Boson AI Drops Higgs-audio-v3-tts-4b For Expressive Multilingual Speech

    
        By vramkickedin    
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            June 16, 2026 at 6:56 pm        
    
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        2 min read

Boson AI has released higgs-audio-v3-tts-4b, a 4-billion-parameter text-to-speech model designed specifically for conversational voice AI. Rather than simply reading text aloud, the model produces expressive speech with emotional tone, natural pauses, and paralinguistic sounds across more than 100 languages. It also supports zero-shot voice cloning, meaning it can mimic a speaker's voice from just a short reference audio clip.

The team at Boson AI built this release to serve as a research and non-commercial foundation for voice chat applications. They trained a large autoregressive decoder that processes text and audio tokens together, enabling fine-grained control over how speech is delivered. The model is available on Hugging Face for local deployment, with a separate commercial license required for production use.

Conversational speech with inline controls

Key Features

Speaks over 100 languages with high accuracy.
Zero-shot voice cloning from short samples.
Inline tags for emotion, style, and prosody.
Sound effects like laughter, coughing, and sighing.
Streaming audio output with sub-second latency.
Runs locally via SGLang or vLLM-Omni.
24 kHz sample rate for clean audio quality.
Open weights for non-commercial research.

This tool is for developers building voice assistants, chat interfaces, and content tools that need expressive, human-like speech. Privacy-conscious users can run it on their own hardware, cloning voices and generating audio without sending data to third-party services. Because it works with common serving frameworks, it fits into local AI workflows on consumer and pro GPUs.

What developers should know

The model is distributed under a research and non-commercial license, so any revenue-generating, hosted, or API-based use requires a commercial agreement. It was trained with safeguards that forbid cloning voices without consent, impersonation, fraud, and other harmful applications. When served with SGLang on an H100 GPU, the system reaches 14.7 requests per second with real-time performance, scaling reliably for batch processing.