ASSEMBLYAISPEECH-TO-TEXT80,940 SAMPLES / 30 DAYSLAST RUN SEP 15, 2026, 09:00 UTC

official resource

Universal Streaming speech-to-text benchmarks

Universal Streaming, hosted by AssemblyAI (Assembly AI, assemblyai.com), measures 6.9% word error rate (23rd of 30) among STT systems. Results cover the last 30 days. Coval benchmarks hosted endpoints daily using a consistent evaluation methodology. Each hosted endpoint is measured separately under the same benchmark conditions. Last measured .

Universal Streaming is AssemblyAI's real-time speech recognition model.

Word Error Rate#23 / 30
6.9%
Time to First Token#13 / 26
1514ms

Overview

AssemblyAI provides it through a persistent real-time API with voice activity, diarization and keyterm support.

Universal Streaming 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
AssemblyAI
Hosted by
AssemblyAI
Source
Official API
Licensing
Proprietary
Deployment
On-prem
Region
US
Features
Diarization, Keyterm biasing, VAD

How Universal Streaming 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 Universal Streaming highlighted.
  1. #1Qwen3 ASR 1.7b39 ms
  2. #3STT RT v557 ms
  3. #4STT 165 ms
  4. #6Nova 389 ms
  5. #7Nova 292 ms
  6. #9Flux99 ms
  7. #10Ink 2122 ms
  8. #11Whisper Large v3via Baseten125 ms
Show all 28 models
  1. #14Grok STT207 ms
  2. #15Defaultvia Speechmatics209 ms
  3. #16Pulse212 ms
  4. #17Defaultvia Gradium246 ms
  5. #18resonant-1264 ms
  6. #19Whisper Large v3via Together AI295 ms
  7. #20Enhanced299 ms
  8. #26Chirp 3776 ms
  9. #27Solaria 1805 ms
  10. #28Chirp 2873 ms
median of all models · 208 ms
STT models over the last 30 days, ranked on Time to Final Segment.
#ModelHostTTFSWERTTFTSamples
1Qwen3 ASR 1.7bBaseten39 ms931 ms1,256
2Qwen3 ASR FastNari46 ms1748 ms4,451
3STT RT v5Soniox57 ms1529 ms22,468
4STT 1Inworld AI65 ms1400 ms22,836
5Parakeet TDT 0.6B v3Together AI81 ms1215 ms22,488
6Nova 3Deepgram89 ms1419 ms22,855
7Nova 2Deepgram92 ms1420 ms22,733
8Flux MultilingualDeepgram98 ms1164 ms12,251
9FluxDeepgram99 ms1076 ms12,243
10Ink 2Cartesia122 ms1827 ms22,862
11Whisper Large v3Baseten125 ms912 ms1,252
12Scribe v2 RealtimeElevenLabs133 ms2175 ms22,866
13Universal 3.5 ProAssemblyAI173 ms1041 ms20,253
14Grok STTxAI207 ms22,853
15DefaultSpeechmatics209 ms1428 ms22,876
16PulseSmallest212 ms2011 ms22,856
17DefaultGradium246 ms1980 ms22,839
18resonant-1Reson8264 ms22,860
19Whisper Large v3Together AI295 ms1338 ms22,744
20EnhancedSpeechmatics299 ms1492 ms22,876
21Gemini 3.5 Transcribe LiveGemini305 ms1679 ms16,403
22Voxtral Mini Transcribe Realtime 2602Mistral401 ms1851 ms22,583
23GPT Realtime WhisperOpenAI551 ms1814 ms22,812
24GPT-4o mini TranscribeOpenAI690 ms22,830
25GPT-4o TranscribeOpenAI754 ms22,831
26Chirp 3Google776 ms5974 ms22,875
27Solaria 1Gladia805 ms1804 ms22,439
28Chirp 2Google873 ms6071 ms22,789
Nemotron 3.5 ASR StreamingTogether AI1548 ms22,747
Universal StreamingAssemblyAI1514 ms20,235
Under-sampled models are excluded; tied models share a place. Dotted WER values split into substitutions, deletions and insertions on hover or tap.

Universal Streaming hasn't logged enough qualifying samples in the last 30 days to hold a rank on Time to Final Segment.

Where the errors come from

WER compositionUniversal Streaming's Word Error Rate split by error type · 30-day averageUniversal Streaming's WER split into substitutions, deletions and insertions.
  • Universal Streaming6.9%
SubstitutionsDeletionsInsertions

Averages and tail latency

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

Universal Streaming latency distributionMilliseconds · shared axis across metrics · last 30 daysUniversal Streaming's latency percentiles per metric: p25–p75 band, p50 tick, whisker to p99.
  • Time to First Tokenp50 1482 ms · p99 3276 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
Word Error Rate6.9%0.0%3.2%10.0%19.0%25.0%46.7%20,235
Time to First Token1514 ms1186 ms1482 ms1731 ms2082 ms2377 ms3276 ms20,235

How fast is Universal Streaming?

On AssemblyAI, Universal Streaming measures mean 1514 ms time to first token (13th of 26). Last measured 2026-09-15.

How accurate is Universal Streaming?

On AssemblyAI, Universal Streaming measures 6.9% word error rate (23rd of 30). Last measured 2026-09-15.

Who hosts Universal Streaming?

Universal Streaming is created by AssemblyAI and served by AssemblyAI. Coval measures each hosted endpoint separately.

Limits of this comparison

Coval reports partial-transcript timing, final-transcript timing and recognition accuracy.

  • Production endpointing and turn detection can add latency outside the interval Coval attributes to the model.

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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