Voice AI BenchmarksBy

PROVIDERLAST 30 DAYS

official resource

Gladia voice AI models and benchmarks

Gladia lists 1 STT model in Coval. Its fastest dated STT result is Solaria 1 at mean 614 ms time to final segment (25th of 29) among STT systems, with 6.1% WER. Results cover the last 30 days. Last measured .

Gladia builds real-time and asynchronous speech recognition services.

Measured models
1
STT
Best STT model#25 / 29
614ms
Solaria 1

Overview

The measured service includes multilingual transcription, translation, code switching and vocabulary controls, while Coval ranks its STT outcomes only.

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
Solaria 1

Speech-to-Text

Full STT dashboard

Ranked on Time to Final Segment against 29 measured models.

Time to Final Segmentms · lower is better · Gladia models markedEvery measured STT model on Time to Final Segment, with Gladia's models highlighted.
  1. #1Qwen3 ASR 1.7b39 ms
  2. #2STT RT v544 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. #25Solaria 1614 ms
leaders plus Gladia models · 21 other models in the full table
Word Error Rate% · lower is better · Gladia models markedEvery measured STT model on Word Error Rate, with Gladia's models highlighted.
  1. #1Universal 3.6 Pro2.1%
  2. #2Universal 3.5 Pro2.4%
  3. #3Qwen3 ASR Fast2.6%
  4. #4resonant-12.6%
  5. #5Qwen3 ASR 1.7b2.9%
  6. #6Gemini 3.5 Transcribe Live3.0%
  7. #7Chirp 33.2%
  8. #24Solaria 16.1%
leaders plus Gladia models · 23 other models in the full table
Time to First Tokenms · lower is better · Gladia models markedEvery measured STT model on Time to First Token, with Gladia's models highlighted.
  1. #1Whisper Large v3via Baseten924 ms
  2. #2Qwen3 ASR 1.7b946 ms
  3. #3Universal 3.5 Pro1025 ms
  4. #4Universal 3.6 Pro1071 ms
  5. #5Flux1091 ms
  6. #6Flux Multilingual1165 ms
  7. #7STT 11197 ms
  8. #18Solaria 11757 ms
leaders plus Gladia models · 19 other models in the full table
TTFS vs WER — Gladia vs every measured modelEach point is one measured STT model · Gladia models highlighted · 30-day averagesTime to Final Segment against Word Error Rate for every measured STT model, with Gladia's models highlighted.
Qwen3 ASR 1.7b — 39 ms, 2.9%STT RT v5 — 44 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 — 98 ms, 5.8%Scribe v2 Realtime — 121 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 — 170 ms, 2.4%Whisper Large v3 via Together AI — 196 ms, 7.4%Pulse — 205 ms, 4.6%Grok STT — 222 ms, 4.1%resonant-1 — 252 ms, 2.6%Default — 262 ms, 8.8%Linden 1 — 275 ms, 3.9%Gemini 3.5 Transcribe Live — 319 ms, 3.0%Daytona STT — 399 ms, 4.9%Voxtral Mini Transcribe Realtime 2602 — 416 ms, 5.3%GPT Realtime Whisper — 599 ms, 4.0%GPT-4o mini Transcribe — 711 ms, 3.9%Chirp 3 — 767 ms, 3.2%GPT-4o Transcribe — 784 ms, 3.7%Chirp 2 — 910 ms, 3.9%Solaria 1 — 614 ms, 6.1%
Benchmarked models with their Time to Final Segment over the last 30 days.
ModelHostTTFSRank
Solaria 1Gladia614 ms25th of 29

How fast are Gladia's STT models?

Solaria 1 measures mean 614 ms time to final segment (25th of 29) among STT systems. Last measured 2026-10-15.

How accurate are Gladia's STT models?

Solaria 1 measures 6.1% word error rate (24th of 31) among STT systems. Last measured 2026-10-15.

Which Gladia model is fastest?

Its fastest dated STT result is Solaria 1 at mean 614 ms time to final segment (25th of 29) among STT systems, with 6.1% WER. Last measured 2026-10-15.

Limits of this comparison

Coval measures the Solaria 1 streaming endpoint served by Gladia.

  • Translation quality and the wider Gladia audio-intelligence platform are outside the current public metrics.

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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