Voice AI BenchmarksBy

ALIBABASPEECH-TO-TEXT133,360 SAMPLES / 30 DAYSLAST RUN OCT 16, 2026, 23:30 UTC

Qwen3 ASR Fast speech-to-text benchmarks

Qwen3 ASR Fast, hosted by Nari Labs, measures mean 47 ms time to final segment (3rd of 29) and 2.6% word error rate (4th of 31) among STT systems. Results cover the last 30 days. Coval benchmarks hosted endpoints daily using a consistent evaluation methodology. Last measured .

Coval has active speech-to-text measurements for Qwen3 ASR Fast, created by Alibaba and served on Nari Labs.

Time to Final Segment#3 / 29
47ms
Word Error Rate#4 / 31
2.6%
Time to First Token#18 / 27
1752ms

Overview

Qwen3 ASR Fast 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
Alibaba
Hosted by
Nari Labs
Source
Shared inference
Licensing
Open-weight
Deployment
Cloud
Region
US
Features
Multilingual

How Qwen3 ASR Fast 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 Qwen3 ASR Fast highlighted.
  1. #1Qwen3 ASR 1.7b39 ms
  2. #2STT RT v545 ms
  3. #3Qwen3 ASR Fast47 ms
  4. #4STT 168 ms
  5. #5Nova 385 ms
  6. #6Nova 287 ms
  7. #7Parakeet TDT 0.6B v396 ms
  8. #8Flux Multilingual98 ms
  9. #9Flux99 ms
  10. #10Scribe v2 Realtime120 ms
  11. #11Whisper Large v3via Baseten132 ms
  12. #12Universal 3.6 Pro134 ms
Show all 29 models
  1. #13Ink 2149 ms
  2. #14Universal 3.5 Pro165 ms
  3. #15Whisper Large v3via Together AI192 ms
  4. #16Pulse206 ms
  5. #17Grok STT222 ms
  6. #18resonant-1250 ms
  7. #19Default262 ms
  8. #20Linden 1275 ms
  9. #21Gemini 3.5 Transcribe Live323 ms
  10. #22Daytona STT399 ms
  11. #23Voxtral Mini Transcribe Realtime 2602431 ms
  12. #24Solaria 1534 ms
  13. #25GPT Realtime Whisper598 ms
  14. #26GPT-4o mini Transcribe712 ms
  15. #27Chirp 3769 ms
  16. #28GPT-4o Transcribe784 ms
  17. #29Chirp 2910 ms
median of all models · 192 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 ms1519 ms25,416
3Qwen3 ASR FastNari Labs47 ms1752 ms26,672
4STT 1Inworld AI68 ms1166 ms24,769
5Nova 3Deepgram85 ms1436 ms26,023
6Nova 2Deepgram87 ms1418 ms25,978
7Parakeet TDT 0.6B v3Together AI96 ms1222 ms26,478
8Flux MultilingualDeepgram98 ms1166 ms26,026
9FluxDeepgram99 ms1091 ms26,027
10Scribe v2 RealtimeElevenLabs120 ms2154 ms26,660
11Whisper Large v3Baseten132 ms925 ms13,667
12Universal 3.6 ProAssemblyAI134 ms1074 ms26,636
13Ink 2Cartesia149 ms1985 ms26,673
14Universal 3.5 ProAssemblyAI165 ms1023 ms26,674
15Whisper Large v3Together AI192 ms1246 ms26,487
16PulseSmallest206 ms1977 ms26,674
17Grok STTSpaceXAI222 ms—26,596
18resonant-1Reson8250 ms—26,673
19DefaultGradium262 ms1991 ms26,671
20Linden 1Speechmatics275 ms1539 ms26,615
21Gemini 3.5 Transcribe LiveGemini323 ms1574 ms26,580
22Daytona STTGuava399 ms5690 ms6,088
23Voxtral Mini Transcribe Realtime 2602Mistral431 ms1858 ms25,852
24Solaria 1Gladia534 ms1678 ms26,491
25GPT Realtime WhisperOpenAI598 ms1825 ms26,641
26GPT-4o mini TranscribeOpenAI712 ms—26,641
27Chirp 3Google769 ms5958 ms26,659
28GPT-4o TranscribeOpenAI784 ms—26,643
29Chirp 2Google910 ms6101 ms26,670
—Nemotron 3.5 ASR StreamingTogether AI—1547 ms26,536
—Universal StreamingAssemblyAI—1510 ms26,644
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 · Qwen3 ASR Fast highlighted · 30-day averagesTime to Final Segment against Word Error Rate for every measured STT model, with Qwen3 ASR Fast highlighted.
Qwen3 ASR 1.7b — 39 ms, 2.9%STT RT v5 — 45 ms, 4.8%STT 1 — 68 ms, 6.8%Nova 3 — 85 ms, 5.3%Nova 2 — 87 ms, 6.7%Parakeet TDT 0.6B v3 — 96 ms, 11.1%Flux Multilingual — 98 ms, 7.5%Flux — 99 ms, 5.8%Scribe v2 Realtime — 120 ms, 4.3%Whisper Large v3 via Baseten — 132 ms, 4.4%Universal 3.6 Pro — 134 ms, 2.2%Ink 2 — 149 ms, 3.6%Universal 3.5 Pro — 165 ms, 2.4%Whisper Large v3 via Together AI — 192 ms, 7.4%Pulse — 206 ms, 4.6%Grok STT — 222 ms, 4.2%resonant-1 — 250 ms, 2.6%Default — 262 ms, 8.7%Linden 1 — 275 ms, 3.9%Gemini 3.5 Transcribe Live — 323 ms, 3.0%Daytona STT — 399 ms, 4.9%Voxtral Mini Transcribe Realtime 2602 — 431 ms, 5.4%Solaria 1 — 534 ms, 6.1%GPT Realtime Whisper — 598 ms, 4.1%GPT-4o mini Transcribe — 712 ms, 3.9%Chirp 3 — 769 ms, 3.2%GPT-4o Transcribe — 784 ms, 3.7%Chirp 2 — 910 ms, 3.9%Qwen3 ASR Fast — 47 ms, 2.6%

