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Gradium's 31M-parameter TTS model runs 2.6x faster than a 2.37B model in hands-on test

10/23/2026 — 10/23, 07:18·2 sources (all)·2 reports (all)

Key takeaways

  • Gradium has open-sourced Phonon, a family of on-device text-to-speech models;
  • the English Phonon 31m variant ships under Apache 2.0 at 64.5 MB and starts speaking in about 7 ms on a laptop CPU. In a hands-on Mac mini t…

Background & analysis

On October 23, 2026, MarkTechPost reported that Gradium has open-sourced Phonon, a family of text-to-speech models designed to run locally on devices. The English release, Phonon 31m, is distributed under the Apache 2.0 license and fits in 64.5 MB. According to the report, it begins speaking in about 7 ms on a laptop CPU. The model has 31M parameters. The material does not include comparisons with other models, nor does it mention later updates or additional versions, so the public record currently stops at the open-source release.

AI-generated from 1 reports · updated 6 hours ago

Latest turnThe author swapped the local TTS setup on a Mac mini and compared two models on wall-clock time and Whisper round-trip word error rate. A 31.2M-parameter model ran 2.6x faster than the previous 2.37B model, with prose coming back at 0.0% WER. The takeaway is that model size is not a reliable predictor for choosing a local TTS model.

24-hour heatHeat index 177 · peak 183 · 1h ago
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Reports on this story headlines open the original

Today
  1. The author swapped the local TTS setup on a Mac mini and compared two models on wall-clock time and Whisper round-trip word error rate. A 31.2M-parameter model ran 2.6x faster than the previous 2.37B model, with prose coming back at 0.0% WER. The takeaway is that model size is not a reliable predictor for choosing a local TTS model.

    DEV Community · AIAI score 55
  2. Gradium has open-sourced Phonon, a family of on-device text-to-speech models, MarkTechPost reports. The English Phonon 31m ships under Apache 2.0, fits in 64.5 MB and starts speaking in about 7 ms on a laptop CPU. The release targets fully local inference; no head-to-head benchmark results were included.

    MarkTechPostAI score 53

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