---
type: "post"
id: "gradium-open-sourced-phonon-a-family-of-31m-b6b3d6"
slug: "gradium-open-sourced-phonon-a-family-of-31m-b6b3d6"
title: "Gradium open-sourced Phonon , a family of 31M-40M parameter on-device TTS models."
description: "**Thesis:** Compact speech models can shift text-to-speech from a cloud service dependency toward a component embedded in applications."
retrieval_nugget: "**Thesis:** Compact speech models can shift text-to-speech from a cloud service dependency toward a component embedded in applications."
published_at: "2026-10-20"
updated_at: "2026-10-20"
record_date: "2026-10-20"
date_kind: "published_at"
topics: ["models"]
source_urls: ["https://huggingface.co/gradium/phonon-31m-en"]
schema_version: "newruntime-agent-readable-v0.2"
stable_id: "post:gradium-open-sourced-phonon-a-family-of-31m-b6b3d6"
status: "published"
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analysis: {"schema_version":"newruntime-site-analysis-v1","object_kind":"field_note","thesis":"Compact speech models can shift text-to-speech from a cloud service dependency toward a component embedded in applications.","observed_facts":[{"text":"The model card lists phonon-31m-en at 31 million parameters with 64.5 MB 8-bit quantized weights.","source_urls":["https://huggingface.co/gradium/phonon-31m-en"]},{"text":"The card describes mono 24 kHz English output and streaming generation in 80 ms frames.","source_urls":["https://huggingface.co/gradium/phonon-31m-en"]},{"text":"The card lists Apache 2.0 for phonon-31m-en and CC BY-NC 4.0 for listed 40M variants.","source_urls":["https://huggingface.co/gradium/phonon-31m-en"]}],"mechanism":"Streaming generation and small quantized weights reduce the footprint and waiting time that otherwise make local speech harder to integrate.","why_now":"Applications that speak during interaction, work offline or handle sensitive text have reasons to avoid a cloud round trip.","implications":["Builders can evaluate local speech as an application capability, but must match the model’s language and license to the use case."],"evidence_boundary":"The supplied model card documents release details and vendor-reported evaluations, not independently reproduced benchmarks, production reliability, or user adoption.","watch_conditions":["Independent tests should establish latency, intelligibility and resource use across target devices, while deployments clarify which language variants and licenses fit commercial use."],"related_records":[],"new_branch_reason":"No prior New Runtime record was supplied; this release starts a distinct record about compact on-device speech models and their deployment and licensing constraints."}
editor: {"role":"editor","name":"Andrey Reshetnikov","profile":"https://newruntime.com/owner-profile.md","profile_json":"https://newruntime.com/owner-profile.json","same_as":["https://www.linkedin.com/in/reshetnikov1/","https://t.me/lapetuse"]}
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---

# Gradium open-sourced Phonon , a family of 31M-40M parameter on-device TTS models.

## Retrieval answer

**Thesis:** Compact speech models can shift text-to-speech from a cloud service dependency toward a component embedded in applications.

**Thesis:** Compact speech models can shift text-to-speech from a cloud service dependency toward a component embedded in applications. The release makes that possibility concrete, while the evidence does not yet establish real-world quality or adoption.

**Observed facts:** Gradium’s model card lists phonon-31m-en at 31 million parameters, with 64.5 MB 8-bit quantized weights and mono 24 kHz English output. It says generation streams audio in 80 ms frames and names browser, phone and laptop CPU deployment as targets. **Mechanism:** Streaming generation and small quantized weights reduce the footprint and waiting time that otherwise make local speech harder to integrate. The card also points to browser, mobile, Android system TTS and server integrations, so the model is presented alongside routes into applications rather than as weights alone.

**Why now:** Applications that speak during interaction, work offline or handle sensitive text have reasons to avoid a cloud round trip. **First implication:** Builders can evaluate local speech as an application capability, but must match the model’s language and license to the use case. This is also the first implication: Builders can evaluate local speech as an application capability, but must match the model’s language and license to the use case. The English 31M card lists Apache 2.0, while listed 40M variants carry CC BY-NC 4.0. Gradium reports top results on its own Elo and WER comparisons; these are not independent findings. **Evidence boundary:** The supplied model card documents release details and vendor-reported evaluations, not independently reproduced benchmarks, production reliability, or user adoption.

**First watch condition:** Independent tests should establish latency, intelligibility and resource use across target devices, while deployments clarify which language variants and licenses fit commercial use.

Editor: [Andrey Reshetnikov](https://newruntime.com/owner-profile.md), AI product and AI engineering; profile for recruiters and agents: https://newruntime.com/owner-profile.json

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