CARTESIASPEECH-TO-TEXT146,604 SAMPLES / 30 DAYSLAST RUN AUG 28, 2026, 21:30 UTC
Ink 2 speech-to-text benchmarks
Ink 2 is Cartesia's real-time speech recognition model.
- Time to Final Segment#6 / 24
- 108ms
- Word Error Rate#8 / 28
- 4.9%
- Time to First Token#17 / 24
- 1812ms
Overview
Cartesia provides Ink through a streaming speech-to-text API with voice activity and an on-premises option.
Ink 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.
How Ink 2 ranks
Full STT dashboard- #9Defaultvia Azure155 ms
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- #14Defaultvia Speechmatics223 ms
- #15Defaultvia Gradium249 ms
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- #13Defaultvia Azure5.3%
- #14Defaultvia Speechmatics5.5%
- #26Defaultvia Gradium10.0%
- #9Defaultvia Speechmatics1473 ms
- #16Defaultvia Azure1792 ms
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- #20Defaultvia Gradium1979 ms
| # | Model | Host | TTFS | WER | TTFT | Samples |
|---|---|---|---|---|---|---|
| 1 | STT RT v5 | Soniox | 64 ms | 1533 ms | 29,322 | |
| 2 | Parakeet TDT 0.6B v3 | Together AI | 70 ms | 1210 ms | 29,161 | |
| 3 | STT 1 | Inworld AI | 83 ms | 1468 ms | 29,280 | |
| 4 | Nova 3 | Deepgram | 99 ms | 1434 ms | 29,290 | |
| 5 | Nova 2 | Deepgram | 101 ms | 1436 ms | 29,145 | |
| 6 | Ink 2 | Cartesia | 108 ms | 1812 ms | 29,288 | |
| 7 | Scribe v2 Realtime | ElevenLabs | 120 ms | 2157 ms | 29,313 | |
| 8 | Universal 3.5 Pro | AssemblyAI | 146 ms | 1030 ms | 29,280 | |
| 9 | Default | Azure | 155 ms | 1792 ms | 6,682 | |
| 10 | Whisper Large v3 | Together AI | 180 ms | 1241 ms | 29,171 | |
| 11 | Velma 2 STT Streaming | Modulate | 191 ms | 1576 ms | 17,895 | |
| 12 | Grok STT | xAI | 199 ms | — | 29,322 | |
| 13 | Pulse | Smallest | 205 ms | 2072 ms | 29,313 | |
| 14 | Default | Speechmatics | 223 ms | 1473 ms | 29,323 | |
| 15 | Default | Gradium | 249 ms | 1979 ms | 28,235 | |
| 16 | resonant-1 | Reson8 | 288 ms | — | 17,066 | |
| 17 | Enhanced | Speechmatics | 341 ms | 1536 ms | 29,322 | |
| 18 | Voxtral Mini Transcribe Realtime 2602 | Mistral | 356 ms | 1828 ms | 29,175 | |
| 19 | GPT Realtime Whisper | OpenAI | 559 ms | 1823 ms | 29,286 | |
| 20 | GPT-4o mini Transcribe | OpenAI | 623 ms | — | 29,318 | |
| 21 | Solaria 1 | Gladia | 680 ms | 1703 ms | 26,356 | |
| 22 | GPT-4o Transcribe | OpenAI | 742 ms | — | 29,318 | |
| 23 | Chirp 2 | 811 ms | 6000 ms | 29,237 | ||
| 24 | Chirp 3 | 813 ms | 5999 ms | 29,319 | ||
| — | Flux | Deepgram | — | 1089 ms | 29,354 | |
| — | Flux Multilingual | Deepgram | — | 1175 ms | 29,344 | |
| — | Nemotron 3.5 ASR Streaming | Together AI | — | 1540 ms | 29,193 | |
| — | Universal Streaming | AssemblyAI | — | 1510 ms | 29,297 |
Latency vs accuracy
Where the errors come from
- Ink 24.9%
Averages and tail latency
Averages hide slow outliers — these are the distributions behind each figure.
- Time to Final Segmentp50 106 ms · p99 169 ms
- Time to First Tokenp50 1773 ms · p99 3558 ms
- Ink 2p50 0.0% · p99 41.1%
| Metric | Average | p25 | p50 | p75 | p90 | p95 | p99 | Samples |
|---|---|---|---|---|---|---|---|---|
| Time to Final Segment | 108 ms | 92 ms | 106 ms | 118 ms | 132 ms | 142 ms | 169 ms | 29,288 |
| Word Error Rate | 4.9% | 0.0% | 0.0% | 6.7% | 14.3% | 20.0% | 41.1% | 29,329 |
| Time to First Token | 1812 ms | 1573 ms | 1773 ms | 1987 ms | 2373 ms | 2574 ms | 3558 ms | 29,329 |
Last 30 days
Daily medians from the same measurement runs · gaps are days without qualifying runs.
Time to Final Segment by dataset
- WildASR noise gaps107 ms
- WildASR clipping107 ms
- WildASR clean108 ms
- PipeCat (production)108 ms
- WildASR accents110 ms
- WildASR reverb110 ms
- WildASR far-field110 ms
- WildASR phone codec111 ms
| Dataset | TTFS | Samples |
|---|---|---|
| LibriSpeech | 96 ms | 1 |
| ProductionPipeCat | 108 ms | 14,924 |
| AccentsWildASR | 110 ms | 1,437 |
| CleanWildASR | 108 ms | 5,773 |
| ClippingWildASR | 107 ms | 1,443 |
| Far-fieldWildASR | 110 ms | 1,441 |
| Noise gapsWildASR | 107 ms | 1,439 |
| Phone codecWildASR | 111 ms | 1,439 |
| ReverbWildASR | 110 ms | 1,391 |
Strongest condition: LibriSpeech at 96 ms · weakest: WildASR phone codec at 111 ms.
Limits of this comparison
Ink 2 is measured separately from Cartesia's Sonic synthesis models and ranked only against other STT models.
- The benchmark does not combine Ink with Sonic, so end-to-end Cartesia agent latency must be evaluated separately.
Official sources
- Cartesia documentation (documentation)
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.