 20: 6.7%Chirp 2 · Sep 21: 4.0%Chirp 2 · Sep 22: 4.9%Chirp 2 · Sep 23: 4.9%Chirp 2 · Sep 24: 5.7%Chirp 2 · Sep 25: 4.6%Chirp 2 · Sep 26: 5.9%Chirp 2 · Sep 27: 5.4%Chirp 2 · Sep 28: 3.8%Chirp 2 · Sep 29: 4.3%Chirp 2 · Sep 30: 5.3%Chirp 2 · Oct 1: 4.7%Chirp 2 · Oct 2: 3.5%Chirp 2 · Oct 3: 5.9%Chirp 2 · Oct 4: 5.2%Chirp 2 · Oct 5: 5.1%Chirp 2 · Oct 6: 5.7%Chirp 2 · Oct 7: 5.5%Chirp 2 · Oct 8: 5.9%Chirp 2 · Oct 9: 4.8%Chirp 2 · Oct 10: 4.9%Chirp 2 · Oct 11: 4.4%Chirp 2 · Oct 12: 5.4%Chirp 2 · Oct 13: 5.1%Chirp 2 · Oct 14: 4.9%

Time to Final Segment by dataset

Chirp 2 by test conditionMilliseconds · lower is better · best condition firstChirp 2's Time to Final Segment on each benchmark dataset.
  1. WildASR accents793 ms
  2. WildASR noise gaps884 ms
  3. WildASR clipping888 ms
  4. WildASR clean897 ms
  5. WildASR far-field917 ms
  6. PipeCat (production)925 ms
  7. WildASR phone codec939 ms
Time to Final Segment per dataset, with the number of samples behind each figure.
DatasetTTFSSamples
ProductionPipeCat925 ms14,017
AccentsWildASR793 ms1,403
CleanWildASR897 ms5,612
ClippingWildASR888 ms1,404
Far-fieldWildASR917 ms1,406
Noise gapsWildASR884 ms1,403
Phone codecWildASR939 ms1,405

Strongest condition: WildASR accents at 793 ms · weakest: WildASR phone codec at 939 ms.

How fast is Chirp 2?

On Google, Chirp 2 measures mean 908 ms time to final segment (29th of 29) and mean 6099 ms time to first token (27th of 27). Last measured 2026-10-14.

How accurate is Chirp 2?

On Google, Chirp 2 measures 3.9% word error rate (10th of 31). Last measured 2026-10-14.

Who hosts Chirp 2?

Chirp 2 is created by Google and served by Google. Coval measures each hosted endpoint separately.

Limits of this comparison

Coval keeps it distinct from Chirp 3 so a generation change can be evaluated on the same audio and scoring rules.

  • The results describe Coval's configured US endpoint; Cloud region, recognizer settings and adaptation choices can change production behavior.

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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