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LatestBosonaiv3-4b
BosonaiText → Speech

Boson AI's Higgs Audio v3 Offers Expressive, Multilingual TTS

The new 4-billion-parameter text-to-speech model is available for non-commercial use, promising fine-grained control over vocal delivery.

Jun 4, 2026
NotableOther
Higgs Audio v3 TTS 4B

Boson AI has released Higgs Audio v3, a new 4-billion-parameter model for text-to-speech (TTS) synthesis. The model is designed to generate highly expressive and controllable speech across multiple languages, positioning it as a powerful new tool for creators and researchers in the open-source audio space.

Fine-Grained Vocal Control

The primary differentiator for Higgs Audio v3 is its focus on granular control over vocal delivery. The system allows users to influence the output's style, emotion, and prosody in two main ways:

  • Text Prompts: Users can describe the desired vocal characteristics directly in a text prompt.
  • Audio References: The model can also clone a voice and its style from a reference audio clip.

This dual-control mechanism provides flexibility for a range of applications, from character voice generation to dynamic audiobook narration. The model currently supports eight languages, including English, French, German, Spanish, and Polish.

Higgs Audio v3 enters a competitive field of open TTS models. Its 4B parameter size and emphasis on direct, prompt-based style control offer a compelling alternative for developers and creators who require more than just a simple voice clone. This level of expressiveness is critical for applications where emotional nuance and specific delivery are key.

The model is available for download from the Boson AI repository on Hugging Face. It has been released under a Creative Commons (CC-BY-NC-SA-4.0) license, which allows for broad non-commercial use and adaptation.

Sources

  • bosonai/higgs-audio-v3-tts-4b

    Hugging Face

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OlderIdeogram 4.0 arrives as an open-weight image modelStability AI · Text → Image · 5 months agoNewerCohere Releases North-Mini-Code, an Open MoE ModelCohere · Code · 5 months ago

Get the model

Hugging Face

Specs

Parameters4B
Sample rate24 kHz
Languages102 languages
Size9.3 GB
PrecisionBF16
ArchitectureHiggsMultimodalQwen3ForConditionalGeneration
LicenseOTHER
Downloads124.3K
Likes828

Can you run it?

Runs on a laptop — about 5.7 GB at FP8.

  • BF16 (as published)

    12 GB GPU (RTX 3060 / 4070) · 16 GB Mac

    10.3 GB
  • FP8

    8 GB GPU (RTX 4060) · 16 GB laptop or Mac

    5.7 GB
Your machine

Based on Hugging Face weights metadata. Assumes an 8K context and ~1 GB runtime overhead; actual needs vary. How we estimate


Modalities

Text → Speech

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