Where the errors come from

WER compositionQwen3 ASR Fast's Word Error Rate split by error type · 30-day averageQwen3 ASR Fast's WER split into substitutions, deletions and insertions.
  • Qwen3 ASR Fast2.6%
SubstitutionsDeletionsInsertions

Averages and tail latency

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

Qwen3 ASR Fast latency distributionMilliseconds · shared axis across metrics · last 30 daysQwen3 ASR Fast's latency percentiles per metric: p25–p75 band, p50 tick, whisker to max.
  • Time to Final Segmentp50 45 ms · Max 8082 ms
  • Time to First Tokenp50 1749 ms · Max 4543 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 Segment47 ms39 ms45 ms50 ms58 ms67 ms8082 ms26,672
Word Error Rate2.6%0.0%0.0%4.3%10.0%14.3%57.1%26,672
Time to First Token1752 ms1746 ms1749 ms1753 ms1760 ms1768 ms4543 ms26,672

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 daysQwen3 ASR Fast's daily median Time to Final Segment over the last 30 days.
Qwen3 ASR Fast · Sep 17: 43 msQwen3 ASR Fast · Sep 18: 44 msQwen3 ASR Fast · Sep 19: 46 msQwen3 ASR Fast · Sep 20: 47 msQwen3 ASR Fast · Sep 21: 41 msQwen3 ASR Fast · Sep 22: 47 msQwen3 ASR Fast · Sep 23: 56 msQwen3 ASR Fast · Sep 24: 41 msQwen3 ASR Fast · Sep 25: 49 msQwen3 ASR Fast · Sep 26: 43 msQwen3 ASR Fast · Sep 27: 41 msQwen3 ASR Fast · Sep 28: 47 msQwen3 ASR Fast · Sep 29: 44 msQwen3 ASR Fast · Sep 30: 44 msQwen3 ASR Fast · Oct 1: 44 msQwen3 ASR Fast · Oct 2: 44 msQwen3 ASR Fast · Oct 3: 44 msQwen3 ASR Fast · Oct 4: 42 msQwen3 ASR Fast · Oct 5: 44 msQwen3 ASR Fast · Oct 6: 42 msQwen3 ASR Fast · Oct 7: 44 msQwen3 ASR Fast · Oct 8: 43 msQwen3 ASR Fast · Oct 9: 46 msQwen3 ASR Fast · Oct 10: 46 msQwen3 ASR Fast · Oct 11: 44 msQwen3 ASR Fast · Oct 12: 44 msQwen3 ASR Fast · Oct 13: 46 msQwen3 ASR Fast · Oct 14: 45 msQwen3 ASR Fast · Oct 15: 46 msQwen3 ASR Fast · Oct 16: 47 ms
Word Error Rate — daily averageDaily average · UTC daysQwen3 ASR Fast's daily Word Error Rate over the last 30 days.
