Voice AI BenchmarksBy

PROVIDERLAST 30 DAYS

official resource

Baseten voice AI models and benchmarks

Baseten lists 3 STT and TTS models in Coval. Fastest dated mean latency over 30 days: STT: Qwen3 ASR 1.7b (dedicated inference) at 39 ms TTFS, with 2.9% WER. TTS: Qwen3 TTS 1.7b (dedicated inference) at 107 ms TTFA, with 1.8% WER. Last measured .

Baseten is an inference platform for deploying open-source and custom AI models on dedicated GPUs.

Measured models
3
STTTTS
Best STT model#1 / 29
39ms
Qwen3 ASR 1.7b
Best TTS model#5 / 32
107ms
Qwen3 TTS 1.7b

Overview

Baseten serves models created by others rather than training its own. Each measured endpoint is a streaming WebSocket deployment from its model library, with hardware and concurrency chosen per deployment.

Every model below is measured daily on the same fixed inputs and ranked against the full field, never blended into a company score.

Model lineup

Speech-to-Text
serves Whisper Large v3, Qwen3 ASR 1.7b
Text-to-Speech
serves Qwen3 TTS 1.7b

Speech-to-Text

Full STT dashboard

Ranked on Time to Final Segment against 29 measured models.

Time to Final Segmentms · lower is better · Baseten models markedEvery measured STT model on Time to Final Segment, with Baseten's models 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. #11Whisper Large v3via Baseten132 ms
leaders plus Baseten models · 21 other models in the full table
Word Error Rate% · lower is better · Baseten models markedEvery measured STT model on Word Error Rate, with Baseten's models highlighted.
  1. #1Universal 3.6 Pro2.2%
  2. #2Universal 3.5 Pro2.4%
  3. #3resonant-12.6%
  4. #4Qwen3 ASR Fast2.6%
  5. #5Qwen3 ASR 1.7b2.9%
  6. #6Gemini 3.5 Transcribe Live3.0%
  7. #7Chirp 33.2%
  8. #16Whisper Large v3via Baseten4.4%
leaders plus Baseten models · 23 other models in the full table
Time to First Tokenms · lower is better · Baseten models markedEvery measured STT model on Time to First Token, with Baseten's models highlighted.
  1. #1Whisper Large v3via Baseten925 ms
  2. #2Qwen3 ASR 1.7b946 ms
  3. #3Universal 3.5 Pro1023 ms
  4. #4Universal 3.6 Pro1074 ms
  5. #5Flux1091 ms
  6. #6Flux Multilingual1166 ms
  7. #7STT 11167 ms
leaders plus Baseten models · 20 other models in the full table
TTFS vs WER — Baseten vs every measured modelEach point is one measured STT model · Baseten models highlighted · 30-day averagesTime to Final Segment against Word Error Rate for every measured STT model, with Baseten's models highlighted.
STT RT v5 — 45 ms, 4.8%Qwen3 ASR Fast — 47 ms, 2.6%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%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 — 251 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 1.7b — 39 ms, 2.9%Whisper Large v3 via Baseten — 132 ms, 4.4%
Benchmarked models with their Time to Final Segment over the last 30 days.
ModelHostTTFSRank
Whisper Large v3Baseten132 ms11th of 29
Qwen3 ASR 1.7bBaseten39 ms1st of 29

Text-to-Speech

Full TTS dashboard

Ranked on Time to First Audio against 32 measured models.

