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Wednesday, 7 October 2026
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Universal-3.5 Pro

Change history

  1. 6 Oct 2026
    AssemblyAI launches Sync API: full transcript in a single HTTP call, ~134ms latency
    ParameterBeforeNow
    Latency (2s clip)5-6s (Async submit-and-poll)~134ms (Sync API, p50)
    Word error rate (short-form)Not specified1.59%
    PriceNot specified$0.45/hr
    Clip length supportedNot specified80ms to 2 minutes
    File size limitNot specifiedUp to 40 MB
    LanguagesNot specified18 (same as Universal-3.5 Pro)
  2. 6 Oct 2026
    AssemblyAI launches Universal-3.5 Pro with native code-switching and improved speaker diarization
    ParameterBeforeNow
    Code-switching WER (avg, 5 language pairs)9.07% (Universal-3 Pro)7.69%
    Languages supported at full accuracyNot specified18 languages with native mid-sentence code-switching
    Diarization accuracy (cpWER avg)Not specified30.17% (lowest/best among compared models)
    PriceNot specified$0.21/hr

News

Voice AI· Important· 🧪 Worth Testing

AssemblyAI launches Sync API: full transcript in a single HTTP call, ~134ms latency

AssemblyAI introduced the Sync API, a new transport for transcribing short audio clips: one HTTP POST request returns a finished Universal-3.5 Pro transcript in the same response, at roughly 134ms median latency. It fills the gap between the Async API (submit-and-poll, 5-6 seconds of added latency) and the Realtime API (WebSocket, built for ongoing sessions), targeting workloads like dictation, voice-agent turn transcription, IVR, and push-to-talk. Clips from 80ms to 2 minutes and up to 40MB are supported, with word error rate of 1.59% on short-form audio. Pricing is $0.45/hr, the same rate as Universal-3.5 Pro Realtime.

AssemblyAI
Voice AI· Important· 🧪 Worth Testing

AssemblyAI launches Universal-3.5 Pro with native code-switching and improved speaker diarization

AssemblyAI released Universal-3.5 Pro, a new flagship async speech-to-text model priced at $0.21/hr. It natively transcribes code-switched conversations across 18 languages without separate configuration, introduces jointly modeled speaker diarization built directly into the transcript (rather than stitched from a separate system), and supports contextual prompting to prime the model with domain knowledge. Benchmarks show lower word error rate on code-switched audio and higher cpWER accuracy on diarization compared to several competitor models and AssemblyAI's own prior Universal-3 Pro.

AssemblyAI
Universal-3.5 Pro · TENESYS AI NEWS