Qwen3 ASR Fast · Sep 17: 3.8%Qwen3 ASR Fast · Sep 18: 4.1%Qwen3 ASR Fast · Sep 19: 3.0%Qwen3 ASR Fast · Sep 20: 3.9%Qwen3 ASR Fast · Sep 21: 3.3%Qwen3 ASR Fast · Sep 22: 4.7%Qwen3 ASR Fast · Sep 23: 2.9%Qwen3 ASR Fast · Sep 24: 4.2%Qwen3 ASR Fast · Sep 25: 4.4%Qwen3 ASR Fast · Sep 26: 3.5%Qwen3 ASR Fast · Sep 27: 3.1%Qwen3 ASR Fast · Sep 28: 4.0%Qwen3 ASR Fast · Sep 29: 3.5%Qwen3 ASR Fast · Sep 30: 3.7%Qwen3 ASR Fast · Oct 1: 3.0%Qwen3 ASR Fast · Oct 2: 3.1%Qwen3 ASR Fast · Oct 3: 3.5%Qwen3 ASR Fast · Oct 4: 3.6%Qwen3 ASR Fast · Oct 5: 2.9%Qwen3 ASR Fast · Oct 6: 4.3%Qwen3 ASR Fast · Oct 7: 3.6%Qwen3 ASR Fast · Oct 8: 3.2%Qwen3 ASR Fast · Oct 9: 3.3%Qwen3 ASR Fast · Oct 10: 3.3%Qwen3 ASR Fast · Oct 11: 2.4%Qwen3 ASR Fast · Oct 12: 3.6%Qwen3 ASR Fast · Oct 13: 3.4%Qwen3 ASR Fast · Oct 14: 3.1%Qwen3 ASR Fast · Oct 15: 3.9%Qwen3 ASR Fast · Oct 16: 4.3%

Time to Final Segment by dataset

Qwen3 ASR Fast by test conditionMilliseconds · lower is better · best condition firstQwen3 ASR Fast's Time to Final Segment on each benchmark dataset.
  1. WildASR accents45 ms
  2. WildASR noise gaps46 ms
  3. WildASR clipping46 ms
  4. WildASR far-field47 ms
  5. WildASR clean47 ms
  6. WildASR phone codec47 ms
  7. PipeCat (production)47 ms
Time to Final Segment per dataset, with the number of samples behind each figure.
DatasetTTFSSamples
ProductionPipeCat47 ms14,029
AccentsWildASR45 ms1,404
CleanWildASR47 ms5,616
ClippingWildASR46 ms1,407
Far-fieldWildASR47 ms1,407
Noise gapsWildASR46 ms1,403
Phone codecWildASR47 ms1,406

Strongest condition: WildASR accents at 45 ms · weakest: PipeCat (production) at 47 ms.

How fast is Qwen3 ASR Fast?

On Nari Labs, Qwen3 ASR Fast measures mean 47 ms time to final segment (3rd of 29) and mean 1752 ms time to first token (18th of 27). Last measured 2026-10-16.

How accurate is Qwen3 ASR Fast?

On Nari Labs, Qwen3 ASR Fast measures 2.6% word error rate (4th of 31). Last measured 2026-10-16.

Who hosts Qwen3 ASR Fast?

Qwen3 ASR Fast is created by Alibaba and served by Nari Labs. Coval measures each hosted endpoint separately.

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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