Time to First Audioms · lower is better · Baseten models markedEvery measured TTS model on Time to First Audio, with Baseten's models highlighted.
  1. #1vui57 ms
  2. #2Default63 ms
  3. #3Qwen3 TTS Fast67 ms
  4. #4TTS Flash 288 ms
  5. #5Qwen3 TTS 1.7b107 ms
  6. #6Simba 3.0110 ms
  7. #7Palabra TTS121 ms
leaders plus Baseten models · 25 other models in the full table
Word Error Rate% · lower is better · Baseten models markedEvery measured TTS model on Word Error Rate, with Baseten's models highlighted.
  1. #1Sonic 3.61.5%
  2. #2S2.1 Pro Free1.5%
  3. #3Sonic 3.51.6%
  4. #4S2.1 Pro1.6%
  5. #5Lightning v3.1 Pro1.6%
  6. #6Simba 3.01.6%
  7. #7Chirp 3 HD1.6%
  8. #15Qwen3 TTS 1.7b1.8%
leaders plus Baseten models · 24 other models in the full table
TTFA vs WER — Baseten vs every measured modelEach point is one measured TTS model · Baseten models highlighted · 30-day averagesTime to First Audio against Word Error Rate for every measured TTS model, with Baseten's models highlighted.
vui — 57 ms, 2.1%Default — 63 ms, 1.9%Qwen3 TTS Fast — 67 ms, 1.8%TTS Flash 2 — 88 ms, 1.7%Simba 3.0 — 110 ms, 1.6%Palabra TTS — 121 ms, 2.7%Simba 3.2 — 125 ms, 2.0%drama3-preview — 185 ms, 1.9%TTS 2 — 186 ms, 1.6%Flash v2.5 — 193 ms, 1.9%Eleven v4 Turbo — 199 ms, 1.7%Flux TTS — 204 ms, 1.7%TTS RT v1 — 255 ms, 2.5%TTS Rt v2 — 257 ms, 2.4%Phantom Z 3.4 conversational — 267 ms, 1.9%Falcon 2 — 282 ms, 1.7%Mist v3 — 287 ms, 2.1%Sonic 3.5 — 292 ms, 1.6%Aura 2 — 297 ms, 1.9%Sonic 3.6 — 297 ms, 1.5%Coda — 332 ms, 9.5%S2.1 Pro — 343 ms, 1.6%Grok TTS — 361 ms, 1.6%S1 — 391 ms, 1.8%Lightning v3.1 Pro — 392 ms, 1.6%Daytona TTS — 485 ms, 1.7%Aura 2 En — 565 ms, 2.1%Chirp 3 HD — 599 ms, 1.6%Qwen3 TTS Flash Realtime — 719 ms, 3.0%S2.1 Pro Free — 849 ms, 1.5%GPT-4o mini TTS — 2568 ms, 1.8%Qwen3 TTS 1.7b — 107 ms, 1.8%
Benchmarked models with their Time to First Audio over the last 30 days.
ModelHostTTFARank
Qwen3 TTS 1.7bBaseten107 ms5th of 32

How fast are Baseten's STT and TTS models?

Qwen3 ASR 1.7b (dedicated inference) measures mean 39 ms time to final segment (1st of 29) among STT systems. Last measured 2026-10-16. Whisper Large v3 (dedicated inference) measures mean 132 ms time to final segment (11th of 29) among STT systems. Last measured 2026-10-16. Qwen3 TTS 1.7b (dedicated inference) measures mean 107 ms time to first audio (5th of 32) among TTS systems. Last measured 2026-10-16.

How accurate are Baseten's STT and TTS models?

Qwen3 ASR 1.7b (dedicated inference) measures 2.9% word error rate (5th of 31) among STT systems. Last measured 2026-10-16. Whisper Large v3 (dedicated inference) measures 4.4% word error rate (16th of 31) among STT systems. Last measured 2026-10-16. Qwen3 TTS 1.7b (dedicated inference) measures 1.8% word error rate (15th of 32) among TTS systems. Last measured 2026-10-16.

Which Baseten model is fastest?

Its fastest dated STT result is Qwen3 ASR 1.7b (dedicated inference) at mean 39 ms time to final segment (1st of 29) among STT systems, with 2.9% WER. Last measured 2026-10-16. Its fastest dated TTS result is Qwen3 TTS 1.7b (dedicated inference) at mean 107 ms time to first audio (5th of 32) among TTS systems, with 1.8% WER. Last measured 2026-10-16.

Limits of this comparison

Coval measures three open-weight models served from Baseten dedicated endpoints: Whisper Large v3 and Qwen3-ASR 1.7B for transcription, and Qwen3-TTS 1.7B for synthesis.

  • Dedicated endpoints run on hardware reserved for a single customer, so their latency is not ranked against shared APIs here; accuracy is compared across the full field. Results describe Coval's deployments, not every configuration Baseten's library offers.

Official resources

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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