PROVIDERLAST 30 DAYS

official resource

Microsoft Azure voice AI models and benchmarks

Microsoft Azure hosts the measured Microsoft speech-to-text and text-to-speech endpoints.

Measured models
3
STTTTS
Best STT model#9 / 24
155ms
Default

Overview

Azure spans speech recognition and synthesis, and its latency rows describe Microsoft's managed cloud infrastructure rather than downloadable model weights.

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 Default
Text-to-Speech
serves Neural, Dragon HD Latest

Ranked on Time to Final Segment against 24 measured models.

Time to Final Segmentms · lower is better · Microsoft Azure models markedEvery measured STT model on Time to Final Segment, with Microsoft Azure's models highlighted.
  1. #1STT RT v564 ms
  2. #3STT 183 ms
  3. #4Nova 399 ms
  4. #5Nova 2101 ms
  5. #6Ink 2108 ms
  6. #9Defaultvia Azure155 ms
leaders plus Microsoft Azure models · 16 other models in the full table
Word Error Rate% · lower is better · Microsoft Azure models markedEvery measured STT model on Word Error Rate, with Microsoft Azure's models highlighted.
  1. #2resonant-13.4%
  2. #3Chirp 34.1%
  3. #4Enhanced4.3%
  4. #6Grok STT4.8%
  5. #7STT 14.8%
  6. #13Defaultvia Azure5.3%
leaders plus Microsoft Azure models · 20 other models in the full table
Time to First Tokenms · lower is better · Microsoft Azure models markedEvery measured STT model on Time to First Token, with Microsoft Azure's models highlighted.
  1. #2Flux1089 ms
  2. #6Nova 31434 ms
  3. #7Nova 21436 ms
  4. #16Defaultvia Azure1792 ms
leaders plus Microsoft Azure models · 16 other models in the full table
TTFS vs WER — Microsoft Azure vs every measured modelEach point is one measured STT model · Microsoft Azure models highlighted · 30-day averagesTime to Final Segment against Word Error Rate for every measured STT model, with Microsoft Azure's models highlighted.
Benchmarked models with their Time to Final Segment over the last 30 days.
ModelHostTTFSRank
DefaultAzure155 ms9th of 24

Ranked on Time to First Audio against 30 measured models.

Time to First Audioms · lower is better · Microsoft Azure models markedEvery measured TTS model on Time to First Audio, with Microsoft Azure's models highlighted.
  1. #2vui124 ms
  2. #3TTS Flash 2128 ms
  3. #4TTS 2176 ms
  4. #5Blizzard235 ms
  5. #6Neural236 ms
  6. #7Mist v3256 ms
leaders plus Microsoft Azure models · 22 other models in the full table
Word Error Rate% · lower is better · Microsoft Azure models markedEvery measured TTS model on Word Error Rate, with Microsoft Azure's models highlighted.
  1. #1TTS RT v13.7%
  2. #2TTS Rt v23.9%
  3. #3Neural4.3%
  4. #6Default4.6%
  5. #7S2.1 Pro4.6%
leaders plus Microsoft Azure models · 22 other models in the full table
Benchmarked models with their Time to First Audio over the last 30 days.
ModelHostTTFARank
NeuralAzure236 ms6th of 30
Dragon HD LatestAzure310 ms11th of 30

Limits of this comparison

Microsoft creates the models; Azure serves the measured endpoints.

  • Azure regions, resource tiers and speech configurations can differ; Coval reports its published endpoint configuration rather than every Azure deployment.

Official resources

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.

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